Enhancing Urban Mobility with Iot: A Versatile Parking Solution Integrating Real-Time Surveillance and Machine Learning

This paper proposes and implements a versatile IoTenabled parking solution that provides real-time statistics on available parking spaces and includes a surveillance system to detect unusual vehicle behavior using a license plate recognition solution. Efficient algorithms are introduced to develop a parking perception system, utilizing advanced machine learning models such as YOLO-v5 and Convolutional Neural Networks (CNNs) for object detection and classification, providing precise parking lot statistics. Furthermore, the study presents an innovative approach to accurately identify vehicle number plates to monitor unusual behavior. A custom dataset was developed, and the proposed solutions were evaluated using various metrics.