Smart Vehicle Parking System on Fog Computing for Effective Resource Management

The rapid advance in the number of vehicles on the road led to a corresponding growth in demand for parking spaces. However, conventional car parking systems are inefficient and time-consuming. Smart Parking systems also require immediate response, and low latency, which may be impacted by data transfer delays to and from the cloud. Cloud computing can provide infrastructure-level services. Also, the smart parking system is a sensitive application that can lead to disaster if an immediate decision has not been taken. To address these challenges, this research proposes the smart car parking system using fog computing that reduces latency. The suggested smart vehicle parking system uses a combination of sensors, cameras, and edge devices to collect and process parking-related data. This connection generates an enormous bundle of data that is required to be saved and processed. Fog computing widens cloud services to the end of the network to cut down latency and congestion. The major challenge in implementing Fog computing is managing the resources, which involves applications to determine each edge gadget effectively, which reduces latency and increases throughput. The proposed simulation that portrays IoT and Fog nodes and evaluates the consequences of resource management approaches in terms of QoS parameters. The proposed hybrid markov system have been utilized in various parking scenarios, including shopping centres airports, and residential areas. The paper contributes to the development of a smart vehicle parking system by proposing a computing-based approach using fog that optimizes resource utilization and provides real-time processing for parking management.