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10,045 | https://devpost.com/software/countdown-timer-for-confluence-cloud | Configurable date and size
View mode
Edit mode
We have a Countdown Timer for Confluence server edition and we have requests to port it for Confluence Cloud.
Atlassian Forge looks like a viable option since there is no need for a separate hosting infrastructure to provide the service.
It is a bit challenging because it is not possible to embed CSS and Javascript. Nevertheless, I think we addressed the objective since a Confluence page is not a static dashboard. People only need the information when the page is refreshed.
Built With
forge
node.js
Try it out
akeles.jira.com | Countdown Timer for Confluence Cloud | Team members can align on the same page by having clear visibility on the time left to the next release/milestone.This can be easily done by adding a Confluence macro and setting the due date. | ['Hua Soon Sim'] | [] | ['forge', 'node.js'] | 258 |
10,045 | https://devpost.com/software/remote-requester | Example of the rendered plugin
You can select from JSON on plain text responses
You can select where to request from and use a JSONPath to extract just the data you are interested in
Inspiration
At my company wanted an easy way to have a Confluence page display the versions and statuses of the various components which make up our product. They already had JSON endpoints returning this information so I wanted to use those endpoints.
What it does
Makes remote requests to either JSON and plain text endpoints and allows a JSONPath query to be used to extract just the part of the response you are interested in.
How I built it
Used the new Forge app system.
Challenges I ran into
Getting started and understanding the whole new Forge ecosystem. Also finding some npm modules which were not compatible with Forge.
Accomplishments that I'm proud of
Solving the above challenges.
What I learned
Getting started with Forge is actually really easy and having all the deployment handled for you makes it very convenient. Also the Forge Slack channel is very useful for getting help.
What's next for Remote Requester
Adding support for XML endpoints and finding a way to release it to customers.
Built With
confluence
forge
javascript | Remote Requester | Easily display the results on remote requests in a Confluence page. Useful for displaying the versions and statuses of your websites/apps. | ['Matthew Grover'] | [] | ['confluence', 'forge', 'javascript'] | 259 |
10,045 | https://devpost.com/software/timelloc | Forge App
Configuration
Logo
Inspiration
Companies are full of diverse people- whether that be the culture, background experience, or location. Nowadays, remote work and working with people all across the globe are becoming more prevalent. The problem that is now seen is communication across timezones and messaging co-workers at appropriate reply times. There is a need for more effective communication between global teammates.
This is were TimeLoc becomes useful. Especially with a larger magnitude of teammates abroad, TimeLoc provides a convenient Confluence Macro for collaborators of a Space to check on each other’s timezones, availability, and location. It puts all of that information in one place, so users don’t have to remember every teammate’s current time/make unnecessary google searches. —Hence you can save
time
and
energy
with TimeLoc!
What it does
TimeLoc is an Atlassian Confluence Macro. It fetches all the collaborators that have connections to a Space and lists their timezone/location, live time, and day/night availably. It is a simple, compact macro, allowing for easy reference as the project develops. It’s even customizable, so the Macro can fit seamlessly between confluence pages and better suit the user’s needs.
How I built it
Using Atlassian’s new Forge (Beta) platform and infrastructure, the app can be launched in minutes with little to no experience in cloud app development. It was perfect for making the set-up extremely easy and allowed me to focus on my idea and becoming more familiar with typescript.
The list below outlines some of the features this Macro includes!
@name + avatar
night/day identifier
location
timezone
local real time
customizable design
title of widget
24hr or 12 hr clock
Challenges I ran into
-Learning Typescript and the Forge UI syntax to align with my app idea. Some of the things I was used to in React and Javascript were slightly different, so this adjustment was a bit of a challenge.
-Since Forge is still in Beta, I had to do some research to go around some of the limitations such as authentication when grabbing information with the confluence REST API- hence I had to use Jira’s REST API!
Accomplishments that I'm proud of
Incorporating all the APIs (Jira, WorldTime)
Figuring out how to import SVG's into Forge
Using Moment.js for calendar conversion
What I learned
Everything that I submitted I learned. This includes Jira/Confluence usage, programming on the Forge platform and its tools, learning typescript, and using REST apis for the first time.
What's next for TimeLoc
In the future, I hope to add more configuration options such as color choice, and style the Forge app a bit better. Additional features can include an option to set up times with a user based on their availability in their timezone, and a comparison feature of two user’s times.
Built With
atlassian
confluence
forge
macro
typescript
Try it out
github.com
timeloc.atlassian.net | TimeLoc | A confluence macro that allows for easier communication and awareness between global teammates! | ['Nicole Streltsov'] | [] | ['atlassian', 'confluence', 'forge', 'macro', 'typescript'] | 260 |
10,045 | https://devpost.com/software/todoista | TODOISTA - Todo Apps made simpler
This web application is made with MongoDB, Express.js, React.js and Node.js. It has a simple motive to fulfil- making todo lists simple.
Features
Logged Exercises
Your todo list
Create todo Logged
Create User
Start date and deadlines included
ScreenShots
Check out the video on Vimeo
🤝 How to Contribute
For sending PR:-
Pick an open issue from the
issue list
and claim it in the comments. After approval fix the issue and send us a pull request (PR).
All the PR’s need to be sent to the appropriate branch (usually "master").
For Open issue:-
You can create a new issue and send a pull request.
Please go through our issue list first (open as well as closed) and make sure the issue you are reporting does not replicate an issue already reported. If you have issues on multiple pages, report them separately. Do not combine them into a single issue.
Our submission for the StackHack 1.0 Online Hackathon
Link
Important points
On Front End:
Implement a feature to add Tasks.
Implement a feature to set the due date for these tasks.
On Back end:
Implement the backend in one of the desired Tech-Stacks provided below.
Your backend is supposed to store all the tasks data received from the Frontend and store it in the Database.
You are also supposed to implement a Database in the Backend which should store all this structured data.
The data sharing between Frontend and Backend should be in JSON format rendered over REST APIs.
Zip all your Source Code, Screenshots, Deployment Instructions and Upload.
Contributors
Garima Singh
Mrinal
This project was bootstrapped with
Create React App
.
Available Scripts
In the project directory, you can run:
npm start
Runs the app in the development mode.
Open
http://localhost:3000
to view it in the browser.
The page will reload if you make edits.
You will also see any lint errors in the console.
npm test
Launches the test runner in the interactive watch mode.
See the section about
running tests
for more information.
npm run build
Builds the app for production to the
build
folder.
It correctly bundles React in production mode and optimizes the build for the best performance.
The build is minified and the filenames include the hashes.
Your app is ready to be deployed!
See the section about
deployment
for more information.
npm run eject
Note: this is a one-way operation. Once you
eject
, you can’t go back!
If you aren’t satisfied with the build tool and configuration choices, you can
eject
at any time. This command will remove the single build dependency from your project.
Instead, it will copy all the configuration files and the transitive dependencies (webpack, Babel, ESLint, etc) right into your project so you have full control over them. All of the commands except
eject
will still work, but they will point to the copied scripts so you can tweak them. At this point you’re on your own.
You don’t have to ever use
eject
. The curated feature set is suitable for small and middle deployments, and you shouldn’t feel obligated to use this feature. However we understand that this tool wouldn’t be useful if you couldn’t customize it when you are ready for it.
Learn More
You can learn more in the
Create React App documentation
.
To learn React, check out the
React documentation
.
Code Splitting
This section has moved here:
https://facebook.github.io/create-react-app/docs/code-splitting
Analyzing the Bundle Size
This section has moved here:
https://facebook.github.io/create-react-app/docs/analyzing-the-bundle-size
Making a Progressive Web App
This section has moved here:
https://facebook.github.io/create-react-app/docs/making-a-progressive-web-app
Advanced Configuration
This section has moved here:
https://facebook.github.io/create-react-app/docs/advanced-configuration
Deployment
This section has moved here:
https://facebook.github.io/create-react-app/docs/deployment
npm run build
fails to minify
This section has moved here:
https://facebook.github.io/create-react-app/docs/troubleshooting#npm-run-build-fails-to-minify
💜
Thanks
Built With
css
html
javascript
Try it out
vigorous-kalam-504459.netlify.app
github.com | ToDoista | A ToDo app :orange_book: made using MERN. Keep a track of your activities on a single click. :thought_balloon: :computer: | ['Garima Singh'] | [] | ['css', 'html', 'javascript'] | 261 |
10,045 | https://devpost.com/software/issue-links-metrics | A circle visualisation where a target needs to be reached
A bar visualisation where a target needs to be reached
A number view where a target needs to be reached
Multiple metrics and targets on a dashboard
Many configuration options
Inspiration
I wanted to take Issue Links for Jira further, add some context around metrics. Give the users far more value from the dashboard gadgets.
What it does
The app counts the number of issues with or without certain issue links. You can get a count of Epics without blocking bugs or Stories with blocking Bugs and display these on a dashboard gadget.
This update allows a target value to be set for any metric gathered, giving context to the number. Metrics alone are great, but you often need some context. Is 100 good or bad? Is 10 way under or way over what you expected? When do you need to be concerned about a metric?
With a target set, you can now also visualise your metrtic and target as numbers, a circle chart or a progress bar.
How I built it
I used Atlassian Connect Express, with React used throughout, including React Hooks.
Accomplishments that I'm proud of
Using react hooks for the first time in a production app was rewarding, especially the use of Context.
What I learned
A lot about React Hooks and increasing (my limited) design skills.
What's next for Issue Links Metrics
Perhaps going beyond Issue Links for metrics and looking at other areas of Jira which would deliver useful metrics.
Built With
javascript
react
Try it out
marketplace.atlassian.com | Issue Links Metrics | Ever wanted to check how many blocking bugs you have? How many Epics with Reviews? How many tasks with Security Risks? Issue Links Metrics enables you to show metris for all your linked issues. | ['Paul Cutting'] | [] | ['javascript', 'react'] | 262 |
10,045 | https://devpost.com/software/canned-search-for-confluence | CQL Counter Macro Configuration
CQL Table Macro Configuration
CQL Counter Macro
CQL Table Macro
Canned Search For Confluence
What it does
The Canned Search allows search on a particular field (e.g. title) within a particular context using CQL.
For example, users can search for blogposts with title containing a specific search term, created by a particular user (title ~ "searchTerm" and type = blogpost and creator = username).
In addition to what the Confluence Search offers, users will also be able to sort the results by using order by, specify the no. of results to display and preload the results whenever the user access the page with the macro.
Built With
forge
typescript | Canned Search for Confluence | Canned Search For Confluence (Forge) is a powerful macro empowers the users to execute contextual search within a particular context using CQL and to display the results permanently on the page. | ['Liang Cao'] | [] | ['forge', 'typescript'] | 263 |
10,045 | https://devpost.com/software/spreadsheet-issue-editor-for-jira-cloud | Set the dates in the date pickers and quickly access the spreadsheet with issues.
Choose what columns to show on the issue spreadsheet.
Edit the text fields and pick users as assignees or reporters.
Change issue types, priorities, and statuses for issues. Pick the required option in the single select fields.
Inspiration
The existing way of editing Jira issues is convenient, but not fast enough. We decided to move the Excel approach to Jira Cloud, so that users can view and edit all the required issues on the single spreadsheet without the constant switching between the list and issue details. This way users can keep the context of the whole project, version or sprint and edit all the necessary issue attributes at once.
What it does
The Spreadsheet Issue Editor shows the list of issues matching the specified JQL query and provides a way for their inline editing. You can quickly change columns and apply the required values to fields.
How we built it
Initial work on the app started from the RnD task when we evaluated the general capability to edit Jira issues inline. We reviewed the most frequently used custom fields and create a quick prototype in AdobeXD. We discussed the solution and its user experience within the team trying to understand what challenges may occur during the planning and task tracking. We decided to use the reliable and proven the technologies, such as Atlassian Connect with SpringBoot and Java 8. For front-end we used React, JavaScript and AtlasKit. The app is running in AWS (production) and in Heroku (staging).
Challenges we ran into
The main challenge for us was to recognize custom field types and treat them accordingly. As of now the challenge for us is to support multiple instances of the same custom field in next-gen projects and to add support for text areas.
Accomplishments that we're proud of
We managed to integrate the app with the issue editing mechanism, so that our users can edit all issues inline on a single spreadsheet. The app supports all the essential field types, so our users can save quite enough time on other project activities.
What we learned
We learned that inline editing of Jira Issues is not so easy as we expected with a plenty of peculiarities in each field type.
What's next for Spreadsheet Issue Editor for Jira Cloud
We want to add support for the following:
text area fields
multi-select fields
saving of issue views with custom fields on them
Built With
amazon-web-services
atlaskit
atlassian-connect
heroku
java-8
javascript
react
spring-boot
Try it out
cutt.ly | Spreadsheet Issue Editor for Jira Cloud | We wanted to create a solution that allows users to editing Jira issues inline like in an Excel spreadsheet simply and easily. | ['Vadim Rutkevich', 'Alexander Ovsyannikov', 'Dmitry Kostochko'] | [] | ['amazon-web-services', 'atlaskit', 'atlassian-connect', 'heroku', 'java-8', 'javascript', 'react', 'spring-boot'] | 264 |
10,045 | https://devpost.com/software/confluence-renderer | CoJi configuration overview
Configuration of generating new Confluence pages
Configuration of displaying existing Confluence pages
Inspiration
Often when working with software, we find ourselves navigating between Jira issues and dozens of related Confluence pages distributed across different spaces: how to handle different issues, how to respond to clients, or looking for test environments data, just to name a few. We thought that it can, and should be automated, so it led to creating this app.
What it does
This app integrates creating and displaying Confluence pages into Jira, allowing for a smooth workflow. No need for jumping between context related documentation and Jira issues anymore!
How we built it
First, we brainstormed as many ideas as we could. There were many good ones, so it was painful to decide which one to develop. We decided to select the one that had many potential use cases and that integrates two great tools that we use in our daily work: Jira and Confluence.
Then we used the Atlassian Connect framework, with atlaskit library for UI, prepared the graphics, video, tried the solution out ourselves, done some corrections to it, and once we were satisfied with it, we published it here.
Challenges we ran into
One of first and challenging problems that we had to deal with, was how to properly display confluence page, preserving confluence styles, and if possible, macros output.
Accomplishments that we're proud of
We're proud that we've created something so simple yet so powerful, which looks to us like a missing piece between Jira and Confluence.
What we learned
Cooperation is the key component for building anything successful.
What's next for CoJi - Confluence Pages for Jira
This is just a start for CoJi. Our MVP only shows a glimpse of what's possible, and we'll be working on delivering more exciting features.
Built With
kotlin
react
spring
typescript
Try it out
confluence-renderer-staging.deviniti.com | CoJi - Confluence Pages for Jira | Display confluence pages on Jira issues using user-defined rules.Create confluence pages automatically when creating new Jira issue using user-defined rules. | ['Radosław Cichocki', 'Tomek Bar', 'Marcin Kosmala', 'Justyna Kumor', 'Krystian Chmielowski', 'Nina Zaradniak', 'Michał Malicki'] | [] | ['kotlin', 'react', 'spring', 'typescript'] | 265 |
10,045 | https://devpost.com/software/employee-performance-ratings-for-jira-cloud | Assess work of a person against the three metrics: speed, quality, and skills
View the charts on the recent performance assessments and details per each issue
View the dashboard with average performance ratings and trend for specific users
Let customers assess work of your support agents to better understand what to improve
Inspiration
The idea of this app came suddenly. We were discussing the way to simplify the way of collecting data for regular performance reviews from multiple people. The main challenge was to get the objective data based on opinions of multiple people, so that we decided to think over some solution that can enable assessment of tickets by multiple team leads or department supervisors.
What it does
How easy is it to prepare performance reviews? How difficult is it to get unbiased data about performance of employees?
The Employee Performance Ratings app allows you assess work on tasks against three metrics:
Speed - how quickly the task was completed.
Quality - how well it was completed.
Skills - how efficiently the was completed.
The app collects metrics from multiple tickets and calculates the average values for each metric, including the trend. For each user you can view details on metrics and for a particular Jira issue. Additionally, the app integrates with the customer portal, so that you can let customers assess the work of your support agents to better understand how you can improve it.
How we built it
Initial work on the app started from creation of prototypes in AdobeXD. We discussed the solution and its user experience within the team trying to understand what challenges managers and supervisors encounter during assessment of their colleagues.
We decided to use the reliable and proven the technology stack of Atlassian Connect with SpringBoot and Java 8. For front-end we used React, JavaScript and AtlasKit. The app is running in AWS (production) and Heroku (staging).
Challenges we ran into
The key challenge we encountered is the end users' understanding when the button for assessment should appear :) Everyone has different points of views, some wanted to assess when the task is closed, the others right after the task creation.
The other challenge that we encountered is the integration of the app into the task management pipeline. We wanted the app to be an essential part of the task screen, so that end users do not need to go somewhere else and can assess the task and the assignee in the context of the issue.
Accomplishments that we're proud of
We are happy that we managed to create the solution for in-context assessment of performance of individual employees in Jira Cloud. It does not require much time to get familiar with the app, and team managers and supervisors can receive valuable information about work of their colleagues and see the ways how to improve the overall team performance.
What we learned
We learned that the assessment of performance metrics differs greatly from company to company, as well as approaches and metrics that are important to this or that team. Our solution allows team to organize the centralized assessment of the work performed by specific people and get insights into things that should be improved.
What's next for Employee Performance Ratings for Jira Cloud
We plan to continue improving the app and hope to deliver in future releases the following:
management of performance metrics per project
provision of additional feedback when submitting performance ratings
recommendation system for task assessment
Built With
amazon-web-services
atlaskit
atlassian-connect
heroku
java-8
javascript
react
spring-boot
Try it out
cutt.ly | Employee Performance Ratings for Jira Cloud | The app provides a way to assess work of employees and support agents in Jira Cloud and on the customer portal of Jira Service Desk. You can use the collected data for regular performance reviews. | ['Vadim Rutkevich', 'Alexander Ovsyannikov', 'Dmitry Kostochko'] | [] | ['amazon-web-services', 'atlaskit', 'atlassian-connect', 'heroku', 'java-8', 'javascript', 'react', 'spring-boot'] | 266 |
10,045 | https://devpost.com/software/benkodesk-7pz4wv | Inspiration
BenkoDesk came about as a result of having built BenkoBoard (my other codegeist submission). I realised that people wanted to share their emails with team members since Trello is such a naturally collaborative environment. They actually share the same codebase, so BenkoDesk is really just a differently configured BenkoBoard that will allow more than one member to write messages rather than restricting access to a single user account.
I'm submitting BenkoDesk as a separate submission because it might fall into the category of best app for remote work, which BenkoBoard is less likely to, so even though they're both basically the same code configured differently, I'm sending them as separate submissions.
What it does
BenkoDesk connects a shared Gmail account to a shared Trello account (or you could use it to share your email with, for example, a virtual assistant). Each Gmail thread is imported to a card, and users can reply directly from Trello to emails. It runs as a "bot" user, rather than a powerup, so it can be used from any device (super important when it comes to email!) You can also use it to send new emails, forward existing emails, cc and bcc (all using Google Contacts integration) and to send attachments, all right from Trello on any device!
How I built it
The BenkoDesk story starts with BenkoBoard (my other submission). Late last year, I realised that people I spoke to were expecting that BenkoBoard would allow them to easily share emails with their team. When I saw this, I created BenkoDesk as a variation of BenkoBoard. At the time it was a Google Apps Script, the same as BenkoBoard, and went through the same challenge of rebuilding as an add-on and later as a standalone PHP web application.
It was verified by Google at the same time as BenkoBoard, so during the submission period I have created a sign-up and on-boarding process for "self-service" signups using the "Sign in with Google" button as well as launching the new, public facing web page:
http://www.benkodesk.com/
Challenges I ran into
The biggest challenge was taking something that was basically a connector between 2 other products and building it as a "real SaaS" application that people could sign up to. You can see more in the challenges section of my BenkoBoard submission.
Accomplishments that I'm proud of
Rebuilding as both a Google Sheets Add-On and then subsequently as a standalone PHP web application all within a couple of months and then raising money via presales to existing clients to get the Google security verification done (see BenkoBoard submission).
What I learned
The key to remote working is better collaboration. When people don't use shared email properly, they rely on being able to "turn to the person next to them" or call/txt their team members. This requires that everyone be either in the same space or in the same timezone or both. When you can use the same shared space for both external and internal communications, working remotely and asynchronously becomes much simpler.
What's next for BenkoDesk
The big challenge now that I have a fully "self service" product is getting the design and on-boarding right to build enough confidence for people to be able to sign up and use it without me having to speak to each and everyone person, set them up and train them personally, which is what I've been doing up until now.
Built With
beanstalkd
google-gmail-oauth
node.js
php
trellinator
trello
Try it out
app.benkodesk.com | BenkoDesk | BenkoDesk allows you to share a Gmail account via Trello. Unlimited team members can send and receive emails and keep track of tasks and priorities, replacing more expensive options such as HelpScout. | ['Iain Dooley'] | [] | ['beanstalkd', 'google-gmail-oauth', 'node.js', 'php', 'trellinator', 'trello'] | 267 |
10,045 | https://devpost.com/software/benkodesk | Inspiration
I started off working with small business owners to write procedures in 2014. I was running a web based software company and the goal was to get more leads for software development by helping them systemise. After a few years of trying different approaches, I couldn't figure out why I wasn't able to produce the same results in my clients' businesses, as I had been able to in my own. In November 2016, a frustrated client called me and I asked him to jump on Skype (remember Skype?) and share his screen with me. As soon as he started talking me through his situation I could see his problem. His email was chaos!
I had read Getting Things Done in 2007 and my inbox had been empty ever since -- I had just forgotten that it was even something I had to learn. I had just assumed that everyone else had a good way to manage their email but I couldn't have been more wrong.
That night, I created the first version of what would later become BenkoBoard: a Zapier integration that put Gmail threads into Trello cards. I deployed it for that one client and the difference was immediate. I took the same approach out to my other clients with similar success, and that was the beginning of the journey to build an email client that worked from Trello!
What it does
BenkoBoard turns each email into a card. All attachments are imported and stored automatically in Google Drive. You can reply directly from the Trello card comments by typing "@reply". You can also create new emails, forward existing ones, send attachments, cc and bcc people (all connected via Google Contacts). Because BenkoBoard runs as a "bot" user the person's Trello account, you can use it from any device (ie. it's not written as a power up). This is critical because when it comes to email, nothing is more important than being able to deal with things on the go from any device!
BenkoBoard also improves on Trello's native cards view by adding a linked copy of any card you're added to throughout Trello into your inbox.
It improves on notifications by automatically unwatching any card you're added to, so that you're only notified (by default) when you are added to or removed from a card/board or mentioned in a comment. This makes Trello much more useful as a core internal communication tool and obviates the need for things like Slack or other project management tools
It also improves notifications by giving you a linked copy of every comment you're mentioned in, in your inbox. This means you can reprioritise replying to each and every comment, and/or treat each comment like a task rather than having to keep track of things as either "read" or "unread" in the notifications section.
How I built it
The earliest version was just a Zapier integration from Gmail to Trello. This gave me the validation that getting my clients' emails into Trello was the key to operational success. It then grew into a Google Apps Script as I worked with clients to perfect our workflows, and later I rewrote it as a standalone PHP web application that connects Gmail to Trello. The interaction with Trello is all done using my open source Trellinator framework to work with Trello's REST API and handle notification webhooks via a beanstalkd queue, and the Gmail, Google Drive and Google Contacts integration is done via PHP using the Google REST API. It's hosted on Google Cloud Platform running Linux.
Challenges I ran into
The biggest challenge has always been setting people up! The first version was a Zapier automation linking Gmail to Trello. Getting that set up required having clients login to my Zapier account via screenshare to connect their Gmail accounts. Later, when I rewrote it as a Google Apps Script, I had to copy a spreadsheet and go through a process to publish the script as a web app while logged in as that user, also done via screensharing, so setup took approx 30 minutes. In October 2019, I got a client who wanted me to deploy BenkoBoard for 40 staff and I knew I couldn't go through setting them all up individually, so I redeveloped it as a Google Sheets add-on, this went really well until disaster struck! A crippling (and as yet STILL unresolved) bug in Google's platform meant that BenkoBoard would simply die and not recover. I tried desperately to make it work, since I had already deployed it for staff in this new company, but it turned into a total train wreck. Ultimately they stopped using it. Once I realised Google were never going to fix the problem, I rewrote BenkoBoard as a standalone PHP web application over the Christmas break 2019/2020. This required redeveloping all the Google Apps Script API calls to run over the Google REST API, including authentication with Google's OAuth system, as well as adapting Trellinator code to respond to notifications from a web server rather than from Google Apps Script.
It worked great! I got it written and was off to the races until ... DISASTER STRUCK AGAIN! When I went to submit the app for verification so people could sign in using their Google account without a big ugly "This app is unverified" warning, I had to go through lots of painstaking details to get my documentation and privacy policy online looking correct, then Google replied and said that since I was posting restricted scope data to a 3rd party server (Trello) I had to undertake an external security review from one of three gigantic global security companies.
The cheapest quote I could get for this was A$24,000 which I totally didn't have, so I went out to all my existing customers and told them I was moving to a new server and that, if they wanted to get in on this new version they would need to pay a yearly license fee, but that they could buy lifetime access if they prepaid now for 4 years up front.
Enough of them agreed that I was able to raise $14,000 and I negotiated with the security company to allow me to make that initial payment to get the letter of assessment for Google, then pay the remaining $10,000 in 5 monthly installments. They agreed, and after another 3 months of verification and testing, Google finally verified the app just last Friday June 26, 2020!
As soon as it was verified, I was able to put together real "self-service" sign up/on-boarding and publish the new product page at:
http://www.benkoboard.com/
with a "free 14 day trial" button, people can now just sign up and use it just like "Real Software(TM)". Note that although BenkoBoard does predate the hackathon submission period, it's release as a "self service" SaaS product that people can just sign up to and use is a significant change that has occurred during the submission period.
Now I just have to convince enough people to sign up so I can afford to pay the $2,000/month that I owe the security company :S
Accomplishments that I'm proud of
I'm really proud that I was able not only rewrite BenkoBoard nights and weekends over Christmas/NYE, but that I was then able to raise enough money through pre-sales to pay the verification costs, and also that I was able to have my app verified by a professional security company as being strong and robust enough to allow such privileged access to people's Gmail accounts.
What I learned
Developing BenkoBoard in response to real world customer demand has been a huge journey. I've learned that people will forgive you for all sorts of bumps and bruises along the way as long as you're solving a serious problem for them. I've learned that email is, by default, the system in every business that sits around all other systems and that, unless you replace that, getting effective organisational change is very difficult. Of all the products on the market, Trello is the only product capable of doing that.
What's next for BenkoBoard
Now that BenkoBoard is truly "self-service" my new challenge is improving the design and on-boarding process. Up until now my sales process has been very high touch and I have been setting people up and training them to use BenkoBoard via Zoom, largely as an initial step in a service delivery model. The big change now is that BenkoBoard is at the tip of the sales funnel, and that any services I offer will extend upwards from that, so I need to make BenkoBoard compelling and easy to sign up and use without my having to sell and train each and every person that does so.
I have uploaded a demo video to YouTube, but there is a more comprehensive one that shows my personal board, not for public display:
https://iain.wistia.com/medias/57o5jcvlji
Built With
beanstalkd
gmail
google-gmail-oauth
node.js
php
trellinator
trello
Try it out
app.benkoboard.com | BenkoBoard | BenkoBoard lets you use Trello as a Gmail client. Gmail threads are linked to Trello cards, and you can reply, create new emails, cc, bcc and send attachments directly from Trello. | ['Iain Dooley'] | [] | ['beanstalkd', 'gmail', 'google-gmail-oauth', 'node.js', 'php', 'trellinator', 'trello'] | 268 |
10,045 | https://devpost.com/software/smart-values-for-confluence | Results are displayed inline for smooth reading
Include multiple values in one template
Inspiration
A similar capability is exposed in Jira and I saw someone online requesting the functionality.
What it does
Allows you to easily include information about the Page inline in your Confluence Pages.
How I built it
Using the atlas-connect tool to create an initial Nodejs app. Functionality was then added using the Confluence Connect API.
Challenges I ran into
Really nothing major as the Confluence API was very easy to work with.
Accomplishments that I'm proud of
How quickly I was able to go from having an idea to a working app.
What I learned
atlas-connect and the Confluence Connect API have made creating an app super easy.
What's next for Smart Values for Confluence
Adding more template tags and solving more problems for customers
Built With
confluence
docker
javascript
Try it out
marketplace.atlassian.com | Smart Values for Confluence | Easily include information about the Page inline in your Confluence Pages. | ['Matthew Grover'] | [] | ['confluence', 'docker', 'javascript'] | 269 |
10,045 | https://devpost.com/software/sharepoint-connector-for-confluence-cloud | Embed SharePoint or One Drive documents in Confluence Cloud
Select teh rendered view for each document
Add a new macro
Simple filtering and configuation of macros
Inspiration
What it does
How we built it
Challenges we ran into
Authentication with two separate systems (i.e. Confluence and SharePoint Online) is not funny. That caused quite a few issues ot the point that we changed the way of authentication in the end (see below)
Accomplishments that we're proud of
Added new feature: Display O365 (+pdf) Documents as full view embed > responsive behavior of the document (e.g. in tables it uses the maximum space)
Changed authentification from ADAL to MSAL
Easier authentification for customers
Easier installation of the app itself
New column types for the default view of SharePoint lists
Choice
Managed Metadata
What we learned
What's next for SharePoint Connector for Confluence Cloud
We're improving it further. Things on our Roadmap include easier configuration, embeding Confluence Cloud pages in SharePoint (via WebPart)
Built With
react
Try it out
marketplace.atlassian.com | SharePoint Connector for Confluence Cloud | We brought the SharePoint Connector to Confluence Cloud and improved it every other week with new features. It helps integrating Confluence with SharePoint and OneDrive in Office 365. | ['David Toussaint'] | [] | ['react'] | 270 |
10,045 | https://devpost.com/software/sentimental-ef1cns | Context Menu
Page Summary
Sentiment of Page
Sentiment Macros
Sentiment Content Action
Sentiment Content Display
Inspiration
When blogging I need all the help I can get. I often can't tell how a post will be received. Sentiment analysis can help with understanding if a post is positive or negative in nature.
What it does
Sentimental uses
https://www.meaningcloud.com/
to analyse sentiment and summarise content. It adds a context menus for calculating the sentiment of and summarising a whole page. These are displayed in a modal dialog. A content action is added to calculate the sentiment of a portion of text and macros can display a summary or sentiment description of the current page
How I built it
Sentimental was built in an afternoon with an intended 4 hour limit. Within those four hours the context menus and content action were complete. A further hour added the macros and caching for performance.
What I learned
My main goal in building Sentimental was to learn Forge. I learned that it is possible to build useful tools with Forge quickly, the development feddback cycle is fast and whilst restrictive, it is possible to build functional interfaces using Forge UI.
What's next for Sentimental
Evaluate the success or not to decide if it should be taken further. I'll continue to use it for my own purposes regardless.
Built With
forge | Sentimental | Analyse the sentiment of your Confluence page. How will your content be received? Sentimental can help you find out. Also included is a quick way to summarise a page to five sentences! | ['Jon Mort'] | [] | ['forge'] | 271 |
10,045 | https://devpost.com/software/reminderz-oedrya | Inspiration
Having only basic capabilities in reminders addons, got us to create state-of-the-art reminders functionality.
Having issues stuck for days in a specific status, without good capability to get notify (for e.g. get notification after 2 days in status "Blocked")
Helping Team leaders and Project managers to make sure the work stream is always in progress got us inspired.
What it does
With ReminderZ it is simple to make sure important issues do not fall between the cracks, overseen or forgotten. From within the relevant issue screen, simply click the Issue Reminder and set up a single one time reminder or a repeating reminder.
One time reminders can be set for a specific date and time, for the issue’s Due Date (get reminded that the Due Date is about to be reached, and/or that it already passed), or for when the issue has been in a selected Status for specific set amount of days.
Repeating reminders can be set on a daily basis, a weekly basis where the wanted days of the week can be chosen, a monthly basis where the reminder will be every month according to the set start date for the reminder, or a yearly basis having the reminder sent on the same date every year (happy reminder birthday!). All repeating reminders can be set to start on reminder creation, or at a future selected date and time.
How I built it
Challenges I ran into
Getting sophisticated GUI on Jira cloud is not an easy task. screen sizes and regulations needed to be addressed.
Controlling several time zones of users.
Accessing the Jira cloud in-screen functionality
Accomplishments that I'm proud of
We have created a cool addon that will help project managers and team mates not to forget issues, or get notification upon issue that got blocked for several days.
What I learned
What's next for ReminderZ
Connectivity to other notification applications, such as slack, intercom and others.
Built With
connect
java
jira-api
Try it out
practiproject.atlassian.net | ReminderZ | Having a cool ability to set a reminder to an issue.Reminders for specific date, for status change, recurrent reminders.All with great GUI. | ['Addons Experts Center'] | [] | ['connect', 'java', 'jira-api'] | 272 |
10,045 | https://devpost.com/software/atlassian-forge-webhook-macro-for-confluence | The Macro Config screen.
Inspiration
I wanted to build something simple, yet useful for a wide variety of use-cases. I landed on webhooks as an ideal macro to develop, as many developer tools such as Jenkins and no-code tools such as Zapier use webhooks to trigger actions.
What it does
It's a pretty simple Macro: it allows a user to create a button that sends a request to a certain webhook URL. You can configure the Macro to configure the button text, the webhook URL, the HTTP method as well as the request body and headers.
How I built it
With a lot of trial and error as well as help from the Forge Slack!
Challenges I ran into
I'm not too familiar with React and Node.js, so I had to learn a lot from that.
Accomplishments that I'm proud of
It works pretty well and can provide immediate value.
What I learned
A bunch about Node.js and React development!
What's next for Atlassian Forge Webhook Macro for Confluence
I want to make it available on the Atlassian Marketplace so that other people can use it as well. Currently Forge apps don't support that, but hopefully they will in the future! I also open sourced the code (still deciding on a license) so people can use it as a base for their own applications.
Built With
atlassian-forge
confluence
node.js
react
Try it out
github.com | Atlassian Forge Webhook Macro for Confluence | A highly configurable macro for Confluence that allows users to trigger a webhook with the click of a button! | ['Robert Rose'] | [] | ['atlassian-forge', 'confluence', 'node.js', 'react'] | 273 |
10,045 | https://devpost.com/software/quick-filter-sum-up | Sum up time spent by a team
Sum up original estimate for a user
Sum up story points completed by a user
Inspiration
I noticed that on many Atlassian Forums people were complaining about not having an easy way to sum up their JQL queries.
Specifically, users wanted to be able to:
Sum up the
story points completed per assignee
Sum up a
custom field
created by the user
I encountered situations in the past where I wanted to see the summed up value of a filter AND the issues that make up that filter on the same page.
An app which let you pick the filter you want and select the field to sum up seemed like it would solve all of these recurring problems.
What it does
Quick Filter Sum Up lets you select a filter, select a field and sum up that field.
How I built it
I built it using ACE and Next.js. I used a
boilerplate
I created which lets you build ACE apps fast using modern frontend tools like React.js and Styled Components. It has a bunch of bundled features such as automatic license validation, cancellation page, loading components, Sentry integration, and some functions to make API calls from the frontend much simpler.
Challenges I ran into
I struggled with exactly how to calculate the summed up data.
I considered going through every Quick Filter on the server and creating webhooks for each one. Their sum would be recalculated whenever an issue field changed so they'd be available when a user loads Quick Filter Sum Up.
This approached seemed overly server intensive.
I settled on calculating the sum of the issues on the frontend when the app loads using a recursive function which goes through all issues in the filter. Although this can be slow, it's made much faster by only querying the field to sum up.
This approach saved 1000s of webhooks being created on larger Jira instances and still retained a good sum up speed.
Accomplishments that I'm proud of
I'm proud to have built an ACE app using Next.js. I was able to use the latest frontend tools without spending lots of time rejigging the ACE framework.
I was happy to solve a big pain point for lots of Atlassian users.
What I learned
I learned how to build a new app very quickly using ACE and Next.js. The hackathon was a great opportunity to try out my boilerplate and see where it was lacking and could be improved.
I also learned lots about the kinds of pain points Atlassian users experience.
What's next for Quick Filter Sum Up
To get traction on the Atlassian Marketplace and get feedback from users which can guide new feature development. I'd also like to create a server and data center version which reuses the bulk of my code.
