A Real-Time Road Traffic Congestion Detectionmodel Using Big Data

This abstract identifies the road traffic events and analyse the delay in the estimated routes. The congested areas will be traced and identified with the help of big data techniques. The aim is to understand traffic patterns in the particular City. In cities, massive population and large number ofvehicles cause problems, like congestion and accidents. A number of efforts to address these problems havebeen proven effectively. The new techniquesroad traffic model was named as Trafficshare which is used to find the unusual traffic events on the roads. The model shows the travel route, travel time, weather delays, road work alerts, emergency road blockage and traffic event messages will be notified. Traffic data refer to datasets generated and collected on moving vehicles and objects. The alert messages were correlated with real-time traffic. Using the detection model will detect the exact delays in the particular road of the city in case of blockage in the road. based on the detection techniques the user can choose the alternate route. The observations that are tracked through GPS and Geotrackerwill be providing the traffic detection analysis using the model.