EDGE COMPUTING FOR REAL-TIME TRAFFIC MANAGEMENT IN INTELLIGENT TRANSPORTATION SYSTEMS

Abstract

Edge computing has emerged as a transformative technology in the realm of Intelligent Transportation Systems (ITS), particularly for real-time traffic management. The integration of edge computing allows data processing and analytics closer to the source of data generation, significantly reducing latency and bandwidth usage. This paper explores the role of edge computing in enhancing the efficiency and responsiveness of ITS for urban traffic management. It examines how edge devices, sensors, and cloud services work in concert to optimize traffic flow, reduce congestion, and improve safety. The paper also discusses the challenges and opportunities posed by the adoption of edge computing in ITS, including issues related to data security, system scalability, and the need for robust network infrastructure.