What We Built (Goals)
Our team built an app called Aspen. Aspen has 3 core features to its operation:
- An ML-powered camera to identify the material of an image if its recyclable, and how it could be used in a DIY project. This enabled recycling to become significantly easier and more convenient.
- A competition system where users can compete with other users to see who can recycle the most. This encourages users to recycle more and it provides companies with the opportunity to show their impact on the community by sponsoring these competitions.
- A visualizer that shows users across the world and how much they've recycled in addition to different competitions and the number of items the participants have collectively recycled. The data enables users and companies to have a visual way to not only see how they are doing but also determining which areas they could help encourage recycling in.
We were inspired by the idea to try to use games in order to encourage people to do good in their communities/environments. As a result, we decided on trying to create an app that encourages recycling through this process.
The National Geographic challenge and ArcGIS talk inspired our team to explore geographical visualizations to help provide a more effective means of communicating data to inspire more effective and educated action.
What We've Learned
For most of our members, this was our first hackathon. As a result, we learned a lot about how they work, the design process, and working under a very short time frame.
Furthermore, all of our members are in high school, and participating in EarthXHack allowed us to go greatly beyond what our comfort zones along with the support of several amazing mentors. Some of the things we were able to explore include:
- ArcGIS map making
- Firebase and Firestore Database creation and manipulation
- Automated Github manipulation
- Swift UI camera integration
- Using Amazon AWS Lambdas
- Creating an ML API to identify material types
- Google web scraper to find DIY projects with a certain material
- An ArcGIS map that can automatically update with values from a Firebase Database
- An ML image classifier
- Integration of an iPhone app with ML and Camera
- Having the iPhone app interface with Firebase
- Learning how to use Firebase
- Avoiding module conflicts with AWS Lambda
- In the future, we aim to better integrate all of the web features (and other back-end) with the front end
- In addition, we aim to expand from just recycling to also including water consumption and electricity consumption
- This is an inclusive challenge so we want to market it as such