Traffic Management Scheduling using Image/Video Processing for Smart Cities

Nowadays, traffic has been the major problem in many urban regions as the number of vehicles has been increasing rapidly. So, the traffic management at the traffic signals has become a complex issue as using the conventional system does not detect the traffic and it will not check the traffic density at the signals. Even there are no vehicles; the signal will be green for that empty road. Traffic issues in urban areas are road networks, free networks. To address this problem, image and video processing is a method to perform some operations on an image, to enhance or extract. It is a rapidly growing technology and it is a part of an AI. The traffic can be managed by a suitable solution based on the instantaneous images and videos captured by the cameras at the crossroads, traffic signals, etc. The tools used for this system are Raspberry Pi board and OpenCV tool for image and video processing. So many technologies used in this traffic Management control system Consists to control traffic Density, traffic clearance, Computation of Overlapping Images, Alert systems and self-learning systems. The paper concludes with a brief discussion of future needs in these important technologies.