Abstract—The number of lives and possessions lost because of ineffective and dangerous traffic management has risen significantly in recent years. Innovative solutions are required for effective transportation management due to the accelerated urbanisation and rising demands on the transportation infrastructure. We propose a Fog-Based Smart Transportation System (FSTS) that utilizes fog computing to enhance traffic management, environmental monitoring, and road safety. In contrast to traditional centralized cloud solutions, the FSTS combines fog nodes, proxy servers, and cloud servers to facilitate low-latency, energy-efficient, and dynamic execution of data. The proposed framework was validated by iFogSim2, simulating up to 60 fog nodes together with various smart cameras and sensors. A comparison is conducted by utilizing two parameters, namely latency and energy consumption. The results indicated that the FSTS decreases latency by as much as 82% and energy consumption by approximately 75% in comparison to leading methodologies like Scalable Microservices Placement (SMP) and Reliable Resource Allocation and Management (R2AM). These enhancements underscore the system’s capacity to reduce congestion, facilitate real-time accident identification, and optimize energy use. The suggested architecture prioritizes data security and privacy through the integration of encryption and safe communication between fog nodes and the cloud. Therefore, experimental results validate that the proposed FSTS approach outperforms alternatives by reducing latency, energy consumption, and optimized traffic efficiency.
 
Keywords—fog commuting, smart transportation system, iFogSim, smart city, cloud computing, Internet of Things (IoT)


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