Published Paper Details:

As the urban fleet of vehicles is growing rapidly, parking management by intelligent and automated means has become more important. This paper proposes a real-time smart parking system utilizing computer vision and deep learning methods for vehicle detection, dynamic assignment of slots, and automatic billing. The suggested system uses the YOLOv8 object detection model to detect license plates from images with high accuracy followed by Optical Character Recognition (OCR) with added image pre-processing and luminosity normalization to ensure enhanced accuracy in extracting text. After identifying a license plate, the system auto-assigns available parking slots, captures entry and exit times, and computes charges for the stay duration. All parking transactions, including encoded plate images and timestamps, are recorded in an Excel-based database. The suggested framework presents a scalable, cost-efficient, and low-cost solution to urban traffic and parking management issues.