Smart Parking Safety and Surveillance System Using Computer Vision

This chapter presents a comprehensive framework for designing a Smart Parking Safety and Surveillance System leveraging computer vision technologies to enhance urban security. The objective is to automate and improve the monitoring of vehicles and pedestrians in parking environments using in-vehicle and multi-view camera systems. The approach employs OpenCV-based modules for pedestrian detection, lane and sign recognition, foreground–background extraction, and multi-camera tracking, integrated through a modular architecture. Sample lab exercises and system simulation demonstrate practical applicability. The findings indicate the system's potential to significantly reduce human error, improve vehicle tracking accuracy, and strengthen surveillance coverage in smart cities. The chapter concludes that such vision-enabled systems are integral to modern urban infrastructure, especially when aligned with emerging technologies like IoT and blockchain. The proposed model serves as a scalable foundation for future smart surveillance initiatives.