IoT-based parking surveillance scheme: Emerging a smart, effective, and secured solution for urban parking management and performance improvement

Abstract

Parking spots have become a prevalent concern in urban growth. The number of automobiles is increasing faster than accessible parking spaces. This problem is addressed by implementing an Internet of Things (IoT)-based Parking Surveillance Scheme (IoT-PSS) for the smart campus. The system aims to efficiently match vehicles with available parking spaces, resulting in time savings, improved parking space usage, reduced management expenses, and decreased traffic congestion. Edge computing provides a new answer to data processing in monitoring systems by using advancements in IoT, artificial intelligence, and transmission technologies to analyze data regionally at the edge. This research explores the viability of using edge computing for smart parking monitoring, focusing on detecting parking occupancy via a real-time video stream. The structure operating pipeline to prioritize adaptability, online surveillance, data transfer, detection precision, and system dependability. The experimental findings show that the final detection approach achieves more than 95% accuracy in real-world situations with outstanding effectiveness and reliability. The IoT-PSS system is essential for smart cities and is a strong basis for future use in smart transportation networks.