Built With
ace
next.js
react
Try it out
marketplace-cdn.atlassian.com | Quick Filter Sum Up | Sum up any field using your existing Quick Filters. Quickly and easily see the number of story points completed per assignee, the summed up original estimate total for your project, and more! | ['Rhys Diab'] | [] | ['ace', 'next.js', 'react'] | 274 |
10,045 | https://devpost.com/software/navigator-for-jira | Administration Page of NFJ
Links on the Navigation Bar
Inspiration
We have several plugins for the on-premise side and we would like to migrate our plugins to the cloud, with this hackathon we would like to start this with Navigator for Jira.
What it does
It lets you add links to the top navigation bar.
How I built it
We used the ACE framework to build this plugin. Menu administration screen was already ready for on-premise but we also improved its visuality and we need to restrict it to single level because of a bug on Jira Cloud.
Challenges I ran into
We found a bug submitting dynamic modules that tides to another dynamic module and unfortunately contacting Atlassian Cloud Devs is very hard. I created a ticket (DEVHELP-4400) and no-one informed me or contacted back. Then I able to access one of Dev Ent. from Slack and he informed the related team and they created a public ticket for this bug
https://ecosystem.atlassian.net/browse/ACJIRA-2132
Accomplishments that I'm proud of
We're happy to have a cloud plugin finally.
What I learned
Easy, learned how we'll create plugins for Atlassian Cloud.
What's next for Navigator for Jira
Having multi-level menus!
Built With
ace
react
Try it out
nfj.whitesoftware.dev | Navigator for Jira | It lets you add links to the top bar. | ['Omer Faruk Ak'] | [] | ['ace', 'react'] | 275 |
10,045 | https://devpost.com/software/sprint-capacity | Program View Report
Sprint Capacity Bars
Inspiration
The constant need for a team to plan and review their work capacity, see their actual utilization, and review past sprints performance
What it does
We introduced a major update- the Program View Report.
The report presents both the sprint history performance indications, the current sprint KPIs and the future sprint planning potential.
This addition, helps the team to review the full program, rather than sprint by sprint evaluation. You can view the full team KPIs or drill down to the team members performance bars.
How I built it
It was built as add-on to Jira, using connect, REST API, Java
Challenges I ran into
Decision of what metrics are interested by teams (we perform a survey with several companies to get the most meaningful KPI and performance measurement needed by teams)
Gather and store information not supplied by Jira API
Accomplishments that I'm proud of
It seems that this is a missing tool for Jira scrum teams, and assists many teams to better perform from sprint to sprint
What I learned
What's next for Sprint Capacity
Automatic task/stories assignment for future sprints based on future sprint capacity and availability
Early warning prediction for missing out sprint content.
Built With
connect
java
jiraapi | Sprint Capacity | Track your planned capacity, track your Plan vs. actual, and retrospective based on measurments | ['Addons Experts Center', 'Itamar Ben Sinai', 'Shai Gilboa'] | [] | ['connect', 'java', 'jiraapi'] | 276 |
10,045 | https://devpost.com/software/custom-code-highlight-for-confluence | Highlight just the parts of the code you want to focus on including partial lines, and get automatic syntax highlighting of the rest.
Easy to just paste or type in code and add <highlight> and </highlight> tags to choose what to highlight
Inspiration
When trying to share our team coding best practices, I wanted away to show off our code in Confluence in a way which allowed me to show the full context whilst also bringing attention to the most important parts/examples.
What it does
It automatically detects the programming language being supplied, performs syntax highlighting of all of it and then specifically highlights the requested parts of the code and renders all of this as a Confluence macro.
How I built it
Using Node.js for ease of development, the Confluence connect API for the macro intergration and Docker for ease of hosting.
Challenges I ran into
It was very difficult to produce a generic system which would performing full syntax highlighting and maintain that highlighting whilst allowing the freedom for people to highlight whatever part of the code they wanted, whether that was half way through a line or function or not.
Accomplishments that I'm proud of
Solving the challenge above.
What I learned
It's actually really easy to create content to be rendered for Confluence macros ad it is just needs standard HTML.
What's next for Custom Code Highlight for Confluence
Responding to customer feedback to make it the best code highlighting tool available.
Built With
atlassian
confluence
docker
html
javascript
node.js
Try it out
marketplace.atlassian.com
grovrdev.atlassian.net | Custom Code Highlight for Confluence | An app to highlight specific lines and pieces of code in a Confluence Macro. Great for sharing examples of company style. Also automatically detect the code language and apply syntax highlighting. | ['Matthew Grover'] | [] | ['atlassian', 'confluence', 'docker', 'html', 'javascript', 'node.js'] | 277 |
10,045 | https://devpost.com/software/random-quote | Page View
Macro Configuration
Inspiration
I was inspired by a question on the Atlassian Community (
https://community.atlassian.com/t5/Confluence-questions/Showing-random-content-text-on-a-page/qaq-p/363607
). It currently has 300+ views. Also it was interesting to get my feet wet with Forge Beta to learn this new platform and to get new skills.
What it does
The app provides a Confluence macro which inserts to a page one single random text / quote from a list. It's super easy to use: just type the list of lines and the macro will randomly show one of them.
How I built it
I requested Beta access to Forge. As I’m back end developer I'm not familiar with Node.js and React so I built a hello world app using tutorials. Then I modified the app to meet my idea.
Challenges I ran into
II wanted to create a macro with RICH-TEXT body type as it is possible with Connect. It'd allow you to use UI components such as quotes, images, and GIPHYs. But Forge currently only supports body-less macro. As a workaround I use TextArea in the macro configuration. This is why the macro works only with plain text lines.
Accomplishments that I'm proud of
My creation resolves practical issues that people actually need to deal with.
What I learned
Through my work, I got a basic understanding of Forge.
What's next for Random quote
I'll wait for Forge to be extended to have a macro with a rich text body and update the macro to support all possible UI components.
Built With
forge
Try it out
bitbucket.org | Random Quote | Confluence macro which inserts to a page one single random text/quote from a list. It's super easy to use: just type the list of lines and the macro will randomly show one of them. | ['Aliaksandr Zuyevich'] | [] | ['forge'] | 278 |
10,045 | https://devpost.com/software/story-mapping-board-for-jira | Inspiration
The Idea came after reading Story Mapping book written by Jeff Patton. It could be tricky to prioritize hundreds of user stories in spreadsheet or Jira, you need to know which of them are the highest value features are so that you can build them next. An advanced technique to organise stories is more preferred than a messy product backlog. This is how user story map can help by a simple way to tell story and break it down into parts.
What it does
User Story Mapping has became a popular user story management technique.It is an engaging activity where all participants are involved in the process of building the product backlog.
DevSamurai User Story Mapping plugin brings all flowwing capabilities to you within Jira
A visual model of a Product Backlog from the users perspective
A tool for deliberate product discovery and learning
A way of creating a shared understanding
A method of exploring product capabilities and features
A prioritisation and release management tool
A way to build consensus between teams
A visual representation of progress and scope
How I built it
Built with Atlassian Connect
Frontend: ReactJS
Backend: AWS Lambda, DynamoDB, S3
Accomplishments that I'm proud of
500 installs after 2 months listed on Atlassian Marketplace
What's next for Story Mapping Board for Jira
Improve UI/UX and add more features to make the board more flexible to work with 2 or 3 level of mapping, release or sprint .
Built With
amazon-dynamodb
amazon-web-services
atlassian-connect
lambda
node.js
react
Try it out
marketplace.atlassian.com | Agile User Story Mapping Board for Jira | A a visual board which shows a big picture and all stories about the product from user's perspectives. A tool to discover, prioritize, plan, communicate and create shared understanding. | ['Shin Nagasada'] | [] | ['amazon-dynamodb', 'amazon-web-services', 'atlassian-connect', 'lambda', 'node.js', 'react'] | 279 |
10,045 | https://devpost.com/software/jira-toxicity-warning | Toxicity Warning Jira Issue Panel
Help your team avoid a toxic culture by identifying Jira Issues that could come across as insulting, threatening, or otherwise toxic... using machine learning.
Analysis is performed with TensorFlow.js in the cloud.
Technology
Atlassian Forge
TensorFlow.js
TF Toxicity classifier
Forge Issue
I tried to run TensorFlow.js on Forge, but ran into compatibility issues (
TypeError: this.util.TextEncoder is not a constructor at new PlatformNode (index.js:17446:28)
) that I think are due to the version of node being used. I talk about this in my video. After trying various options, I used Glitch to build a
lightweight API
around tfjs, then called it from my Forge environment.
Built With
forge
tfjs
Try it out
github.com | Jira Toxicity Warning | Help your team avoid a toxic culture by identifying Jira Issues that could come across as insulting, threatening, or otherwise toxic... using machine learning. | ['Andrew Cantino'] | [] | ['forge', 'tfjs'] | 280 |
10,045 | https://devpost.com/software/toxicity-warning-trello-power-up | The README for the repo.
A card that may promote a toxic culture.
A non-toxic card.
Toxicity Warning Trello Power-Up
Help your team avoid a toxic culture by identifying Trello Cards that could come across as insulting, threatening, or otherwise toxic... using machine learning.
All analysis happens locally using neural networks running in your browser with
TensorFlow.js
and your GPU.
Technology
TensorFlow.js
TF Toxicity classifier
Trello Power-Up API
Glitch
Installation
You can install this Power-Up from this repo by following the
instructions here
.
The
Iframe Connector URL
will be
https://trello-toxicity-warning.glitch.me/
and the icon is
https://cdn.glitch.com/13410d40-45af-4b97-b54c-d189f5a2e3c0%2Flogo-small.png?v=1591674427733
.
Built With
tfjs
trello
Try it out
glitch.com | Toxicity Warning Trello Power-Up | Help your team avoid a toxic culture by identifying Trello Cards that could come across as insulting, threatening, or otherwise toxic... using local machine learning in your browser. | ['Andrew Cantino'] | [] | ['tfjs', 'trello'] | 281 |
10,045 | https://devpost.com/software/slack-officebot-app-admin-forge-macro-app | Inspiration
Slack app developer was a bottleneck for any slack app office bot-message update that has to be done by Office Manager. What if we can eliminate the developer so that the Office Manager can schedule a message on her own without the need for developer support.
What it does
It lets you create instant Slack app message, schedule message & view schedules messages.
How I built it
Forge Marco app
for
Confluence
and using
Slack API
.
Challenges I ran into
Not able to use the Slack Node SDK, end up building my slack API calls using the Forge API fetch.
Accomplishments that I'm proud of
Eliminate the Slack app developer's need to create and schedule a message for the Slack office bot: no waiting time, freedom for Office Manager.
The zero learning curve for the Office Manager, Quicker to schedule messages, as office manager, is already comfortable using Confluence.
Instead of creating another Slack app-admin UI web app with worrying about server, hosting deployment, and security, Forge lets you build apps faster.
What I learned
You can create Forge apps faster and secure, without worrying about the hosting, design, UI frameworks for faster development.
What's next for Slack Officebot App Admin Forge Macro app
Delete scheduled message
Schedule message to a specific user, birthday wishes, anniversary …
Use current user time for scheduling the message
Built With
api
forge
forgemacro
slack
Try it out
bitbucket.org | Slack Officebot App Admin Forge Macro app | Create Instant message, schedule message & view schedules messages for Slack app. | [] | [] | ['api', 'forge', 'forgemacro', 'slack'] | 282 |
10,045 | https://devpost.com/software/jira-search-for-alfred | GIF
Jira search using Alfred
Inspiration
I've been using the
Alfred app
for macOS for many years to help me quickly find and open information. I had a very simple Alfred workflow which lets me open a Jira issue quickly by typing
Cmd-Space
then the issue key. It was super useful when speaking with someone who mentions an issue key; with that keyboard shortcut I'd have the issue they mentioned open in a second.
But that Alfred workflow was very basic and there was so much more I wanted to do, like search Jira when I don't know the exact issue key. The Codegeist competition was impetus for me to finally implement a fully featured search for Alfred.
What it does
The 'Jira search for Alfred' is a Forge app which lets you configure an Alfred workflow specifically for your Jira Cloud instance. It lets you pick projects you want to search on, then generates an Alfred workflow file which you download onto your Mac. Once installed into Alfred you can search your Jira Cloud instance by:
Typing an issue key — which shows you that issue and its linked issues
Typing a project key plus a search query
Typing
jira
plus a search query
Then select an issue by pressing the down arrow on your keyboard, and then press enter to open it in your browser. Once you're used to it you'll have issues open in a fraction of a second!
How I built it
The app turned out to be trickier than I expected because it required three distinct pieces of code: the UI code as a Forge app, the code to generate the Alfred workflow as a Netlify function / AWS lambda, and the Alfred workflow itself as a Python script.
Challenges I ran into
I had hoped I could generate the Alfred workflow directly inside the Forge app, but unfortunately that turned out to not be possible. Though Forge does provide functionality like web triggers which could theoretically download a file, they don't suit an Alfred workflow which is a zip file with a custom
.alfredworkflow
extension. Though it is possible to generate such a file entirely within Javascript, Forge doesn't allow the binary output in a web trigger response which would allow the file to be downloaded.
I ended up dealing with that by moving that part of the code to a Netlify function, which like a Forge is an AWS Lambda. The Forge app provides the UI for configuration, then hands over to the Netlify app to generate the file.
What's next for Jira search for Alfred
I'd love to work out a way to move everything into the Forge app so it can be self-contained. I don't think that's possible just yet but I'm looking forward to more features in Forge so one day it can take on full responsibility...
Built With
forge
gatsby
netlify-functions
react
typescript
Try it out
bitbucket.org
alfred-jira.netlify.app | Jira search for Alfred | Alfred is a macOS app which lets you quickly find and open information. This 'Jira search for Alfred' app lets find and open Jira Cloud issues instantly from Alfred. | ['Charles Gutjahr'] | [] | ['forge', 'gatsby', 'netlify-functions', 'react', 'typescript'] | 283 |
10,045 | https://devpost.com/software/to-do-forge-issue-panel-app-for-jira | Inspiration
I love Trello checklist and helps me to get more small actional items on my task. helps me to identify loopholes and which I might miss out and realize during the middle of the sprint. What if we can have todo for Jira?
What it does
Add to-do item
Delete to do item
Mark to-do item as done
Mark to-do item as not done
How I built it
I built it using the
Forge Jira issue panel
and
onJiraProject store API
to store todo data.
Challenges I ran into
Compare to my other projects, this one was straight forward and the only challenge was finding the
onJiraProject store API
documentation.
Accomplishments that I'm proud of
Able to create a todo list inside Jira story instead of using any 3rd party apps.
What I learned
Store API is simple to use and very powerful. You don’t need a separate database to store data for most of the cases of building Forge apps.
What's next for To do Forge issue panel app for Jira
Add expiry date for the todo item
Add a flag to distinguish different types of to-do
Add any new TODO list feature
Show number of items finished from the list
Assign a to-do item to a specific team member.
Built With
forge
forgeui
onjiraproject
storeapi
Try it out
bitbucket.org | To do Forge issue panel app for Jira | Create small actionable items for your Jira task & get the big picture. | [] | [] | ['forge', 'forgeui', 'onjiraproject', 'storeapi'] | 284 |
10,045 | https://devpost.com/software/product-ideas-forge-macro-app | GIF
GIF
GIF
Inspiration
What if we have a single source of great product ideas for next big opportunity for the product/company?
Anyone in the organization can contribute to the next big opportunity.
What it does
Able to add a new idea
List ideas based on the priority
View idea details and who created it
View all the ideas
How I built it
Understood the pain points and goals of the persona (Product manager).
Using Forge macro
Airtable
for storing the ideas data.
Forge UI components used
Table, Row, Cell, Head
Image
Avatar
ButtonSet
Button
Text
ModalDialog
Fragment
useProductContext
Challenges I ran into
Sometimes Forge app shows only Error -
error rendering app
, without further information about what's wrong with the current app. It actually took a lot of my time debugging this issue and try trial and error to get back to the working version of the app.
Layout, Forge offers a very limited setup of UI components, it was challenging to come with layout fit with sufficient white spaces.
Challenges with using icons in the Forge UI buttons
Accomplishments that I'm proud of
Able to provide product ideas by priority and help the team to focus on top priority feature quickly.
Ability to bring original contributor to the discussion, sometimes, ideas travel from one person to another person till it reaches implementation, we can invite the person to the discussion and understand the problem better.
Single source truth product ideas and all the employees can contribute to the success of the company.
What I learned
Forge has a hidden blue background button when the form is used in the model dialog.
You can use Forge UI Select and option components to create Rating UI.
jsx
<Select label={label} name={name} description={description}>
<Option defaultSelected label="1" value={1} />
<Option label="2" value={2} />
<Option label="3" value={3} />
<Option label="4" value={4} />
<Option label="5" value={5} />
<Option label="6" value={6} />
<Option label="7" value={7} />
<Option label="8" value={8} />
<Option label="9" value={9} />
<Option label="10" value={10} />
</Select>
Vertical spacing, it’s possible to have vertical spacing using the empty string Forge UI Text component.
jsx
{/* For spacing starts here */}
<Text>{' '}</Text>
<Text>{' '}</Text>
{/* For spacing ends */}
What's next for Product Ideas Forge Macro app
Add create Jira ticket from the idea details, so you can create the idea quickly.
The set expiration date for each idea and force team to work on or discord and trigger message when the expiration date is near.
Integrate with Google form, Typeform, Slack, WhatsApp
Built With
airtable
api
forge
forgeui
Try it out
bitbucket.org
anil-forge.atlassian.net | Product Ideas Forge Macro app | 💡 Great ideas can come from anyone. Collect the next big product ideas from your team. | [] | [] | ['airtable', 'api', 'forge', 'forgeui'] | 285 |
10,045 | https://devpost.com/software/clerk-invoices | Inspiration
I worked with Jira a lot while working in a service company and I know how painful to manually create invoices from Jira worklogs. So I have decided to build the app which automates this process!
What it does
The app that helps to create invoices from Jira worklogs in a few clicks, find uninvoiced time and build analytics on top of that.
You can find animated quick start guide here
https://helloclerk.io/help-center/getting-started/quick-start-guide/
it shows the step-by-step usage example.
How I built it
The process is pretty standard, I have started with research, then did a design with user testing, then development.
Challenges I ran into
A lack of time, so I had to hire 2 front-end developers to help me with a product
Accomplishments that I'm proud of
Since I have 20 years experience in IT, I have enough skills to make design, back-end development and devops by myself. So I have used all my possible skills at maximum here.
What I learned
The earlier I start getting feedback from customers, the better. Every product maker should learn marketing skills. It is like the idea worth $1, to create the product worth $10 and to sell it is $100. So I have read a few books on marketing and continue learning it.
What's next for Clerk Invoices
The plans are huge! I have tons of ideas after getting the feedback from first users and straight to Mars! 🚀😀
Built With
angular.js
css3
digitalocean
html5
mysql
php
restful
Try it out
helloclerk.io | Clerk Invoices | Automated Invoicing for Jira. The app that helps to create invoices from Jira worklogs in a few clicks, find uninvoiced time and build analytics on top of that. | ['Anton Skorniakov'] | [] | ['angular.js', 'css3', 'digitalocean', 'html5', 'mysql', 'php', 'restful'] | 286 |
10,045 | https://devpost.com/software/sprintsummary | Inspiration
We've had a hard time getting management and others to use Jira as our primary TO-DO list software.
We've got a handful Google Sheets that are shared with the appropriate people who need to know some summary information about the projects we're working on.
We worked with the Google Sheets to the point that they KIND OF look like our Jira sprint board, but more condensed.
The problem is a human has to do the condensing. A human has to update the Google Sheets. Maybe we can make the job a bit easier on the human.
What it does
JiraSummary allows you to connect Jira issues to cells on a Google Sheet.
The summary of Jira issues are formatted in the way that our outside departments want to see them.
How I built it
The plugin started with the
Atlassian-Connect-Express
source as it's base. Next was a proof of concept that the needed meta-data on could get stored on Jira issues. Then was a proof of concept that the Jira plugin could read & send data to the Google Sheets API. After that, all the ground work was laid out and from there it's all custom code to get & summarize Jira issues.
Challenges I ran into
It was very challenging to get started with the all the new APIs. It felt like an insurmountable learning curve when collecting all the docs & examples pages.
Accomplishments that I'm proud of
A lot of first evers. First ever JIRA plugin. First ever Heroku site. First ever Google Sheets API integration.
What I learned
The basics, like Googling error messages, are still important.
A ton about Jira plugin development.
What's next for JiraSummary
Robust formatting options:
Multiple stock summary formats.
Let the user choose to include
Assignees
,
Time Tracking
,
Story Points/Effort Remaining
etc.
Multi-Google Sheet Cell summary options like [ Development Status | QA Status ] .
Strengthening connection to Google Sheets API:
Charts!
Metadata on linked Google Sheets cells & ranges for persistence of data.
Peeking into linked cells to combat possible data overwriting.
Auto-sync to Google Sheets using webhooks or automation (if possible).
Built With
angular.js
atlassian-connect-express
google-spreadsheets
heroku | JiraSummary | You want to show Jira to management? It's TOO MUCH! What's this lane? Don't care? That lane? Don't Care? What's the summary? It's in JiraSummary. | ['Jesse Clifft'] | [] | ['angular.js', 'atlassian-connect-express', 'google-spreadsheets', 'heroku'] | 287 |
10,045 | https://devpost.com/software/assetforms-for-jira | Dialogs to add/edit assets of any type
Asset types view
Import API - easy import from Excel/CSV
Creating asset views, with all the options you may think of... Easy to add to Jira dashboards
Inspiration
We have an app for Confluence that does very well - it is called ConfiForms (
https://marketplace.atlassian.com/apps/1211860/confiforms-data-forms-workflows?hosting=cloud&tab=overview
)
But we always wanted to build something for Jira. And the natural choice has been to create something around teh domain we know best - "forms". And here it is - AssetForms for Jira (cloud)
What it does
It helps you to register and manage company assets right in your Jira.
How I built it
Using Atlassian connect / spring boot
Challenges I ran into
Asset API in Jira cloud is unfortunately very limited and we struggle very much to fulfil customer requirements and wishes because of that
Accomplishments that I'm proud of
Got first clients in under a week! :-)
What I learned
That we need to get a closer contact with Atlassian, and specifically with Assets API team to understand their plans and plan our work accordingly
What's next for AssetForms for Jira
Hopefully the limitations of the Asset APIs in Jira will be lifted and Assets API will have more attention and gets new features, so we can extend our app and integrate it deeper into Jira
Built With
atlassian
cloud
connect
jira
jiraservicedesk
jsd
Try it out
marketplace.atlassian.com | AssetForms for Jira and Jira Service Desk | Introducing AssetForms for Jira, the new app that puts you in control of all your company assets. Efficient and cost effective, integrated right in your Jira. | ['Alex Medved'] | [] | ['atlassian', 'cloud', 'connect', 'jira', 'jiraservicedesk', 'jsd'] | 288 |
10,045 | https://devpost.com/software/vs-code-forge-snippets-extension | GIF
Demo of Forge snippets VScode extension
Inspiration
Forge app developer documentation nice, but every time I have switched from code editor to developer documentation page to refer how to use new component. What if I can get a list of all available Forge UI components in the Editor itself? I want to make Forge app development even faster.
What it does
Provides Forge developers quickly access all the Forge UI components as Forge snippets in the VScode without switching between editor and Forge developer documentation page.
How I built it
Identified commonly used
Forge UI components
and created a list of code
snippets
for widely used Forge UI components with meaningful
shortcuts
and documented as
VScode snippets extension project
.
Challenges I ran into
Choosing commonly used Forge UI components snippets instead of creating snippets for all the Forge UI components.
Accomplishments that I'm proud of
Help to build the Forge app even
faster
.
Reduce
developer time referring to Forge documentation every time. Speed up of their Forge app development process.
Got a chance to look and read into
all Forge UI components documentation
.
What I learned
Code snippets can save a lot of
developer time
.
Make Forge app developers efficient with Forge snippets.
What's next for VS code Forge snippets extension
Support more
complex
Forge UI components and common
UI hooks pattern
snippets.
Built With
docs
json
markdown
react
snippet
Try it out
marketplace.visualstudio.com | VScode Forge snippets extension | Make Forge app development even faster with Forge snippets extension. | [] | [] | ['docs', 'json', 'markdown', 'react', 'snippet'] | 289 |
10,045 | https://devpost.com/software/virtual-health-checkup-modelling-of-coronavirus-technoband | Technoband
Software Modelling of Future conditions of CoronaVirus
Inspiration
Daily surge in cases, health conditions of citizens pushed me to work hard
What it does
It predicts the curve of future conditions of any country w.r.t. data set available
How I built it
I built it through software, that have been mentioned.
Challenges I ran into
Lots of challenges, but overcomes and got the results as expected
Accomplishments that I'm proud of
That I did something, which satisfies and help at least one citizen, then the chain will follow up.
What I learned
I learned new softwares, skills
What's next for Virtual Health Checkup|Modelling of CoronaVirus|Technoband
If got success, wanna make it open source.
Built With
arduino
c++
embedded
matlab
python
webex | Virtual Health Checkup|Modelling of CoronaVirus|Technoband | Future prediction with Virtual checkup online and Smart electronic band | ['Shreyansh Pagaria', 'Maor Mashiaxch'] | [] | ['arduino', 'c++', 'embedded', 'matlab', 'python', 'webex'] | 290 |
10,045 | https://devpost.com/software/todos-mas-cerca-r13v4x | Inspiration
we want to support every kilometer of the planet to revive the economy
What it does
Our platform supports giving visibility to all businesses close to users, supporting small businesses to reactivate their sales, thus preventing them from going bankrupt and large chains being the ones to keep these revenues. Focusing on the collaborative economy and fair trade
How we built it
A group of Ecuadorian entrepreneurs developed a platform to connect the owners of commercial establishments with their clients. They are:
www.todosmascerca.com
Ricardo Mancero and Andrés Dueñas, project leaders have been working for several years in the development of digital projects and during the quarantine process due to Covid19; They looked for a technological solution to help those most economically affected by the crisis. The premise is to prevent people from crowding into supermarkets and help revive the economy of small and medium-sized companies, which have been forced to close their operations due to a lack of customers.
Challenges we ran into
Revive the small business economy.
Avoid crowds.
Digitize small businesses.
Connect 1km around users with shops.
Connection facilities between businesses and users through a webapp.
Visibility of small businesses due to scarce advertising resources.
Accomplishments that we're proud of
This Startup has been very well received at the international level, being chosen by Unesco to spread it worldwide within its #YouthOfUnesco program. On the other hand, the Inter-American Development Bank in its IDB LAB platform has placed the project within “COVID-19 Map of Innovators of Latin America and the Caribbean”.
In Mexico, the venture was chosen as the winner in the call "Hack The Crisis Mx" among more than 400 proposals. He was chosen winner in the economic reactivation category in the "Hacking Covid" call organized by the government of the Canary Islands-Spain.
Currently the project is as a finalist in the call: "Ecuador Post-Crisis Hackathon" and as a finalist project in the "Ideas for Our Mexico" contest with which they have managed to reach the final among more than 1500 proposals.
What we learned
We learn to get to know people closer, understanding their needs and anxieties, and we continue learning as we want to reactivate the planet's economy.
What's next for todos mas cerca
1.- The next steps is to have a multichannel bot that connects users with businesses 1km around.
2.- implement payment gateways, so that the user can buy through the platform
3.- Develop an ERP for the inventory of shops, so that when a user wants to search for example nutella, they can see according to their geolocation which store has nutella.
4.- create our own delivery app
5.- connect farmers with businesses to generate fair trade
6.- We have a fremium model, which means that any business can have an ecommerce website if they wish, we want to democratize electronic commerce.
Try the platform
Go to
https://www.todosmascerca.com
In the address field next to the city “Quito”, write a Quito Street for example “6 de Diciembre”, and choose a category for your search, for example “restaurants”
Press the search button and you will get the option, to move the pointer to get the best place close where you are.
Press search in the red button to confirm your location and get the results.
Nice! You can see now the stores inside the category you choose, nearest you, and the number of other stores from other categories, and contact them by whatsapp.
Of course you can choose the map view, just clicking in the icon on the top of the list, and check your location.
As a store:
As store you can go to:
https://www.todosmascerca.com/registrar
Go to the bottom of the page and fill the form, we include the location of your store using google maps pointer move, or autocomplete functions.
You have to fill all the fields, and click on register.
Check that the all the information is correct before proceed-
Nice, you are inside Todos más cerca!
Built With
amazon-web-services
angular.js
apiwhatsapp
digitalocean
google-maps
html5
mongodb
whatsapp
Try it out
www.todosmascerca.com | Todos más cerca | We are the first platform that connects businesses and users 1 km away through whatsapp. | ['Ricardo Mancero', 'Xavier Flores', 'carilucas'] | [] | ['amazon-web-services', 'angular.js', 'apiwhatsapp', 'digitalocean', 'google-maps', 'html5', 'mongodb', 'whatsapp'] | 291 |
10,045 | https://devpost.com/software/life-skills-and-techniques-l53g0m | successful life quote
Inspiration
success is not final and failure is not fatal
What it does
Help become successful in life
How I built it
through successful people inspiration
Challenges I ran into
financial challenges and how to get my quotes
Accomplishments that I'm proud of having all that I want make my quotes
What I learned
Hardworking leads to success
What's next for life skills and techniques
how to become rich
Built With
language | life skills and techniques | To help people become successful in life | ['Nyarko Elvis'] | [] | ['language'] | 292 |
10,046 | https://devpost.com/software/queue-with-kyoo-4ocd2h | Choose location to get in line
Enter your phone number and indicate when you will arrive
Select what time you will arrive (upcoming feature)
Confirmation that you have a reservation in line
Ability to place and order while you wait and have it brought to you in line
SMS messages notifying customers of their progress in the queue
Line manager dashboard (upcoming feature)
Scannable QR code to join the line
Inspiration
The other day, a member of our team went to Trader Joe’s to pick up a couple groceries and found themself in quite the predicament. It was a boiling hot day in San Rafael and the line outside was over 30 people long, with everyone standing 6 feet apart on the makeshift painted yellow lines for proper social distancing. They noticed Trader Joe’s had three people dedicated just to managing this line, with two people at either door counting people and one person bringing out waters so customers wouldn’t overheat – they still did. Meanwhile, everyone in line was getting anxious because it was unnerving to be in such close proximity to so many people (many not wearing masks) for such a long period of time, despite all social distancing precautions.
Since the COVID-19 crisis hit, many retail stores and grocery outlets have this same issue, and all of us are suffering waiting in lines. With more people leaving their homes and summer heat fast approaching, we’re positive that the pain experienced waiting in line will only get worse.
What it does
Queue with Kyoo is a simple line management solution built on top of Square that helps solve the pain of long socially-distanced lines at retail shops, grocery stores...anywhere with a socially-distanced line, because of limiting the number of customers in a store.
Here’s how it works for customers:
Customers enter the queue one of three ways:
i) scan a QR code (we’ll help you generate one that is on-brand)
ii) visit your custom link (e.g. kyoo.tech/yourbusiness)
iii) in-person: an employee will issue a number (like at a meat counter)*
Customers will be notified via text when they are “next in line”
Customers will be notified via text when they are allowed to enter
Customers are offered the opportunity to place a “while you wait” order, which can be brought to them while they are waiting in line. This option is perfect for getting a bottle of water or a free coffee (if you happen to be using this at Trader Joe’s!). “While you wait” order may also be used for essential items such as a pack of toilet paper or a carton of milk so the customer never needs to enter the store and the customer can complete their order and be sent on their way, which makes the line more efficient for other customers placing larger orders.
*in-person customers who do not wish to receive text updates can simply listen for their
number to be called, the old-fashioned way
Here’s how it works for businesses:
The “line manager” tells customers to either scan the QR code or type in a shortlink, or for those not wishing to provide their phone number, he/she can manually enter his/her own phone number using his/her own phone and provide the customer with a paper spot-in-line number.
Line manager uses Square POS to advance the line by changing order status for customers reaching the front* (*note: we intend to replace this with our own automated “line manager” per the attached designs). The following are the status equivalents:
NEW = CUSTOMER IS IN LINE
IN-PROGRESS = CUSTOMER SHOULD CHECK IN WITH LINE MANAGER
READY = CUSTOMER CLEARED TO ENTER THE STORE
COMPLETE = CUSTOMER HAS ENTERED STORE, INCREMENT COUNT
Upon changing order status of each “spot in line,” customers receive a text message to either begin heading over to the store entrance or that they are now allowed to enter the store
Line manager asks for the confirmation number (order #) to allow the customer to enter the store
Queue with Kyoo was specifically designed with COVID-19 in mind – minimizing the time and anxiety of standing outside near other people. With summer fast approaching, customers will also feel much happier and safer waiting in a virtual line – they can stroll around the block or wait in the comfort of their air-conditioned vehicle until it’s their turn!
How we built it
To build Queue with Kyoo, we made use of Square’s new $0 order capability to enter each customer in line as a new $0 order with a saved customer (including their phone number for contacting them). We added a new route and environment for the customer to go to our “/line/” links, where they could begin by entering their phone number and immediately enter the line. We wanted this to replicate the simple experience of tearing off a ticket at a meat counter and waiting for your number to be called. In our case, we’re using Twilio to text the customer when their number is being called so they know to enter the store.
We’re using the Orders API to create the $0 order for each customer who joins the line.
We’re using the Customers API to create a customer with a phone number so the line manager has the option to contact them and our backend is able to send them status updates about their position in line.
We then provide a confirmation screen that provides the customer with their spot in line and offers them the option to place a “while you wait” order. Clicking this redirects the customer back to the merchant’s Kyoo Pickup page, where the customer can place regular orders.
Challenges we ran into
The Square Orders tab in the Point of Sale app does not allow us to rename the states to become more applicable to a line, so we probably will need to build our own UI for the employee managing the store’s line. For example, we are using “Picked Up” to mean “Entered the Store” and while this is fine as a hack, it may be too confusing for something we could release as a product.
We wanted to use a Square item to model the number of people in the store at a given time, but this won’t work for people scheduling their spot in line in advance, because the quantity will be deducted at the time the place the order. -- We would need to control when the quantity moves in order to use the item quantity to model the number of people in the store.
We tried to make this very simple with just the phone number input, but we found that a merchant probably will need more sophisticated features and UI, and we did not have time to build these features into the hackathon version, so we decided to launch something basic but fully design the end product so we can finish it after the hackathon. We are including the fully featured version’s design in the submission as it took a lot of work.
Accomplishments that we're proud of
We’ve already contacted a few grocery stores, hardware stores and boutique businesses and are fielding inquiries even before we officially launched the feature
Queue with Kyoo helps customers stay safe in the comfort of their own vehicle or they can take a walk in the neighborhood and not be too close to other customers; it’s also especially helpful for people with disabilities and older persons, so they are not waiting outside in the elements
Businesses can shift staff from counting customers/dealing with a line, to bringing essential/while you wait orders out to customers, reducing the number of people in the store/keeping customers happy/generating additional revenue for the store
We built this feature in under two weeks
What we learned
Businesses are requesting to have scheduled Queue with Kyoo (see fully featured designs attached)
What's next for Queue with Kyoo
Roll this out at a large grocery store (like Trader Joe’s) and also offer the ability to order “while you wait” to some of our existing merchants who experience long lines
Test the extensibility of this feature for solving all types of line problems and offer it to overloaded locations which are experiencing especially long lines due to COVID-19. We believe this same technology would be equally effective at solving a line problem at a walk-in clinic, bank, COVID testing center, or post office/shipping center
Give customers the ability to schedule a time to enter the business (i.e. make a “reservation”) and add custom limits for the number of customers who can reserve each time slot
Create a “smart throttling” system that allows more customers to enter the store when there is still space and cuts off the line when the limit is reached. The fairly closely resembles the “clicker” that a bouncer uses to monitor how many people are in a venue at any given time
Built With
angular.js
spring
square-customers-api
square-orders-api
square-transactions-api
twilio
Try it out
kyoo.tech | Queue with Kyoo | Social distance lines suck. Queue with Kyoo is the line management solution that lets you join a virtual line and receive a text when you're allowed to enter – you can even order while you wait. | ['Ruth Nott', 'Donald Johns', 'Albert Brown'] | ['First Place - Retail'] | ['angular.js', 'spring', 'square-customers-api', 'square-orders-api', 'square-transactions-api', 'twilio'] | 0 |
10,046 | https://devpost.com/software/inventory-squared | Inspiration
My wife and I own a candy shop and updating inventory when receiving new shipments was very time consuming. I wrote Inventory
Squared
to enable multiple people to use phones (or tablets) to update inventory. We no longer have use the POS or crowd around the store laptop to update Square inventory. We also use the app when we are recounting items.
What it does
Inventory
Squared
uses the phone's or tablet's camera as a UPC barcode scanner. After the user logs into their Square account, they select if they are receiving new stock or recounting existing items. Next, they hold the camera over barcode. Inventory Squared automatically recognizes the UPC and displays a popup. The user can enter the number of new items or recount of existing items. The app updates Square inventory and returns to scan mode ready for the next barcode.
