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Proposed Proof of Concept to solve Traffic Congestion and Prediction Problem for Smart Cities by using LSTM(for future prediction) + CNN(To detect traffic density) + using tweets and combine all three to produce a traffic congestion factor and suggest routes based on that using Google API at any time in future.

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flaredragon/traffic-congestion-prediction

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Traffic Prediction

Proposed Proof of Concept to solve Traffic Congestion and Prediction Problem for Smart Cities. Used - LSTM(for future prediction) + CNN(To detect traffic density) + Real Time Tweets Combined all three to produce a traffic congestion factor(TCF) and suggest routes based on that using Google API at any time in future.

Contents -

Public Folder -

TCF Data till 18th September

LSTM Predicted Time till 18th September

src Folder - React Application

Utility Files -

tweets_realtime.py - To scrape geolocation tagged tweets about traffic

tempserver - Temporary server to queue all tweets recieved from scraping and act as an API for the React Application.

Screenshots

Dense Traffic Light Traffic Twitter Based Events

Note: Code Cleanup is still in progress, this project was made for a hackathon

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Proposed Proof of Concept to solve Traffic Congestion and Prediction Problem for Smart Cities by using LSTM(for future prediction) + CNN(To detect traffic density) + using tweets and combine all three to produce a traffic congestion factor and suggest routes based on that using Google API at any time in future.

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