The Role of Internet of Things on Intelligent Transport System: A Traffic Optimization Model

The road traffic congestion has become an excessive problem and a great pressure on both the governmental and social aspects especially in megacities. Hence, developing control systems that administrate the traffic flows is a vigorous solution, which can solve the problem of traffic congestion especially in megacities that should convert their services to be smart. The Intelligent Transport System (ITS) one of the Internet of Things (IoT) applications that provides a group of pioneer schemes for handling the challenges of traffic congestion. Traditionally, sensor-based structures have been used for gathering traffic information, but the coverage, cost, and real-time matters have remained unexplained. Thus, this paper aims at proposing a new model named Traffic Flow Optimization Model (TFOM) applied in Alexandria as a case study, which is considered a cost-effective and easily maintainable traffic congestion minimization method. It combines Infra-Red (IR) and active Radio Frequency Identification (RFID) technologies. TFOM is designed to minimize traffic congestion, given reroute options to the users, taken decisions regarding congestion, and finally it could be an initial step to help future predictions in linear megacities.