IoT Enabled Infrastructure for Peri-Urban Communities

Parking occupancy detection is a critical component of modern smart city infrastructure, aimed at optimizing parking space utilization and reducing traffic congestion. This project proposes a computer vision-based solution using OpenCV to detect and monitor parking space occupancy in real-time. The system utilizes image processing techniques to analyze video feeds from surveillance cameras installed in parking lots. By employing background subtraction, contour detection, and object classification algorithms, the system identifies occupied and vacant parking spaces with high accuracy. The proposed solution is cost-effective, scalable, and capable of integrating with existing parking management systems. The results demonstrate the system's ability to provide real-time occupancy data, enabling efficient parking management and enhancing user experience. This project highlights the potential of computer vision technologies in addressing urban parking challenges and contributing to the development of smart cities. Keywords - Parking Occupancy Detection, OpenCV, Computer Vision, Image Processing, Smart Parking, Real-Time Monitoring.