An IoT Architecture for Real-time Traffic Management System with Cloud and Edge Computing

The real-time traffic management systems are the methodology for managing the traffic by using the data from the detectors and computers for optimizing the traffic signal parameters in real-time. They are proven as an effective way to reduce the delay and congestion of the traffic, especially in urban areas. The widely adopted real-time traffic management systems (e.g., SCATS, SCOOTS) were developed many decades ago with the last decade's local network architecture and the centralized client-server model. They are complex and expensive because of the physical infrastructure. They need the physical control center and the reliable physical network infrastructure because they are designed with the latest technologies of the last decade. Today's cloud computing technologies and the internet of things can make the system more simple and less physical infrastructure by connecting all the devices virtually via the cellular network to process in the cloud. The Edge computer installed inside or near the traffic controller can primarily optimize the traffic at the intersection instead of sending all the data to be processed at the control center. This paper presents the novel architecture for the real-time traffic management system based on current technologies of cloud computing, edge computing, and the internet of things that makes the system less complicated, cheaper, and can be widely adopted.