Adapted Traffic Congestion Mapping
Classify Traffic Congestion using Neural Network and map it on the web
Binh Duong
Technologies Used
IBM BluemixProject Team
About
A.T.C.M. is a artificial-intelligent application developed by Team VGU 2015 that can detect congestion at the intersections and the roundabouts. Traffic jams can be avoided by using the neural network module of this app. This will help you save more time and be more economical. A.T.C.M. can detect and evaluate the traffic density’s level and, furthermore, give the users the option to find alternative routes that fit their need. We built ATCM on machine-learning conccept, which is based on Neural Network module utilizing: OpenCV as traffic congestion classifier Bluemix Cloudant as public web app system. The application also uses Google Map API, Flask Microframework and Python platform. Link Github : https://github.com/anindex/atcm
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