How I built it
Inventory
Squared
was written using Apple's Xcode and uses the SwiftUI framework.
Challenges I ran into
The authentication process was the biggest challenge.
Accomplishments that I'm proud of
I'm most proud of the app's ease of use and its speed.
What I learned
I learned the Swift framework and several Square APIs.
What's next for Inventory
Squared
When possible using the Inventory API, I want to add the ability to handle items that are sold by weight.
Built With
amazon-web-services
inventory
location
merchant
oauth
swift
Try it out
inventorysquared.com | Inventory Squared | Inventory Squared allows you to update your Square inventory in a flash using only a mobile device. The app uses the camera to scan UPC codes and allows a users to add or update item counts. | ['wwashington Washington'] | ['Second Place - Retail'] | ['amazon-web-services', 'inventory', 'location', 'merchant', 'oauth', 'swift'] | 1 |
10,046 | https://devpost.com/software/fetcha-just-sit-we-ll-fetch | Inspiration
COVID-19 shutdowns have been hard on us all, but pubs and bars have felt the effects more acutely than others. This has hit our family particularly hard, with our brother having to shut down his venues during the lock down. Thankfully, restrictions are starting to ease and reopening is on the horizon, but food and beverage businesses must adapt to this new environment.
Given the current restrictions, there is a renewed push for businesses to move towards separated table service, with minimal interactions with staff and other patrons. For the foreseeable future, walking up to a busy bar to order a drink may be a thing of the past.
Fetcha enables food and beverage businesses to easily transition into this new world, offering a simple, easy and seamless way to offer table service to patrons.
What it does
Fetcha is the easiest way for food and beverage stores to offer safe table service to their customers. Once linked with the merchants square account, Fetcha builds a digital menu using all of the items already stored in their Square point of sales system. Merchants can then issue QR codes for all the tables in their venue, allowing customers to simply order from their seat. This provides huge value to small businesses, helping them grow and adapt.
QR Code and Digital Menu
Customers can easily scan QR codes that have embedded locations and table numbers, which are sent along with customer orders. The menu itself is built using the items that the merchant already has stored in their Square Point of Sales system.
Online Checkout
Online check-out is quick and simple, using Apple Pay, Google Pay or Square's credit card payment form.
Merchant Dashboard and OAuth Flow
The merchant dashboard allows venues to generate QR codes for tables at any of their locations. They can also toggle on or off the contact tracing feature.
COVID Contact Tracing
Many jurisdictions (including our own state of Victoria in Australia) are mandating that venues keep a list of all patrons who attend. Our contact tracing feature ensures that these details are kept securely by the merchant, and accessed only by request of health authorities.
How we built it
We have taken advantage of many of the APIs Square has to offer, including:
Catalogue API
Orders API
Payments API
Locations API
Merchant API
OAuth Flow
We have also implemented our own account and authentication system using Firebase.
Our front end code is built using Typescript, React and Grommet UI. Our back end code is built using Typescript, node.js, Firebase Realtime Database and Firebase Functions.
Challenges we ran into
We ran into several challenges around how to make this as easy and seamless for the customer as possible. We are really happy with the QR code mechanism and the simplicity of checkout.
Accomplishments that we're proud of
We are really proud about the seamless UX and the design that we have implemented in this application. We have also taken advantage of many of the APIs Square has to offer, and have a road map (se below) of all the other features and APIs we want to build out!
What we learned
We have learnt a lot about Square APIs, secure OAuth flows, Firebase Functions and how to use QR codes effectively.
What's next for Fetcha - Just sit, we'll fetch!
We are excited to announce a partnership with Chei Wen Wine Bar and Fly Lie Bar in Melbourne! We are planning to launch with these venues as they re-open from COVID-19 lockdown. Both of these venues currently do not offer table service, and would be difficult / unfeasible for them to operate without the use of Fetcha.
We also have a long backlog of features we are developing to incorporate into the app including
Menu builder
- offer merchants and even easier process to build their items online, including stock photos and suggested descriptions.
Customer accounts
- integrate with Square's customer APIs to enable card on file payments and a more personalised experience
Rewards & Loyalty
- take advantage of Square's Loyalty API to offer rewards to customers
Merchant branding
- Give merchants the ability to theme and brand Fetcha with their own fonts, colours and logos
Printer
- integrate with a docket printer so orders are automatically printed
User experience
- further iterate on the user experience to provide a seamless ordering and checkout experience
...and heaps more!
See it all at
https://www.fetcha.app
See our code repo at
https://bitbucket.org/kylemantesso/fetcha/
How to test
Landing page:
https://fetcha.app/
Menu:
https://fetcha.app/cheiwen
Merchant:
https://fetcha.app/merchant
Username:
[email protected]
Password: tester
Scan this QR code to pre-populate location and table:
http://fetcha.app/assets/docs/qr-example.png
Built With
firebase
grommet
node.js
react
squareapi
typescript
Try it out
fetcha.app | Fetcha - Just sit, we'll fetch! | Fetcha enables food and beverage businesses to easily transition into this new world, offering a simple, easy and seamless way to offer table service to patrons. | ['Kyle Mantesso', 'Will Mantesso', 'Madison Hunt'] | ['First Place - Food & Beverage'] | ['firebase', 'grommet', 'node.js', 'react', 'squareapi', 'typescript'] | 2 |
10,046 | https://devpost.com/software/voice-order | Voice Order app logged into Burger Boy account.
Admin interface showing menu.
Voice Order ready to take an order.
Creating a new order via voice commands.
Ready to accept payment.
Voice Pay app while creating order.
Voice Pay app ready to make payment.
Inspiration
As a care giver, I have been hyper-sensitive about my contacts in this COVID-19 world. In looking for ways to use technology to improve on processes, I considered my local small businesses. Order taking requires risky face-to-face dwell time that can be limited with the right solution.
What it does
Voice Order implements an automated contactless order taking and payment service using a voice-enabled kiosk and Square services for a catalog of items, order logging, payments, and loyalty rewards. The kiosk runs on an iPad and interfaces with 2 printers - one for the customer to print their order ticket, and one for the kitchen or fulfillment area for prepping the order. There is a companion Voice Pay app that interfaces over bluetooth with the kiosk Voice Order app. The Voice Pay app identifies you to the service, and enables contactless payment via a credit card with Square, or Apple Pay.
The merchant logs into the Voice Order app and can set up their service by identifying their printers and reviewing their menu. They can also review recent orders. When ready, they enter kiosk mode in the app to take orders. A user launches the Voice Pay app and brings their phone near the kiosk to sync. They are then presented with a guided menu of things they can say on the kiosk to place their order. As they speak to the kiosk, it assembles their order and shows the total cost. The Voice Order app automatically applies any earned rewards, such as a free item. When done they can add a tip, and finish their order. The kiosk then prompts to make a payment on their Voice Pay app. When that's done, the kiosk shows confirmation and prints a confirmation slip on the nearby Brother printer. This serves as an order confirmation for the user, an includes their order number, order items, total cost, and loyalty points. The order is also printed on the "kitchen" or backroom printer for preparation or fulfillment.
The system is then ready for the next customer.
The whole system uses the Square service to host the order item catalog, to record orders, take payments, track customer loyalty, etc.
How I built it
I created 2 iOS apps in Swift - Voice Order and Voice Pay. I used the Brother SDK to interface to the 2 printers. The Voice Order app uses iOS voice recognition technology to implement the order taking process. Both apps use bluetooth technology to synchronize information between them. They both use the Square SDK to interface with the payments service. The Voice Order app further interfaces with the Square service over their REST API.
Challenges I ran into
There were numerous challenges in building this service from scratch. First, getting the voice interface working so that one can navigate through a series of hierarchical menus took a lot of experimentation and testing. Second was interfacing to the Brother printers, which took a while to learn, but I had some help from Brother support. Third was implementing the bluetooth sync interface between the two apps. That was very hard to debug any issues. Finally, interfacing to the Square service took a while to figure out, debug, and test. The payment SDK was somewhat easier to integrate, and there was some good example code. But the REST API required a lot of experimentation with the API explorer, trial and error in the code implementation, and proper sequencing of the calls to effect the transactions.
Accomplishments that I'm proud of
I'm very happy with the progress I was able to make in just a few weeks. While it still needs work before deployment, it's working well as a demonstration. There were a lot of pieces that all had to work together to even get to that stage.
What I learned
I learned a great deal about each of the various pieces. How to implement a voice-controlled interface, how to talk to Brother printers, how to sync information over bluetooth, and how to work with the Square service with their SDK and REST API.
What's next for Voice Order
I want to identify a local merchant where I can field test the service. There is still work to do for account creation, merchant definition, menu editing, and some other components before Voice Order is ready for deployment.
Built With
bluetooth
brother
ios
square
swift | Voice Order | Voice Order is a contactless automated order taking service for use by restaurants, food and beverage locations, and the retail industry. | ['Ed Arenberg'] | ['Second Place - Food & Beverage'] | ['bluetooth', 'brother', 'ios', 'square', 'swift'] | 3 |
10,046 | https://devpost.com/software/streammd-5vb9ix | Appointment Scheduling
Patient Signup
Test results
Labs and Doctor's Note
Here's the whole story
Be sure to write what inspired you, what you learned, how you built, and challenges you faced.
Inspiration
What it does
What I learned
What's next for StreamMD
When the Covid-19 pandemic landed here in California in mid-March, I was building a concierge telemedicine platform called Opt Health focused on addressing and optimizing men’s health issues through proactive and preventive medicine protocols, including hormone therapy and sexual health. We were getting close to launch but decided to put Opt Health on hold because the onboarding process requires an in-person visit between our licensed practitioners and our clients and we felt it both tone deaf and logistically challenging to launch during these times
The same week, a physician friend of mine in San Diego that knew about Opt Health called to inquire whether it might be possible to use our platform to see patients, at a social distance. Like many physicians and other healthcare workers, he was very concerned about his own, and his staff’s, direct exposure to patients that may have an active Covid-19 infection. Within days, several of his physician friends and colleagues also wanted to use our platform for the same reason.
We saw a massive opportunity, not only from a business perspective to repurpose portions of our technology to create a new product line, but more importantly, to meaningfully contribute to the global fight against the coronavirus pandemic. We decided to build a Covid-19 telemedicine solution called StreamMD that allows licensed physicians to screen, treat, and test (we have access to FDA EUA home-collection test kids) patients while minimizing community spread, mitigating person-to-person infection, and reducing unnecessary and inefficient overflow of patients in emergency departments at hospitals.
In addition to StreamMD facilitating live medical consultations while keeping doctors and patients safe, StreamMD is contributing to the reemergence of cautious commerce by partnering with leaders in certain sectors and industries that have essential and non-essential employees that require a screening, Covid-19 test, or return-to-work letters in order to safely perform their job functions. We believe that when and as society is prepared to re-open and slowly return to business as usual, it should occur in the most prudent way possible.
We wanted to make a difference and help during these unprecedented times, and we believe that StreamMD is an invaluable tool that both businesses and consumers can utilize to stay safe, healthy, and productive.
During this journey, I learned many things. I learned that our doctors, as one of the primary user groups, could be and were tremendously helpful in designing certain portions of our product. In fact, Opt Health’s chief medical officer, Dr. John Tidwell, has an engineering degree, which proved extremely useful in creating a doctor UX for scheduling using DrChrono, consultation, and post-consult note that is clean, smooth and seamless. To wit, any physician can be trained to successfully use our platform in less than ten minutes. Currently, StreamMD has eight physicians on board and can scale quickly and nimbly. I also learned that Covid-19 disproportionately impacts African American and LatinX populations, and in response we are actively developing partnerships to make our services available to impacted communities.
Finally, I learned first-hand about the power and ability of a group of dedicated people to rise and meet challenges in the face of fear, uncertainty, and chaos. Many people during the last couple of months were frozen, unproductive, or worse; however, our team was able to build something from scratch that has the potential to save lives. That is very real, and I am proud of that accomplishment above all else.
The future of StreamMD is promising, and exciting. We are presently: exploring new business opportunities and partnerships to get StreamMD in front of the right people in the right sectors to get people back to work; deploying the service to disproportionately-impacted populations; and continuing to test and improve the platform with ongoing feedback from patients and physicians.
How I built it
Using APIs we combined Dr. Chrono, OpenTok and Square Payments to create a HIPAA compliant telemedicine solution!
Challenges I ran into
Before saving the final clinical note, we needed to store and retrieve the patient intake data in a HIPAA compliant manner before saving the final note in discrete templates. We ended up using a “hidden” form field on Dr. Chrono Clinical Note Template to store patient data as json.
Engineering Accomplishment that I'm proud of
Distributive Appointment Reassignment Solution. When a physician has to cancel, we seamlessly reassign the appointment to another available physician with the least amount of appointments.
2 Video Demos
In this demo
, the patient registers as a StreamMD user and schedules and pays for an appointment. The patient’s health data and appointment is stored in Dr. Chrono and the payment is handled through Square Developer API. After the patient meets with their physician, they are redirected to purchase a COVID-19 test. This payment also uses Square Developer API.
In this demo
, the physician logs in to join an appointment with a patient. The clinical note is pulled from the Dr. Chrono API and can be reviewed before and during the call. Afterwards, the physician edits and saves the notes back into Dr. Chrono.
Built With
amazon
drchrono
heroku
javascript
node.js
react
sequelize
square
Try it out
streammd-dev.herokuapp.com
www.streammd.com | StreamMD | StreamMD is the first full-service Covid-19 testing and treatment telehealth company to get your team back to work. Built by doctors for everyone! | ['Greg Tidwell'] | ['First Place - Healthcare'] | ['amazon', 'drchrono', 'heroku', 'javascript', 'node.js', 'react', 'sequelize', 'square'] | 4 |
10,046 | https://devpost.com/software/curatio | Connecting with a doctor
Locating nearest hospital
Locating nearest pharmacy
Login page
Inspiration
We wanted to come up with a simple solution for contactless healthcare.
What it does
Curatio helps patients connect to doctors and receive information regarding healthcare according to the patients needs as much as possible without physically being in contact with the doctor or be at a hospital
How we built it
Curatio has been made using the Flask web framework and Node.js runtime environment. We built it by combining multiple modules made from scratch, APIs from square and google cloud and also some open source modules that were made available to the public on the internet.
Challenges we ran into
We had a difficult time building a database management system for the logging in module for the webapp. We also faced some challenges when implementing the video calling feature but much research and trials, we managed to make it work. Another challenge we were facing was trying to find the user location for our map based features but in the end we managed to overcome all of them.
Accomplishments that we're proud of
We are proud of what we have built so far and believe that it is a well thought out solution for contactless healthcare. It was an amazing learning experience for us.
What we learned
1) To make a low level database and manage it
2) How to build a login and sign up system from scratch
3) How to use flask
4) How to use google maps API to find nearest locations of specific type of places (pharmacies/hospitals)
5) How to create a search filter
6) How to use node.js
7) How to build a video calling webpage using webRTC
What's next for Curatio
We hope to build it into an even more well designed and full of features webapp that can help both doctors and patients during this time of social distancing.
Built With
css3
flask
html5
javascript
json
npm
python
Try it out
github.com | Curatio | Webapp that helps patients connect to specific doctors, find hospitals and pharmacies . | ['Meah Tahmeed Ahmed', 'Rahat Al Shehab'] | ['Second Place - Healthcare'] | ['css3', 'flask', 'html5', 'javascript', 'json', 'npm', 'python'] | 5 |
10,046 | https://devpost.com/software/profit-fw5oyn | Inspiration
We all know by now that as an effect of Covid-19, large numbers of people are losing their jobs at no fault of their own, but globally, fitness professionals are getting hit harder than most. From Taekwondo, to CrossFit, to Pilates, the fitness industry is a powerhouse for small businesses and independent professionals, but there are drawbacks to not being a part of large corporations. Our eyes were immediately opened to the sharp decrease in people attending the gym, forcing most trainers and instructors out of work. The problem plaguing them isn't that they face huge competition, or that they've lost demand, but that they, as individuals, can't market themselves or put themselves into the world. The best way to help these professionals get back on their feet is to build an application that allows them to safely develop and market their business in a place that will be seen, and trusted by many users. Seamless transactions, cutting edge technology, and a passion for fitness set us aside. Accomplishing this was the goal of ProFit, and we are thrilled to have completed it, ready to share with the world. ProFit - Financial profit for fitness professionals!
What it does
ProFit targets the many needs of fitness professionals such that they can build and spread their business across a platform that encourages social distancing and ease of access for both trainers and users. Trainers can build and customize a personal page detailing their skills, prices, and other specifics as to peak interest in trainees similar to them, this works vice versa as well. Flexible pricing options at every step of the way lets professionals using the app run their business on their terms, not on those of the epidemic.
It allows trainers to schedule both live streams, which can be broadcast to thousands of viewers, and video recordings for their customers, as well as entering 1v1 private sessions where users can emulate the experience of having a personal trainer, just like if things were normal. Furthermore, our On Demand option enables trainers to put out pre-recorded videos, with simple workout routines that customers can purchase and view at their leisure in seconds.
With cutting edge technology like pose detection for aiding trainers in assessing customer performance beyond the 2D limitations of screens, and dashboards and statistical tracking of customer purchase that enable professionals to assess when / where / how they can ideally maximize their profits and grow their brand, our app transcends what's possible with rudimentary solutions like logistically difficult zoom calls, or videos online. This, implemented with our seamless in-app payment system, allows for groups of trainers to finally have a place to grow their business around during around and beyond the times of Covid-19. Customers, in turn, are given an easy, accessible platform where in spite of the virus they can continue to pursue their aspirations of getting in shape.
How we built it
ProFit is the fusion of new technology, and beautiful design. To build our app, we used flutter, a popular cross-platform app development framework that works with android and iOS. It's great for quick development cycles since refreshing and reloading code is so fast. It's also really flexible, and allows development of beautiful user interfaces.
For our database storage, the core of our app that allows for scheduling, tracking and storage, we used Firebase Storage, Authentication, and Firestore.
For video storage, for our on demand functionality, we also use firebase storage. Due to the limitations of firebase storage, and to limit cloud storage costs, we use ffmpeg, an open source project dedicated to video compression. We implement this and write video streaming code to optimize video storage by over 70x and enables us to go much further with much less with the ondemand service within our app.
Our streaming platform is built using agora.io, a platform which simplifies the process of creating high quality streaming experiences. We use their flutter SDK to do this. For our pose detection functionality we use tensor flow lite's flutter plugin, and use an implementation of the famous PoseNet architecture for real-time pose detection which, using algorithms on a time-series, we can accurately generate scores on how accurate student actions are given a 'correct' action, this technology generalizes to any motions, which is good considering the wide diversity our platform caters to (danse, exercise, martial arts, etc.).
Perhaps most importantly, money, or the in-app transactions that define our app as a marketplace where fitness professionals legitimately can make up for, and thrive despite the coronavirus and beyond. This was powered by none other than Square's in app payment SDK.
Challenges we ran into
We had more than our fair share of errors and challenges to overcome in the process of creating ProFit. We'll go ahead and put them in list format for you :)
Setting up pose detection on TensorFlow lite was shockingly difficult. Once we had a model we had to spend a long time figuring out why it wouldn't load, to learn we had to set it up slightly differently with another model file.
The process for getting video compression, and setting up that aspect of our service was perhaps one of the toughest, more grueling parts of the app since first we rapidly ran out of storage, learning we needed to compress, going through several compression libraries, optimizing the algorithms to the point where compression was sufficient, and everything ended up taking a couple of days. Truly the technical challenge of the project.
One of the more frustrating (and somewhat funny) problems we ran into a lot during the project was work overlap and git errors, accidentally doing the same stuff as some of our counterparts, having code bounce between working and not working between commits, and a whole pandemonium of other annoying errors. Either way, we worked through it and are all the prouder.
Accomplishments that we're proud of
We're proud that we were able to work through this app timely and finish everything that we sought to accomplish with this app. We're proud that we were able to finish on time, which we weren't necessarily expecting fully, and take the app to it's full potential.
What we learned
There was a ton of technical learning that went on. We learned about flare and flutter animations, ffmpeg and video compression, streaming apps, in-app payment with square, tflite (we already new machine learning), and more. Technical skills aside, we all learned a great deal about group communication and working as a team. This aspect of a hackathon is magnified when given only a short time to complete the project, where each mistake could be crucial. We're also very proud of learning about Square's system of payments, and the ease for developers like us to integrate Square tools into the app, which helped us expand our coding knowledge to the business area as well.
What's next for ProFit
As cliche as it sounds, we truly plan on releasing ProFit to the public as quickly as possible in order to get this platform available to trainers worldwide and to give users a way to continue their physical lifestyle throughout the social isolation period. We see this legitimately as a business idea that we want to build a startup out of and grow to become the biggest fitness app out there, this is just the starting ground. Expanding our data analytics (recommendation tools on pricing for trainers), user experience (features like calorie counters, group fitness, social aspect), and much more are all great for this app, the sky really is the limit!!! Higher integrations with square tools, which are widely diverse, for trainer payment will enhance our app even more. This is not only a great startup idea, but something that can have a positive impact on millions of lives, and we don't plan on leaving this impact short.
**Note - due to file size constraints and some time constraints, we weren't able to include fully integrating pose detection scoring into our app. Nonetheless if you wanted to
try that out
here's an apk!
Built With
agora
agora.io
ffmpeg
firebase
flutter
square
tf-lite
Try it out
github.com | ProFit | ProFit is a marketplace designed to help a plethora of fitness professionals develop and grow remotely in spite of large scale displacement during the COVID-19 pandemic. | ['Prasann Singhal', 'Prasann Singhal', 'Doug Mohn', 'David Cai', 'Veronica Do', 'Mark Yuan', 'ss kim', 'Lucas Cai', 'Qasim Aziz'] | ['First Place - Services & Other Use Cases'] | ['agora', 'agora.io', 'ffmpeg', 'firebase', 'flutter', 'square', 'tf-lite'] | 6 |
10,046 | https://devpost.com/software/hurdlr-s-automatic-business-expense-deduction-finder | Deduction Finder for Square Sellers Analysis
Deduction Finder for Square Sellers Intro
Deduction Finder for Square Sellers Confirmation
Inspiration
Thank you for the opportunity and your consideration. My brother and I founded Hurdlr to help people earn more money with their micro to small businesses, freelancing, and side gigs. We automate their business expense tracking, self-employed tax estimates and financial reporting so they can focus on doing what they love.
Meet Hurdlr, your number-crunching, paper-pushing, mobile accounting machine. Our Hurdlr app icon was designed to personify a machine that helps people easily overcome the obstacles that all of these complex and administrative “hurdles” present. Similar to how Square simplifies payments (or getting paid), Hurdlr simplifies expenses and taxes -- it’s the perfect complement to Square.
With the growth of the “1099 Economy”, the Future of Work movement, and people transitioning to independent work, we wanted to automate these business and accounting roadblocks (or hurdles) to business success, so people could more easily thrive without having to become experts in self-employed business accounting and taxes. Finances, accounting and taxes for these people -- many of whom are our friends and family -- should be as easy as grabbing a Lyft or Uber.
After helping hundreds of thousands of people track $8B in finances and save $300M in taxes, we thought we had enough data that we could leverage to help people automatically find expense deductions they were overlooking or not taking advantage of, in order to reduce their taxable income and increase their take home pay.
What it does
Square Sellers self-identify into a business type, as do Hurdlr users. For this hackathon, we added a feature that goes through all of a Square Sellers expenses (via a linked credit card) and surfaces up the “likely” and “not likely” tax deductions.
How we built it
We built this by creating an algorithm that weights CPA-vetted best practices, for each Square Seller business type, against user behavior (in aggregate) for the comparable Hurdlr users’ business type. We combined that with our existing Machine Learning that learns/predicts user behavior, so that Square Sellers can capture the bulk of their tax deductions without having to manually classify each of their expenses. We have been tightly integrated with the Square API for some time now, but it was fun modifying our algorithms to provide this major win specifically for Square Sellers, as a part of this hackathon.
Challenges we ran into
The main challenge in building the Deduction Finder was the portion of the algorithm that weights similar-user behavior as one of the inputs. Specifically, we cannot assume that users behave in a tax compliant manner. For example, many self-employed individuals incorrectly mark their normal meals as business expenses. So we had to build in a mechanism that allows our CPA-vetted “best practices” to override erroneous user behavior.
Accomplishments that we're proud of
Square Sellers are sellers, not accountants or tax experts, and our new Deduction Finder feature for Square Sellers allows them to focus on selling and growing their revenue even more, while still getting the bulk of the benefit of being a tax expert. This feature furthers our mission to help solopreneurs and micro-business owners be more profitable. As a developer, I am proud that we were able to leverage external data (i.e. Square’s) to provide insights based on our data. The combination is very powerful.
What we learned
Our product is solving the Sellers’ painpoints that Square doesn’t resolve yet. After years of running our product in production, with over 500k registered users, we have taken our user’s feedback and honed the expense/mileage/tax portion of the micro-business owner’s financial puzzle. That includes building automation and user-customizable rules, so that users don’t need to constantly classify items or have tax-specific domain knowledge. I’ve learned that Square Sellers value these features as a complement to Square, and that it is not much work for Square Sellers to leverage what we have built, due to the streamlined integration that we’ve built here.
What's next for Hurdlr's Automatic Business Expense & Deduction Finder
We’ve added this to
our API
, so platforms like Square can leverage our proven tech and help their Sellers automate their expenses and taxes, within their own product.
Built With
amazon-web-services
android
java
react
react-native
square
swift
Try it out
www.hurdlr.com
projects.invisionapp.com
squareup.com | Hurdlr's Automatic Business Expense & Deduction Finder | Hurdlr for Square Sellers automatically tracks their business expenses and self-employed taxes so they can keep selling. Our Deduction Finder scans their expense accounts for valuable tax deductions. | ['Anu Bhaskar'] | ['Second Place - Services & Other Use Cases'] | ['amazon-web-services', 'android', 'java', 'react', 'react-native', 'square', 'swift'] | 7 |
10,046 | https://devpost.com/software/project-arya | Inspiration
Traditional retail is undergoing a seismic shift where self-serve technology is essential for growth, operations, and more with almost every facet of the merchant and consumer experience being redefined through new cultural norms. Our main inspiration for this project came from our community and these new times of uncertainty.
What it does
Our application runs solely from existing square merchant menus. These menus then populate on our user-friendly self-serve software. Our main objective for the software is to emphasize customer loyalty and safety, by being able to create an intuitive/gamified loyalty program with squares API and promote COVID-19 safety guidelines given by the CDC.
How we built it
Engineer Aspect:
Most of the transaction, order, and customer information were acquired through robust Square APIs that track large volumes of this incoming data. Using our own NodeJS Rest Server we were able to access this information, along with menu and category information. With this repository of data, we were able to create a visual representation of the menu. Our newest functionality uses the Square Loyalty program to store customer information, and create a rewards program that will get customers back into stores.
Design Aspect:
We determined the target audience & understanding their needs based on research:
> merchant: to build relationships with customers & increase revenue, cope with COVID
> customer: to have a smooth & enjoyable self-order experience, incorporating a social aspect
Identified opportunity areas: customer loyalty program & set pick up time
Created wireframes based on these needs, ranked & determined to go with the ones with more priority because of limited time.
Communicated with engineers about flows & feasibilities
Challenges we ran into
Engineer Aspect:
One of the biggest challenges we had was using the Square API functionalities in our iOS program. The API does not have the best documentation for iOS so we had to create our JS Server to more feasibly create queries for the information we needed. Another challenge we faced was linking information across the Square APIs. Since the API information is inherently linked, we had to build our own infrastructure that stored and organized all Square data.
Design:
Ranking desired functionalities & having to make compromises within the limited time
understand that not everything can be implemented.
Accomplishments that we are proud of
Engineer Aspect:
Our engineer team is proud that they created a fully functional application that was robust and easy to use. We were especially proud that our team was able to build an infrastructure that we believe improves on Squares data storage. We were able to leverage this interconnected, yet flexible repository of information to create an application that better tailored to the needs of the customer.
Design:
Delightful customer journey
Provided a way to benefit both merchant & customers
incorporated pleasing & fun visual elements
The biggest accomplishment for the whole team was the fact that we were able to complete all this in one week
What we learned
Engineer Aspects:
Getting experience in full-stack development is very important and utilizing the Square API required me to learn a lot of skills across UI/UX, networking, Swift, Javascript, databases, and more.
Designers:
The importance of user stories to establish the team's common understandings.
The need to consider consistency when designing to save the need to create various screens from engineering's perspective
While it's important to think about edge cases, it's more important to focus on the most relevant user journey and making that journey delightful first
What's next for Project Arya
As we continue making improvements to project Arya, our main goal is to help our communities and their businesses grow in the crazy world we live in today. That's why with these updates made within this hackathon we are going go to continue to reach out to our fellow communities with our services to help grow.
Built With
catalog
figma
ios
jsserver
loyaltytoolkit
miro
notion
ordermanagerapi | Project Arya | Streamlining the New Food Ordering Experience with Self-Serve Kiosks | ['Gabriel Canizales', 'jjc', 'Grace Lam', 'Aniruddha Alawani', 'Carol Chen', 'Davy Chang'] | [] | ['catalog', 'figma', 'ios', 'jsserver', 'loyaltytoolkit', 'miro', 'notion', 'ordermanagerapi'] | 8 |
10,046 | https://devpost.com/software/standwithsmall | This tool works on top of large marketplaces like Amazon, Target, and others.
This tool pops up similar products at similar prices to users shopping for products online.
New feature #StandWithSmall allows users to discover small businesses while shopping on large marketplaces
Meet the Trestle Founding team - Jennifer, Carl, and Damola
Inspiration
COVID-19 is hurting small businesses we love. Meanwhile, large marketplaces like Amazon cannot even keep up with demand.
If we can redirect even a small percentage of sales currently going to large marketplaces to local small businesses, we might be able to help make a huge impact in helping them survive. That's what this tool does.
Who might want this?
This tool is for those who, like most, don’t have the time to fully research every company behind every product we buy online – but understand supporting small businesses is really important – especially during COVID-19. It is the most convenient way to find and buy from small businesses in your local area.
How Does It Work?
Anytime you land on a product on Amazon.com, Target.com, and other marketplaces – we’ll pop up similar products at similar prices from small businesses in your local area – like magic!
Now you can #StandWithSmall by doing what you already do - shopping for products you need online.
What it does
Here's an example of how this works.
Carla, a Portland mom, needs new games for her kids while they’re home. Like she usually does, she goes to Amazon and types in “best kids games”. The myTrestle Button pops up and shows her small companies from Carla’s local area that sell kids games, like Black Wagon and Grasshopper.
Carla can now easily support her local small businesses during this hard time.
How we built it
We built the Trestle Button using a combination of technologies which include React, google cloud, .net, c#, square SDK. It leverages the Square JS code to form our frontend for the payments gateway and the underlying C# sdk to make the payments call. We would like to have tighter integrations with Locations and or Merchants API's as well.
Challenges we ran into
Submission issues! We recorded our submission video using loom instead of one of the approved options. Of course we were running behind and discovered this issue at the last minute. This caused us to scramble at the last minute.
Accomplishments that we're proud of
We rallied and really put together some amazing functionality! And because we've built this, we've already heard multiple stories from users who have chosen to buy from a small local business instead of their bigger competitors. For example, one user shared with us that she was on Sephora.com looking for skin care - our tool popped up local small business Rarity Natural Beauty who is not currently selling in Sephora, and the user chose that product instead. That's a sale for a local small business that would have otherwise gone elsewhere.
To date, having JUST launched this product a couple weeks ago, we've already acquired 35 small businesses and over 1500 weekly users.
We are glad to be able to support small businesses during this crazy and trying time.
What we learned
Square has great integrations and is a potentially great way for companies and people affected by COVID-19 to move their businesses online. In addition, don't use Loom for future Devpost submissions!
What's next for #StandWithSmall
We will continue to iterate on this idea building it and adding additional functionality. We would love to see this browser extension grow in usage so we can better help more small businesses!
The majority of the 35 businesses are in the Portland, OR area. Next we'll onboard small businesses in other markets.
Want to try it for yourself?
Take these steps:
Download the extension from the Chrome store here:
https://chrome.google.com/webstore/detail/mytrestle-button/ilbgeihhbjaehjedemfkdgahgflmladn
Sign up and create an account on mytrestle.com (After you download from the Chrome store you will be redirected to create an account. Make sure to select Small & Local Business as one of your values.)
Make sure you are signed in with the same username and password in the Chrome extension
Finally navigate to this link (Big box store competitor) ->
https://www.amazon.com/African-Shea-Butter-Unrefined-Organic/dp/B0711576DH/
From here you should see the Trestle Button pop up and should be able to click the "Buy" button which takes you to our Square hosted checkout page.
Make sure to enter a valid test Square Credit Card Number (4111-1111-1111-1111 for example)
Pat yourself on the back! You just exercised your values and supported a small business!
Built With
.net
c#
google-cloud
react
square-sdk
Try it out
mytrestle.com | #StandWithSmall | Trestle integrates the Square API to support discovery, customer acquisition, and payment for small businesses new to e-commerce. It leverages large marketplaces to help small biz be found online. | ['Jennifer Johnson', 'Damola Omotosho', 'Carl Hickerson'] | [] | ['.net', 'c#', 'google-cloud', 'react', 'square-sdk'] | 9 |
10,046 | https://devpost.com/software/eventbit | home screen
in-app game to get into a secret room
event floor
video networking
Inspiration
Prior to learning to code, I ran developer conferences. During Coronavirus, obviously these events gone virtual. While they tend to be OK, they're missing a lot of what makes developer events "fun". So my partner and I decided to build it.
What it does
There are the usual video presentations, but the primary piece of the site is a 2D game. You walk around a virtual floor, chat with people nearby, interact with sponsors, and other surprises.
How we built it
Frontend is built with React, and game interface is built with Phaser framework. There are two backends - website is on Ruby on Rails, and game backend is built with Kotlin. Authentification is done with Firebase, and payments are processed with Square.
Accomplishments that I'm proud of
Implementing Square online payments! It was the first time I implemented payments into my apps, and even though it wasn't easy, I think Square Developer team did a great job to explain how to do that.
Built With
activerecord
javascript
kotlin
phaser.js
react
ruby-on-rails
square
Try it out
bink-dog.github.io | EventBit | Adding some fun to virtual events! It's a 2D game with live attendees to allow some spontaneous networking and a few surprises ;) | ['Kevin Galligan', 'Natalie Galligan'] | [] | ['activerecord', 'javascript', 'kotlin', 'phaser.js', 'react', 'ruby-on-rails', 'square'] | 10 |
10,046 | https://devpost.com/software/bundled-deals-across-businesses | Inspiration
Due to COVID-19, small businesses have suffered the most. Now more than ever, small businesses need better, faster, and more creative discovery and sales channels to ensure their recovery and growth. And customers need better ways to discover their neighborhood offerings and support their favorite businesses, with one click. Square Bundle is a new Small Business Partner Program for neighboring businesses to display and bundle complementary offers, products and deals from other businesses on their Square terminal, during checkout.
During the COVID-19 quarantine and shelter-in-place restrictions, we saw local businesses (1) pivot their business models and offerings; (2) partner with other small businesses that had complementary but not competitive offerings (i.e., formal dinner-only restaurant & wholesale breakfast baker); and (3) businesses creatively selling and host pop-ups for other small businesses at their location during closures, because they had better foot traffic or the proper licenses or clearances to remain open (i.e., restaurant selling floral bouquets on behalf of local floral designers during the closures for non-essential businesses).
What it does
Bundle helps small businesses bundle their deals, offerings, or products with other businesses, during checkout.
After opting-in to Bundle, small businesses can (1) create their own unique deals and offers; (2) pick the businesses where they want their deal or offer to be displayed; and (3) receive a notification when a customer has purchased their deal. This helps businesses grow their audience and customer base, and inform their product and marketing efforts.
How we built it
We built a web app using Node.js, React and Square's API to mimic Square's terminal experience. When a customer makes a purchase using the terminal at one business, it displays bundled offers or products with neighboring businesses.
Customers check out with one single payment like they normally would. Behind the scenes, this is really two or more different sales to the different businesses selected.
Challenges we ran into
Navigating Square's API
Accomplishments that we're proud of
Building a web app that has real impact and immediate application for small businesses and cities now and into the future.
What we learned
With Bundle, there is tremendous opportunity for Bundle to grow and scale further, unite communities and neighbors and grow sales and marketing outreach.
What's next for Bundled deals across businesses
After opting-in to Bundle, small businesses can (1) create their own unique deals and offers; (2) pick the other business categories where they want their deal to be displayed; and (3) receive a notification when a customer has purchased their deal. Bundle enables small businesses to belong to a self-selected community- or neighborhood- with other businesses to support each other's recovery, survival, and growth.
