The rapid urbanization and the growing quantity of automobiles on the road have created a pressing need for efficient parking management systems. This paper represents a novel approach to address this challenge by integrating fog nodes, cloud computing, and a sophisticated scheduling algorithm. The proposed system optimizes parking allotment in real time, making both parties overall parking experiences better for both the drivers and administrators. Fog nodes are strategically deployed within parking areas to collect and process data from various sensors, such as occupancy sensors, cameras, and vehicle entry/exit points. These fog nodes alleviate the data processing burden on the cloud and enable rapid decision-making at the edge. Data from the nodes in the fog are seamlessly transmitted over to the cloud to further analysis and to long-term storage. To allocate parking spaces efficiently, a scheduling algorithm is implemented, which takes into account various factors such as real-time occupancy data, user preferences, and historical parking patterns. The algorithm optimizes parking allotment by considering the shortest walking distance for drivers, reducing congestion within parking facilities, and ensuring fair and equitable space distribution. The synergy of fog nodes, cloud computing, and the scheduling algorithm provides several benefits, including reduced parking search times, lower operational costs, and a more sustainable and eco-friendly approach to urban mobility. The system offers real-time updates to drivers through mobile applications and information displays at parking and information displays at parking entrances. This research represents a significant step toward realizing a smart parking ecosystem that enhances urban mobility reduces traffic congestion, and improves the quality of life in modern cities.