Inspiration
What it does
How we built it
The backend is built in python with flask. It queries the GE SmartCity API for real-time pedestrian data and passes that on to the iOS app. For requests in the future, it reads pre-generated data from a file. The data was generated with a version of Andrej Karpathy's LSTM ported to tensorflow and trained on a little more than a week of pedestrian traffic.
Challenges we ran into
The data returned by the SmartCity API isn't very consistent as it's still in the works. Also, despite being CS grad students, neither of us actually knows how to code.
Accomplishments that we're proud of
What we learned
What's next for Pedestrian Predictor
Built With
- flask
- google-maps
- ios
- lstm
- python
- rnn
- swift
- tensorflow
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