Built With
node.js
react
square
vercel
Try it out
react-bundle.giacaglia.vercel.app | Bundled deals across businesses | Pay once and get service from more than one business. Users can add products from nearby merchants to their Total on the Square Terminal creating trust, partnership, and a thriving SMB community. | ['Giuliano Pezzolo Giacaglia', 'Arpit Gupta'] | [] | ['node.js', 'react', 'square', 'vercel'] | 11 |
10,046 | https://devpost.com/software/dineline | Inspiration
When I was traveling in Taiwan two summers ago, I found that many restaurants did not use the typical 1:1 server to customer experience for dining in. Instead, they employed sheets of paper which customers would use to mark their orders, which would be picked up by any server, brought to the back for food preparation, and then served when it was ready. At any point, the customer could add to their sheet and then these additional items would be added to their order and subsequently served. When the customer was ready to pay the bill, they wouldn't need to wait for the server to come around with the check. They would head towards the exit, where a manager would be sitting next to a cash register, ready to help them complete their meal checkout flow.
After this dining experience, I had been intrigued by the possibility of integrating it with a POS system such as Square. However, with today's COVID-caused "new normal", I found additional pain points that needed to be addressed in a solution such as this one. These are:
The wastefulness and environmental damage of paper menus.
Waiters and waitresses are currently stretched thin as a result of additional sanitation tasks; they are also put at increased risk of COVID transmission as they interact with more and more customers.
While many restaurants have adopted online pickup/delivery ordering flows with contactless payment options, most dine-in experiences still lack this feature, putting both the customer and restaurant employees at risk of COVID-transmission.
What it does
A mobile-optimized dine-in experience. Customers can view the menu in an accessible and optimized format for their mobile phones, order items with variations and modifiers as defined in the Square CatalogAPI (all information is drawn from there), call the waiter/waitress to the table when they need human support, check on the progress of their order throughout their meal, and checkout with either an in-person or contactless payment solution (via Square).
How I built it
When customers view the menu, it is blazingly fast as a result of Gatsby.js and Square's CatalogAPI - the catalog items are preloaded during the build stage so that no time is wasted in calling the Square CatalogAPI for each user to visit the page.
Challenges I ran into
Building the logic for any number of variations and modifiers on items was quite difficult. While Gatsby.js' GraphQL interface certainly helped with retrieving the data from Square's Catalog, being able to handle a variable number of item options (which combine together to form unique variations) as well as both single and multiple select modifiers was quite a challenge. However, I'm proud of the fact that I was able to finally solve these challenges with some (slightly messy) code which I hope to improve upon at a later date.
Accomplishments that I'm proud of
As previously mentioned, solving the algorithmic challenges associated with handling variations and modifiers on items, as that information was necessary for adding items (with their variations and modifiers) to an order.
Another accomplishment was the look and feel of the application. In the past I've built web applications, but I've always targeted laptop and computer screens. This was a unique challenge in that my target audience would be on mobile devices, and so optimizing for that experience was interesting. I think in the end, I not only learned more about how to wield CSS but also how to really consider mobile applications from a user experience perspective. For example, there are no hover events (something which I love to use in typical web applications) and it is easy to misinterpret a scroll for a click on mobile. Both of these challenges are things that I had to overcome with my application.
What I learned
Three major things:
How to navigate Square's API. At first it was very confusing due to its nested nature, but as I used it more and more, things started to make a lot of logical sense and as I accepted the patterns they employed, it became easier to enjoy using it. I will say, Square's API would be a great candidate for a GraphQL API - with GatsbyJS I was able to try this out a little with the excellent
gatsby-source-apiserver
plugin.
I learned to love and understand the importance of the JAMstack. The performance and speed of this app was incredible, and is also very necessary given that its competition (a paper menu) would never have any loading time. With Gatsby.js, this app was able to give paper menus a run for its money. Additionally, I learned how to leverage both dynamic and static content in a JAMstack application, as some information (such as the order information) had to be dynamically populated from the server.
Finally, I really enjoyed this project on a conceptual level. I had originally conceived this idea back in Taiwan during the summer of 2018, and while there I frequently ate out and experienced their unique ordering flow on a daily basis. Upon returning to the US, I wanted to build this out but didn't have enough technical knowhow to do so at the time, and the hypotheses behind adjusting the project weren't validated. However, as a result of COVID, new pain points in the dine-in experience emerged which I saw could be addressed with slight modifications to the ordering flow I had originally envisioned. Thus, building out this application was not just technical but also conceptual, as I had to put myself in the shoes of the customer and the small business owners to determine if the solution I was proposing would truly address the pain points they faced.
What's next for Dineline
There were three main things that I didn't get to address in this project, but will be important moving forward for Dineline:
Currently, only a single customer at a table can order for everyone. This is because a new order would be created if someone else at the table tries to place an order. Clearly, this is not the best solution due to the potential for COVID-transmission, as well as the general user experience that most people are used to (typically in a restaurant you are given your own menu and don't need to pass one around). However, this limitation is a little tough to solve as it would require some real-time updates to be pushed to the applications of all members of the table in order to keep the data in sync.
This application is currently only a customer-facing application. While information propagates to the Seller's actual Square account, I believe that a vendor-side application or extension to Square's POS would be necessary in order to handle adjusting the additional order states which the application utilizes (through the metadata field of the Order object). This is because Square's current order states only include "OPEN", "COMPLETED", and "CANCELED", which is too limited for this application.
Finally, Square Checkout needs to be fully implemented to fulfill the third pain point previously mentioned, which was that of contactless payments for dine-in customers.
Built With
gatsby
node.js
react
square
Try it out
kind-bhabha-dcb291.netlify.app
github.com
github.com | Dineline | Dineline provides small businesses with a safe, environmentally-friendly, and efficient way of dining in that their customers will love. | ['Will Mundy'] | [] | ['gatsby', 'node.js', 'react', 'square'] | 12 |
10,046 | https://devpost.com/software/smalltalk-er2odk | Welcome page for SmallTalk
Payments and COVID-19 rating page
Notes page from contractor view
Contractor profile
Friends page from client view
Display of recommended small businesses from client view
Transaction history from contractor view
Client profile
Client landing page
Login page
Registration page
Registration for contractors
Inspiration
We were inspired by the difficulties faced by small businesses in getting enough customers, particularly those which provided home services like plumbing, due to the coronavirus pandemic. These services are usually very hands-on, and thus we wanted to create a service that would allow small businesses to gain publicity in these difficult times.
What it does
We provide a recommendation service, including COVID-19 safety ratings as a feature, on the side of the client, giving greater weight to contractors and small business service-providers who were given positive ratings provided by friends. Clients are able to search for contractors, receive recommendations, and pay and rate contractors on the website. On the side of the contractors, we provide a note-taking interface and transaction log, along with a profile page to update categories of service.
How we built it
We built the back-end based on Django and the front-end from HTML, CSS, and Javascript. The Square Payments API is integrated in our Payments tab. The code is available in our GitHub repository.
Challenges we ran into
We were unfamiliar with the Square API, and had not built a complete website from scratch before. We utilized datasets from Yelp (
https://www.yelp.com/dataset
) to train the AI recommendation model; constructing the model to weight COVID-19 ratings (for the purposes of this demo, a ratings column in the Yelp dataset) while incorporating user friendship relations and geographical boundaries was took thought. We ran into several errors and conflicts along the way, but eventually succeeded in building our complete product.
Accomplishments that we're proud of
We’re proud of completing the basic features that we identified on the client and contractor sides of our website, a service that will provide benefit to boosting contractor reputation to combat the decline in business brought on due to the coronavirus pandemic.
What we learned
We learned how to build a full-stack web app, complete from end-to-end, and honing our development skills.
Business Model
We hope that SmallTalk’s revenue model possesses user stickiness. By enabling contractors to connect with clients, our service offers contractors additional business while simultaneously reassuring clients that their choices are sound, by leveraging their friends network. In return, SmallTalk would take a small portion of the payments clients send to the service application via the “Payments” tab, and is responsible for transferring payments to contractors in a timely manner.
What's next for SmallTalk
We hope to add additional features to our recommendation model and host our website for public use. Please find directions on running the application at our GitHub repo’s README (
https://github.com/agnikumar/summer-hackathon
).
Built With
css
django
html
javascript
python
Try it out
github.com | SmallTalk | We present a service to aid small businesses in gaining publicity, particularly in response to the coronavirus pandemic, leveraging user friendships to generate recommendations. | ['Agni Kumar', 'Sarbari Sarkar'] | [] | ['css', 'django', 'html', 'javascript', 'python'] | 13 |
10,046 | https://devpost.com/software/infikiosk | Inspiration
For coffee shops and bubble tea shops, they want to print a label and stick it on the cup as part of their operation.
However Square doesn't support label printer. We help them using Square API integration
What it does
Our solution captures Square orders from Square Register, Square POS and Online Store and send them to a controller, from which those orders are dispatched to different label printer stations based on their categories.
How I built it
For Register and POS orders, we use payment.update Webhook to capture transaction details. Then we use the retrieve_payment API with entity_id and location_id to get the payment itemization detail. Then we notify our controller with web sockets and the last step is printing the itemizations with the corresponding formats.
For Online Store orders, we use order.updated Webhook and then use batch_retrive_orders to get orders details. Then we use the same web socket notification method to notify our controllers.
Challenges I ran into
Square has v1 and v2 API and both of them have different limitations. For example v2 API cannot get cash payment from Register and POS. We have to use V1 API but it seems will be retire soon.
In addition, we cannot get order/ticket number from any API so the solution have some tedious steps we cannot omit
Accomplishments that I'm proud of
Even with many limitations, our solution is loved by many of our clients and they are using it in daily operations and it indeed saved them a lot of time in operation.
What I learned
This is our first real project with Square API and we learned a lot in technical design with Square's object models and webhook events.
What's next for Square + Label Printer
We will keep optimize the solution with Square API updates and hopefully it can become more easy to use
Built With
api
hardware
sdk | Square + Label Printer | Square does not support any printer that can print labels, which is a severe problems for a busy coffee shop and bubble tea shop. We fixed this problem with Square API with an easy solution | ['Lucas Liu, Ph.D'] | [] | ['api', 'hardware', 'sdk'] | 14 |
10,046 | https://devpost.com/software/queue-with-kyoo | Scan the QR code to place an order (from table #42)
Select tableside ordering from checkout and enter table number
Table number appears in display name on Square order
Inspiration
Some of our QSR customers had switched entirely to online ordering, but wanted to open up some tableside options as their cities permitted. It was not sanitary to keep handing out the same “number” markers for each table, nor was it ideal to permit a line to form near the register. Our solution is tableside ordering – it prevents a line from forming at the register and removes the need to use the same “number” markers over and over again.
What it does
Customers can scan a QR code at their table and order from the menu without needing to interact with wait staff for ordering or purchasing, providing less personal interaction, making all parties safer during the COVID-19 crisis.
How we built it
We added a way for our app to read additional path parameters for /tables/X, which can be manually entered by the customer - e.g. kyoo.tech/bobscoffee/tables/2 or be embedded into a QR code
Our app pre-fills in a new “table number” field if it’s in the URL, or the user can manually enter it, and we attach this to our internal version of the order prior to submission to Square’s Orders API
We append the “table number” to the end of the Display Name field in the Order Fulfillment Details object within the Square Order
We added an option to allow tableside orders in our Kyoo Dashboard for existing merchants to opt-in to this feature
Challenges we ran into
We don’t have an easy way to allow customers to order before they have a table, we could re-use our curbside architecture but worry this could be confusing for merchants to find the table number potentially in two places
If a business is using pickup orders and tableside orders, their Order tab in Square may become cluttered, we may later use the “Shipping” fulfillment type so they are separated
We opted to not solve the problem of multiple customers wanting to order from their own phones, yet combine their order and/or share a tab in the initial version
Accomplishments that we're proud of
We think the simplicity of using the QR codes will work for most users
We were able to build this feature in under three days
Provides a safer environment for business employees and customers
What we learned
Square does not offer a table management API
Square does not allow for open checks to be used in the same way as the POS
What's next for Tableside
We’d like to authorize a card as a “tab” at the beginning of a meal, and allow several customers to order using the same card, and/or add additional line items to their order during the meal without having to incur additional flat $0.30 processing fees
We’d like to provide a way for merchants to define their tables in advance, rather than rely on free text inputted by the customer or a QR code, which also would allow for automatic QR code generation and potentially even table reservations in the future
Built With
angular.js
spring
twilio
Try it out
kyoo.tech
kyoo.tech | Tableside (by Kyoo) | For all the restaurants and bars now reopening, Tableside by Kyoo provides a no-contact, sit down experience that protects the server and guests. | ['Albert Brown', 'Donald Johns', 'Ruth Nott'] | [] | ['angular.js', 'spring', 'twilio'] | 15 |
10,046 | https://devpost.com/software/bubbly-solutions | Context
It all started in 2017 after I had graduated from high school. As an international student, I knew the tuition burden would be unbearable so I decided to start my own business to help pay my way through college. After pitching the idea to my parents, my father loaned me his pickup truck which helped me kickstart the operation, and from there Bubbly — Mobile Car Care was born.
The idea was to create a complete frictionless mobile car care solution that would make car maintenance simpler and more up-to-date with current technology. After studying the market, we learned that most competitors were informal individuals who did not offer the reliability and professionalism the market was demanding. With all that in mind, Bubbly began operating during the summer of 2017, offering an on-demand mobile car wash service in Houston, TX. Thanks to our competitive advantages, Bubbly was able to exceed the market demand and grow throughout these years, resulting in strong brand recognition in the area.
However, with this growth, we quickly realized that our operation was not scalable. Our once advantageous booking system (third party) was no longer meeting our needs, and the payroll spreadsheets were becoming a nightmare - it was time for an upgrade.
Inspiration
After identifying our bottlenecks, I decided to put those hours of youtube tutorials to work and build out a suite of solutions that would not only solve Bubbly's problems but also other similar services.
You can also watch this presentation on
https://www.youtube.com/watch?v=D3vb3-Ybruc
After some careful planning, this is what we found:
1. Lack of service customization results in poor customer experience
In our perspective, there were two ways to solve this problem, we either offer many different services to cover a large spectrum of customer needs, or we somehow create base services that can be customized to better fit the customer needs. Since the whole mission behind Bubbly was to make car care simpler, we decided to create very well thought out base services that could be customized with "upgrades". However, the current website/booking system would not support that.
2. Unable to book more than one service at a time
Throughout the years, we have noticed that most of our customers want to schedule 2 or more vehicles at the same time; however, with the current implementation, our users need to go through the entire booking flow twice - which is extremely inefficient and generates more friction.
3. Customers can't manage their appointments
Part of our customer-oriented culture is to allow for flexible rescheduling and canceling. However, currently, it is extremely tedious and confusing for customers to manage their appointments - in most cases, they have to email or call to get anything done.
4. No support for recurring services
A big part of achieving our goal of a complete car care solution is the ability to offer recurring services. Being able to create their own service schedule (i.e. every Monday service A, every 3 months service B) is extremely important to our users and guarantees them to always have a well-maintained vehicle.
5. No manager dashboard
On the employee side of things, managing appointments is extremely difficult, due to the lack of a manager dashboard.
6. Appointments are distributed inefficiently
Currently, the appointments are scheduled on a first come first serve basis. Which for a small scale operation is fine, but once the operation grows, it becomes inefficient. In other words, employees have to drive longer distances, which results in many problems (i.e. increased delays, increased operation costs, etc.)
7. No employee-facing system
The current booking system gives us very little flexibility in terms of data. This means we cannot give our employees key information about their schedule, and keep the customer updated regarding the status of their appointments. Ultimately, increasing no-shows, delays, and cancelations.
What it does
Now let's talk about the interesting stuff. This suite of solutions was designed to completely fix all the problems mentioned above and more.
Customer Facing app
Available for both iOS and Android, this native app will allow our customers to:
Save their vehicles, addresses, and payment methods, resulting in faster checkouts
Easily customize their services by adding upgrades, which increases the flexibility of our services and the average ticket price.
Re-book appointments with one tap
Add more than one appointment per order
Rewards program
Manage their appointments
Track their appointments in real-time
Enroll in recurring services that are fully customizable
Authorize employees to remotely unlock/lock and locate their vehicle, which further removes friction
Employee facing app
Available for both iOS and Android, this native app will allow our employees to:
Keep track of their hours and earnings
Provide appointment updates to customers
Improve overall day-to-day operations
lock/unlock customer vehicles in-app as well as locate them
How I built it
Customer/Employee apps
When choosing what technology to use, I tried to be as objective as possible. As a team of one, I had to choose the most efficient tool for the job. After some research, I landed on Flutter -- Google's UI toolkit for building natively compiled applications for mobile with a single codebase. This framework is what allowed me to create both Android and iOS applications quickly and jumpstart the project.
Manager Dashboard web app
This application was built with React, which offers great performance and community support due to its popularity.
Backend infraestructure
We decided to go with Firebase since it is extremely easy to bootstrap the project and flexible enough to allow for customizations.
Challenges I ran into
Lack of experience
Being a sophomore in college, and never taking a computer science class before, I knew it was going to be a challenge. With no previous experience, I did not know how larger teams approached a project like this. With some research I was able to set up a decent workflow, using story tracking and CI/CD pipelines to streamline the development process.
Time management
Planning, designing, and building this whole project on my own, while running a business and studying computer engineering has not been easy, to say the least. This is a big hurdle I face every day, but also made me learn a lot.
Accomplishments that I'm proud of
Booking system
One of the hardest problems to solve during this project was to create a booking system from the ground up. I did not want to rely on previously built booking systems once again. Creating a fully custom booking system from scratch was a tough challenge, but extremely rewarding. At this stage, there's still a lot that can be improved, but so far it is working like a charm :D
Appointment distribution system
As mentioned before, the appointments were previously distributed on a first come first serve basis which is extremely inefficient. Designing an algorithm that automatically gives the employees the optimal combination of routes and appointments was a huge improvement. This change greatly reduce operating costs and customer friction. It also has a lot of room for improvement, but it's a big step towards a more efficient future.
What I learned
Planning is key...
In the beginning, I would just sit down, make myself some coffee, and starting coding away. I quickly realized this wasn't the best approach. While I was coding I would make wrong decisions that could've been easily avoided with some planning. After failed attempts, I started to plan out every single feature that I wanted to add. How would the data flow? how should the data look like? how is this screen going to look like?
...so is resting
Sitting down for hours writing code is good and all until you have to leave the "autopilot mode". When a difficult problem comes to light and you have spent hours coding, it is almost impossible to solve it. I learned that by taking a break, or "sleeping it off", will allow your brain to better process the information and help you come up with better solutions much faster.
Simple is often better
When trying to solve all these problems, it is easy to get carried away and architect some extremely complex and over-engineered solutions. However, I later learned that simple solutions are often much better.
What's next for Bubbly Solutions
We will continue to build our solutions and improve its modularity to allow other small businesses to take advantage of this technology. Solving Bubbly's problems is awesome, but enabling our community to grow is extremely important. I like to think of it as "lifting while you climb."
Small businesses are at the core of this country. The current state of the world is uncertain, but by enabling small businesses to grow and reach their full potential, we can make the world a better place, community by community.
Built With
express.js
firebase
flutter
google-geocoding
google-maps
node.js
react
smart-car
square
Try it out
docs.google.com
heuristic-shaw-1467c5.netlify.app
testflight.apple.com | Bubbly Solutions | A suite of software solutions that enables small businesses to achieve their full potential, while providing their customers with a frictionless experience. | ['Rodrigo Mascarenhas'] | [] | ['express.js', 'firebase', 'flutter', 'google-geocoding', 'google-maps', 'node.js', 'react', 'smart-car', 'square'] | 16 |
10,046 | https://devpost.com/software/android-pos-for-square-transactions | Enter Amount
Reports
Confirmation screen
Account information
Iddle Screen with configurable video
Order hardware from Amazon
View POS
Specs
Inspiration
SQUARE POS is a very good terminal for processing credit/debit transactions, but does not allow to install other Apps from google play. Having a low cost Android POS will allow small stores such as restaurants and shops to install and use all the apps they need in a single POS terminal, while using SQUARE to process credit/debit transactions and print receipts and reports.
It also has the functionality of accepting fix amount donations, tips and payments.
What it does
Application for running SQUARE credit/debit transactions in an Android POS.
How I built it
Using Square POS SDK for Android. Also integrated printer drivers for WISENET7 pos from
www.wiseasy.com
pos manufacturer.
Challenges I ran into
Locating POS terminal that is compatible with square and has Play store certification.
Accomplishments that I'm proud of
Integrating the Square reader to the Android POS in a semi-unattended mode.
What I learned
How to control receipt printer for generating reports and receipts.
What's next for Android POS for Square transactions
Promote the app and monetize
Built With
android
hardware
pos
Try it out
play.google.com | Android POS for Square transactions | Lost cost Android POS that is compatible with SQUARE POS and allows to install Apps from PlayStore | ['Juan Carlos Vera'] | [] | ['android', 'hardware', 'pos'] | 17 |
10,046 | https://devpost.com/software/swachev-wabtvr | Inspiration
The business-to-consumer aspect of product commerce (e-commerce) is the most visible business use of the World Wide Web. The primary goal of an e-commerce app is to sell goods online.
This aplication was inspired base on the recent outbreake of disease, the application aims at solving the issue of people moving into local stores to buy their daily needs. Hence, local store owners can advert their produce using the application and users gets to buy things from their own local stores and get it delivered to them very fast and safe.
What it does
This project deals with developing an e-commerce app for Local businesses. It provides the users with a catalog of different local produce available close to them for purchase. In other to facilitate online purchase a shopping cart is provided to the user. The system is implemented using a 2-tier approach, with a backend database and an application interface.
Let's say for example John wants to buy a vegetable, instead of going to Gifts shop were he normally buy's vegetables, he uses swachev app to order the vegetable and gift deliverers directly to his house fast and safe. And he is secure against any disease. Gift does this to all her customers keeping them secure against coming to cue or line up in her store exposing themselves to possible infections with virus.
How I built it
I started with the development of a UI/UX design were I made a prototype design first, before going ahead to build an MVP.
Challenges I ran into
One of the challenges I had was to be able to get users feedback on what they feel the app should look like, The local buyers wanted something that imitates their local shopping system, so it was a challenge to make it suit in.
Accomplishments that I'm proud of
I am very proud of what I have archived so far, it took a great work and consistency to get to this point. I have an MVP which users are able to interact with.
What I learned
I learnt a lot of new technologies, I learnt how to solve problems considering the locals. And I also learnt how to use the square payment system which is fast and secure.
What's next
The next thing is to keep building until I have a finished product and lauched for local stores to use as a means of goods distributions.
Built With
kotlin
mongodb
node.js
Try it out
www.figma.com
github.com | Swachev | An e-commerce application for local businesses. | ['David Sunday'] | [] | ['kotlin', 'mongodb', 'node.js'] | 18 |
10,046 | https://devpost.com/software/retentionforce | Inspiration
We always wanted to make the collection of loyalty points more fun, asking for customer feedback much more easier and emotionally engaging, getting more 5 star reviews easier and other way growing business much more effective. Most current communication tools like email and sms are dull and have low open and click rates. So we made this much more engaging for consumers by using emojis, gifs and buttons as an interactive conversation in the Facebook Messenger.
What it does
We have built an integration between Square and RetentionForce. First of all it creates a lasting conversation between brand and customer in their Facebook page. Whenever loyalty points are accumulated in the Square clients receive a message from the brand via Messenger, it then asks for feedback that can be answered in one click. Later if clients are happy they will be asked either to review the business on Yelp/Facebook/Google/etc or refer their facebook friend. Afterwards RetentionForce automatically tries to recover lapsed customers, do all kinds of marketing automation, helps to launch SMS Marketing campaign that connects with the Messenger Marketing and many more things.
How I built it
RetentionForce is a web application. We have built the integration with Loyalty and Order APIs and use the Loyalty API webhooks.
Challenges I ran into
Sandbox environment doesn't provide the customer enrollment to the loyalty program and to test the integration the simulation complete implemented using api script. Additionally node.js sdk seems like doesn't contain endpoints for loyalty api. And it was challenging to find the source_id field value for the sandbox when we were trying to create a payment for the order.
On the RetentionForce side the integration required complete rewrite several major modules, so it became possible to override points accumulation logic, order tracking and other changes.
Accomplishments that I'm proud of
That everything works automatically and no manual labor except for setup is ever needed.
What I learned
Square API structure, webhooks, Square entities and their relations. It was fun :)
What's next for RetentionForce
We will be doing deeper integration so having a loyalty program enabled will not be necessary. We would like to integrate the coupons and gifts part of the system with the Square. And last but not least chatbot integration with the Catalog API
Built With
facebook-graph
facebook-messenger
javascript
mongodb
node.js
sms
vue
Try it out
www.retentionforce.com | RetentionForce | We help businesses to establish engaging conversations with their customers using chatbots that helps to retain and attract them using marketing and customer care automation tools. | ['Alexander Adamyan'] | [] | ['facebook-graph', 'facebook-messenger', 'javascript', 'mongodb', 'node.js', 'sms', 'vue'] | 19 |
10,046 | https://devpost.com/software/squareaway | We wanted a way to efficiently get the supplies that people need while having no trouble to pay for it.
Built With
css
firebase
html
javascript
square
twilio
uber | SquareAway | This is an app that will work with Uber API to get customers the food that they want. | ['Abhinav Mamidipaka'] | [] | ['css', 'firebase', 'html', 'javascript', 'square', 'twilio', 'uber'] | 20 |
10,046 | https://devpost.com/software/nova-rewards-the-rewards-companion-app | How we built it
App screenshots
Inspiration
The rewards companion app was inspired by Square’s Loyalty Program. Our idea is, how can we combine contact tracing and gamification together? Check-in to receive rewards!
What it does
Customers
Use Nova Rewards to keep track of all of your rewards across businesses in this single app. There is no extra account required, simply confirm the same phone number you used when checking out at the business’s other forms of ordering. After confirming your number, track your existing rewards and accure more points when you return to their store. Use Nova Rewards app to check-in when you're visiting the store, whether your picking up an order or browsing around, no purchase required! Nova Rewards will trace and monitor contacts of infected people at the businesses you visit and notify you immediately.
Sellers
Join Nova Rewards to let customers discover your business and learn more about your Square loyalty program. It's free to join and simply works with your existing Square account. Confirm your Square locations, adjust your existing Square loyalty program to provide an incentive for check-in when they are at your store. Nova Rewards will trace and monitor contacts of infected people at any of your locations and notify you immediately.
How I built it
See system diagram for how we built it
Challenges I ran into
With just two of us being developers, we had lots of ideas and things we wanted to build but found it hard to create a concise UI that looked pretty.
Accomplishments that I'm proud of
We built a platform that allows for multiple sellers to be apart of, giving value back to the customers, and a pipeline that includes a development (sandbox endpoints) and production app.
What I learned
A lot about Square APIs and what they have to offer for the sellers and customers.
What's next for Nova Rewards - the rewards companion app
A lot of work on UI/UX to truely convey our idea. Get Square feedback on our use of loyalty programs, get seller feedback to understand how the platform can build a valuable engagement channel for them, customer feedback to understand the incentives for an end-user to come back to the app.
Built With
express.js
firebase
node.js
react
square
swift
swiftui
Try it out
nova-frontend-dev.herokuapp.com | Nova Rewards App | The rewards companion app was inspired by Square’s Loyalty Program. Our idea is, how can we combine contact tracing and gamification together? Check-in to receive rewards! | ['Kingly Yee'] | [] | ['express.js', 'firebase', 'node.js', 'react', 'square', 'swift', 'swiftui'] | 21 |
10,046 | https://devpost.com/software/small-business-website-template | Cart
Checkout
ContactUs
Order
Inspiration
We saw many small businesses suffering due to a lack of technology in their business model.
What it does
It provides a basic template for any small business to use and customize how they want.
How we built it
We used Django and the Square Payments API to receive orders.
Challenges we ran into
The API was difficult to integrate as post requests were denied often.
Accomplishments that we're proud of
Integrating a true payment form and creating a complete website from scratch.
What we learned
How to use the Square Payments API and how to use cookies to advance a website.
What's next for Small Business Website Template
Expand to small businesses around America.
Built With
css3
django
html5
javascript
python
square
Try it out
github.com | Small Business Website Template | Small businesses that cannot support deliveries or carryout through their website are suffering financially. We provide a template website for these businesses to allow them to grow. | ['Saksham Gupta', 'Soham Gupta'] | [] | ['css3', 'django', 'html5', 'javascript', 'python', 'square'] | 22 |
10,046 | https://devpost.com/software/taptable | Table talker: one per table
TapTable QR: Visit https://order.taptable.io on your mobile to scan!
Inspiration
Given the impact of COVID19 on the hospitality sector and the changing nature of the dining out experience we wanted to provide an easy to use 'order at the table' solution for restaurants that requires no technical expertise on behalf of the restauranteur and minimal setup time.
What it does
With TapTable restaurant owners can sign up and connect their account to an existing Square POS account. As long as they have a Restaurant PoS system setup with Square, their menu and locations will be automatically pulled into the TapTable system.
The system automatically generates unique QR codes and NFC URLs for each table in a restaurant and our team is able to manufacture and encode table top promotional materials (e.g. table talkers) that are sent to the restaurant owner after sign up.
When people visit the restaurant they can interact with the table talker by tapping it with an NFC smartphone, scanning the QR code with their phone's camera or by visiting
https://order.taptable.io
and scanning the QR code with the built-in camera widget. The user will then see the restaurant's menu where they can select items, add items to their order, and complete checkout. The table number will be automatically selected and the user can pay with credit or debit card, Google Pay or Apple Pay.
The order is then forwarded to the Square Restaurant PoS to be picked up by restaurant staff and the order brought to the users table.
How we built it
The frontend is built on Angular, for both the portal and the order pages. We use MongoDB for persistent storage and NodeJS as an API layer to query MongoDB and the Square API.
We've built the system using Square OAuth, allowing a restaurant to link their Square account with their TapTable account so that we can make queries to Square on the users behalf.
The menu is then listed using the Square Catalog API. Orders are created using the Orders API and then paid with using the Payment API. We have queries and checks on the serverside to ensure orders are paid for and relay this state to the user.
Challenges we ran into
Time constraints have meant we weren't able to polish the portal, and more features are required on the order frontend to make it complete.
There are also some limits to the Square API (it can't be amazing for everything!) which we'll need to work into the system, such as re-ordering positions for categories and items provided by the Catalog API.
Accomplishments that we're proud of
Hitting a point where we're very pleased with the UX and speed of the order frontend when creating an order.
Creating a nice brand to showcase the solution
Testing the solution end to end and seeing a very smooth ordering process
Getting QR scanning working in the browser
What we learned
How to get QR scanning working in the browser
Animations and route animations in Angular.
Deep dive into a variety of Square APIs, and finding they're pleasantly easy to work with!
What's next for TapTable
Complete features for the order page
Add payment subscription functionality to the portal
Build additional features and functionality to the platform based on feedback from beta users
Built With
amazon-web-services
angular.js
mongodb
node.js
rxjs
Try it out
order.taptable.io
taptable.io | TapTable | Our application allows diners at restaurants or bars to purchase items from an online menu that is accessed using a QR code or NFC sticker, straight from the table they are sat at. | ['Nathan B', 'Chris Kane', 'Alex McGrath'] | [] | ['amazon-web-services', 'angular.js', 'mongodb', 'node.js', 'rxjs'] | 23 |
10,046 | https://devpost.com/software/pandaflow | Create Workflow
Inspiration
Did the Quickbooks reconciliation every month or every two weeks and thought there must be a better way to automate this process so that I didn't have to do this manually.
What it does
Basically, will add your POS, eCommerce transactions in QuickBooks,Xero, Wave and connect to your bank accounts and make sure it can reconcile them. It will also try to forecast cashflow and inventory from your past data and give you some business insights on you are doing and how you may do in the future.
How I built it
I started with connecting various APIs and then added a workflow UI so that I could create customer workflows.
Challenges I ran into
The APIs are very different for different apps so in-order to make them in the same format using OpenAPI - it was a lot of work
Accomplishments that I'm proud of
I am able to create all kinds of workflows to automate everyday tasks that saves us tons of time
What I learned
I am learning how SMBs are trying to create new business opportunities moving everything online.
What's next for Pandaflow
We are planning to help SMB get enterprise type tools so that they can automate their day to day business process.
Built With
api
azure
quickbook
react
square
xero
Try it out
pandaflow.io | Pandaflow | Automate your day to day tasks with your Square data and save time and focus on growing your business. | ['Niraj Shah'] | [] | ['api', 'azure', 'quickbook', 'react', 'square', 'xero'] | 24 |
10,046 | https://devpost.com/software/salonwaiver-com | website cover
Inspiration
Our business was closed due to COVID-19.
What it does
It's a contactless salon waiver system with supporting materials for salons to comply with re-opening requirements. There's also an option for customers to purchase one-time COVID-19 sick leave insurance.
How I built it
LAMP
Challenges I ran into
We're still waiting to hear back from the insurance company that's considering underwriting the coverage.
Accomplishments that I'm proud of
We made a working version just in time for our June 19th re-opening — and the Square hack offered the insurance company a useful visual.
What I learned
The need to focus on core functionality first. Then make it look pretty later.
What's next for SalonWaiver.com
Finalizing the agreement with the insurance underwriter. Then sign up beauty, hair and nail salons to use this.
Built With
lamp
square
Try it out
salonwaiver.com | SalonWaiver.com | Contactless waiver with supporting materials for salons and option for COVID-19 sick leave insurance | ['Wynn Nail Spa'] | [] | ['lamp', 'square'] | 25 |
10,046 | https://devpost.com/software/spilt-coffee | spilt coffee logo
spilt coffee screens (Search History, Results Page, Competitive Analysis)
☕️ spilt coffee
Media monitoring and brand reputation trends powered by AI.
We help small businesses take control of their brand by giving them instant access to and sentiment analysis on mentions across social, reviews, news and and more.
✨ Mission
We believe everyone has room to grow and thrive. We commoditize big data for small businesses, reviews are better when they’re heard. No one should be left out because the cost is too great or the technology too complex. So we build easy tools to empower businesses to take control of their brand. Tools that make media monitoring, competitive analysis and reputation tracking effortless—spill the coffee.
📈 Features
SEARCH
We scrape data from Yelp, Twitter and News about your brand (and any brand), bucket reviews by sentiment and display results on user-friendly charts.
MONITOR
We automate searches to easily monitor brand sentiments over time, and display historical trends on this data.
SENTIMENT ANALYSIS
We utilize advanced sentiment detection tools like VADER and wit.ai to segment positive, negative and neutral mentions, and assign overall sentiment to each mention.
COMPETITIVE ANALYSIS
We allow businesses to compare and overlay competitor data with their own, keeping up to date with what the
people
are saying.
🧱 Architecture
A brief overview of our application, with some key features (green) on the left and how we handle them on the backend on the right.
🔮 NLP Model
MODEL
Sentiment analysis was conducted based on an ensemble model aggregating both the
VADER model
and Facebook’s wit.ai NLP model. Train and test data was primarily formed from Yelp’s open data set (>8,000,000 user reviews) and the Sentiment140 Twitter dataset.
ACCURACY
Running our ensemble model on a subset (test) dataset, we achieved an accuracy 73.35% on a set of 2000 test Yelp points as well as a 74.25% for the Sentiment140 set on their given test set of 497 tweets.
NEXT STEPS
With spilt coffee, we can eventually provide further detailed analysis per company via reviews and collected text. Analysis on very negative reviews during dips historical trends can provide us with bi- and tri-grams of common phrases used in negative reviews. We can see what users tend to have issues with, and provide actionable recommendations to improve these businesses.
💻 Tech Stack
UI frameworks:
ElasticUI
Recharts
Frontend:
React.js
Backend:
Django
DB:
PostgreSQL
Authentication:
Auth0
Model:
VADER
wit.ai
✔️ To Do
☐ Provide helpful feedback and insights for businesses (actionable recommendations!).
☐ Perform more in depth competitor sentiment analysis, and ability to recognize competitors.
☐ Allow users to mark wrong sentiments (and correct them). Our models aren't perfect, we have room to grow too!
☐ We already provide a set of content marked as "extremely negative" or "extremely positive". Now, it's time to extrapolate reasons and analyze severity.
☐ Scrape more platforms (Facebook, Instagram, more news sources, etc.)
👻 Fun Facts
In our first (virtual) meeting where we were struggling to decide on our product name, one member spilled coffee on himself—with that, "spilt coffee" was born.
"8 million rows [of yelp review data] is a lot of rows."
