A Smart, Efficient, and Reliable Parking Surveillance System with Edge Artificial Intelligence on IoT Devices

TL;DR

This paper presents a novel edge computing-based smart parking surveillance system that leverages AI for real-time detection, achieving over 95% accuracy with high efficiency and reliability in real-world tests.

Contribution

It introduces an edge AI system with an enhanced SSD detector for smart parking, optimizing accuracy and efficiency in urban surveillance.

Findings

Over 95% detection accuracy in real-world parking scenarios

High system efficiency and reliability demonstrated in field tests

Effective edge-based AI processing for smart city applications

Abstract

Cloud computing has been a main-stream computing service for years. Recently, with the rapid development in urbanization, massive video surveillance data are produced at an unprecedented speed. A traditional solution to deal with the big data would require a large amount of computing and storage resources. With the advances in Internet of things (IoT), artificial intelligence, and communication technologies, edge computing offers a new solution to the problem by processing the data partially or wholly on the edge of a surveillance system. In this study, we investigate the feasibility of using edge computing for smart parking surveillance tasks, which is a key component of Smart City. The system processing pipeline is carefully designed with the consideration of flexibility, online surveillance, data transmission, detection accuracy, and system reliability. It enables artificial intelligence at the edge by implementing an enhanced single shot multibox detector (SSD). A few more algorithms are developed on both the edge and the server targeting optimal system efficiency and accuracy. Thorough field tests were conducted in the Angle Lake parking garage for three months. The experimental results are promising that the final detection method achieves over 95% accuracy in real-world scenarios with high efficiency and reliability. The proposed smart parking surveillance system can be a solid foundation for future applications of intelligent transportation systems.