A Unified Fog Computing Architecture for Next-Generation Smart City Traffic and Crime Management

The rapid growth of urbanization has led to a surge in demand for smart city systems that can efficiently manage resources and ensure safety. This paper delves into the design and simulation of a Smart City System that leverages Fog Computing. Fog Computing involves distributing computation and storage resources across devices located at the network edge. The system integrates a diverse range of sensors, including surveillance cameras, VPR (Vehicle Plate Recognition) cameras, and audio sensors, strategically deployed across different city areas. These sensors monitor traffic, detect anomalies, and promptly provide real-time alerts. The Fog architecture enhances system responsiveness by processing data closer to its source, thereby reducing latency and bandwidth consumption. To model and simulate the interaction between various Fog devices, cloud resources, and edge-based applications, we employ CloudSim, a cloud simulation tool. By meticulously mapping different application modules to devices based on their capabilities, we simulate the execution of smart city applications, such as video capture, traffic detection, and audio alarm triggering. The results show the possibility of employing Fog Computing for building an efficient, scalable, and responsive system for a smart city. Fog computing has the potential to significantly impact large urban areas by processing data at the edge, thereby reducing latency and bandwidth consumption.