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In the new evolving world, traffic rule violations have become a central issue for majority of the developing countries. The number of vehicles is increasing rapidly as well as the number of traffic rule violations are increasing exponentially. Managing traffic rule violations has always been a tedious and compromising task. Even though the process of traffic management has become automated, it’s a very challenging problem, due to the diversity of plate formats, different scales, rotations and non-uniform illumination conditions during image acquisition. The increased vehicular traffic has also increased the traffic and the road accidents to take place frequently which causes loss of life and property because of the poor emergency facilities. Due to huge traffic, emergency vehicles like ambulances are not able to reach their destinations in time, resulting into loss of human lives. This project will provide an optimum solution to this draw back. If any other vehicles are blocking ambulance, the vehicle is first identified for its type, using yolo v4 algorithm whether it is a car or a truck or any other vehicle. Then the number plate of the blocking vehicle is detected using OCR algorithm. After recognizing the vehicle’s number from number plate, it is then saved so that the driver could be given penalty.