Built With
amazon-web-services
django
firebase
postgresql
react
square
twitter
wit.ai
yelp
Try it out
spilt-coffee.web.app | spilt coffee | Media monitoring and brand reputation trends powered by AI. | ['Kevin Wang', 'Jonathan Dai', 'David Jin', 'Min Hwan Kim', 'Jonathan Yiu'] | [] | ['amazon-web-services', 'django', 'firebase', 'postgresql', 'react', 'square', 'twitter', 'wit.ai', 'yelp'] | 26 |
10,046 | https://devpost.com/software/skip-the-waiters | instructions
creating and joining a room
virtual line-up
menu and adding items to cart
messages from staff to rooms
cart view
checkout and order summary
User Persona
What is Skip the Waiters?
A web app for contactless queueing, ordering, and checkout when dine-in in restaurants.
Tech
Square API Integration
Payments API
Order API
Customers API
Firebase API integration
User Authentication
Database
Deployment
Heroku and AWS
Project Goals
Alleviate some responsibilities (taking orders and payment) from the staff
Help James keep the restaurant running with limited staff
James’ restaurant can operate with less staff at a time
Minimize contact between guests
Avoid having crowded in-person line ups with a virtual line-up
Allow guests to let the staff know which dishes to share to make dining-in more time efficient
Minimize contact between James’ staff and guests
Allow customers to have order ready while on virtual line-up
Contactless ordering and payment system for restaurant guests
Allow staff to send customers a default reminder to follow health and safety guidelines
Retain the social aspect of dining out
Allow staff to send customers custom messages
Allow customers to dine in with minimum hassle, maximum time efficiency
Retain customer information for contact tracing
Save customer information along with order information for easier contact tracing if needed
Testing
instructions attached in image gallery
You can use either QR Code
If you choose to use the QR code 1 (for if you're not in the restaurant yet), when prompted to enter table id, you can use a table number (i.e. "2")
You can register upon checkout with any fake email that doesn't exist yet in our user database.
Test values from Square:https: //developer.squareup.com/docs/testing/test-values
Admin page url: /Admin
send messages to rooms
remove a customer group from the virtual line (i.e. when they got a table already)
Clicking exit (top right button in menu page) should reset your session if you need to test with a new cart
What's next for Skip the Waiters
Further minimize interactions with staff
Also let customers message staff through the web app
Add features to help build back customer confidence in dining in
Add loyalty and in app perks with Square’s Loyalty API
More sophisticated cart sharing features
Leveraging Square’s Order API to create split bills based on each guests’ orders
Allow liking menu items for more efficient ordering
Provide better user experience
Ability to share rooms via chat or link
Automatically create a room when joining app from the same table
Leverage Square’s API to categorize items and provide customizations
Stricter form validations
More features and security on the Admin page of the app
Built With
amazon-web-services
express.js
figma
firebase
heroku
node.js
square
Try it out
squary.s3-website.ca-central-1.amazonaws.com | Skip the Waiters | Skip the waiting in line, in-person ordering and checkout. Keep the fun and social aspect of dining in while staying safe in this new normal. | ['Thomas Wong', 'sukh khera', 'Pinia Chandra', 'Farga Krishnanta'] | [] | ['amazon-web-services', 'express.js', 'figma', 'firebase', 'heroku', 'node.js', 'square'] | 27 |
10,046 | https://devpost.com/software/this-1pos2g | Venue's dashboard
Manage orders section
Accept orders
Decline orders providing a customized reason
Venue's manage menu section
Add new item form
Venue's stock management section where items can be removed from the menu or featured as out of stock.
Venue's order history and summary section
Venue's settings
"Choose University" section
"Choose a venue" section
Recommendation for users
Digital menu featuring meals
Digital menu featuring drinks
User's cart
Delivery form
Choose a time form
Checkout phase
User's order history
Inspiration
In light of recent events, on-campus food outlets face great challenges bringing their customers back and regaining their trust. The platforms out there, such as Deliveroo and Just Eat, are helping high-street vendors maintain their revenue during these trying times. However, university campuses in the UK seem to be lagging behind adopting these technologies, a reason for it being the strict branding guidelines and high fees that companies such as the ones mentioned above have.
This inspired us to build a low-commission food ordering platform specially designed for university campuses, that is highly customizable for each institution.
What it does
The mobile app gives students and staff the possibility to order and pay for their items online using their card, Apple Pay or Google Pay. Users are able to choose a pick-up, eat in or delivery option, depending on each outlets’ preferences. Outlets can manage incoming and outgoing orders, manage their stock, menus and keep track of their inventory live. Also, they can send push notifications to customers, informing them about daily offers or discounts, this strategy being very effective towards the end of the day to avoid food waste.
Using this platform, university outlets can keep their staff and customers safe by minimizing physical interaction, while increasing their revenue. With the new social distancing measures in place, serving customers is much slower, therefore fewer customers can be served. By using this mobile channel, outlets can better communicate with their audience and increase their selling capacity significantly.
How we built it
The mobile app for customers was built using Flutter and it runs on both iOS and Android operating systems. For database/server purposes, Firebase Database has been used.
The Payments, Orders, Locations and Customers APIs have been used for implementing in-app payments. Both Apple Pay and Google Pay have been implemented following Square’s documentation.
Also we've built a recommender system for customers using a word2vec algorithm in Python.
The software for the venues was also built using Flutter and it has been adapted for tablets having a 10 inch screen size.
We reached out to multiple universities across the UK and discussed with them about their problems, needs and what would be the best solution for them during these uncertain times. Having conversations with catering managers, we found out that they would need to have a live stock management feature on the platform, as well as to be able to limit the number of orders during certain time intervals to comply with social distancing rules. One UK university suggested having an on-campus delivery option, which we have successfully implemented. They have also suggested having the option to pause deliveries, in case there is no staff to fulfill orders during certain times.
Challenges we ran into
Business and communication challenges
Without having the possibility of having physical contact with the catering managers from the universities with whom we’ve been in touch, it has been challenging to communicate exactly how the platform works, as they were not able to have a feel of it. Instead, we have been using Microsoft Teams and Zoom for communication purposes and it has proved to be the best solution in these circumstances.
Getting in touch and discussing with potential customers has proven to be more difficult, as we couldn’t attend common conferences or meet them in person to showcase our product. Therefore it has been more difficult to gain their trust online (especially because we are an early-stage company).
Technical challenges
At times, the sandbox testing with Square was not reflecting accurate results in respect to payment processing. Strong Customer Authentication was not working accurately when having to save a credit card within the app using the sandbox environment. We have used the #buildwithsquare Slack channel to ask questions about what we’ve encountered and we were assured that in production this will work.
Some other challenges faced have been implementing suggested features from UK universities, such as an on-campus delivery option, or stock management features for the venue’s software. These have proven to be successful in the development of the product.
Accomplishments that we're proud of
Building a food ordering platform for higher education campuses that will help them overcome their catering challenges during this difficult time, allowing their staff and customers to feel safe buying food from their on-campus outlets.
Listening to feedback and suggestions from the universities that we’ve been in contact with and incorporating the best ideas. For example, building an on-campus delivery option and adding stock management features on the venue’s tablets have proved to be very important in the development of the overall product. Stock management features include adding or deleting items, making items live and having the possibility to make items out of or in stock during working hours. Also, all universities requested a sales report which will be available within the software. An end of the day report will be shown with the meal names, quantities and total earnings on each day.
What we learned
Even during these difficult and uncertain times we are facing, businesses can still thrive and implement solutions to make a difference.
We have learnt that it is very important to constantly listen to our customers’ feedback in order to improve and further develop our product (by adding essential features or optimising our current processes). Many of the features suggested by one partner university have been desired by the next few universities that showed interest in the platform, so listening to our partner university’s advice has proved to be extremely valuable.
Having a good code structure, so that adding and removing features for certain food venues would be easily customizable, has proved to be a great lesson.
An important lesson has been designing the product not only for being relevant during the pandemic but also after things get back to normal as well. In this way, we are able to continue helping and engaging with our customers in the long term.
What's next for Dill
Starting in July, one of our partner institutions in London is opening one of their on-campus outlets, where we’re going to implement our solution.
In the next few months, we will continue approaching new customers, while working with our current partners to improve Dill.
Improving the accuracy of the python recommender script for providing users with recommendations. This would allow us to have a stable version of the recommender system and include it in one of our future app releases.
Introducing a loyalty scheme for customers.
For on-campus food outlets we are planning to build a web version of the software for an easier menu management.
Apart from higher education institutions, we are planning to implement Dill within NHS Wales & England hospitals in the next months, in order to be used by patients, staff and visitors. Food outlets within hospitals lack technology solutions to improve their services and in many cases, patients have a difficult time communicating their preferred meals, particularly patients that have to rest in bed for a longer time period. Our solution would help hospitals improve their capabilities in a similar way that it currently helps higher education institutions, but adapted to each hospital’s specific needs.
Notes
A Google Play Store link has been attached, with an android app version in production environment but campus venues are closed and orders can't be processed. Therefore we have prepared apks featuring multiple venues and universities so that the app flow can be observed.
Second link is an android apk in sandbox environment (platform for users) where the first university has available venues. College Cafe is the only venue which has an available menu and it is the last one in the list. For trying to place an order College Cafe is the one that should be used.
Third link is the apk featuring the platform for institutions with the username:
[email protected]
and password: 123456.
Built With
android
android-studio
customersapi
dart
firebase
flutter
google-cloud
ios
javascript
locationsapi
node.js
ordersapi
paymentsapi
python
Try it out
play.google.com
drive.google.com
drive.google.com
mydill.co.uk | Dill | Dill is a food ordering platform designed for higher education campuses. Orders are processed and paid for digitally, minimizing physical interaction and increasing the outlets’ operating revenue. | ['Alex-Ioan Coldea'] | [] | ['android', 'android-studio', 'customersapi', 'dart', 'firebase', 'flutter', 'google-cloud', 'ios', 'javascript', 'locationsapi', 'node.js', 'ordersapi', 'paymentsapi', 'python'] | 28 |
10,046 | https://devpost.com/software/smart-tracker-covid-19-ewyhzx | Inspiration
Now a days whole world facing the novel Corona Virus, to track the spread of novel Corona Virus country-wise, details of confirmed cases, deaths and Recovered, awareness regarding COVID-19. This Android app was created to spread awareness about the covid -19 virus.
What it does
The Android app named as ‘SmartTracker-Covid-19’ created to spread awareness about the COVID -19 virus. App includes following functionalities:
CoronaEx Section - This section having following sub components: • News tab: Having latest new updates. Fake news seems to be spreading just as fast as the virus but as we have integrated from official sources so everyone will be aware from fake news. • World Statistic tab: Real-time Dashboard that tracks the recent cases of covid-19 across the world. • India Statistic tab: Coronavirus cases across different states in India with relevant death and recovered cases. • Prevention tab: Some Prevention to be carried out in order to defeat corona.
CoronaQuiz section - quiz that will help people know about the Corona virus and its effects on human body. It chooses random questions and show the correct answer for the questions and at the end user will get to know their highest score.
Helpline Section - As this application particularly made for Indian citizen to use, all state helpline number of India included.
Chatbot Section - A self-assisted bot made for the people navigate corona virus situation. Common Questions: Start screening,what is COVID-19? , What are the symptoms?
How I built it
We built with using Android studio. For the quiz section we have used sqlite database and live news data we have integrated from the News API. For the coronavirus statistic we have collected data from worldometer and coronameter.
Challenges I ran into
At time of integrating the chatbot in application.
Accomplishments that I'm proud of
Though , It was the first attempt to create chatbot.we have tried to up our level at some extent.
What's next for Smart-Tracker-COVID-19
For the better conversation we will be looking to work more on chatbot.
Built With
ai
android
dialogflow
newsapi
sqlite
Try it out
drive.google.com | Smart-Tracker-COVID-19 | Developed an android application to track COVID-19 current situation in all over world and stats, all state wise in India | ['Pramod Paratabadi'] | [] | ['ai', 'android', 'dialogflow', 'newsapi', 'sqlite'] | 29 |
10,046 | https://devpost.com/software/orderhere | QR Code Sticker on each table
OrderHere landing page to request a demo
Menu generated from QR Code
Payment screen offering Credit Card or Digital Wallet options
Business Card 2
Business Card 1
Inspiration
The concept for OrderHere was formed in late 2019 between two friends who wanted a simpler way to order drinks at their favorite brew houses. This is the classic example of a solution being created to fix a problem the founders personally experienced. We were tired of waiting for a server to ask us if we wanted another beer, or even worse, needing to wait in a bottlenecked line at the bar.
As the impact of the COVID-19 pandemic became clearer, particularly with the need to eliminate paper menus that could transmit the virus, we quickly realized this is a real business opportunity and ramped up our development efforts to offer a contactless ordering solution for dine-in customers. Our mission is to empower local restaurant operators with the ability to provide a superior level of customer service in a safe manner, while also enabling them to run their operations more efficiently.
What it does
OrderHere changes the process of ordering & payment for any restaurant operator. Each table contains a QR code that is linked to the specific table number. With a quick scan from a native smartphone camera, the customer is brought directly to the restaurant menu. The customer can order from the menu directly from their own device, without ever needing to create an account. Payment is collected by either Apple Pay, Google Pay, or a credit card.
This allows for a superior customer service that eliminates the need for physical menus. It also eliminates the need for waiting on a server to place an order, allowing users to be fully engaged in their conversation and place orders on demand - no more flagging down a server!
By eliminating the need for staff to take orders, operators can instead focus their staffs efforts on tending to guests needs in a more personalized way, while also operating in a leaner model.
How we built it
While Rob focused on the design of the user experience, Erik took the lead on the development work. We began with conceptual testing using lo-fidelity prototypes, and iterated on them to the experience we offer today.
Tools Used:
QR Code Generator
Kiss-Cut Sticker Vendor
Sketch
Invision
react.js
webpack
node.js
AWS API Gateway
AWS-Lambda
AWS-DynamoDB
AWS-S3
Square APIs: Orders, Items, Customers, Payments
Challenges we ran into
Integrating with Apple Pay was not as seamless as we expected it would be, and took considerably more development time than expected.
We also gained a further appreciation for UI & Visual designers, as neither of us have formal UI design training.
Accomplishments that we're proud of
We are very proud that we have built a ready-to-scale solution with 0 outside investment. where the concept, strategy & execution has been 100% delivered by a 2-man team. We are happy to be able to support our local community restaurant operators in their recovery efforts from the COVID-19 pandemic.
What we learned
We have learned that the hardest part to starting your own business is just getting started. It is impossible to answer all of the unknowns at the beginning, and the most important thing is to keep making progress everyday, pivoting as necessary when new obstacles present themselves.
What's next for OrderHere
OrderHere is launching to the public in late June 2020. We will begin onboarding customers to the platform and are excited to learn from our users. The future roadmap contains several features that will further enhance the experience, with the goal of reimagining how the local restaurant operates.
Built With
amazon-dynamodb
amazon-lambda
amazon-web-services
ant
node.js
react.js
s3
square-customers-api
square-items-api
square-orders-api
square-payments-api
webpack
Try it out
staging.customer.orderhere.store
www.orderhere.store | OrderHere | Contactless Ordering & Payment for in-person dining. Simply Scan, Tap & Enjoy. | ['Rob Wiederecht', 'Erik Koebke'] | [] | ['amazon-dynamodb', 'amazon-lambda', 'amazon-web-services', 'ant', 'node.js', 'react.js', 's3', 'square-customers-api', 'square-items-api', 'square-orders-api', 'square-payments-api', 'webpack'] | 30 |
10,046 | https://devpost.com/software/sleek | Payment Screen
Express Lane
Inspiration
No one enjoys waiting in lines, it's no secret. For centuries this hasn't been reinvented and the biggest innovations we have seen have been 'take a number' systems. At Sleek, we have taken this and made it digital, and here's the magic - we have introduced a dynamic surge pricing.
What it does
Monetizes on the long wait times for SMBs, so they don't lose revenue - they make up to 20% in profits (not revenue) with us.
How we built it
We assess wait times based on a couple of different data integrations - POS, location data, Computer Vision & apply deep learning to assess a dynamic fee.
Challenges we ran into
Marketing
Accomplishments that we're proud of
Improved revenues by 20%, made $600 in dynamic surge fees for one SMB
Large customer with about 20k food truck SMBs onboarded, about ~9k of those customers being on square.
What we learned
Waiting in lines is a customer problem, not an SMB problem - so customers are more willing to pay a price for that.
What's next for Sleek
Identifying newer segments for popular SMBs and bringing them onboard.
Built With
ai
amazon-dynamodb
amazon-web-services
checkout
insights
ml
node.js
pay-it-square
queue
react
square
visa
visa-pos-solutions-program
Try it out
demo.sleek.fyi | Sleek | Waiting in lines, reinvented. Popular SMBs with long lines can lose up to 30% revenue, we solve this with a dynamic 'surge fee' - No cashier, No app download, no signup and no commissions taken. | ['Gaurav Aggarwal'] | [] | ['ai', 'amazon-dynamodb', 'amazon-web-services', 'checkout', 'insights', 'ml', 'node.js', 'pay-it-square', 'queue', 'react', 'square', 'visa', 'visa-pos-solutions-program'] | 31 |
10,046 | https://devpost.com/software/ohana-mobile-app | Inspiration
Ohana is a brand new restaurant serving donuts, ice cream, and more that opened their doors near the start of the Covid-19 pandemic. Like many other businesses, Ohana became especially reliant on mobile orders. Previously utilizing their website to provide an ordering system, the company was in need of an upgraded, robust system that was integrated with Square. Ohana's new mobile app for Android and iOS is the solution. The app was built from the ground up to satisfy all of their needs.
What it does
The mobile-ordering app provides customers an avenue to quickly submit in-store or curbside pickup orders and earn rewards for doing so.
How I built it
I used Flutter for cross-platform mobile development and Google's Firebase for the backend of the app. I used Square's Customers, Items, Orders, and Payments APIs to interact with Square. I also used Square's In-App Payments SDK for Flutter.
Challenges I ran into
It was my first time creating a public mobile app from start to finish, but I enjoyed the challenge. Integrating the app with Square was mostly straightforward, but when I had trouble understanding the behavior of Square's API, the forum was there to provide guidance.
Accomplishments that I'm proud of
I am glad to have been able to fulfill all of Ohana's requests. Based on Ohana's specifications, I created a reward system that incentivizes customer loyalty by providing discounts for repeat customers which I am especially proud of.
What I learned
The hackathon has taught me that many small businesses using Square were faced with unprecedented challenges due to Covid-19. During these trying times, I was eager to help a growing company in an area that is crucial to their success. I have learned that businesses must remain agile and willing to change in every aspect.
What's next for Ohana Mobile App
The app will soon make a production release on the Google Play Store and Apple's App Store, following additional testing. After a successful production release, Ohana will be looking forward to adding more features to the app such as location selection, better network image caching, and enhanced customer rewards.
Built With
dart
firebase
flutter
node.js
Try it out
play.google.com | Ohana Mobile App | Mobile Ordering App for Ice Cream/Donut Business | ['Kade Dentel'] | [] | ['dart', 'firebase', 'flutter', 'node.js'] | 32 |
10,046 | https://devpost.com/software/winegenie-square | WineGenie
Inspiration
We always found the online and offline retail situation for wine exceptionally challenging.
We were overwhelmed by the huge selection of wines available in wine shops. We were lost finding wines that we liked and often we were not able to exactly explain what we like or what kind of wine we were looking for.
Also the staff in wine stores had problems to properly identify our preferences so that it took quite a long time of interaction and tasting many wines to find a good match.
At the moment the situtation got even worse, since tasting wines in stores is not possible due to corona.
This inspired us to create Wine Genie - Your Personal Digital Sommelier as a tool to solve these issues. We think it would be a perfect add on for Square in any wine related retail situation online or offline in stores and even restaurants.
What it does
WineGenie integrates data (ERP, POS, e-commerce systems, spreadsheets etc.) holding the inventory of a wine store.
A mobile website specific for a wine store enables customers to identify their taste profile with a short innovative questionaire. Based on that profile WineGenie can recommend matching wines.
WineGenie can also be deployed as plugins to webshops.
Challenges we ran into
Setup a demo store to showcase the solution with Square.
What we learned
We need to get in touch with Square staff to elaborate integration options in more detail.
What's next for WineGenie@Square
Finalize interface to Square synchronize inventory data.
Built With
amazon-web-services
angular.js
java
python
spring
tensorflow
typescript
Try it out
generic.winegenie.io | WineGenie@Square | WineGenie, the personal digital sommelier, integrates with Square to leverage inventory data. | ['Jean-Paul Okada', 'Thomas Keßler', 'Regina Keßler'] | [] | ['amazon-web-services', 'angular.js', 'java', 'python', 'spring', 'tensorflow', 'typescript'] | 33 |
10,046 | https://devpost.com/software/tap-to-donate-m50vyp | Language selection
Reports
Selection the Amount for kiosk mode
Demo or register
Confirmation screen entering reference
Settings
Account information
Idle video with options to kiosk, credit/debit or cash
Sample sign of Tap to Donate applied to a charity
side view of square donation case
back view of square donation case
Sample use for charity organization including information sign
Inspiration
It is getting very common to encounter a Salvation Army volunteer or be at a church and not being able to donate because we don't have coins or even small bills in our wallets. As we become a cashless society, the charities and not for profit organizations are negatively affected and experience a reduction in their cash collection from donors.
There are 1.8 million IRS-recognized charities and not for profit organizations in US, 180K in Canada and similar number in UK, and all will benefit from having a low cost solution for accepting credit and debit donations using contactless and chip and pin payments, either at their head offices and at charity events at the hands of their volunteer and employees.
Charity organizations can currently use the Square reader and phone to accept donations, but the standard Square POS software is not integrated to the charities system for issuing tax receipts and tracking donations, and is subject to deposit the money in a different bank account either by mistake or as result of fraud.
"Tap to Donate" system solves this problem by integrating the Android APP to a back end system to track the donations and post them online and/or issuing tax receipts. The system includes an epaper display with information about the organization name and amount to be charged. The App is locked to only deposit money in the charity bank account.
The epaper display is controlled by the application, it improves the user experience by giving feedback when transaction is successful or failed.
What it does
The application is intended to be compiled for a specific organization, and it validates that the Square POS app belongs to that organization ir order to prevent fraud.
The application has 3 options to help collect donations:
1) It has a kiosk mode for collecting fixed denomination donations using credit and debit card. This is intended for impulse donations with minimum intervention.
2) Variable amount credit and debit donations. This mode is intended to accept higher denominations. The operator will select the option and enter the amount as well as a reference such as account number for registered donors or phone number. After the transaction is processed, the app will connect to the server where the donor can request a tax receipt
3) Cash donation. This mode is intended to issue a receipt
The application communicates to a back end server provided by ipayzone.net to track the transactions, payments and cash collections and to provide a link where donors can obtain a tax receipt.
The Application also communicates to the epaper display via bluetooth to modify the messages.
It can be installed in a compatible Android POS terminal or use in a phone with external bluetooth receipt printer, or send the receipt via whatsapp or email.
How I built it
The application integrates to Square POS for Android. It integrates to IPayzone.net back end for reporting transactions, and controls the epaper display via bluetooth.
Challenges I ran into
Integrate the app to Square POS in a way that the reader will not timeout. Integrated to epaper display
Accomplishments that I'm proud of
The potential that this solution has to help small charities and non for profit. The ability to keep the Square reader in a loop for semi-unattended operation. The charity might have a local bank POS and use the Square reader as a secondary unit just to accept donations.
What I learned
How to control ePaper display via bluetooth. Integrate Square POS for Android
What's next for Tap to Donate
Create an IOS version.
Built With
acrylic
android
docking
epaper
square
Try it out
play.google.com | Tap to Donate | Non for profit and charity organizations depends on cash donations and are negatively affected as societies becomes cashless. Tap to Donate enable volunteers to accept credit and debit using Square | ['Juan Carlos Vera'] | [] | ['acrylic', 'android', 'docking', 'epaper', 'square'] | 34 |
10,046 | https://devpost.com/software/textbot-qsagz7 | iPad screen (merchant)
iPhone screen (consumers)
Inspiration
Every time I visited Philz, I stood in line while enviously seeing people skipping the line and picking up their mobile orders directly from the counter. But the thought of downloading yet another app, signing up to yet another account, just so I can order coffee, have always reminded me why I preferred standing in line. Even visiting websites to order a drink feels like too much of a mental investment for average consumers. I thought to myself, what if I can just text my order?
As a product guy, I observe details, but always look at the macro-economic trends. Self-driving car is inevitable, so is digital payment (credit card is old-school!). On top of that, I believe the future of business communications is via chat/text. It's an evolution from websites to apps, and now moving to chat/text.
Then COVID hit, and I see small businesses struggling with the lack of in-person ordering. I want to help them. And this clearly would be the catalyst to bring an average brick & mortar shop to the digital age. This is also when I finally realize my idea and started building a solution for it.
What it does
Textbot works with any food & drinks (and perhaps other) services. Consumers don't need to download and app or sign up. They simply text "new order @bluecoffee" and can checkout directly from text message. They can also share an order via text with family & friends. When order is ready, we text the end users to pick up their orders.
For merchants, we integrate with Square to provide payment, orders, and customer management. We have our own "order management" UI that they can tap "fulfill", which texts the customer that their order is ready for pick up.
We have a single phone number - 215-8TEXTME - which end users can save and use to text their orders. Eventually, they use this same number to text to multiple businesses using @[handle], and we would have built a marketplace for food, drinks, and services.
Consumers: Try live demo: Text "
new order @textbot
" to 215-8TEXTME
Merchants: Try our order management app:
https://app.gettextbot.com/users/sign_up
How I built it
The entire app is built on Ruby on Rails with very minimal front-end (jQuery + bootstrap). Merchant uses our web app. The consumer UI is SMS, powered by Twilio. For payment processor, we use Square and Stripe, which Square being the preferred platform for smbs.
Challenges I ran into
I have experience integrating with Stripe before because of my SaaS business. Their documentation is rich, and they have a product called Connected Accounts that works perfectly with what we're trying to accomplish. However, we quickly discovered that most of our target customers are on Square, which actually fits even better before of the way Orders can be managed on POS.
Square documentation is good, however, wasn't enough to get us started. Office hour was helpful, because I didn't know there's already a RoR sample app that I can leverage. These examples help a great deal, and we're able to get rolling from there. Other challenges are relatively minor, including the best way to parse Square API response. Turns out it's a combination of objects and hash, which wasn't intuitive (and was basically trial & error). For example, getting customer_id requires this
sq_customer.data.customer[:id]
, instead of
sq_customer.data.customer.id
or
sq_customer[:data][:customer][:id]
.
Accomplishments that I'm proud of
Even though this is a hackathon, I'm coding as if I'm going to start a company around it. In fact, this was my second startup idea if I wasn't working on the first one. In addition, I went to farmers market and coffee shops to ask customers about how we can help, and received some invaluable feedback.
What I learned
Technically: Everything about payments and its complexities. Also, I never thought rounding with floating point can be so sensitive in Ruby (1 cent off, Square rejects the payment)!
Product/Market: Customers don't like to pay 30% to DoorDash or Grubhub, naturally.
Alternative option is pay $100/month subscription for websites / apps to enable online order.
Our business model differs. We started out charge 5% for each order (but no monthly / setup fee). However, that still doesn't make sense if we're helping SMBs. So now our new revenue model is charge 5% to customers who are ordering. Most people don't mind paying 15cents extra for a $3 coffee. If they do, they can always wait in line, pay, and wait for their order.
Customers really detest setting up menus with all the services above. We intentionally keep our menu easy to setup.
What's next for Textbot
Keep a simple menu means we can't have complex combinations / add-ons. A coffee can be L/S, Hot/Cold, 2%/Fat free/Soy, etc. etc. Therefore, we plan to have Textbot act like a cashier and ask follow-up questions about all the add-ons & customizations. This means we will integration with Items.
Rewards program
Go-to-market!
Built With
amazon-web-services
bootstrap
ruby-on-rails
square
twilio
Try it out
gettextbot.com | Textbot | Order-ahead and pick-up made easy, with text messages. | ['Will Cheung'] | [] | ['amazon-web-services', 'bootstrap', 'ruby-on-rails', 'square', 'twilio'] | 35 |
10,046 | https://devpost.com/software/square-export | Dashboard.
Inspiration
Many responses in the Square seller community echoed the lack of features in both dashboard reports and the exported Excel file. Wanting to contribute to local businesses utilizing Square, I decided to implement this functionality using React and a data-grid library.
What it does
Further enhances the Square dashboard/report features with filter/sort methods and an export option that saves filtering decisions.
How I built it
Express.js to handle the API logic: communicating with Square's APIs using Square Connect and then retrieving the order(s) information simulated by the
Order Ahead
demo application as shown in the developer documentation.
React.js for fast performance.
Kendo UI for the data grid and export.
Challenges I ran into
I originally wanted to incorporate TypeScript with this project, however there were compilation issues that were too time-consuming.
Accomplishments that I'm proud of
Developing this on my own.
What I learned
How to use Square connect and Kendo UI.
What's next for Square Export
Other business information can definitely be fed using Kendo UI.
Built With
express.js
javascript
kendo
node.js
react
Try it out
github.com | Square Export | Enhancement to the existing Square dashboard/report functionality with a Kendo UI implementation and better export options. | [] | [] | ['express.js', 'javascript', 'kendo', 'node.js', 'react'] | 36 |
10,046 | https://devpost.com/software/wecare-0fjkb9 | Summary: Home Screen of app, which allows you to report your symptoms, check the status of your circle, and get daily personalized tips.
Home Screen of app, which allows you to report your symptoms, check the status of your circle, and get daily personalized tips.
Map Screen of app, which allows you to see hotspots around you and your Care Circle.
Care Circle screen of app, which allows you to health conditions of your loved ones.
Web interface, which can be used to update the symptoms. It is synced with the app.
The problem WeCare solves
As the outbreak of COVID-19 continues to spread throughout the entire world, more stringent containment measures from social distancing to city closure are being put into place, greatly stressing people we care about. To address the outbreak, there have been many ad hoc solutions for symptom tracking (e.g.,
UK app
), contact tracing (e.g.,
PPEP-PT
), and environmental risk dashboards (
covidmap
). However, these fragmented solutions may lead to false risk communication to citizens, while violating the privacy, adding extra layers of pressure to authorities and public health, and are not effective to follow the conditions of our cared ones. Until now, there is no privacy-preserving platform in the world to 1) let us follow the health conditions of our cared ones, 2) use a statistically rigorous live hotspots mapping to visualize current potential risks around localities based on available and important factors (environment, contacts, and symptoms) so the community can stay safer while resuming their normal life, and 3) collect accurate information for policymakers to better plan their limited resources.
Such a unified solution would help many families who are not able to see each other due to self-quarantine and enable early detection and risk evaluation, which may save many lives, especially for vulnerable groups. These urgent needs would remain for many months given that the quarantine conditions may be in place for the upcoming months, as the outbreak is not reported to occur yet in Africa, the potential arrival of second and third waves, and COVID-19 potential reappearance next year at a smaller scale (like seasonal flu). There is still uncertain information about immunity after being infected and recovered from COVID-19. Therefore, it is of paramount importance to address them using an easy-to-use and privacy-preserving solution that helps individuals, governments, and public health authorities. The closest solution is
COVID Aggregated Risk Evaluation project
, which tries to aggregate environment, contacts, and symptoms into a single risk factor. WeCare takes a different approach and a) visualizes those factors (instead of combining them into a single risk value) for more tangible risk communication and b) incentivizes individuals to regularly check their symptoms and share it with their Care Circle or health authorities.
WeCare Solution
WeCare is a digital platform, both app and website. Both platforms can be used separately, and with freedom of choice towards the user. The app, however, will give users more information and mobile resources throughout the day. Our cross-platform app enables symptom tracking, contact tracing, and environmental risk evaluation (using official data from public health authorities). Individuals can add their family members and friends to a Care Circle and track their health status and get personalized daily updates. In particular, individuals can opt-in to fill a simple questionnaire, supervised by our epidemiologist team member, about their symptoms, comorbidities, and demographic information. The app then tracks their location and informs them of potential hotspots for them and for vulnerable populations over a live map, built using opt-in reports of individuals. This map is accessible on the app and our website. Moreover, symptoms of individuals will be tracked frequently to enable sending a notification to the Care Circle and health authorities once the conditions get more severe. We have also designed a citizen point, where individuals get badges based on their contributions to solving pandemic by daily checkup, staying healthy, avoiding highly risky zones, protecting vulnerable groups, and sharing their anonymous data.
Our contact tracing module follows guidelines of Decentralized Pan-European Privacy-Preserving Proximity Tracing
(PEPP-PT)
, which is an international collaboration of top European universities and research institutes to ensure safety and privacy of individuals.
What we have done during the summer.
We have updated the app-design. New contacts with Brasil, Chile and Singapore. We have also made some translation work with the app. Shared more on social media about the project and also connected to more people on slack and LinkedIn.
We have consolidated the idea and validated it with a customer survey. We then developed a new interface for
website
and changed the python backend to make it compatible with the WeCare app. We have also designed the app prototype and all main functionalities:
Environment: We have developed the notion of hotspots where we have developed a machine learning model that maps the certified number of infected people in a city and the spatial distribution of city population to the approximate number of infected in the neighbourhood of everyone.
Contact tracing: We have developed and successfully tested a privacy-preserving decentralized contact tracing module following the
(PEPP-PT)
, guidelines.
Symptoms tracking: We have developed a symptom tracking module for the app and website.
Care Circle: We have designed and implemented Care Circle where individuals can add significant ones to their circle using an anonymous ID and track their health status and the risk map around their location.
You can change what info you want to share with Care Circle during the crisis.
The app is very easy-to-use with minimal input (less than a minute per day) from the user.
We are proud of the achievements of our team, given the very limited time and all the challenges.
Challenges we ran into
EUvsVirus Hackathon Challenge opened its online borders recently to the global audiences which brought together plenty of people of different expertise and skills. There were challenges that we faced that were very unique, as we faced a variety of communication platforms on top of open-source development tools.
Online Slack workspaces and Zoom meetings and webinars presented challenges in forms of inactive team members, cross-communications, and information bombardment in several separate threads and channels in Slack and online meetings of strangers that are coordinated across different time zones. In developing the website and app for user input data, our next challenge was in preserving the privacy of user information.
In the development of a live map indicating hotspot regions of the COVID-19 real-time dataset, our biggest challenge here was to ensure we do not misrepresent risk and prediction into our live mapping models. We approached Skill Mentor Alise. E, a specialist in epidemiology, who then explained in greater detail that the proper prediction and risk modelling should take into account a large number of factors such as population, epidemiology, and mitigations, etc., and take caution on the information we are presenting to the public. Coupled with the lack of official datasets available for specific municipalities for regions, we based geocoding data mining of user input by area codes cross-compared with available Sweden cities number of fatalities, infected and in intensive care due to COVID-19.
The solution’s impact on the crisis
We believe that WeCare would help many families who can see each other due to self-quarantine and enable early detection and risk evaluation, which may save many lives, especially for vulnerable groups. The ability to check up on their Care Circle and the hotspots around them substantially reduces the stress level and enables a much more effective and safer re-opening of the communities. Also, individuals can have a better understanding of the COVID-19 situation in their local neighbourhood, which is of paramount importance but not available today.
The live hotspot map enables many people of at-risk groups to have their daily walk and exercise, which are essential to improve their immunity system, yet sadly almost impossible today in many countries.
The concept of Care Circle motivates many people to invite a few others to monitor their symptoms on a daily basis (incentivized also through badges and notifications) and take more effective prevention practices.
Thereby, WeCare enables everyone to make important contributions toward addressing the crisis.
Moreover, data sharing would enable a better visual mapping model for public assessment, but also better data collection for the public health authorities and policymakers to make more informed decisions.
The necessities to continue the project
We plan to continue the project and fully develop the app. However, to realize the vision of WeCare we need the followings:
Social acceptance: though being confirmed using a small customer survey, we need more people to use the WeCare app and share their data, to build a better live risk map. We would also appreciate more fine-grained data from the health authorities, including the number of infected cases in small city zones and municipalities.
Public support: a partnership with authorities and potentially being as a part of government services, though not being necessary, to make it more legitimate. This would increase the level of reporting and therefore having a better overview and control of the crisis.
Resources: So far, we are voluntarily (and happily) paying for the costs of the servers. Given that all the services of the app and website would be free, we may need some support to run the services in the long-run.
The value of your solution(s) after the crisis
The quarantine conditions and strict isolation policies may still be in place for upcoming months and year, as the outbreak is not reported to occur yet in Africa, the potential arrival of second and third waves, and possible COVID-19 reappearance next year at a smaller scale (like seasonal flu).
Therefore, we believe that WeCare is a sustainable solution and remains very valuable after the current COVID-19 crisis.
