Article Details

Abstract

To address the limitations of single/dual-sensor urban roadside parking monitoring systems (insufficient detection accuracy, poor scene adaptability, and high operational costs), this study proposes an intelligent monitoring system based on “triple-mode collaboration + hierarchical verification”. The system consists of three core components including a triple-mode fusion terminal, an edge computing unit, and a cloud platform. The array camera covers 4 to 8 parking spaces and identifies vehicle characteristics, the millimeter-wave radar performs high-precision detection of vehicle status, and the environmental sensors acquire environmental parameters. These three components work collaboratively to provide the basis for the device's adaptive regulation. With data verification and local screening, edge computing reduces data transmission by 60%. The cloud platform handles vehicle information storage, early warning, and operation & maintenance. Field tests in typical urban scenarios validate the system's performance. Results show that the system significantly improves operational stability and recognition accuracy while cutting maintenance costs, achieving “contactless parking” and refined management.

Keywords

vehicle information monitoring; multi-sensor fusion; roadside parking system; parking management

References

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Funding

Youth Science Research Fund Project for Higher Education Institutions in Hebei Province in 2025 (QN2025296)

About the authors

Liu Yanyang (1989-), female, Han nationality, from Changchun, Jilin, engineer, master's student, research direction: artificial intelligence and big data technology; Zhang Jiamin (1982-), female, Manchu, from Tangshan, Hebei, lecturer, doctoral student, research direction: artificial intelligence and Internet of Things technology; Zheng Xu (1993-), female, Hui ethnic, from Zhangjiakou, Hebei, engineer, master's student, research direction: intelligent transportation parking management technology; Cui Jiayi (2004-), female, Han ethnicity, from Dingzhou, Hebei Province, undergraduate studies, research direction: Internet of Things technology.