Methodologies For Traffic Congestion Prediction For A Iot Based Smart City Using Machine Learning and CNN

Abstract

This paper aims at providing a machine learning model for the traffic congestion for Iot based smart city. We assume that the city is well equipped with the sensors on the streets and all the necessary parts of the city. The convolutionneural networks (CNN) and various machine learning classification and prediction algorithms are used to check which algorithm gives more accuracy for the data set generated.