The URL to the prototype
We believe in open science and open-source developments. You can find all the codes and documentation (so far) at our
Website
.
Github repo
.
Other channels.
https://www.facebook.com/wecareteamsweden
https://www.instagram.com/wecare_team
https://www.linkedin.com/company/42699280
https://youtu.be/_4wAGCkwInw
(new app demo 2020-05)
Interview:
https://www.ingenjoren.se/2020/04/29/de-jobbar-pa-fritiden-med-en-svensk-smittspridnings-app
Built With
node.js
python
react
vue.js
Try it out
www.covidmap.se
github.com | WeCare | WeCare is a privacy-preserving app & page that keeps you & your family safer. You can track the health status of your cared ones & use a live hotspot map to start your normal life while staying safer. | [] | ['2nd place', 'Best EUvsVirus Continuation', 'Best Privacy Project'] | ['node.js', 'python', 'react', 'vue.js'] | 37 |
10,046 | https://devpost.com/software/sound-browser-pbxhez | Browse and purchase items sold by local and mainstream musicians
Detailed item pages for sold items, integrate.
View live and pre-recorded streams and purchase merchandise.
Integrated purchases of merchandise using the square in-app android sdk
View recorded concerts and performances right from your TV
Purchase completed
SoundBrowser
Live concerts and musician merchandise sales from your FireTV.
Inspiration
Small and large musicians alike are struggling during the current COVID-19 pandemic. SoundBrowser is a FireTV platform for hosting online / from home concerts and selling merchandise directly through your TV. This app adds a new way for fans to engage with the content of local musicians while simultaneously supporting musicians through merchandise sales.
How we built it
Took a base FireTV application and updated to accommodate videos of live music artists
Added in logic to pull in merchandise information from a live API
Powered by Square payments to collect and make purchases of items from your television set.
Challenges we ran into
Merging square payments sdk into a FireTV application.
Integrating in-app purchases
What we learned
How to set up our first square application
What's next for Sound Browser
Integrate user accounts
Add musician portal for customizing purchases
Social media integrations
Demo:
https://youtu.be/s6praVIxEJc
Built With
amazon-web-services
android
firetv
square
Try it out
github.com | Sound Browser | Support musicians by watching at-home concerts and purchasing merchandise via Square on your TV | ['Chris Buonocore', 'Brian Cottrell'] | [] | ['amazon-web-services', 'android', 'firetv', 'square'] | 38 |
10,046 | https://devpost.com/software/barista-station | Orders
Orders History
Multiple device support
Team Notifications
Dark mode! Because it is 2020
Theming (Example: One Drop Coffee Company)
Inspiration
Barista Station was created while working with my sister who opened a coffee shop in Oct 2019. We were trying solve the communication problem between the cashier and the barista...because let's face it people can make some complex coffee orders!
What it does
Barista Station automatically prioritizes and organizes orders as they come in from the Square point-of-sale and online while allowing the barista to focus on what is most important to them.
How I built it
reactJS + serverless
(Because I'm not an animal)
Challenges I ran into
Adding support for multiple devices was quite tricky while maintaining a single sign on with Square.
Accomplishments that I'm proud of
Barista Station started as just a fun project and has developed into something I'm really proud of. I love seeing my sister use this in her coffee shop everyday.
What's next for Barista Station
I love seeing people use something I built and get value from it. I would really like to make Barista Station more accessible to any Square merchant for
free
through
https://baristastation.app
(not deployed quite yet). In addition, I am planning to open source all of my work on Barista Station. I am excited to see what great ideas the community comes up with!
Finally, my sisters coffee shop had to close for a month during covid and I would love nothing more to give back to her small business that inspired me.
Built With
firebase
node.js
react
square
Try it out
barista-station-demo.web.app | Barista Station | The perfect companion for coffee shops with seamless integration between the Square point-of-sale and online ordering. | ['Darren Furr'] | [] | ['firebase', 'node.js', 'react', 'square'] | 39 |
10,046 | https://devpost.com/software/pretamenu | Admin business options.
Admin calendar with item tally.
Admin food truck sales report with map.
Admin basic media customization.
Admin sales dashboard.
Admin super sales by restaurant.
Burger Dog sample restaurant map view.
Mr Potato Spread (real client) map view.
Mr Potato Spread (real client) menu view.
The Bakeshop NSB (real client) menu view.
Check out view Square Loyalty Reward indicator.
Inspiration
The food and beverage industry have very specific needs. With Pretamenu, we address the specific needs of restaurants, food trucks, cafes and bakeries with a powerful suite of tools that tightly integrate with Square to get their business online to reach their customers.
What it does
Pretamenu allows an existing Square restaurant to connect their account and instantly bring their menu online. After some style and customization, they can make it look like a part of their own website and get tools specific to their needs such as having multiple locations, food truck scheduling, group ordering, order queuing, variable prep times, a simple homepage and many more.
How I built it
I built this using NodeJS, VueJS and PostgresSQL. I got my first restaurant client Mister Potato Spread (mrpotatospread.com) which had a food truck with specific needs requiring multiple locations and time slots. Then my second client was a bakery (thebakeshopnsb.com) which had special requests like variable prep times, and item tallying to prepare batches of cakes. My third client was a boba cafe (easylifeboba.com) which had higher traffic and needed to queue their orders, they still opted to use normal order ahead. Combined, I built Pretamenu to address all these concerns and hope to get more diverse clients in the future.
Challenges I ran into
Some of the Square APIs I used were in beta such as Square Loyalty and Square Gift Cards. I had to become a beta tester to get these added. Another challenge was working with brave and patient restaurants who were willing to work with me to get their needs addressed.
Accomplishments that I'm proud of
I am proud that I was able to develop this system to help small business restaurants with their issues at a reasonable cost. I hope to keep costs low and develop more tools to help them grow their business.
What I learned
I learned a lot about the restaurant business and how different their issues were. Many of their issues are easy to develop, it just takes someone to listen and implement it in a simple and thoughtful way.
What's next for Pretamenu
I hope to increase my clients by ramping up marketing efforts and join the Square App Marketplace. Other issues I can tackle in the future are a kitchen display system (KDS) and the ability to cloud print labels for takeout and drinks. Hopefully I can signup over 10 clients soon. Thanks for checking out my submission!
Built With
bootstrap
jquery
mailchimp
node.js
postgresql
redis
square
twilio
vuejs
Try it out
burger.pretamenu.com
boba.pretamenu.com
order.thebakeshopnsb.com
order.mrpotatospread.com
sushi.pretamenu.com | Pretamenu | A powerful suite of tools for small business restaurants to get online. | ['Tony Suriyathep'] | [] | ['bootstrap', 'jquery', 'mailchimp', 'node.js', 'postgresql', 'redis', 'square', 'twilio', 'vuejs'] | 40 |
10,046 | https://devpost.com/software/nexttakeout | (Seller App) Add your restaurant.
(Seller App) Add your restaurant menu.
(Seller App) Restaurant menu
(Customer App) User sign in and browse restaurant
(Customer App) User browse restaurant menu
(Customer App) User buy the meal subscription
(Customer App) User make payment via Square
(Customer App) User set up their schedule
(Customer App) User choose the dish they want for selected date
(Customer App) the order is placed for that date
(Customer App) Home screen now show user upcoming meals
(Seller App) Home screen show list of the dishes due for pick up today. They can mark as dish ready for pickup and completed.
(Seller App) Order screen show the subscription packages sold, as well as the schedule of all the dishes for upcoming orders
Inspiration
As the restaurants starting to reopen after the shutdown, their seating capacity for dine-in option are still limited by the government. To get through these times, they would likely needed to rely on their takeout/delivery sales to get by. Many restaurants have already closed down for good. Throughout the years I have lost so many of my favorites restaurants that have great food but perhaps does not adequate fund or cashflow.
What it does
NextTakeout is a meal subscription service, users will be able to buy a prepaid monthly allotment for his/her favorite local eateries. They will then be able to schedule the meal selection and pickup when it's ready.
How I built it
Using Flutter as a frontend and Firebase as a backend with Square as a payment system.
Challenges I ran into
As a team of one, I have to choose which features I have to leave out of the MVP.
Never join hackathon before and not knowing how flesh out the prototype should be for the submission.
Not enough time to finish what i want.
Accomplishments that I'm proud of
First time participating in a hackathon, utilizing new languages/technology that i've never use before and manage to finish prototype within the deadline while super busy with OT at my fulltime job this past few weeks.
What I learned
Flutter/Dart and Firebase
What's next for NextTakeout
Unfinished
QR code delivery pickup
Map base with gps location range for restaurant search menu
Next Phase
put gamification aspect to this, so user can compete to be the top supporter of the restaurant/bakery/coffee shop. e.g. Showing the top 10 patrons of each business. (Business can choose to reward these patrons)
Also plan to provide delivery service that is more cost effective than Uber/SkipTheDish/DoorDash so that the business can pocket more of the money.
Built With
firebase
flutter
square
Try it out
github.com
drive.google.com | NextTakeout | A takeout subscription service: Show support for your favorite eateries and save them from going out of business. | ['VancityGunny Sukprasongphol'] | [] | ['firebase', 'flutter', 'square'] | 41 |
10,046 | https://devpost.com/software/salon-boi | Data Flow
GIF
Project Gif
Signup Page
Login Page
Discover Page
Business Page
Reviews
Booking Page
Schedule Page 1
Schedule Page 2
Confirmation Page
Add Card
Appointment Page
Appointment Modal
Loyalty Page
Loyalty Modal
Saved Page
Profile Page
Logo
Check it out @
http://206.189.232.188:3000/
Site is Mobile optimized so it will not look as good on a computer screen!
Inspiration
Many salons currently handle payments/bookings inefficiently through phone calls, pen, and paper. After the COVID-19 pandemic, salons can anticipate an influx of customers, which can be overwhelming. Our goal with this application is to help digitize appointment based service businesses and streamline their operations using Square technology. Additionally, businesses who want to increase their customer base and customer loyalty can utilize our application, which has loyalty points built in.
What it does
Users get to put in their availability on the app and the app will find them the nearest salons closest to their preferences. Users will be able to book the appointment, add it to their calendar and pay all through the app.
How I built it
The entire application's UI/UX was designed using Figma. The frontend is built with React.js, Redux and includes the Square React Card Component. It communicates with our backend Python Flask API which queries data from MongoDB and accesses Square's Payment, Customer, and Loyalty APIs.
Challenges I ran into
Having not worked with Square's APIs before, understanding Nonces and setting up Loyalty took some learning.
There were problems with the fake credit card not working with the Loyalty api and some nuances with the Customer creation
Accomplishments that I'm proud of.
We created a very flushed out working application in a short amount of time.
What I learned
We learned how to develop using the Square API. We also learned about the business flows of salons and understood the needs of businesses which are still offline.
What's next for AppointMate
We will create the business side of the application since the business needs to accept customers, handle customer base/loyalty, and accept payment.
Built With
css3
flask
google-calendar
google-directions
google-maps
javascript
python
react
square
Try it out
github.com
206.189.232.188
www.figma.com | AppointMate | Your appointments. One seamless experience. | ['Halmon Lui', 'Parker Van Roy', 'Sonam Ghosh', 'Brian He', 'Vanessa Tsang'] | [] | ['css3', 'flask', 'google-calendar', 'google-directions', 'google-maps', 'javascript', 'python', 'react', 'square'] | 42 |
10,046 | https://devpost.com/software/zero-cost-square-pos-terminal-by-payment-source-canada | Inspiration
The Association of Alberta Registry Agents represent the interest of 207 agents in Alberta Canada. The members provide a wide range of services to all Albertans including issue driver's licences, register your vehicles, help you apply for birth certificates, and much more. They are in need of a card present payment solution where consumers pay with a credit card, and the agent receives 100% of its billed amount.
The same need is present for other merchants in Canada.
The Alberta Registry Agents are small businesses that obtain from Alberta's government a fixed amount ($9) per completing a car or truck registration, and they are not allow to charge the user, not afford to absorb the credit card fees, so they typically limit to accept cash or debit as in store payment. They need a third party company to provide the service of accepting credit card payments from the customers and give the net amount to the registry. The third party company charges the customer a convenience fee for that service. Consider that there are 5 million vehicles in Alberta, and average charge is $80 per year, is a $400M Cnd total amount to be paid including debit, cash and credit.
Other companies that do similar work is cardx.com in USA, they provide zero cost credit card payment solutions to schools, universities, cities.
In Canada and USA the regulations and rules from Visa/MC are moving toward allowing surcharge to the customer under certain scenarios.
What it does
The App is configured to add administrative fees and service charges to the amount, and then process the transaction with Square server, after the transaction is completed it connects to Payment Source server and reports the information for later reconciliation. The application can be configured to have receive the payment at the merchant 's bank account, or at Payment Source's bank account.
The APP allows to have configurable receipt text and generate reports.
How I built it
The app was built with Android Studio, and uses Square Android POS to process the transaction, and proprietary code communicate to Payment Source's Server. It supports multiple printers including bluetooth receipt printers, and Android POS terminal
Challenges I ran into
Understanding the business needs of the customer and translating it into a solution that works.
Accomplishments that I'm proud of
Locating an Android POS that is compatible with Square.
What I learned
Square POS is a flexible suite of payment tools that allows customization of unique payment requirements.
What's next for Zero cost Square POS terminal by Payment Source Canada
Find other organizations that require zero cost terminal solutions.
Built With
android
java
square
Try it out
play.google.com
drive.google.com | Zero cost Square POS terminal by Payment Source Canada | Use your Square account to implement zero cost terminal for government entities, schools and other organizations by adding service fee to cover the cost of credit card transactions | ['Juan Carlos Vera'] | [] | ['android', 'java', 'square'] | 43 |
10,046 | https://devpost.com/software/tap-for-photo | Inspiration
Photo booths are becoming popular at church events, schools, parties, charity and gala events, etc. The photographer has to accept the payment, take the photo and take the customer's details such as email and phone to give them access to digital photos. Customers also struggle if they did not have cash with them, or limit the number of photos to the amount of cash they have. A better solution is to use a Square reader in a semi unattended mode connected to a receipt printer, and have the customers tap the card to print instructions and receipt, then handle the receipt to the photographer to have the pictures taken. The App automatically creates a link, password, and instructions that are printed for the customer to download the digital pictures and order physical prints.
The photographer then takes the photos and upload the files to the link created by the app.
What it does
The App accepts fixed amount payments automatically, allowing the photographer to concentrate on taking the pictures and not worry about the payment, giving cash change, etc. The App also generates a link in SmugMug,com and assigns the password. All the photographer has to do is upload the pictures to that link as the customer already has the information in the receipt.
The customer can then order prints and copies from SmugMug.com
How I built it
Used Square POS for Android, integrated such that the app passes the information in an automatic loop. It also communicates to the printer via bluetooth.
Challenges I ran into
How to make the app automatically loop and avoid the square reader to go idle.
Accomplishments that I'm proud of
Adapting Square POS to automatically charge a fixed amount and print
What I learned
How to integrate Square POS to apps.
What's next for Tap for Photo
Promote it and monetize the app.
Built With
android
pos
square
Try it out
play.google.com | Tap for Photo | Are you a photographer? this is App is for you, accept fixed amount card payments and prints receipts automatically, it includes instructions on password on how to access the photos from smugmug.com | ['Juan Carlos Vera'] | [] | ['android', 'pos', 'square'] | 44 |
10,046 | https://devpost.com/software/tap-to-buy | Inspiration
Attending a movie night at my kid's school and waiting in line to pay for a pizza slice and drinks made me realized that there are many cases where you just want to buy fixed price items as quick as possible and obtain a receipt you can give to the person serving. Having contactless payments and printing a receipt speeds up the line and improves customer satisfaction. Multiple taps of the reader can accommodate for buying more than one unit.
What it does
It automatically accepts fixed amount payments and prints configurable receipts. Receipts can be event tickets, food and drink vouchers, instructions, etc.
How I built it
Using Android Studio to integrate to Square POS, and added bluetooth printing support.
Challenges I ran into
Having the Square reader not to timeout when idle.
Accomplishments that I'm proud of
Figured out how to keep the Square POS in a loop
What I learned
I learned about Square POS for Android
What's next for Tap to Buy
Promote and monetize.
Built With
android
java
pos
square
Try it out
play.google.com | Tap to Buy | Accept fixed amount card payments automatically and print receipts. Use it to sell event tickets, food and drink vouchers, instructions and more. It processes semi unattended transactions | ['Juan Carlos Vera'] | [] | ['android', 'java', 'pos', 'square'] | 45 |
10,046 | https://devpost.com/software/insta-fare | Amadeus Flight Choice Prediction help determines best flights
Get best flight fares directly from images in the page you're browsing
Easy one click use, no settings, no selections just best prices
Inspiration
I want to be able to know how much would it cost me to fly to a destination that I see in a web page that I'm browsing without leaving that page to visit flight booking websites
What it does
Insta Fare is a browser extension, once installed I can hover over any image on the page, and a search button will appear, I can then click the search button to get the best flight options to the place that's in the image, departing from the nearest airport.
How I built it
Using computer vision and machine learning, to get the location of of the place that appears in the image, to get nearest airport, APIs from Amadeus including Low-fare search API, and Flight Choice Prediction Artificial Intelligence API. Spring boot for the backend. The browser extension it self is JS, CSS and HTML
Challenges I ran into
The machine learning model need to be trained with more images to recognize more places. Also the dataset for flights and airports is the Amadeus dataset which does not include all possible flights from each airport
Accomplishments that I'm proud of
Combining Machine Learning and Artificial intelligence to create the first frictionless way of finding flights from within any page that I'm browsing
What I learned
Artificial intelligence prediction is the way forward for travellers in terms of for helping sift through the many flights available to return the best flights
What's next for Insta fare
Amadeus APIs are rich with features, next is returning information about the destination from Destination Content API, points of interest. Add hotel results to the search
Built With
amadeus
computervision
css
html
javascript
machine-learning
spring | Insta_Fare | Get the best ticket fare for a flight from images without interrupting your browsing | [] | [] | ['amadeus', 'computervision', 'css', 'html', 'javascript', 'machine-learning', 'spring'] | 46 |
10,046 | https://devpost.com/software/bella-stayhome | Stay Home powered by BEK Service GmbH
Due to the current COVID-19 situation, we stay at home. Use Stay Home especially now to connect yourself with your neighbours, to stay in touch with your social network and get through quarantine healthier. We have decided to provide “Stay Home” free of charge until further notice! Sharing is caring <3
Stay Home is a Real Social Network, in which you can meet and support your neighbourhood and the surrounding areas. Stay Home enables you to bring the advantages of the digital world into the analogue world.
Just imagine: Your neighbour goes shopping and can bring you something. You urgently need flour, because you are going to bake a cake? Or, you need a screwdriver but don't have one by yourself? No problem! With Stay Home, your neighbour is just a click away.
Searching-Radius: Meet people in your surrounding areas has never been closer.
Post your contribution: Need something? Great! Just post it and tell it to your neighbours. You can help? Awesome! Post your contribution and tell the granny in your surrounding areas that you plan to go shopping. You would deserve grandma's kiss!
News: You have an individual concern? Just ask your neighbours.
Easy Login: Use your Facebook- or Xing- Account to get ready within a few seconds.
I'm proud of 200k Users in 1 Week
Built With
android
google-geocoding
google-places
ios
node.js
react
Try it out
stayhome.app.link
bekservice.de | Bella #Stayhome | Stay Home: Neighbourhood hub / Connect with people around you | ['BEK Service GmbH'] | ['The Wolfram Award'] | ['android', 'google-geocoding', 'google-places', 'ios', 'node.js', 'react'] | 47 |
10,046 | https://devpost.com/software/test-xlnmoe | Street Eatz
Street Truck
Street Eatz
Inspiration
Food trucks have been struggling in the new business environment. With canceled food truck events and prohibiting public gatherings, there have been fewer ways for food trucks to make money.
Being a regular customer of food trucks, I want to help and make it easier for customers to do business with food trucks. The Square API provides contactless commerce options. It also provides the ability to eliminate one of the most inconvenient things about the experience,
waiting in line
.
If you want to get something to eat you usually have to wait in line to order and some of those lines take over 30 minutes. If you want to get some food from more than one truck you will have to wait in line
AGAIN
The waiting time is a big deterrent for those who have only have a short amount of time to eat.
With the new environment we are in, people are social distancing and looking for contactless ways to handle transactions. Both of these things are not currently happening when ordering from a food truck.
I created this app for food trucks and their customers. With the app customers can create their own orders, freeing up the employees to make the food who would otherwise take the order. Instead of waiting in lines and passing payment back and forth, customers can now social distance and get their food in a contactless way.
What it does
There are two mobile apps - a customer app and the food truck app:
Food trucks would set up an account on the
Street Truck
app. They can add their truck information, authorizing square to use this app, and add the menu and their schedule (hours and location). That is all that is needed to start processing orders from customers!!!
Customers can use the
Street Eatz
app to view the menu and make an order to the food truck. No setup needed for a customer. Once an order is processed both the customer and food truck will see the order on in their apps. Once the order is ready the food truck can mark it completed and the customer will receive a notification to pick up their order at the food truck.
Food truck app:
Street Truck
Add truck information
Connect square merchant account
Add menu items and price
Add truck schedule
Take orders from the app
Manage orders that have been paid for
Customer app:
Street Eatz
View available food trucks that are operating at the given time
View menu of the food truck
Order food from the app
View current and previous order history
Push notification when food is ready
How I built it
Using flutter for the frontend and firebase for backend services. I used the square SDKs to handle payments.
Challenges I ran into
Unfamiliarity with all the technologies used. It was a big learning curve.
Working through the square authorization process. A lot of trial and error to figure out what I should be doing. The community forms helped when I was completely stuck.
I ran into a bug that I thought was going to be a blocker from fully integrating the Reader SDK, but I was able to get past it.
https://github.com/square/reader-sdk-flutter-plugin/issues/45
Accomplishments that I'm proud of
I was able to get a functioning app that can help food truck owners in this challenging time.
I think this app adds value to both the food trucks and their customers.
Overcoming the technical challenges presented while working this app increases my confidence in making apps going forward. The knowledge I have gained makes me feel like I have superpowers to create something great.
Excited to see where this leads.
What I learned
I learned all the technologies involved that I can now use to make new apps going forward.
I learned that I would like to pursue an entrepreneurial venture where I can add value and make things better.
I learned I would like to continue pursuing this idea. Maybe one-day food trucks will all be using it.
What's next
I think the next step is to get it out to food trucks to validate the idea and iterate making it better. If successful add more features that I have been thinking about.
Thank you for checking this out!
Built With
android
firebase
ios
square
Try it out
testflight.apple.com
testflight.apple.com
play.google.com
play.google.com | Street Eatz | Street Eatz is a food truck ordering app. It improves customer service and convenience. Customers can view the menu and order right from their smartphone, contactless. No more waiting in line. | ['Tony Diaz'] | [] | ['android', 'firebase', 'ios', 'square'] | 48 |
10,046 | https://devpost.com/software/tap-and-give | Go to Square POS app
Settings menu
reports menu
Select the amount to charge
Accounts menu
Main menu
Buy compatible equipment
Inspiration
I was walking in Vancouver when I found a street artist playing his guitar, after enjoying the performance, I found myself with no cash or coins to give as a tip, that made me think that as we become a cashless society, all those who depend from donations and tips will be negatively affected, and even if he had a Square POS terminal, he could not pause playing the music to enter the amount and complete a payment transaction, Then I realized that what he needed was a low cost solution that allows people to tap their cards and give a tip or donation.
Similar situation is experienced by bartenders, coffee shops, liquor store clerks, yoga instructors, and basically small business and entrepreneurs. They can use the Square reader in a semi unattended mode such that when attending the customers, or even paying with a banking POS, they can use the Square reader as secondary payment terminal to accept tips.
What it does
The Android application allows the user to configure the amount, and once the application is started, it will continue in a loop requesting a payment for that amount. It is intended to have a sign that indicates the user what is the amount that will be charged. Once configured, the user can place the phone in a safe place and let the reader complete the transactions.
How I built it
Using Square POS library to integrate to my application.
Challenges I ran into
The Square reader will timeout and deactivate after about 30 to 35 seconds. A service in the background with a timer will interrupt the application, waking up the Square reader
Accomplishments that I'm proud of
Figure out how to avoid the reader to go to sleep mode.
What I learned
Both the phone and square reader should be connected to power supply
Learn how to have a service in the background with a timer
Learn how to deactivate the screen saver on Android
What's next for Tap and Give
Add a web site, videos with instructions and affiliate program to promote.
Add IOS support.
Built With
android
pos
Try it out
play.google.com | Tap and Give | Accept semi-unattended tips, gratuities, and fixed amount payments with square POS. No need to enter the amount, just put a sign with amount and use square to receive fixed amount payments. | ['Juan Carlos Vera'] | [] | ['android', 'pos'] | 49 |
10,046 | https://devpost.com/software/castme | Main Menu
Motion capture streaming demo
Female avatar professor teaching
Male Avatar professor teaching
presentation screen
view from the back
View from the middle
Customize Character
castme.life website
Splash Screen
Inspiration
Video lectures are present in abundance but the mocap data of those video lectures is 10 times ahead in the form of precise data. High quality and a large amount of data are one of the requirements of best argmax predicting ML models, so we have used here the mocap data. Despite the availability of such promising data, the problem of generating bone transforms from audio is extremely difficult, due in part to the technical challenge of mapping from a 1D signal to a 3D transform (translation, rotation, scale) float values, but also due to the fact that humans are extremely attuned to subtle details in expressing emotions; many previous attempts at simulating talking character have produced results that look uncanny( two company- neon, soul-machine). In addition to generating realistic results, this paper represents the first attempt to solve the audio speech to character bone transform prediction problem by analyzing a large corpus of mocap data of a single person. As such, it opens to the door to modeling other public figures, or any 3D character (through analyzing mocap data). Text to audio to bone transform, aside from being interesting purely from a scientific standpoint, has a range of important practical applications. The ability to generate high-quality textured 3D animated character from audio could significantly reduce the amount of bandwidth needed in video coding/transmission (which makes up a large percentage of current internet bandwidth). For hearing impaired people, animation synthesis from bone transform could enable lip-reading from over-the-phone audio. And digital humans are central to entertainment applications like movies special effects and games.
What it does
Some of the cutting edge technologies like ML and DL have solved many problems of our society with far more better accuracy than an ideal human can ever do. We are using this tech to enhance our learning procedure in the education system.
The problem with every university student is, they have to pay a big amount of money for continuing to study at any college, they have to interact with the lecturers and professors to keep getting better and better. We are solving the problem of money. Our solution to this problem is, we have created here an e-text data to human AR character sparse point mapping machine learning model to replace the professors and use our ai bots to teach the same thing in a far more intractable and intuitive way that can be ever dome with the professors. The students can learn even by themselves AR characters too.
How we built it
This project explores the opportunities of AI, deep learning for character animation, and control. Over the last 2 years, this project has become a modular and stable framework for data-driven character animation, including data processing, network training, and runtime control, developed in Unity3D / Unreal Engine-4/ Tensorflow / Pytorch. This project enables using neural networks for animating character locomotion, face sparse point movements, and character-scene interactions with objects and the environment. Further advances on this project will continue to be added to this pipeline.
Challenges we ran into
For Building, first of all, a studio kind of environment, we have to collect a bunch of equipment, software, and their requisites. Some of them have been listed following.
Mocap suite- SmartSuite Pro from
www.rokoko.com
- single: $2,495 + Extra Textile- $395
GPU + CPU - $5,000
Office premise – $ 2,000
Data preprocessing
Prerequisite software licenses- Unity3D, Unreal Engine-4.24, Maya, Motionbuilder
Model Building
AWS Sagemaker and AWS Lambda inferencing
Database Management System
Further, we started building.
Accomplishments that we're proud of
The thinking of joining a virtual class, hosting a class, having a realtime interaction with your colleagues, talking with him, asking questions, visualizing an augmented view of any equipment, and creating a solution is in itself is an accomplishment.
Some of the great features that we have added in here are:
Asking questions with your avatar professors,
having a discussion with your colleagues,
Learning at your own time with these avatars professors
and many more. some of the detailed descriptions have been given in the submitted files.
What we learned
This section can be entirely technical. All of the C++ and Blueprint part of a Multiplayer Game Development.
We have started developing some of the designs in MotionBuilder, previously we have been all using the Maya and Blender.
What's next for castme
1. We are looking for a tie-up with many colleges and universities. Some of the examples are Galgotiah University, Abdul Kalam Technical University (AKTU), IIT Roorkee, IIT Delhi.
2. Recording an abundance amount of the lecture motion capture data, for better training our (question-answering-motion capture data) machine learning model.
Try it out here:
Intro Demo (2 min):
https://youtu.be/Xm6KWg1YS3k
Complete Demo:
https://youtu.be/1h1ERaDKn6o
Download pipeline here:
https://www.castme.life/wp-content/uploads/2020/04/castme-life%20Win64%20v-2.1beta.zip
Documentation to use this pipeline:
https://www.castme.life/forums/topic/how-to-install-castme-life-win64-v-2-1beta/
Complete source code (1.44 GB):
https://drive.google.com/open?id=1GdTw9iONLywzPCoZbgekFFpZBLjJ3I1p
castme.life:
https://castme.life
More info
For more info on the project contact me here:
[email protected]
, +1626803601
Built With
blueprint
c++
php
python
pytorch
tensorflow
unreal-engine
wordpress
Try it out
castme.life
www.castme.life
github.com
www.castme.life | castme | We are revolutionizing the way the human learns. We uses the Avatar Professors to teach you in a virtual class.Talk to your professors,ask questions,have a discussion with your colleagues in realtime. | ['Md. Zeeshan', 'Rodrixx Studio'] | ['The Wolfram Award'] | ['blueprint', 'c++', 'php', 'python', 'pytorch', 'tensorflow', 'unreal-engine', 'wordpress'] | 50 |
10,046 | https://devpost.com/software/customer-experiences | Inspiration
It turns out that the future of in-person ordering has
a lot
in common with the current challenges we face.
Square has such
incredible
(and affordable) hardware and robust APIs; I wanted to build something that could help the ordering process. Many businesses have moved to pick-up style operations and even businesses that are operating with less restrictions still want to invite more orders -- safely.
How can software help customers order faster and more easily, using the exciting hardware they already own? Thanks to discussions with real employees, owners, and customers; plus using the latest pre-release integrations, I was able to achieve a customizable, self-ordering experience to help employees, customers, and more businesses during these trying times as we enter a new frontier of in-person ordering.
What it does
With
Customer Experiences
customers can walk up and immediately select items (from the catalog) and any customizations (modifiers). Customers can order
and pay
in as few as
two taps
. Screens and instructions are customizable per business and they look gorgeous! After providing a phone number, customers will receive a text notification when their order is ready. This means less lines and less congestion with faster ordering. Optionally tip and no signature required. No more swiveling necessary!
Businesses can easily get started by signing into Square. Behind the counter, employees will use Square Orders on another tablet/computer to fulfill and manage orders as they come in. Not only does this consolidate where orders are coming from, there's also no limit to the amount of in-person ordering anymore! Businesses can easily purchase additional Square stands and even distance them using empty counter space to better comply with CDC guidelines. Thanks to Square and
Customer Experiences
, businesses accept orders more safely and efficiently.
How I built it
I was able to take advantage of the latest pre-release integrations from Square from the ReaderSDK2 to the brand-spanking-new webhooks monitoring fulfillment state. I used Swift, Objective-C, and NodeJS.
Challenges I ran into
There's a long list. All new releases have limitations (see changelog) plus there is a significant amount of work getting software into the App Store that uses third party hardware. Nonetheless, thanks to the helpful crew at Square and a little determination I'm proud to say any business can get started with
Customer Experiences
today that currently uses Square in the US.
Accomplishments that I'm proud of
Automatically using the existing catalog/inventory a business has, beautiful custom branding, supporting item customizations "modifiers", multiple per-item taxes, built-from-scratch tipping controls... building something that solves real & tough aspects of in-person ordering today -- that's what I'm proud of.
What I learned
That the current pipeline and developer support Square has is fantastic.
Businesses are willing to pay for real solutions to real problems.
That NSURLConnection can be problematic!
What's next for Customer Experiences
I can't wait to support more hardware from Square like the new Terminal API and provide a web-based ordering experience with the same ease of use so businesses can just sign-in and get started!
Built With
node.js
objective-c
squarereader
swift
Try it out
apps.apple.com | Customer Experiences | Customer Experiences and Square accelerates safe reopening with fully-branded self ordering experiences, order-ready notifications, and faster checkouts meaning less lines and congestion. | ['Peter Allport'] | [] | ['node.js', 'objective-c', 'squarereader', 'swift'] | 51 |
10,046 | https://devpost.com/software/recipe-and-menu-costing | Top Dashboard
Food Order Guide
Allergen List
Recipe and Menu Scaling
Menu Costs
Nutritional Labels
Login
Bottom Dashboard
Recipe Costing
Recipe Costing With Allergens
Menu Item Details
Food Costs
Menu Items Data Grid
Mobile Phone Login
Mobile Phone Dashboard
Mobile Phone Nutritional Labels
Inspiration - All the restaurants trying to get back after the Covid-19 crisis. More than ever restaurants must know their food costs, recipe costs, and more importantly their plate costs to mitigate further loss after closing for over 60 days.
What it does - Allows restaurant owners to accurately calculate food, beverage costs, menu costs, recipe costs, and nutritional labels.
How we built it - We designed this version specially for SquarePOS users. As former restaurant owners, we decided to start with the food order guide and used the latest cloud-based technologies with human-centered design. We used Squareup's API.
Challenges we ran into - Making it simple to cost out a plate on the menu with multiple recipes, food items, and automatic nutritional labels.
Accomplishments that we're proud of - Keep it simple and user friendly. Giving restaurant owners a product mix with actual sales and costs. A low-cost entry at $25 makes it affordable for any restaurant owner, and the ability to create nutritional labels with a single click.
What we learned - Restaurant owners can improve their bottom line income by dramatically managing and reducing costs.
What's next for Recipe and Menu Costing - We're looking at real-time inventory based on sales from SquarePOS.
Built With
.net
c#
microsoft
sql
Try it out
squareup.recipe-costing.net | Recipe and Menu Costing | The Smarter Way To Manage Your Restaurant | ['Gaurav Arora', 'Robert Vasquez', 'Christopher Hoffman'] | [] | ['.net', 'c#', 'microsoft', 'sql'] | 52 |
10,046 | https://devpost.com/software/get-work-nsza80 | logo
user interface for service seekers
Possibility to change your profile from service seeker to service offers
user interface for service offers
only app where you can see when your service is coming (other then driver like on uber)
6 members of team
Inspiration
Millions people uneployment all around globe. All service providers on one app!
What it does
It is the only app where one can find reviews, price, location, experience and contact of service provider in one place,
focus is on C2C type of mediation and
on traditional services where 2 people phisically meet like: • Home care and design (interior designing, pest control, cleaning, laundry, glasswork, woodwork, waterproofing, masonry, carpentry...) • Repair and maintenance (handyman, locksmith, plumber, electrician...) • Health, wellness, and beauty (manicure, pedicure, physiotherapy, massage, trainer...) • Others (nanny, tutor, cooking, walking pets, shooping...)
How I built it
MY TEAM USE ANDROID AND VISUAL STUDIO.
This solution is disrupting the traditional business models, replacing them with a platform to connect the major stakeholders of a service exchange (Service provider and customer). Current MVP is a web page where one can offer or book services. The process is not automated yet so applications, bookings and all communication is first going to administrator. Furthermore, the implementation of Google maps is missing so locations are added manually on the map. There is no possibility to create and edit a profile or to leave reviews and comments. There is currently 14 service providers offering their services trough the web page.
Challenges I ran into
Financial means needed are for covering first year of operational expenses:
Computers 3.150 USD
Marketing 5.249 USD
Office ownership 42.362 USD
Bookkeeping 1.575 USD
Sallary 35.302 USD
Accomplishments that I'm proud of
WE HAVE PATENT ! Name of patent: SUSTAV ZA POVEZIVANJE PONUDE I POTRAŽNJE USLUGA, reported at Croatian Herald of Intellectual Property (Hrvatskom glasniku intelektualnog vlasništva) No. 5/2019 (8th of March 2019) Patent No. P20171297A. Holder of intellectual property rights: Mario Marević, Podgorske skale 9, Makarska
WE BUY A FIRM IN NORTH SIDE OF CROATIA THAT ALSO FIND SERVICES THROW WEB
What I learned
My team learned app functionalities: • service provider info (name, photo, education, professional experience, list of services) • service provider (and seeker) rating, reviews and comments • possibility for service seeker to determine suitable time and place where he wants the service to be provided — once provider agrees this way they both know particular time of delivery and a time duration • push notifications (when service is booked, when booking is accepted, when appointment time is changed, reminder to leave a review) • location of provider on map + real-time tracking • price of services provided (HRK/h) • browsing trough options with filters like service type, location, price and reviews • recommendations of service based on proximity, reviews, comments and price. • quick and easy payment mode (cash or card) • provider contact info — available once the service is booked which allows easy communication • overview of all available service options, while the most quality ones will appear on top
What's next for Get Work®
LETS PUT THIS WAY:
Unemployment rate goes up. There was 8.995 unemployed people in Split, 16.548 in Zagreb, 3.700 in Rijeka and 5.049 in Osijek in March 2020. There was 8,3% (152.590) unemployed people in Croatia. Unemployment Rate in Croatia averaged 16.9% from 1996 -2020. According to Trading Economics unemployment Rate in Croatia is expected to be around 13.50% in 2021.
