profile page + achivements
map, with marker selected
map, demostrating cluster functionality
map, with menu open and market selected
William is currently taking a course on environmental science which causes him to be cognizant of how we are impacting our ecosystems. While brainstorming how we could help minimize our impact we came up with TRSHY.
What it does
TRSHY helps users locate nearby trashcans. This is useful when someone has a disposable water bottle and does not want to litter. We also add incentives such as achievements for those who are not often inclined to dispose of their trash. Another feature of TRSHY is the ability to mark if a data point is inaccurately marked. This ability further strengthens our product and adds trust from the use. Users are also able to inform the city of overflow in commonly used bins using TRSHY.
How we built it
We used Django as our backend and leveraged the Google Maps API for trashcan waypoints. On the frontend, we customized Bootstrap. We deployed it to Heroku with Postgres as our database.
Challenges we ran into
1) Deploying to Heroku - At times, it seemed like Heroku had a vendetta against us. We would push to production and face errors that couldn't be replicated in our local environments. Eventually, we worked out the kinks and got our project running smoothly.
2) API Calls - Once deployed to Heroku, Google Maps refused to display. At first we thought it was because we made to many API calls on our free account. Eventually, we found out that our API_KEY environment variable included an errant apostrophe and quickly fixed the issue.
3) User Geo-location - We also had some trouble with user Geo-location access on the production site. It turned out that Google disallows users to send their location data on unsecured connections. We were able to get our SSL certificate working and resolved the issue.
Accomplishments that we're proud of
It actually works! We were able to create a viable product in under 20 hours which is quite a feat! Another aspect of our project which we are proud of is that we added real data-points from the city of Detroit. This was also our first time working in a group on a coding project which had a slight learning curve (splitting up work, being on the same page, etc.)
What we learned
Since we had not worked on a group coding project before TRSHY was a great opportunity to learn how to work with others well. Managing group dynamics and ideas went pretty smoothly , which can be attributed to the work we did to flesh out our ideas while brainstorming. We also became much more familiar with tools such as the Google Maps API, Heroku, and Django.
What's next for TRSHY
TRSHY can be easily added to any city either from municipal data or crowd sourcing. Once scaled enough, TRSHY can use the data collected from users to inform the city where they should devote their resources.