Inspiration
Sanitation vehicles are a necessity to keeping basic waste off our streets. These vehicles operate 6 days a week, anywhere from 8-16 hours a day. If we can promote a 1% efficiency boost the municipalities and companies that own these fleets can see thousands of dollars in savings, as well as thousands of tons of CO2 emissions.
What it does
Promotes efficiency in the fleet using Machine Learning to find basic properties that fall outside of the standard deviations for vehicle usage.
How we built it
We built it into a multi-tiered approach, separating the backend and the frontend, for ease of deployment.
Challenges we ran into
The biggest challenge we ran into was getting SSL working on our servers. If any one single component in your app requires HTTPS, every component requires HTTPS, and with the time limit we ran into DNS propegation errors when trying to set up a custom domain name for the SSL Certificate.
Accomplishments that we're proud of
How the app looks, and executing some basic ML algorithms on the data we have.
What we learned
ML algorithms and SSL Complexity
What's next for Fleetser
We can extend the application by ingesting more data and being able to extrapolate more efficiencies from it, as well as adding more customer-facing features.
Log in or sign up for Devpost to join the conversation.