Snover

Early Prototype UI of Users When Reporting a Snow Complaint

Inspiration

The City of Montreal spends 167 million per year on snow removal. This is a crazy amount, considering that this is only necessary for about 4 months/year, and that we have a robust public transportation system already. So what if the removal of snow could be optimized? And what if civillians could have live tracking of when they will get plowed, to plan their routes and parking more effectively?

This is what Snover serves to accomplish.

What it does

Crowd-sourced location tracking of snow plowers to notify civilians real-time while also feeding enterprises this data to optimize snow clearing routes.

How we built it

Built using Python Flask, HTML, CSS, JS, and Google Maps APIs with Mongo DB

Challenges we ran into

Some of the challenges that we ran into include difficulties making an interface for the enterprise and the clients to be different. Because of the time constraint, some had to be done really quickly. Other challenges included transferring the information between front end and back end.

Another challenge was to generate efficient clearing routes for the snowplows. In order to do so, we gather all available clearing data and complaints from our database. From the data we can identify which streets should be prioritized. We generate an efficient clearing route for the snowplow using the Google API.