logo

SpotASpot

Frustrated with current parking procedures, we decided parking lots could be smarter. So we originally wanted to make an app and/or webapp to color where cars are and aren't to help a driver find a spot. However, as we were working, we realized that humans can see a picture just fine and that this technology would work much better for autonomous vehicles that cannot easily recognize objects.

So, we used OpenCV to write a python script that takes an image of a parking lot and tells which spots are empty and which are not. This gives valuable information to all parties.

The autonomous vehicle gets:

Current data on the closest parking spot (which means it will not be driving around until it finds one)
To the spot quicker (saving fuel [whether electric, gas, etc.])

The business owner gets:

Data regarding how full a lot section is
Customers spending less time in the lot and more time in the store

The best part:

It can potentially use existing CCTV/security cameras already installed in the lot for the data feed
Cost is very little considering this can run on a RaspberryPi0

The future:

Once autonomous vehicles are more popular, this will encourage parking lots to be smarter. This means a car may be able to get data from multiple lots and pick the best one to park in based on spot availability and factor in parking lot prices.
Less movement in a parking lot means less chances for accidents (Hack-cidents?)
Humans getting where they need to be quicker