Application of an Integrated Fog-IoT Framework to a Smart Traffic Surveillance Management System

Abstract

In addressing urban traffic management, a prevalent approach involves the installation of surveillance cameras along roadways. However, this approach raises two critical concerns. The primary issue lies in the potential for negligence caused by extended periods of manual monitoring. Hence, the prevailing trend in traffic management has shifted towards the adoption of intelligent traffic surveillance management systems. The second challenge pertains to the need for swift responses to traffic conditions, necessitating real-time and efficient management strategies. In this research paper, we present an integrated Fog-IoT framework for a Smart Traffic Surveillance Management System (STSMS). This framework leverages IoT devices and fog nodes for task processing, significantly enhancing overall system performance. The STSMS utilizes surveillance cameras to collect extensive traffic data. Subsequently, the collected data is rigorously analyzed to accurately assess congestion levels in adjacent areas. The system autonomously generates commands to control traffic signals, effectively coordinating neighboring signals, thereby achieving efficient and intelligent traffic management. Furthermore, the STSMS promptly communicates its findings to administrators, enabling proactive responses. For instance, it can dispatch notifications to nearby police stations, facilitating the allocation of personnel to alleviate traffic congestion. Clearly, the STSMS plays a pivotal role in the development of smart cities, not only by facilitating intelligent traffic management but also by optimizing resource utilization, including reductions in latency and network usage. To assess the effectiveness of the STSMS comprehensively, simulations were conducted using the iFogSim tool. The experimental results demonstrate unequivocally that the Fog-IoT-based STSMS significantly reduces latency and network usage compared to cloud-based frameworks. These findings underscore the transformative potential of the STSMS in revolutionizing urban traffic management, thereby advancing the vision of efficient and intelligent smart cities.