IoT-Based Smart Traffic Monitoring and Control System for Urban Areas

The rapidly growing density of motor vehicles in the cities makes it compulsory to develop new strategies for traffic management and control. This paper presents an IoT-based traffic management system to improve the traffic flow in urban areas by utilizing the real-time modules of sensing, control and decision making. The system integrates ultrasonic sensors, Arduino UNO, GSM, Raspberry Pi, camera, traffic lights and computer vision techniques to achieve the key functionalities of calculating the traffic density, optimizing the timing of traffic lights, identification of traffic violations and recognizing the emergency vehicles. The traffic volume data has been captured across the lanes and then processed to implement the optimized duration of traffic lights to avoid the unnecessary delays. The cameras and Raspberry Pi controller detect the traffic violations by using computer vision algorithms to enforce the traffic rules. The GSM module receives the messages from emergency vehicles for priority passage and sends the information to congestion control center. The device has been fabricated, tested for expected results and found to be working fine. The experimental results illustrate optimized traffic control, identification of emergency vehicles with negligible false positives and the prediction accuracy of 93% for traffic congestions on the roads. The designed system can be used for efficient traffic management in urban areas.