Inspiration
We looked at a common problem that occurs here at UTD, and that is finding parking.
What it does
Our app that we developed looks to see where vacant spots are on campus for the students.
How we built it
In terms of building the project we used python and OpenCV along with javascript and Amazon Alexa. One of the main challenges we faced was how to detect where vacant spaces were in the parking lots. Utilizing OpenCV we can detect these spaces that are vacant and non-vacant and return it back to the App and Alexa.
Challenges we ran into
We followed an misguided outline for implementing our own Alexa lambda function. The correct version of the platform is written in javascript while we built our initial version in python.
Accomplishments that we're proud of
We are proud to be able to detect with high accuracy.
What we learned
However, we learned there are limitations to what we can accomplish. OpenCV is not compatible with all versions of Python, and some parking structures have different angles of light that can misclassify what type of parking is their.
What's next for CometLot
Our next goal would be to make a full implementation of the system for testing and gather analytical data.
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