Smart Parking Navigator": An IoT Fog-Based System for Realtime Car Parking Detection

Emma Qumsiyeh
Isam Ishaq
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Obtaining a parking spot is a significant obstacle for many citizens. With the massive increase in the number of vehicles in crowded cities, finding an unoccupied parking slot may consume time and effort and result in more traffic jams. Travelers often utilize conventional methods to locate a parking space near their destination. They navigate the entire area to locate the nearest open space. The mission is indeed aggravating and difficult. Due to these issues, "Smart Parking Navigator," an IoT fog-based smart parking system, is developed to facilitate searching available roadside parking spaces. The system monitors a predetermined parking space and provides users with real-time data about the occupancy of slots. The system employs image processing techniques, object detection algorithms, and OpenCV to determine whether a parking space is occupied or vacant. A Raspberry Pi camera connected to a Raspberry Pi 4 computer is used for real-time detection. Each parking space's status is stored in a Firebase Realtime Database. A mobile application for Android has been developed to assist clients in locating available parking. The application is connected to the database to retrieve the real-time status of each position. Once the user launches the application, the interface will visualize the condition of each parking slot. The solution is a cost-effective alternative to specialized and costly systems that has the potential for future commercial development.