Real time smart parking system based on IoT and fog computing evaluated through a practical case study.

The increasing urban population and the growing preference for private transportation have led to a significant rise in vehicle numbers, exacerbating traffic congestion and parking challenges. Cruising for parking not only consumes time and fuel but also contributes to environmental and energy inefficiencies. Smart parking systems have emerged as essential solutions to these issues, addressing everyday urban challenges and enabling the development of smart, sustainable cities. By reducing traffic congestion and streamlining parking processes, these systems promote eco-friendly and efficient urban transportation. This paper introduces a provenance-based smart parking system leveraging fog computing to enhance real-time parking space management and resource allocation. The proposed system employs a hierarchical fog architecture, with four layers architecture nodes for efficient data storage, transfer, and resource utilisation. The provenance component empowers users with real-time insights into parking availability, facilitating informed decision-making. Simulations conducted using the iFogSim2 toolkit evaluated the system across key metrics, including end-to-end latency, execution cost, execution time, network usage, and energy consumption in both fog and cloud-based environments. A comparative analysis demonstrates that the fog-based approach significantly outperforms its cloud-based counterpart in terms of efficiency and responsiveness. Additionally, the system minimises network usage and optimises space utilisation, reducing the need for parking area expansion. A real-world case study from SDU University Park validated the proposed system, showcasing its effectiveness in managing parking spaces, particularly during peak hours.