A YOLOv10-based Intelligent Parking Management System with Automated License Plate Detection and Spot Reservation

This paper submits the design and deployment of an Automated Car Lot Booking System, code-named Spaces, specifically to mitigate congestion and inefficiency in urban car parking. ANPR, computer vision, and machine learning were employed for identification of vehicles in real-time. Using OpenCV [11] and YOLOv10 for license plate recognition, and EasyOCR for extracting characters, the system attains 97% accuracy in daylight, although limitations are seen in low-lighting conditions. The system has an easy-to-use interface for slot booking, tracking of availability in real time, and payment gateway incorporation. MongoDB is employed to store and retrieve data efficiently to enable scalability and performance. Experimental results indicate enhanced parking efficiency, shortened waiting times, and higher levels of user satisfaction. This strategy helps in developing smart urban infrastructure, complementing initiatives to make parking management optimal in cities.