Analysis based traffic flow control decision using IoT sensors

Abstract The traffic flow control decision plays a crucial role in many of the main aspects of a future smart city. It is highly configurable and costly for a higher standard of service. This paper proposes an analysis-based traffic flow control decision model (ATFCD) for smarter, better, and efficient regulation of transport services. In this paper, the proposed model explores the extensive use of a well-known paradigm, the Internet of Things (IoT). In this model, the sensors will be used to identify and count cars, riders, on-road pedestrians, trams, subways, and ferries. The proposed model will be applicable in real-time monitoring of the traffic flow, and the data collected from the sensors will be processed further and decision making will be done based on the collected data analysis. The proposed model is focusing to reduce the traffic congestion on highways and busy roads.