Inspiration
We live in an extremely dense urban centre where it is often hard to find vacant spaces in restaurants, libraries, etc. We wanted to tackle this problem with technology.
What it does
OpenSpot is an algorithm paired with an app which detects open spaces in restaurants, cafes, parking lots, and other public establishments. This helps customers save time by knowing where they can go about their day without a headache.
How we built it
The algorithm for detecting empty spots was implemented in Python. The camera system uses a raspberry-pi to stream pictures to a server which processes the images and detects the number of empty seats in an establishment. The iOS app pulls from a real-time database and updates the number of available seats/spots to the end user.
Challenges we ran into
A lot of troubleshooting with the raspberry-pi. Seeing the hardware was not powerful enough to run the algorithm quickly, we had to divert the processing to a server. On top of this, developing the algorithm so that it works quickly and effectively was a challenge.
Accomplishments that we're proud of
We created a fully-functioning prototype of both the algorithm and the server-camera system, paired with the app.
What we learned
How to make use of various visual recognition algorithms, as well as networking between the camera, server, and the app.
What's next for OpenSpot
Optimization of the algorithm, extension for detecting parking spots, and using proprietary hardware for the surveillance system.
Log in or sign up for Devpost to join the conversation.