The fast development of road infrastructure, the volume of vehicle on the road network increases which leads to traffic Congestion. The same scenario exists in the Bangalore of India. Traffic congestions are amongst the top list of the problems faced in other Indian cities such as Mumbai,Delhi,Pune etc. This is mainly caused due to the rapid up rise in the number of vehicles in a short span of time. To overcome such impact of traffic congestions, it is required to develop an IoT and Vehicle detection-based algorithm traffic control system. The proposed system would be based on the measurement of the actual traffic density on the road. This would be achieved using a real time video and image processing techniques with machine learning algorithms. Propose a fast vehicle flow detection algorithm based on a learnt background dictionary. The proposed detection algorithm detects vehicles by background dictionary and has a robust and best performance in real-time. Combining the virtual region and the virtual detection line, the proposed detection algorithm is robust in accuracy.The theme is to control the traffic by determining the traffic density on each side of the road and enabling a controlling option of the traffic signal to the user through a software application and Raspberry Pi3

IOT(Internet Of Things), Image processing, machine Learning, sensors, web application server

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