CENTRALIZE URBAN TRAFFIC MONITORING SYSTEMS AND ITS BIG DATA HANDLING

Abstract

With rapid growth of urban population and increasing number of vehicles on roads Traffic Controlling becomes an important problem to resolve. Solution for this not only saves lot of time but also increases economic growth in terms of fast logistics deliveries, business facilities and decreases energy consumption. Traffic monitoring can be made intelligent by use of computer vision techniques to detect vehicles type, colour, number plate, traffic rule violations, events detection and counting of vehicles automatically. Broader aerial view of cities traffic from Satellites or any other source can perform important task in finding congestion and decision taking. Autonomous driving is a future of transportation, so V2V communication and understanding of its protocol should be a part of urban traffic monitoring. In this paper we have proposed an integrated system of all these systems with one central controlling point with parallel processing facility. We used Apache Spark as big data processing software to analyse big data generated from multiple sources. In the end some useful quires to access important information from stored data are provided and the execution time proves fast access of data by using proposed system.