By 2020, the number of freelancers is projected to outpace full time workers - 73% are looking for a job on dedicated internet platforms.
Because of economic crisis more people will need an extra source of income —79% of existing users in on-demand economy are working as part-time.
APP GET WORK IS TOLL THAT WORD NEED IN THE YEARS TO COME BECAUSE OF ECONOMY CRISES CAUSED BY CORONA-VIRUS
Built With
android-studio
visual-studio
Try it out
drive.google.com | Get Work® | Get Work® - Mobile app between service providers and service seekers. Booking and offering services in accordance with 21st century. | ['Mario Marevic'] | [] | ['android-studio', 'visual-studio'] | 53 |
10,046 | https://devpost.com/software/virtual-health-checkup-modelling-of-coronavirus-technoband | Technoband
Software Modelling of Future conditions of CoronaVirus
Inspiration
Daily surge in cases, health conditions of citizens pushed me to work hard
What it does
It predicts the curve of future conditions of any country w.r.t. data set available
How I built it
I built it through software, that have been mentioned.
Challenges I ran into
Lots of challenges, but overcomes and got the results as expected
Accomplishments that I'm proud of
That I did something, which satisfies and help at least one citizen, then the chain will follow up.
What I learned
I learned new softwares, skills
What's next for Virtual Health Checkup|Modelling of CoronaVirus|Technoband
If got success, wanna make it open source.
Built With
arduino
c++
embedded
matlab
python
webex | Virtual Health Checkup|Modelling of CoronaVirus|Technoband | Future prediction with Virtual checkup online and Smart electronic band | ['Shreyansh Pagaria', 'Maor Mashiaxch'] | [] | ['arduino', 'c++', 'embedded', 'matlab', 'python', 'webex'] | 54 |
10,046 | https://devpost.com/software/todos-mas-cerca-r3ewzc | Inspiration
we want to support every kilometer of the planet to revive the economy
What it does
Our platform supports giving visibility to all businesses close to users, supporting small businesses to reactivate their sales, thus preventing them from going bankrupt and large chains being the ones to keep these revenues. Focusing on the collaborative economy and fair trade
How we built it
A group of Ecuadorian entrepreneurs developed a platform to connect the owners of commercial establishments with their clients. They are:
www.todosmascerca.com
Ricardo Mancero and Andrés Dueñas, project leaders have been working for several years in the development of digital projects and during the quarantine process due to Covid19; They looked for a technological solution to help those most economically affected by the crisis. The premise is to prevent people from crowding into supermarkets and help revive the economy of small and medium-sized companies, which have been forced to close their operations due to a lack of customers.
Challenges we ran into
Revive the small business economy.
Avoid crowds.
Digitize small businesses.
Connect 1km around users with shops.
Connection facilities between businesses and users through a webapp.
Visibility of small businesses due to scarce advertising resources.
Accomplishments that we're proud of
This Startup has been very well received at the international level, being chosen by Unesco to spread it worldwide within its #YouthOfUnesco program. On the other hand, the Inter-American Development Bank in its IDB LAB platform has placed the project within “COVID-19 Map of Innovators of Latin America and the Caribbean”.
In Mexico, the venture was chosen as the winner in the call "Hack The Crisis Mx" among more than 400 proposals. He was chosen winner in the economic reactivation category in the "Hacking Covid" call organized by the government of the Canary Islands-Spain.
Currently the project is as a finalist in the call: "Ecuador Post-Crisis Hackathon" and as a finalist project in the "Ideas for Our Mexico" contest with which they have managed to reach the final among more than 1500 proposals.
What we learned
We learn to get to know people closer, understanding their needs and anxieties, and we continue learning as we want to reactivate the planet's economy.
What's next for todos mas cerca
1.- The next steps is to have a multichannel bot that connects users with businesses 1km around.
2.- implement payment gateways, so that the user can buy through the platform
3.- Develop an ERP for the inventory of shops, so that when a user wants to search for example nutella, they can see according to their geolocation which store has nutella.
4.- create our own delivery app
5.- connect farmers with businesses to generate fair trade
6.- We have a fremium model, which means that any business can have an ecommerce website if they wish, we want to democratize electronic commerce.
Try the platform
Go to
https://www.todosmascerca.com
In the address field next to the city “Quito”, write a Quito Street for example “6 de Diciembre”, and choose a category for your search, for example “restaurants”
Press the search button and you will get the option, to move the pointer to get the best place close where you are.
Press search in the red button to confirm your location and get the results.
Nice! You can see now the stores inside the category you choose, nearest you, and the number of other stores from other categories, and contact them by whatsapp.
Of course you can choose the map view, just clicking in the icon on the top of the list, and check your location.
As a store:
As store you can go to:
https://www.todosmascerca.com/registrar
Go to the bottom of the page and fill the form, we include the location of your store using google maps pointer move, or autocomplete functions.
You have to fill all the fields, and click on register.
Check that the all the information is correct before proceed-
Nice, you are inside Todos más cerca!
Built With
amazon-web-services
angular.js
apiwhatsapp
digitalocean
google-maps
html5
mongodb
whatsapp
Try it out
www.todosmascerca.com | Todos más cerca | We are the first platform that connects businesses and users 1 km away through whatsapp. | ['Ricardo Mancero', 'aduenas13'] | [] | ['amazon-web-services', 'angular.js', 'apiwhatsapp', 'digitalocean', 'google-maps', 'html5', 'mongodb', 'whatsapp'] | 55 |
10,050 | https://devpost.com/software/damagenet-post-wildfire-building-damage-detector | DamageMap is a system composed of rapid buildings damage assessment and a convenient user interface for result visualization.
It uses AI to identify damaged buildings after wildfires using aerial surveys uploaded by users.
DamageMap automates the laborious structure damage inspection process, which is currently performed manually. With a variety of features, including real-time damage assessment and damage report generation, DamageMap can help fasten the post-wildfire recovery and assist those affected by wildfires, including first responders and policy makers.
How can you use DamageMap?
Click
here
to try out DamageMap yourself!
(allow few seconds to load)
On the user interface of DamageMap, first responders or local agencies can upload post-fire aerial images through the upload link and publish it to the general public. Then users can view the damage prediction for each detected structure in the similar way of using Google Map. On top of the webpage, there's also a search bar for residents to type in their addresses to zoom in to their area of interests. On the page, you can also see some statistics that we are able to generate using the prediction and local data.
For first responders:
DamageMap provides real-time structure damage assessments once the aerial images are available. With the 96% of accuracy, this information can help first responders to better allocate human resources during the immediate post-fire phase.
For residents:
Our online visualization of structural damages provides individuals with information of the status of their properties. Evacuees and others who wanted to see the status of their properties, can easily check the high-resolution aerial images using their addresses. The specifically designed screenshot download link can provide evacuees with proof of their property status and ideally, help them start their insurance claims process as soon as possible.
For policy-makers or researchers:
With our damage detection model, we are also able to generate basic statistics, including the estimation of total loss and the statistics of those who are most vulnerable. Such information can be extremely helpful for policy-makers of all levels of governments or researchers in academia to better understand the social justice and equality issues of wildland fires and better organize disaster relief and recovery resources for the local residents.
What inspired us to create DamageMap?
With climate changes and other anthropogenic factors, such as the increase of occupancy in the wildland-urban interface (WUI) and the aging of the electricity system, wildfires have become more frequent and destructive in places like California. According to CALFIRE, in 2017, California experienced a 12% increase in the number of fires and a 76% increase in acres burned from 2016.
Along with the increasing wildfire frequency and magnitude, the number of structures destroyed also increased drastically. In 2017, 10,868 structures were burned down during wildfire, which surpasses any previous records. Meanwhile, the current post-fire identification of destroyed structures rely on manual inspections. During the 2018 Camp Fire, some 60 teams of inspectors were deployed to perform inspections for more than 19,000 structures. As one can imagine, this process is both time-consuming and labor intensive.
Since post-wildfire disaster relief is heavily dependent on rapid damage detection, we decided to create a tool that can automatically detect damaged structures using high resolution drone imagery and deep learning. With this automated technique, we hope to facilitate first responders and local agencies better plan their rehabilitation efforts and help fire victims jump-start their recovery journey.
How does DamageMap work?
DamageMap does the following when a new user uploads an aerial survey:
Ingest aerial survey: DamageMap accepts input aerial survey in GeoTiff Format through a dedicated Google Drive. When user uploads imagery (preferably sub-30cm resolution), DamageMap ingests and stores it in the required format for running the model.
Segmentation: In this step, DamageMap uses a pre-trained ResNet34 model from Microsoft (US Building Footprints) to segment all structures in a landscape.
Cropping: Once all structures are segmented, square scenes centering the structure are cropped from the landscape. Here, the size of the square is determined by the average building size in scene.
Classification: The cropped images are then classified as “damaged building” or “not damaged building” using Microsoft Azure's VM. For our classification model we performed transfer learning using Pytorch. More specifically, we used a ResNet18 network architecture pre-trained on Imagenet. Then, we fine tuned the model using a stochastic gradient descent with Nesterov momentum optimizer and cross entropy loss function for a total of 50 epochs. For fine tuning, we used the pre-labeled dataset of Paradise City, California after the 2018 Camp Fire.
Reconstruction: After classifying each cropped image, DamageMap transposes the images from pixel-space to geospace (lat-lon) by remapping the cropped images onto the original landscape scene.
Visualization: The web-app is updated with the new aerial survey and with damaged and safe buildings overlaid.
The whole process takes ~20 mins for a 50 km² area. Scripts for executing the above process (along with training steps for our model) can be found
here
.
Model's Robustness
DamageMap in operation
We have taken care to make the model generalizable to most wildland urban interfaces. The model provides a 99.4% detection accuracy for the whole U.S. and a 96% classification accuracy on the validation datasets (out-of-sample) collected from Cal Fire. We would expect the classification performance to demonstrate a slight drop if the model is used on a new image taken from a different camera in an area with very different landscape and architecture. However, every time the model sees a new image it will automatically use it to increase its future performance on new different cases. So, if people start to use the model, any bias issue will be eliminated soon.
Socio-economic Assessments and Impacts
Wildfires do not discriminate--they can destroy multi-million dollar mansions and trailer parks with the same blaze. However, the post-wildfire rebuilding and recovery heavily depends on the socio-economic status of those who were affected.
For many low-income households and those are below the poverty line, house insurance in high fire-risk zones has been increasingly unaffordable after catastrophic wildfires, creating huge burden for recovery and likely causing people to become homeless. Take Paradise City as an example, the situation is even worse as 25% of the population is the elderly who has limited income.
Besides socio-economic status, race, ethnicity, and immigration status can also make people more vulnerable to wildfires. After the two devastating wildland fires in Sonoma County in 2017, many of the low-wage workers were undocumented so they were not qualified for the assistance from FEMA. What made the situation worse was that they had to leave the area to restart. Many times, immigrants were also uncomfortable showing up to evacuation centers or accepting the help from governments due to the barriers of language and the extra concerns resulting from their immigration status.
With all the chaos during the aftermath of wildfires, having a clear big picture of the impacted population is the key to establishing efficient rebuilding efforts that support the most vulnerable and underrepresented people. With this aspect in mind, we designed DamageMap with features capable of providing insights about the affected and underrepresented population to ensure social justice and equality in the process of rebuilding and recovery from wildland fires.
By using the results of damage assessment together with data from Census, DamageMap is able to calculate the percentage of damaged structures belonging to a certain vulnerable population group with the granularity of a single neighborhood, which is more detailed than a zip code region. For example, in the case of Paradise City, our DamageMap platform shows that 26% of the damaged structures belong to the elderly (above 65 years old).
With these rapid socio-economic assessment and estimation regarding the vulnerable population, we hope to help all levels of agencies and NGOs better plan and allocate disaster relief resources to support those in need, especially the underrepresented groups in disaster response and recovery.
What's next for DamageMap?
As a team, we would like to continue developing DamageMap as an open-source platform considering that this project can truly benefit multiple stakeholders who are affected by the devastating wildfires. Some of our plans include the followings:
Cross validate with multiple wildfire cases and different roof architectures
Reach out to first responders and policy makers to test and iterate DamageMap
Use data driven approaches to augment training examples to improve detection accuracy on validation sets
Tune model to work on any image resolutions
Use data science tools to perform multi-class instead of binary classification to evaluate percentage of damage for structures
We would like to thank:
We thank Dr. Andrew Fricker (California Polytechnic State University) for providing us access to various datasets. We thank Santa Rosa Deputy Fire Chief, Scott Westrope, and the Santa Rosa Fire Department for providing us with insights of first responders. We thank Stace Maples for guidance on reverse geocoding. We thank all mentors of the Big Earth Hackathon for providing valuable advice and suggestions.
Built With
google-earth
javascript
python
pytorch
Try it out
kkraoj.users.earthengine.app
youtu.be
github.com | DamageMap: A Post-Wildfire Damaged Building Detector | Burned, or not burned, that is the question | ['Krishna Rao', 'Grace Yao', 'Marios Galanis', 'Yi-Lin Tsai'] | ['First Place Project'] | ['google-earth', 'javascript', 'python', 'pytorch'] | 0 |
10,050 | https://devpost.com/software/fire-risk-tracking-for-vulnerable-communities-n2v80q | Project Introduction
Problem Space
Project Mission
Our Solution
Pain points from the Fire Community
Use Cases
Progress to-date
Under the Hood of our architecture
Proposed Tool Enhancements
Tool Walkthrough
Sample wireframe
Sample wireframe
Sample wireframe
Sample wireframe
Sample wireframe
Inspiration
Living in California, our team was keenly aware of how the past few years of wildfires have affected our lives: increasing air pollution, participating in planned public safety power shut-offs, and supporting friends through tragic losses. As we dove into our research, it became clear that the community-level devastation affected communities of all sizes, with an outsized impact on those who are most vulnerable due to their age, education, language ability, mobility, and socio-economic status. As we thought about where we could add value, we wanted to ensure we were prioritizing those who needed the most help.
Our original vision was to build a defensible-space tool for homeowners to better understand, manage, and implement the jurisdiction's requirements. Interviews in the fire community revealed that over 70% of homes pass on their first inspection, while the remaining 30% often require multiple inspections. The current inspection process is highly manual and inefficient for Cal-Fire; oftentimes inspectors don't return to re-inspect a home due to the progression of the fire season and competing priorities.
This led us to turn our efforts to Cal-Fire, which hires 130 inspectors each year to monitor compliance across their 31M acres of State Responsibility Area (SRA). As we spoke with Cal-Fire, we started to hear pain points around information accessibility and defensible space during live fire events.
We decided to investigate the power of remote sensing to detect defensible space during live fire events, optimistic that the combination of this information with social vulnerability data would help to ensure faster, more efficient, and more equitable live fire response.
Our Tool
Our tool assesses predicted fire damage at a "neighborhood" level for groups of California homes in SRA jurisdiction, integrating community vulnerability data, to help Cal-Fire inform live fire response. The tool may also help to triage proactive defensible space inspection to the most risk-prone homes when no fire is present.
It does this by:
1) Improving CALFIRE's information access during live fire events by providing granular information on neighborhood / home defensible space, damage risk, and community vulnerability.
2) Enabling prioritization of the most-at-risk neighborhoods/homes by indexing relative risk either during a live fire event or proactively when CALFIRE is carrying out its inspection process.
Click around in our wireframe prototype here:
Use Case 1 |
Live Fire Event
Use Case 2 |
Inspection Triaging
How we built it
Our system primarily depends on predicting the relative "burn risk" among "threatened communities" (defined as a .5 x .5 KM area). This risk, as well as information informing that prediction and social vulnerability information relevant to that community is then visualized to response planners.
In either a live fire or proactive planning event, the tool takes as use input a lat/long that defines an active or theoretical fire boundary. The system then simulates a series of potential boundaries for the fire and uses the minimum bounding geometry of those various simulations to define the population of "threatened communities". Today, our simulation engine is quite naive as extensive work by groups such as FlamMap and Crowley et al. has been carried out in this domain and we simply did not have the scope to integrate these models into our prototype as we would in a production system.
With the population of "threatened communities" defined as the overlap of the potential burn radius and populated areas ("the WUI"), a series of individual "neighborhoods" is defined via a simple .5x.5KM grid over-layed on this intersection. For each section of this grid, the most recent Landsat 30M resolution image (R, G, B, and Infrared Bands) is extracted from Google Earth engine and passed into the core prediction model. It's worth noting that the use of higher resolution imagery such as Planet Labs 3M resolution or even Sentinel 10M resolution could be used as available.
The core prediction model is a convolutional neural net with 4 layers (Conv-50>Conv-50>Conv-50>Dense-50>Dense-1) that takes as input a 4 channel, 50x50 pixel image and returns a single percentage value (0-100%), which represents the percentage of the image that is likely to truly be damaged or scorched should a fire "come through" the entirety of that area. The model was trained over 350 training examples for 10 epochs using the Adam optimizer and showed solid convergence despite a limited dataset. The ground truth for this training set was established using an unsupervised clustering and pixel difference algorithm adapted from Rossi et al. that approximated the damaged or scorched areas in populated regions in past fire events. Because the ground truth of this model was difficult to verify, we do not feel comfortable reporting the accuracy of this model, however we are reasonably confident that given a more robust labeling based approach or better verification of the unsupervised method, such a model could likely achieve high performance in production.
In order to enable users to interpret the core prediction model, we also layered in the popular Shap Deep Explainer algorithm from Lundeberg et al. So-called "Shapley Values" allow each pixel's "contribution" to a prediction to be scored in terms of both direction and magnitude. As a result, it is possible that this interpretability method could, for an at-risk area, call planners' attention to a particularly risk-prone home or other sub-region of that area. These areas may or may not correlate to areas with poor defensible space, but we do believe a label-based, defensible space classifier could serve as an important additional input to this piece of the pipeline.
Lastly with a series of "neighborhoods" or "threatened communities" defined, a burn risk prediction (simulator), a damage risk prediction (CNN prediction model), and a social vulnerability index score (CDC's SVI) established, we visualize these metrics for a given event to the end user.
On the whole, we believe this group of technologies, especially when put into a more robust production implementation, can ensure faster, more efficient, and more equitable live fire response and proactive management.
Challenges
With no prior geo-spatial backgrounds, our team faced several challenges in building and manipulating our data pipeline. Specific data challenges included:
Data type mismatches due to 'snapped pixels' forcing "squeezed" dimensions
Only low resolution imagery available
Difficulty implementing efficient cloud-cover removal and composite scoring
Lack of familiarity with correct thresholds for filtering, scoring, etc.
These data challenges were also coupled with simple time constraints such as:
Not enough time to collect sufficient labeled images, forcing use of unsupervised approach
Forced to put the "hack" in "hackathon" at a number of points in the pipeline
Difficulty building out a robust UI despite complete model implementations
Lastly, the nature of these constraints did limit us algorithmically:
CNN predictions focused on entire image and not "window panes" or sub-images
Simulation step was Naive and did not leverage RL or other known simulation techniques
Accomplishments that we're proud of
We're proud of both the process and the output. Along the way, our team hit many roadblocks. Despite our varying levels of technical expertise and comfort with geospatial data, we were able to find ways for everyone to push the project forward each week whether it was through primary research, secondary analysis, soliciting help, or hacking away.
While our team would have liked to produce more, we are proud that our vision of creating a live response and defensible space management tool contributes meaningfully to the existing options currently available to Cal-Fire and solves an important pain point. In particular, we view the inclusion of community vulnerability into this project as an imperative for any "go forward" related projects.
What we learned
We learned an immense amount about fire-risk in California and the monumental challenges ahead as global warming continues to heighten wildfire risks. Within the realm of defensible space, we learned this is a highly complex and fragmented area with regulations at both the state and country level. We heard a lot of stories about when the law and reality took divergent paths, fueled by competing end goals that ranged from compliance to education. One of the largest barriers in this space is simply combating human behavior: compelling individuals to act for the good of their neighborhoods, despite their own personal landscaping desires.
Technically, we learned the maintaining data integrity while manipulating geo-spatial data is incredibly challenging. Due to the myriad different data types across different layers, we struggled to extract the data we wanted and at times had to "hack" our way to success. Despite backgrounds in a variety of machine learning techniques, including deep learning, this was also the first time many of us did in-depth work with multi-channel image data and convolutional neural nets.
Finally, we left his hackathon with the conclusion that while much progress has been made in certain areas of machine learned statistical modeling across the domain of wildland fires, there is considerable room for systems based thinking to provide more holistic solutions.
What's next for Fire Risk Tracking for Vulnerable Communities
We are excited to apply the knowledge we have learned in our respective fields both in an academic and professional capacity. This has been an incredible learning experience for us all, and all four of us are grateful for a great quarter!
Built With
clustering
figma
google-earth-engine
landsat
modis
python
shap
tensorflow
tiger
Try it out
github.com | Project Firesafe: Risk Tracking for Vulnerable Communities | Building a tool that assesses predicted fire damage for California homes to support Cal-Fire in live fire response & proactive deployment of defensible space inspection for the most vulnerable homes | ['Hannah Sieber', 'William Steenbergen', 'Joanna Haver Klitzke', 'Will Leopold Ross'] | ['2nd Place Project', 'Data Science Summer Continuation Prize'] | ['clustering', 'figma', 'google-earth-engine', 'landsat', 'modis', 'python', 'shap', 'tensorflow', 'tiger'] | 1 |
10,050 | https://devpost.com/software/ca-carbon-emissions-under-forest-management-scenarios | A glimpse at our interactive web map
VIEW OUR PROJECT
an interactive web map to calculate forest management carbon emissions by county
Inspiration
As students in the
Atmosphere/Energy program
, we are passionate about climate change mitigation and reducing carbon emissions for environmental and health purposes. One of the many impacts of climate change has been increasing California's sensitivity and susceptibility to wildfires, and we must be proactive in reducing wildfire risk.
We are both Northern California natives, from Sonoma and Humboldt Counties. Amy is from Santa Rosa, where her hometown was deeply impacted by the Tubbs Fire back in 2017. Since then, she has focused multiple projects on analyzing wildfires in California. Eli grew up helping his family with fuels reduction work from the time he could walk, and has worked on and off with his dad's thinning crew for nearly a decade. Eli's parents actually met while working on a wildfire, his dad as a hazard tree faller and his mom on a Forest Service hand crew, making his passion for the subject a sort of family tradition. These experiences have led us to this hackathon and to this specific project.
Project Overview
California's
AB 32
set the goal to reduce greenhouse gas emissions to 1990 levels by 2020, which is 431 million metric tonnes of CO2 equivalent. In 2016, California first reached this goal four years earlier than its initial target. However, these state estimates do not include emissions from wildfires. The
California Air Resources Board
estimated that in 2018, 45.5 million metric tonnes of CO2 were emitted from wildfires, pushing us to fail to meet our state emission reduction goals. As wildfire severity in California increases, we must acknowledge the magnitude of the associated emissions and act accordingly.
The frequency and severity of wildfire in the western U.S has been growing for decades, driven by over 100 years of fire suppression policy and ever worsening climate change.[1] However, more progressive forest management practices such as thinning and prescribed fire have been gaining traction as means of preventing such high severity conflagrations. Treating an area with prescribed burning or thinning has shown to significantly reduce the severity of wildfire that may later burn through that area.[1] Lower severity fires kill fewer trees [2] and are more easily kept from destroying human property and life. While these benefits of prescribed fire and thinning have been well established, their potential impact on net carbon dioxide (CO2) emissions has been a point of investigative contention, with some studies suggesting that such practices reduce net CO2 emissions to the atmosphere while other studies suggesting otherwise.[3]
In response to this debate, our project attempts to lend yet another perspective by building a model for quantifying net CO2 emissions from wildfire under three scenarios: suppression, prescribed fire, and thinning. We apply this model to each county in California with the simultaneous intention of providing information to state agencies looking to distribute forest management funding or county governments looking to adopt climate action and/or wildfire preparedness plans.
Both of these entities could use the information provided in our product--an interactive web map--to obtain a ballpark idea of what counties have the greatest wildfire emissions reductions potential, what that potential is, and what it could cost in the context of other emissions reductions measures.
In this way, our research can add analysis to the debate over the net CO2 impacts of these various forest management practices while also providing a potentially useful tool for entities with the inclination and resources to implement these practices.
Methodology
Through an extensive literature review, we have estimated the available carbon fuel content of forest biomass in California and combustion emissions in different forest management scenarios. Using the below formula, we calculated the
average carbon emissions per year
for each county due to wildland fires:
forested area (km2) × average available burnable biomass carbon density (tonnes C/km^2) ×
(tonnes CO2/tonnes C released upon combustion) × % of available biomass consumed from wildfire given the area’s prior forest management treatment ×
forest density correction factor (%) × natural fire return interval (fires/year)
Estimates of each variable in our equation are research-based. Our web-based app includes an "Appendix" tab, which links to our
methodology document
, detailing our assumptions, calculations and the literature that supports our choices.
To visualize our data, we used R Shiny to create an interactive web app allowing for users to adjust forest management scenarios. Our choropleth map, built through Mapbox and Leaflet, highlights the total carbon emissions per year in 100% suppression, 100% prescribed burning, and 100% thinning scenarios. Our app also includes a section for users to be able to adjust suppression, thinning, and burning percentages for specific counties and understand the carbon emission reductions and costs associated with these values.
Reflection
Our project has been redeveloped and redesigned many times due to various challenges and a greater understanding of our research goals. While we feel that our work contributes to current literature surrounding forest management and wildfire risk, we recognize its limitations as well as its potential to be developed into a more robust analysis of carbon emissions.
Challenges
One of the main challenges to our project was, unsurprisingly, data. Because we did not have clean data for the all of the various variables in our equation, we often calculated these individual variables from estimates based off of our research. Specific limitations of our data included:
Estimates occasionally derived from very specific case studies under conditions that are not necessarily generalizable to California and its differing biomes.
Computer memory resources, as more granular sources included hundreds of gigabytes of data that our computers could not support. An area which we would have liked to explore further was
LANDFIRE
Vegetation data, which includes granular geospatial data regarding vegetation types and carbon content throughout California.
An additional challenge was learning how to construct and deploy a web app that allowed for the functionality we desired. Throughout this process, we switched from JavaScript to Python to R, reiterating our dashboard and map and evaluating which features are most important to us. Ultimately, we used R for all data wrangling, cleaning, visualization, and web app deployment.
And finally, largely due to time constraints, we have yet to incorporate the emissions produced from the actual prescribed burning and thinning itself which will cut into the emissions reductions from both practices when compared to suppression.
Learning
Our deep-dive into the world of forest management and carbon emissions has allowed us to better understand the complexities of reducing wildfire risk. There is no general consensus on the role of suppression, prescribed burning, and thinning in greenhouse gas management, and we feel that this is an area that needs to be expanded upon. One key insight our project has taught us is that this field is quite data-limited, which prevents decision-makers from being able to make the most well-informed, strategic forest management choices possible. We hope that our tool can lay a foundation upon which future work in this field can build.
Future Work
As mentioned in
Challenges
, the literature existing around this topic is often patchwork, and a more collaborative and synchronized approach to future research amongst academic, governmental, and professional players in the field could help more smoothly facilitate more accurate analyses of how various forest management practices affect net emissions as well as numerous related questions. Throughout our analysis, we needed to make many, sometimes tenuous, assumptions but have explicitly included our process for transparency- hoping that future researchers could build upon this base, as more research is produced on this topic.
Our tool ultimately provides ballpark estimates, but could greatly benefit from data allowing us to incorporate more specifics of each county's forests and vegetation. We are excited about possible expansions to this project such as improving certain assumptions made, extending the scope of emissions included by incorporating tree mortality and associated carbon sequestration as well as extending our model beyond just forests to shrubland management and other biomes, and what we see as the most necessary next step towards improving the value of this tool: including emissions produced from thinning and prescribed burns.
With further work and research, this too has the potential to guide county governments and state agencies to not only reduce wildfire risk but reduce carbon emissions towards state goals.
Thank You
Thank you to everyone affiliated with the
Big Earth Hackathon Wildland Fire Challenge
course- our fellow classmates, our professors, TA, and the countless number of speakers who taught workshops, took the time to highlight different issues surrounding wildfires, and overall, inspire us. We couldn't have done it without you!
Bibliography
[1] “Yocom Kent et al. - 2015 - Interactions of Fuel Treatments, Wildfire Severity.Pdf.” Accessed May 31, 2020.
https://www.fs.fed.us/rm/pubs_journals/2015/rmrs_2015_kent_l001.pdf
.
[2] Collins, Brandon M., Jamie M. Lydersen, Richard G. Everett, and Scott L. Stephens. “How Does Forest Recovery Following Moderate-Severity Fire Influence Effects of Subsequent Wildfire in Mixed-Conifer Forests?” Fire Ecology 14, no. 2 (August 30, 2018): 3.
https://doi.org/10.1186/s42408-018-0004-x
.
[3] Ryan, Michael G, Mark E Harmon, Richard A Birdsey, Christian P Giardina, Linda S Heath, Richard A Houghton, Robert B Jackson, et al. “A Synthesis of the Science on Forests and Carbon for U.S. Forests,” 2010, 17.
Built With
mapbox
r
shiny
Try it out
kouch.shinyapps.io | CA Carbon Emissions under Forest Management Scenarios | Interactive map to calculate forest management emissions by county | [] | ['Third Place Prize'] | ['mapbox', 'r', 'shiny'] | 2 |
10,050 | https://devpost.com/software/early-wildfire-detection-false-positive-rejection | State of the deep learning model when I joined. A score is given for each 300x300 pixel in the image.
A score above 0.5 raises an alarm.
Fog and clouds often trick the neural network into thinking there is a fire.
Sometimes a real fire is mistaken for fog.
Inspiration
The early detection of wildfires is the very first step in organizing an efficient and coordinated response. Many cameras have been disseminated across the state to monitor the onset of wildfires and raise an alarm as early as possible. There is, however, no automated smoke detection software consistently deployed and the videos still have to be monitored by the human eye. The FUEGO team at Berkeley (
https://fuego.ssl.berkeley.edu/
), in collaboration with Fireball international (
http://fireballit.com/
), has build a smoke detector based on convolutional neural network (inception v3). While the algorithm works well, it still raises a significant number of false positive every day, requiring non-negligible human input. For this project, I joined the team in their effort to hunt those false positive, using classical machine learning approaches (for now). The attached images shows examples of the different cases of true/false positive/negative raised by the current iteration of the deep learning model.
What it does
Building on initial exploratory work by another member of the team, a pipeline is being build to test and deploy false positive rejection algorithms. In a near future, the pipeline should be able to download the camera frames for +/- 10-20min around the detection time and perform a second analysis to confirm or dismiss the alarm.
In its current iteration the pipeline can be used for offline test of false positive rejection algorithms, given a set of camera images. Some methods were previously implemented and tested on a few real and false alarms already, but their robustness can only be validated against a larger number of cases. The pipeline thus aims at facilitating the analysis of many datasets, by providing a convenient way to customize the analysis and save results in a consistent and user-friendly way. Its initial primary use will be for the optimization of hyperparameters, but it is built having in mind that it will eventually be deployed with the live detection software suite and to used to test new algorithm.
How I built it
I unfortunately cannot give access to the code, as it is developed under a non-disclosure agreement in collaboration with Fireball International. I nonetheless want to share what I can.
The pipeline is build in python and consist of two main steps: preprocessing, where functions are applied on single image upon loading, and analysis, where a stack of pre-processed image are analyzed. Preprocessing typically includes elementary operations such as cropping and filtering, while the analysis implements the algorithm themselves. New preprocess and analysis functions can easily be added or removed without a deep knowledge of the underlying pipeline code, by following a few simple rules.
Challenges I ran into
This project took a while to get started. For the most part, I was not aware of the status of smoke detection softwares, and wasn't sure if and where contribution was needed. It then took a couple of weeks to finally reach out to the right team. Retrospectively, the idea of building a deep learning model from scratch for this project was way too ambitious and I am glad I could collaborate on an existing project, where my contribution can really mean something.
Accomplishments that I'm proud of
Rapidly being able to use my knowledge of python and data analysis and apply it to a pressing issue. Hopefully we will be able to deploy this pipeline during this fire season already, and I would be extremely proud to have contributed to it.
What I learned
I learned a lot about the challenges that the fight against wildfire was posing. In particular, I did not realize this was such a constant and recurring issue, nor the incredible amount of people involved in every step of this fight.
From a technical point of view, I learned about the opencv libraries, and am now learning the basics of the google python API and interaction with SQL databases in order to deploy the pipeline.
What's next for Early wildfire detection: false positive rejection
I will definitely continue working on the project over the summer, as there is still a lot to be done. Ideally we would be able to deploy it as soon as possible for real-time analysis, filtering the alarms raised by the main software.
The main code itself will also go under another round of training and I hope to be able to jump in, taking the opportunity to learn more about deep learning.
Built With
numpy
opencv
python | Early wildfire detection: false positive rejection | False positivies are a big issue in the automated early fire detection, hindering the proper use of this system. How can we reduce them? | ['Vincent Esposito'] | ['AI For Earth Challenge'] | ['numpy', 'opencv', 'python'] | 3 |
10,050 | https://devpost.com/software/wildfires-economics-and-cities-ballot-measures | Introduction
When large wildfires occur in California, firefighters make front page news. But do city residents remember these fires when voting on local funding measures for fire departments? Do other factors, such as labor force or party affiliation, play a role in certain cities’ recalcitrance towards funding fire departments? For cities hoping to increase funding for these services, what factors predict a successful ballot measure?
Two specific Californian cities illustrates the complexity of the issue. In Modesto, which is located in the Central Valley, all ballot measures for raising more money for general essential services such as fire have failed. Each citizen in Modesto pays below the average rate for fire services ($119 per capita in Modesto as compared to an average of $166 in our entire data set), and Modesto is also more right-leaning than the average city included in our data set. City managers in Modesto have spoken out in support of these ballot measures to no avail. They face opposition from a particularly vocal Stanislaus Taxpayers Association, whose goal is to “ensure a community’s taxes are necessary and are spent wisely.” Other cities have opted for a different path. The La Habra Heights suburb of Los Angeles provides its own fire and emergency medical services, instead of relying on the Los Angeles County Fire Department. The city has revisited relying on the county for fire protection, but usually the fire protection proposals from the county are too costly. Since 2005, the La Habra Heights fire tax has grown slightly; however, voters have continuously approved measures to extend it. La Habra Heights voters are just under 20% more right-leaning and pay more for fire services ($169 per capita) than Modesto residents.
Here, we sought to understand the importance and influence of several factors towards the outcome of city ballot measures related to funding fire protection services. Using a variety of regression models, we analyze these data and identify a couple of key factors that predict ballot outcomes with surprisingly high accuracy. We hope these findings will inform various stakeholders interested in funding fire and other related ballot measures.
Factors influencing ballot outcomes
We analyzed which factors were most salient in predicting the outcome of local ballot measures related to funding fire departments using a random forest classifier. Of the 15 variables we studied across different subsets of our data, five variables were consistently ranked highest (see Fig. 3) by the model: a) number of fires within the past 5 years, b) percentage of the labor force in rural employment, c) number of days since the last fire within 25 miles of the city, d) political spectrum measures, and e) fraction of revenue spent on fire protection. An assessment of these factors is explained below, and distributions for each are shown in Fig. 4.
a) Number of fires within last 5 years
Areas with ballots that passed had experienced a median of 42 fires over the last 5 years, while areas with ballots that failed had a median of 35 fires. This corresponds to an increase of 20% more fires in areas with ballots that passed, suggesting that fire history, specifically frequency, affects ballot outcomes. The fact that the number of fires over the last 10 years was not as significant a predictor variable in our random forest model suggests that recent fire history, specifically the previous 5 years, is more important.
b) Percentage of labor force in working outdoors
Areas with ballots that passed had higher employment in outdoor sectors than in areas that failed. However, this may be correlated with areas that experience more fires, and needs further investigation.
c) Time since last fire
The time since last fire was found to be one of the statistically significant predictors for the ballot outcome predictive model. Cities where ballots were passed had a fire more recently by nearly 2 weeks compared to areas where ballots did not pass. We further explored this relationship by plotting the ballot pass rate as a function of time since last fire in Fig. 5. Here, we found that the ballot pass rate appears to drop significantly after approximately 3 years. This suggests that there may be a 2-year window of opportunity after a fire during which fire related ballots are more likely to pass.
d) Political ideology
Areas with ballots that passed were in more left-leaning cities, as quantified by the ratio of party registrations. On average, there was a 16% higher ratio of left to right party affiliation in areas where ballots passed compared to those which failed. This supports previous studies which have found that political ideology affects the impact of local wildfire on climate related political behaviors [1].
e) Fraction of revenue spent on fire
Locations where the amount spent on fire was a lower fraction of the budget were more likely to pass. This suggests that either less expensive ballot measures, areas with larger budgets, or some combination of the two.
