Prediction of Traffic Density in Internet Offline Mode

Abstract

Today google maps is the defacto app used for the direction and traffic analysis. The proposed work illustrates the solution to a problem of finding traffic between any two points. The technique adopted in this work is predictive form of Machine Learning and the analysis and the prediction of the traffic is done. The use of machine learning method enables traffic analysis in offline mode much easier and expand the span of maps working. The traffic data is collected from users, through API “here” and several other API’s to collect the data. These data are used to predict the traffic when needed. The application will behave as a normal direction provider on Internet Connectivity but as soon as the user goes offline, the real use of application prevails.