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Nowadays, as the digital era proliferates, there are a number of traffic violation detection systems built using hardware and software to detect violation of traffic rules. This article proposes an integrated method for traffic analysis by detecting vehicles in the video and tracking their motion for multiple violation detection. The purpose of this integrated system is to provide a method to identify different types of traffic violations and to reduce the number of systems used to record violations. This method receives input from traffic surveillance camera and uses DNN to classify the vehicles to reduce the number of personnel needed to do this manually. The authors have implemented modules which are used to track vehicles and detect violations such as line crossing, lane changing, signal jumping, over-speeding and find illegally parked vehicles. The main purpose of this project is to convert manual traffic analysis into a smart traffic management system.