Model Development
To assess the most important factors in a predictive model for ballot outcomes, we created a random forest model with the features listed in Appendix 1. Use of a random forest is appropriate in this context because it is flexible to account for the likely complex and non-linear effects of various factors on voting outcomes, yet provides easily interpretable variable importance rankings. Futhermore, these models are not sensitive to correlations between input features. The predictor features used here spanned fire history, demographic, and economic factors. Categorical data were transformed to numerical features and put into the classification model. The model was created using the scikit-learn python library and hyperparameters were tuned using a randomized grid search model, which optimized the test set accuracy using 3-fold cross validation. The purpose of this was not to build the best model for the training set, but rather to a) identify the features with the most pertinent information influencing ballot outcomes and b) to assess the potential predictive skill of a generalizable model. Accordingly, we assessed the accuracy of the classifier (as calculated by (true positives + true negatives) / total number of samples) on an out of sample test set. For this model, an 80-20 train-test split was used. Among various types of models as described further below, we achieved a relatively high accuracy on the test sets of 0.7-0.8.
We utilized the 5 most salient factors found from our random forest classifier in a K-Nearest Neighbors model to further check the predictive accuracy of this subset. We chose to use the variable representing the percentage of right-wing voters in lieu of the ratio of left-wing and right-wing voters due to the higher separation apparent in the probability density for this variable. The correlation between these two variables is very high (82%) and they communicate very similar information.
We first selected the value of K for our KNN model through 3-fold cross-validation. The cross-validated accuracy was highest at the value of K=21, so we chose to utilize this for our model. We ran 1000 iterations of randomly selecting observations for an 80-20 train-test split, building and testing a KNN-21 model on these partitions in each iteration. When taking the average of our predictive accuracy, we found that the KNN-21 model using the 5 variables chosen from our Random Forest model had predictive accuracy (on test set) of 75.17%.
We then looked at results from a multiple binomial regression model that used these 5 predictors (fraction of revenue spent on fire protection, number of fires within the past 5 years, percentage of the labor force in rural employment, number of days since the last fire within 25 miles of the city, and percentage of right-wing voters) as independent variables, and the outcome (pass/fail) as our dependent variable. Our results indicated that the number of days since the last fire within 25 miles of the city and the percentage of right-wing voters were significant variables, and both had a negative impact on the outcome of a ballot measure.
To further test the tradeoff between predictive skill and potential overfitting, we decided to run robustness checks utilizing only the two significant variables found from our binomial regression. We again utilized KNN, where a value of K=19 was selected from 3-fold cross validation. In the same fashion as our previous model, we found that our KNN-19 model that utilized the number of days since the last fire within 25 miles of the city, and percentage of right-wing voters as independent variables had an average predictive accuracy of 75.44%. We then created a multiple binomial model, as before, using only the significant variables from our previous regression. Our results were similar to that from our previous binomial regression, with both predictors found to be fairly significant, and both showing a negative impact on ballot measure outcome.
Data sources
Ballot Measures
We analyzed 499 ballot measures from 239 Californian cities between the years of 2002 and 2017 that contained the word “fire” [2]. Of these 499 ballot measures, general essential services were the subject of 91.0% (454 measures) [3], fire departments alone were the subject of 5.6% (28 measures) [4], and firearms/fireworks were the subject of the remaining 3.4% (17 measures) [5]. On average, 72.3% of all ballot measures passed, although this does vary across years with the lowest percentage in 2003 (55.5% of 9 ballots) and the highest percentage in 2016 (86.7% of 83 ballots).
We further classified ballot measures by the method by which they financed the proposed action, if applicable [6]. Of the 499 measures, 82.2% (410 measures) used taxes and 2.8% (14 measures) used bonds to finance the proposed project. There were over 20 different types of taxes used across the 410 tax-specific ballot measures. Of these, the three most common tax types were sales (41.9% of the tax measures, 172 measures), utility (17.3% of the tax measures, 71 measures), and property/parcel taxes (5.9% of the tax measures, 24 measures). Together, these three taxes account for 53.5% of all ballot measures analyzed and 65.1% of the tax ballot measures.
Fire and Smoke Data
We used fire maps from CalFire’s (egis.CALFIRE) California Fire Perimeter 2019 dataset to extract various metrics to determine the city’s fire exposure and experience. These data were merged with ballot date and city boundaries from the State Board of Equalization's tax rate area maps. Specifically, we extracted the time since fires within 10 and 25 miles of the city limits, the largest fire areas for fires within 25 miles, and the number of fires within the last 5 and 10 years within 25 miles. To measure smoke exposure, we used the aerosol optical depth (AOD) measurements from the Moderate Resolution Imaging Spectrometer, specifically the MOD08_M3 monthly dataset. To define a smoke day, we set a threshold based on the 90th percentile of all 0.55 μm AOD data, which corresponded to a value of ~0.95. We then counted the number of days the city experienced an AOD value above this threshold within the last 3 years of the ballot measure, as well as the number of days since the last smoke event [7].
For each ballot measure, we included data on the city’s total and per capita fire expenditures for that year [8] and data on the composition of local fire departments in the city. On the composition of local fire departments, we included data about the type (ie volunteer versus paid) and, if paid, the average salary of a firefighter.
Demographic Data
In addition to population, we also determined the percentage of the labor force in rural employment [9]. We defined rural employment as the average number of people working in farming, mining, logging, and construction sectors for each year.
Using the data available from the California Secretary of State, we classified the election type for each ballot measure and used that year’s voter registration data for each city. Left-leaning voters are registered with the Democrat or Green parties, while right-leaning voters are registered as Republican, American Independent or Libertairan parties. While Libertarians are socially liberal, they tend to be fiscally conservative. Because we are analyzing fiscal ballot measures, we assumed they aligned more with other right-leaning parties.
Challenges we ran into
By and large, the biggest challenge of our project was cleaning the data. While many sources publish data on these measures, it is often stored in different locations and conventions for publishing the data have changed over time.
Accomplishments that we're proud of
No one on this team had worked with any of this data before. We worked hard to boil down many of these competing factors into simple metrics. To get the data, we learned new ArcGIS and Python skills, and employed natural language processing techniques for the first time.
What's next for Wildfires, economics, and cities ballot measures
We would like to thank Dr. Iris Hui for proposing this project. We look forward to continuing to work with her. Beyond academic audiences, we hope our data and analysis can be useful to Californian policy makers at the local and state level.
[1]
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3452958
[2] We received no data for the 2004 year.
[3] For example, “To maintain essential city services, including rapid 911 emergency response, fire/police protection, add paramedic services, keep fire stations open/staffed, address homelessness, repair local streets/potholes, improve rapid response to assault, burglaries/crimes, keep public areas safe/clean, maintain senior services, attract/retain jobs/business, increase water conservation; shall the City of Palm Springs establish a 1/2 cent sales tax; requiring annual independent audits/public oversight; all funds used locally?”
[4] For example, “Shall the General Plan of the City of Poway be amended to allow fire stations on property having a natural slope in excess of ten percent?”
[5] For example, “Shall Ordinance No. 570-01 Repealing the sale, use or possession of safe and sane fireworks be adopted?”
[6] For example, the ballot measures in (7) and (8) do not require money or funds.
[7] Other factors, such as smog or pollution could also contribute to high aerosol counts. We believe the 90th percentile is a good threshold for separating smoke aerosol caused by wildfires from these other factors.
[8] For some years, data on city fire expenditure data could not be found. Those entries were left blank, which could decrease its priority in the random forest ranking. Because the per capita fire expenditure factor was still highly ranked, we are confident of its role in determining ballot measure outcomes.
[9] For more information on community archetypes and their influence on wildfire preparedness, see
https://www.fs.usda.gov/rmrs/science-spotlights/archetypes-wildland-urban-interface-communities-making-communities-fire-resilient
Appendix 1. Predictor variable name and descriptions
Ballot data
Year - Year of ballot measure vote
what - what is being funded
how - type of funding source (e.g., sales tax, etc.)
impact - if possible, describe whether this will increase or decrease funding
election_type - general, primary, etc
Fire data
timefire25 - days since last fire within 25 miles
timefire10 - days since last fire within 10 miles
maxfirearea25 - largest fire within last 5 years within 25 miles
countsmoke - number of smoke (or smog) months in last 5 years
timesmoke - days since last smoke event
firecount5 - number of fires within 25 miles within last 5 years
firecount10 - number of fires within 25 miles within last 10 years
Demographic data
population
leftratio - (python random forest implementation only) political spectrum indicator calculated as number of registered Democrats / number of registered Republicans, Libertarians, and American Independent Party members
perc.right - (R model implementations only) political spectrum indicator calculated as number of registered Republicans, Libertarians, and American Independent Party members / total number of registered voters
total - total number of registered voters
Economic data
frac_rev - fraction of revenue that goes to fire expenses
lf.perc - percentage of population working in farming, mining or construction
Built With
esri
python
r
scikit-learn | Predicting the success of fire-related ballot measures | We built and analyzed a data set to understand how wildfires and demographics affect how California cities fund fire protection services. | ['Madeleine Gates', 'Lauren Borja', 'Nathan Dadap'] | [] | ['esri', 'python', 'r', 'scikit-learn'] | 4 |
10,050 | https://devpost.com/software/project-phoenix | Inspiration
In the face of a disaster, donations pour into a community. Yet as the rebuilding process goes on but media attention is lost; communities require sustained philanthropy in an organized way. Our team was really interested in developing a system to track wildfire donation. We decided to focus on tools that would help identify where funding was most effective and what gaps in funding existed? This is prompted by our desire to see more equitable support for communities hit by a disaster. Using the Camp Fire as a case study, we decided to investigate how money flowed into the community by reaching out to community stakeholders.
Our team’s initial research online produced findings that revealed that the recovery process after a fire was an immensely challenging space to navigate. We came across countless articles that depicted the fragmented reality of the recovery process. For example, 11,000 homes were reportedly burned down in the Camp Fire. However, an article published a year after the disaster reported that only 11 homes had been rebuilt.
We reached out to several organizations, and were able to interview four of them: the Rebuild North Bay Foundation, the Center for Disaster Philanthropy, the Rebuild Paradise Foundation and the Camp Fire Long Term Recovery group. We are very grateful to all of them for taking the time to talk with us, as we learned a lot from all of these interviews.
After our set of interviews, we realized a larger issue - few people could capture rigorous donation data, let alone what those donations led to. At the same time, certain philanthropies highlighted the need to empower local organizations with the flexibility to utilize the grants for whatever need arises. We gleaned from interviews that grants that are too prescriptive may lead to projects pursued that do not match the needs of the community. This led to questions on how to balance between accountability and flexibility.
We also poured through recovery documents drawn up by different governments at the local city and county level. We noticed that there were a lot of efforts that were being replicated. Our team started to map out the existing inefficiencies and asked the question: How do we streamline this process for a hypothetical Recovery Task Force? We envisioned the Recovery Task Force to be made up of different stakeholders within a community with representatives from the local government, community organizations, and volunteers from the community. We also conducted an asset mapping exercise by delving into open-source datasets, checklists of action items for recovery, recovery toolkits, willing experts in the field; the plethora of relevant resources that we came across was exhilarating, and we then needed to figure out a solution to connect these seemingly disparate parts together.
What it does
Our dashboard is a design prototype that allows communities, specifically counties or public agencies, to manage the recovery process after a disaster. Communities begin by entering county information and choosing sectors they’d like data on. Our program would create a dashboard and draw from available public data to create a picture of the community before a disaster. Users could also upload any data the community itself had, from a list of businesses to a community evacuation plan. This dashboard could be created before a disaster or immediately after a disaster happens.
The community could also layer on other metrics that would only be measured in light of a disaster, such as the number of homes damaged or estimated amount of recovery to raise money. These could be compared to existing data from before a wildfire or standalone metrics themselves. The final step of the dashboard is inviting collaborators to contribute data. As nonprofits and other agencies gather donations, provide first aid, and participate in other forms of recovery, they could document any updates to community metrics through this dashboard. We would also include multilingual surveys and offline surveys to encompass all communities and account for potential network issues after a disaster. This dashboard exists as a one-stop summary pulling in all community efforts and comparing it to past data or community goals (inputted by the agencies) in order to continue the narrative of recovery and keep track of all progress being made.
How we built it
We used Figma to prototype and design the layout of the dashboard. We chose Lake County, which has ACS data for a pre and post-fire set of years, to explore and document for our dashboard. We also used screenshots of ACS "Narrative Data" for Lake County as placeholders for charts our platform would create. We also began an interactive data visualization platform, an eventual iteration of this design, in the form of a Dash app (see video above, and link to the web app below). The app pulls data from the 5-year average American Community Survey data and was built using Python Flask, Dash and Plotly, and leveraging the power of Mapbox. The design and Dash platform would eventually be part of a website that helps communities set up and manage the dashboard.
Challenges we ran into
Understanding the community recovery process was our biggest difficulty and is still the largest barrier in implementing a flexible dashboard. There are many academic disaster recovery frameworks, but they don’t always converge on metrics to measure and vary greatly depending on the context. Many recovery processes happen retroactively, given how difficult natural disasters are to plan for. Narrowing in on a few features and outlining how communities would use our tool was an iterative process. We also ran into many challenges integrating our datasets (beginning with ACS data), and we foresee challenges in automatically populating or layering existing and crowdsourced data sets. We also faced the question of who would utilize this tool and how we plan to communicate its existence.
Accomplishments that we're proud of
We spent a significant part of the hackathon listening to folks who had worked in communities recovering from wildfires or had done extensive research on them, which allowed us to pivot from a philanthropy-centric project to a larger need of documenting community recovery for all, especially funders, to see. We were committed to the design thinking process as well as researching Camp Fire in-depth (though we later pivoted). In the process, we each explored academic research tools, participated in interviews, and learnt about new APIs or data analysis tools.
What we learned
No one organization has a comprehensive approach to disaster recovery; the first action is to provide immediate support to a community, which involves leveraging lots of federal/state resources and local nonprofits, many of whom focus on a core aspect or sector of recovery. FEMA is in charge of large parts of the recovery process. Organizations like Recovers.org and Disaster Philanthropy help capture where funding goes, but granular data is often not available. Recovery takes on very different meanings and is further exacerbated by equities in terms of race, socioeconomic status, and access to technology, to name a few factors. Lack of sustained funding also halts projects. Disaster recovery is messy, but an organized, flexible approach that empowers communities to lead and manage its own recovery while welcoming the contributions of others is one pathway forward in building resilience.
What's next for Project Phoenix
Our next steps are to:
complete our website/application design by refining the user journey
refine the metrics we’ve chosen through more academic research, user interviews, and past evidence of disaster recovery benchmarks
create sample surveys with both offline and online capabilities (and the means to upload and auto-populate this date)
enable a place to document past wildfire history, data tracking, and future risk
We envision using a combination of data visualization tools, GIS, applications such as the one highlighting American Community Survey data, and spreadsheets to provide the data population capabilities. We want to simplify how communities can pool together and record their work to better understand the state of recovery and advocate for resources past the initial interest in post-disaster needs.
We would also like to talk to more public authorities and disaster recovery groups about their disaster management process, pain points in data collection, and our prototype tool. We would also like to highlight other projects and initiatives in the disaster recovery space while figuring out how to market and improve our tool.
Phoenix image credits: phoenixpwn.com
Built With
api.census.gov
censusdata
dash
figma
flask
google-cloud
mapbox
plotly
python
Try it out
www.figma.com
community-recovery.wl.r.appspot.com
docs.google.com | Project Phoenix | Our solution equips communities with a tool that leverages existing resources, data and community assets to track recovery and encourage sustainable funding throughout the process. | ['Carissa Livan L Ding', 'Shikha Srinivas', 'Pierre Massat'] | [] | ['api.census.gov', 'censusdata', 'dash', 'figma', 'flask', 'google-cloud', 'mapbox', 'plotly', 'python'] | 5 |
10,050 | https://devpost.com/software/wildfire_hackathon | Stanford Wildfire Hackathon CEE 265 2020
Project by Jack Seagrist, Yash Gaur, Hunter Johnson
Please refer to our project webpage to learn more about our project.
https://jackseagrist.github.io/Wildfire_Hackathon/
Built With
esri
flammap
Try it out
jackseagrist.github.io | Live Interactive Fire Evacuation (LIFE) Tool | Our project aims to create an easy to use, government facing, data based tool that assists fire departments in real time evacuation scenarios. | ['Yash Gaur', 'Jack Seagrist', 'Hunter Johnson'] | [] | ['esri', 'flammap'] | 6 |
10,054 | https://devpost.com/software/cloutvocate | Cloutvocate = Clout + Advocate
Note: all names and visuals used within the platform are either team members from this group or those who have granted us written permission to be featured in an effort to avoid any copyright infringement. The typeface used is Roboto available through Google Fonts.
Context
As an outcome of the current economic crisis, nonprofit organizations have been presented with unprecedented challenges in generating the vital donations they need to ensure their survival and to continue to deliver the programs and services that communities depend on for support. Newly implemented social distancing practices have forced nonprofits to reinvent their modes of awareness and fundraising in order to reach audiences to inspire action and drive the critical donations needed to operate and grow. Drawing funding is an ever-persistent challenge as options for giving diversify and nonprofits struggle to stay digitally relevant with emerging generations of donors.
In today's digital world, influencer marketing is becoming an increasingly beneficial strategy to reach new generations of donors on a global scale. Targeting millennials through influencer marketing campaigns can help nonprofit organizations reach coveted audiences in an organic and captivating way, all while inspiring action to reach critical fundraising goals. The millennial population currently represents the largest segment of social media audiences; thus, leveraging the role of social media influencers as part of a nonprofits awareness strategy can play a vital role in the success of a campaign.
The Problem
When nonprofits and funding sources are not well matched, money doesn’t flow to the areas where it will do the greatest good. For nonprofit organizations, attracting millennials through influencer marketing strategies can be challenging -- finding influencers with similar interests, especially in niche categories, can be difficult; and for a campaign to spark action the message must feel meaningful and authentic to the audience. Sourcing and coordinating mutually beneficial partnerships is a time consuming process that may lead to rejection emails or no response at all. Further to this, influencers may not always be interested in using valuable space on their platform(s) to create custom content promoting a cause, that is, unless they have a personal interest in the mission, or they’re receiving monetary compensation for "paid advertising" integration. This ultimately takes much needed funds away from resources that services and communities depend on. This led us to think...
How might we create a platform that helps the nonprofit sector engage the public to drive critical donations to achieve mission goals and advance the impact that they are looking to have?
The Solution
Introducing Cloutvocate…
A new and innovative matchmaking platform for nonprofit organizations to connect with the right partners to augment campaign awareness and drive vital donations. Using AWS products and services, our team has created a scalable tool to help nonprofits adapt to a changing landscape of patron and audience engagement. This advanced technology has allowed us to re-think how nonprofit organizations can be matched with partners in a way that provides value for all parties involved. Recognizing where friction exists in the current nonprofit-influencer business model, our team has created a platform that integrates a corporate sponsorship component to funnel more revenue into a nonprofit’s cause, incentivize influencers, and align corporations with well-matched social causes and coveted audiences.
Example Scenario
The video above is a demonstration of how an influencer and sponsor can partner together help augment fundraising goals for nonprofit organizations.
Original Source:
https://www.youtube.com/watch?v=foLlul8Tl3E
This video is listed as available under a creative commons license on YouTube
How We Started
When we began this project we started off by watching the keynote presentation and taking notes to gather insights about the problems nonprofit organizations are currently facing. We decided to use a design sprint methodology to turn these insights into a solution by re-framing key information as How Might We questions which was following by grouping certain themes into an Affinity Diagram, a Note-N-Map exercise, Lightning Demos, and more. Given the massive scope of the problem and the generous amount of information we were provided with at the start, we found that running this process remotely through Miro helped to narrow down big problems into achievable solutions within a short period of time.
An inside look into our Design Sprint that was used to lead is in the direction of our chosen solution
How It Works
Users are able to sign up as either a nonprofit organization, social media influencer, or corporate sponsor where a series of onboarding questions helps to determine matches based on the user’s chosen parameters.
A nonprofit organization begins by creating and launching a new proposal to a chosen influencer from the list they’ve matched with to determine if their campaign could be of interest to the influencer at that point in time.
The influencer receives the new proposal in their dashboard and is given a chance to review the type of campaign the nonprofit organization has pitched to them. The influencer is able to accept or decline the proposal, and if accepted, they may also decide if they would like to donate a % of the revenue generated from the campaign back to the nonprofit organization in exchange for a tax receipt. Once the influencer approves the campaign, the proposal then enters into the marketplace for a sponsor to buy into.
Once the sponsor receives the proposal, they’re given a chance to review the treatment and decide whether or not buying into the campaign is of interest to them. The sponsor is provided an opportunity to indicate how much of a sponsorship contribution they are willing to make in exchange for brand integration within the content. If approved by the nonprofit and influencer, the sponsor is then able to make their sponsorship payment using AmazonPay that would then be split evenly between a donation to the nonprofit organization and a sponsorship fee to the influencer.
A user flow diagram of the platform created using Cawemo
A diagram demonstrating the value proposition of the platform
How We Built It
Cloudvocate is a simple platform built using open source software, open datasets and various services from AWS’s portfolio, including: Strapi and it’s GraphQL API, Angular, PostgreSQL, EC2, S3, Cloudfront, Amplify Console and RDS, all of which are used to empower and deploy this matchmaking platform.
Further to this, Cloutvocate leverages Amazon Pay to facilitate payments from both influencers and sponsors to the nonprofit organization, as well as donations made by the influencer's viewers to the campaign.
Challenges
We faced multiple crashes with Strapi and after being confused and diagnosed for a couple weeks, it turned out the problem is that PostgreSQL limits table names to 63 characters (MariaDB also limits to 64 characters, so similar restrictions). Because our table names were long, when Strapi generated "many-to-many" tables, they're then truncated and thus created conflicts. So the solution to this is to rename the collection type names to shorter yet still reasonable ones. The good news is that AWS RDS PostgreSQL is performing really well and there is no problem at all, and we're feeling safe that all data is backed up automatically daily, and AWS RDS also performs weekly minor version updates/patches without us having to do anything.
It was challenging to coordinate schedules with a group of international developers but we were able to get together frequently and work cohesively on our application. Using the quite sparse data that was provided by APIs like CharityNavigator, it was a challenge to decide how best to integrate a matching system into the website. While we decided to use the category tag to pair up users and companies, we also brainstormed ways that we can optimize this for even better recommendations.
We discovered late in the development process, after consulting with Alex D., that there is a bug with the Angular framework that is causing issues with AmazonPay integration. We recognize that in theory the platform integration should work seamlessly; however, because of the framework used for this platform there is a bug that is causing issues. Images have been included below to show the code:
Above is the code Michelle received from Alex Dinnouti in an email, and after testing this code it was found to be working flawlessly, but when we integrated this into the Angular framework the code seems to be broken. After further dialogue with Alex it was found that there is a bug with Angular. As far as we've debugged the issue is something with execution of the vanila JS functions (like window.open() method) which is creating a problem inside the Angular component.
Accomplishments
From Hendy...
"I only recently knew about AWS Amplify Console, and tried to deploy our Angular app straight from GitLab using AWS Amplify Console. In less than 5 minutes the Angular app was live, and I didn't write any code! That was really cool."
From Kori...
“This was my first time integrating Amazon products into a UI design. In addition to this, it was also a lot of fun giving consideration towards how Amazon's products and services could be utilized to produce a solution that responds to the challenges nonprofits are currently facing”
From Michelle...
"It was my first time working with AWS and databases, and I practiced implementing code with real life situations. Integrating python with API requests to analyze the data and writing SQL code in python to interact with the frontend was an amazing learning opportunity for me."
From Rohit...
“I learned about Graphql and why it is the most awesome query language way to work with. Also, I explored different AWS services and how creating an architecture of these services helps.”
From Romeo…
“Learning more about non-profit organizations and their ecosystem was very interesting and rewarding, not to mention all the cool technologies like AWS Amplify Console, Strapi etc we got to play with in the meantime.”
From Shelli...
“I haven't worked with AWS in the past, so it was really cool to learn about the software and services that they provide and to implement these things into a final product.”
What We Learned
There's an untapped market in the business of making partnerships easier and more flexible for nonprofit organizations.
Building pipelines for Continuous Integration and Continuous Delivery is ideal, but amplify completely destroys all complexity in writing config files. I (Rohit) learned how and more importantly why we use load balancers. Also, how to map different services in order to host a server for faster response.
Looking at how to create value from a nonprofit's perspective is more challenging than anticipated -- learning how to guide funds in a single direction rather than a typical "buy something / receive something" transaction is tricky.
Working with a team who bring a wide range of skills to the table is the best way to learn from one another about how different products work, different ways to approach a problem, and gain an understanding for how the different roles are interconnected.
What's Next for Cloutvocate
Further iterations aim to include several new features, including:
Use AI/ML to augment our matchmaking capabilities and provide personalized recommendations to show the most relevant NGOs for a given influencer or influencers for a given NGO (use of Sagemaker and/or personalize).
Integration of a feature showing how the nonprofit utilizes a received donation.
Mailbox and messaging integration to facilitate communication within a single platform.
A content creation studio where all invested parties can seamlessly collaborate in real-time on the creation of content before launching (thus, eliminating longer delays in approval and launch time).
Integration of multiple social media login solutions, including: Twitch, Facebook, Instagram, Twitter, etc. Currently only YouTube is available due to time constraints; however, our goal is to ensure all relevant platforms are available moving forward.
The opportunity to partner with multiple influencers and/or sponsors to augment the campaign footprint and increase audience traffic to the platform.
The option to match nonprofit organizations with other nonprofit organizations to collaborate and amplify their collective narrative.
Built With
amazon-cloudfront
amazon-ec2
amazon-rds-relational-database-service
amazon-web-services
amplifyconsole
angular.js
graphql
serverless
strapi
youtubeapi
Try it out
master.ddtfzmv0ytpn4.amplifyapp.com | Cloutvocate | A matchmaking platform designed to connect nonprofit organizations with influencers and sponsors to elevate meaningful causes and drive vital donations | ['Rohit Jain', 'Hendy Irawan', 'Michelle Zyman', 'Kori Skeffington', 'Romeo Radanyi', 'Shelli Gorokhovsky'] | ['Best in Nonprofit Fundraising'] | ['amazon-cloudfront', 'amazon-ec2', 'amazon-rds-relational-database-service', 'amazon-web-services', 'amplifyconsole', 'angular.js', 'graphql', 'serverless', 'strapi', 'youtubeapi'] | 0 |
10,054 | https://devpost.com/software/gudville | Gudville Login
Recommendation of Potential donors
Recommendation of similar non profits
More info about similar NonProfits such as their most recent news articles and tweets about donations. Also included Twitter Analytics.
Hassle free Volunteer and Campaign management. Also included, Fully fledged twitter studio to post to twitter and manage tweets.
Create and Manage Campaigns with ease. Add volunteers to campaigns, post campaigns to twitter and request donations all in one place
Non Profit Profile page
Donor App
Donor Donation Request to pay using Amazon Pay and list of donations
Donate on Gudville using Amazon Pay
Donate on Gudville using Amazon Pay
Donate on Gudville using Amazon Pay
Architecture
Problem
Major challenge many fundraising teams face on the major giving side is identifying the right individuals to cultivate as potential major donors, sponsors and volunteers. As nonprofits are often strapped for resources and time, targeting the right individuals is critical. Also, there's a lot they could learn from their peer nonprofits about how to be more effective - if only they knew who their peers were, what they do, and who funds them.
The problem isn't a lack of information about what other organisations do or who funds them. There's a ton out there, but it's messy -- scattered across the web, in charity databases, in news articles, in social media, in data sources structured and unstructured. In order to make better organisational decisions, putting this information at nonprofits' fingertips will allow nonprofits to spend less time digging around for information and more time focusing on their core missions.
What if we have a platform that can help answer the following question all in one place?
How can I discover possible donors and sponsors that are more inclined to help for my nonprofits cause?
Which companies have partnerships with nonprofits in my sector?
What is my impact on social media, and what are the characteristics of my followers?
How can I retain existing donors and inspire new donors to fund my organisation?
How do I relate to other charities operating in the same sector?Which nonprofits can I partner with?
How can I discover volunteers that are more inclined to help my nonprofits cause?
Solution
There’s plenty of information about nonprofits scattered throughout the web, but nonprofits aren’t sure what to do with it. Gudville uses Machine learning and Natural Language Processing to recommend possible donors, company partnerships, suitable volunteers and similar nonprofits.
How do we do this?
Ever wondered how Amazon recommends products you are likely to buy? We use a similar concept to provide recommendations for nonprofits.
Gudville assembles information on nonprofits scattered throughout the web from structured data such as Charity Navigator, unstructured data such as news articles, Twitter and webpages of nonprofits. With all these sources of information in hand, Gudville uses natural language processing techniques to build a weighted graph that connects nonprofits, companies, and people (twitter followers). It then uses machine learning to make recommendations for nonprofits.
Gudville is also an all in one platform for nonprofits to fund and run their entire mission at one place. Nonprofits can use it to request donations, contact donors, manage campaigns, manage volunteers. Donors can use Gudville to discover nonprofits based on their interest and also donate to them through Amazon Pay.
How do we Identify Potential Donors ?
Nonprofits need to understand who their target audience is and adapt to their behaviours and preferences.
Gudville recommends
possible donors
who are more likely to support the nonprofits cause by identifying donor’s previous donations to other similar nonprofits. Nonprofits can use this to identify right individuals to cultivate as potential major donors. This way nonprofits can spend less time digging around for information and more time focusing on their core missions.
How Nonprofits Can Find the Right Volunteers?
Identifying and recruiting the right volunteers for the right strategic jobs can save a nonprofit a lot of money. Finding the right volunteers for a particular function can be challenging. Gudville identifies
volunteers
with the right motivations to volunteer for the cause that your organization supports. This is done by identifying volunteers that have previously supported Non profits with a cause similar as the non profits under consideration(using twitter analysis).
How Nonprofits Can Be Sustainable?
It is important to identify similar non profits who align with your organisation’s mission, vision, and goals. Nonprofits can learn from each other using this information. They can also get a sense of how effective other nonprofits social media management is and what aspect they can improve on. Nonprofits can also develop strategic partnerships that can dramatically increase nonprofit’s outreach ability, and brand exposure.
Gudville identifies
possible partners
by analysing their cause, mission and events of nonprofits in the same sector and compare it with the non profit under consideration.
How it works
Data Collection
1.Fetching structured data - basic info on nonprofits
Gudville aggregate basic information about a nonprofit from structured databases such as CharityNavigator.
Nonprofit's name, location, description, financials, and issue category (NTEE code).
2.Gathering unstructured data - nonprofits, and companies
It involves fetching unstructured, natural language data from the web in order to link nonprofits to companies, donors and volunteers:
News articles
: Gudville uses web search APIs like News API to gather news stories that mention companies and the nonprofits and causes they support.
Webpages
: CharityNavigator databases often list a nonprofit's homepage. Gudville crawl these webpages and automatically extract company names that support the organisation.
Fetching social data - nonprofits and supporters
Gudville also fetches a nonprofit's twitter such as nonprofit's twitter followers and profit's tweets are retrieved via the Twitter API.
Analysis
Graph building - linking everything together
With all these sources of information in hand, Gudville uses natural language processing techniques to build a weighted graph that connects nonprofits, companies, and people (twitter followers).
Similarity relationships between nonprofits, based on their tweets.
Similarity relationships between nonprofits, based on their webpages.
These similarity calculations are done using NLP topic modeling techniques using the Python gensim library.
Graph analysis - understanding supports, recommending partnerships, finding nonprofit communities, understanding connectedness
We then use social network analysis, including community detection algorithms, to recommend company partnerships, discover communities of similar nonprofits, and understand the network structure of those communities.
Features
For Non Profits
Dashboard to tell their stories and the impact it has on the cause its working on.
Manage all the events, campaigns, donations and volunteers associated with the event
Reach suggested possible donors(Donors who have donated to causes similar to theirs) with prefilled or customizable email from the dashboard.
Reach suggested possible sponsors(Company who have sponsored to causes similar to theirs) with prefilled or customizable email from the dashboard.
Reach suggested possible volunteers(Volunteers who have voluntered to causes similar to theirs) on twitter.
Connect or partner with other nonprofits similar to you
Request donations on click of a button.
Add admins to manage Nonprofit account. Customize nonprofit page on Gudville.
Manage social media activity all in one place. Twitter statistics of nonprofits similar to you.
Detailed Information about other Non-Profits along with twitter statistics, their donations statistics and news mentions about donations. Use this information to see what you can do better to drive more donations and contribute better.
For Donors
Discover nonprofits similar to the ones that you already donate to or partner with.
Access to news feed and twitter feeds of all the Non Profits they have sponsored.
Repeat donations to Non Profits they have sponsored with a single click using Amazon Pay.
Access to list of Non Profits that is doing Amazing job in the cause they are interested and needs their help.
Contact the Non Profits that were suggested and provide their valuable donation through Amazon Pay.
With Gudville, we make insights based on the data thats constantly evolving to make sure that you’re finding the best prospects most likely to give more. All of this process get's automated. Not just that, you can access possible company sponsors and volunteers who are more likely to support the Non Profits cause based on their previous activity.
How I built it
Architecture
Gudville is built using several AWS services and open source technologies. Charity Navigator API is used to fetch list of nonprofits. AWS Lambda is triggered periodically to fetch recent tweets and news articles and then this data is stored in Amazon S3. Then these tweets and news articles are sent to AWS Translate followed by AWS Comprehend for natural language processing. Processed tweets are then analysed and useful information is extracted and stored in Amazon RDS.
Amazon SES is used to send Emails to donors and other nonprofits. We also use Amazon Route53, CloudFront, Application Load Balancer for delivering the web application. Amazon S3 is used for delivering static assets and to store unstructured data. EC2 instances are used to host the backend of the application. Frontend is built using Angular and Backend code is written in Python.
What I learned
I learnt how combination of data from Charity Navigator, web scraping and different social media platform can be used to build a powerful solution to some of the problems commonly faced by Non Profits.
I also learnt how easily I can integrate Amazon Pay to my project.Also, how I can use different services provided by AWS to build scalable application.
Testing instructions:
Clone Github repository
Download AWS CLI and Setup AWS credentials using
aws configure
CLI command. Ensure you have latest version of Node, npm, Angular and python installed.
Open New Terminal, Change directory to "gudville/api" and run
python app.py
command to run Gudville app backend. Note: Your account must be whitelisted to use all the AWS services mentioned above.
Open New Terminal, Change directory to "nonprofit-frontend" and run
ng serve --open --port 4200
to run Gudville Nonprofit app. It will automatically open the app on browser.
Open New Terminal, Change directory to "donor-frontend" and run
ng serve --open --port 4201
to run Gudville Donor app on port 4201. It will automatically open the app on browser.
Now Backend and both the frontend apps are running.
What's Next for Gudville
Extend the Social Studio to allow manage their posts on Social Networks other than Twitter like Facebook, Instagram.
Add support management to help nonprofits easily manage all tasks in one place.
Add bot support so that bot can take care of answering most frequent questions of the volunteers.
Add Volunteer training feature.
Built With
amazon-web-services
application-load-balancer
autoscaling
charity-navigator-api
cloudfront
comprehend
ec2
gensim
lambda
rds
route53
s3
ses
translate
twitter | Gudville | Gudville uses Machine learning and Natural Language Processing to recommend possible donors, company partnerships, suitable volunteers and similar nonprofits. | ['Sumanth Muni', 'Priyadarshini Murugan'] | ['Best in Nonprofit Fundraising - Amazon Pay Integration'] | ['amazon-web-services', 'application-load-balancer', 'autoscaling', 'charity-navigator-api', 'cloudfront', 'comprehend', 'ec2', 'gensim', 'lambda', 'rds', 'route53', 's3', 'ses', 'translate', 'twitter'] | 1 |
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