A User Monitoring Road Traffic Information Collection Using SUMO and Scheme for Road Surveillance with Deep Mind Analytics and Human Behavior Tracking

Road congestion and huge traffic on roads has become a big problem in many urban areas. Investment on planning and processing of traffic information should help to minimize congestion and pollution. So here we propose a way to design our own road networks as required to reduce traffic using a tool called Sumo. Inorder to find the efficiency of that network, a WSN based framework is designed for the same and various routing schemes are applied on it. A fuzzy logic-based traffic light control system and QOS parameters handling system is designed by extracting data available by routing schemes applied. Inorder to make the roads safer artificial intelligence-based security cameras hoping to achieve automated recognition of people and events is planned. Digital brains map the eyes to analyze live video and helping responders to more easily find crimes and accidents on roads. Machine learning is employed to get considerable gains in its ability to identify objects, the skill of analyzing scenes, activities, and movements. Simulations have shown good performance for the proposed routing schemes and fuzzy controller designed shows good results to the urban traffic network.