Vehicle Parking Area Monitoring and Management System using Computer Vision

Abner Cruz; Iel Arvill Villaruel; Daisuke Jilroi Hamo; John Bernie Ruiz; Kian Jade Suarez

doi:10.35974/isc.v11i5.3570

Authors

Abner Cruz Adventist University of the Philippines
Iel Arvill Villaruel
Daisuke Jilroi Hamo
John Bernie Ruiz
Kian Jade Suarez

https://doi.org/10.35974/isc.v11i5.3570

Keywords:

vehicle parking, computer vision, OpenCV, yolov8

Abstract

The increasing number of vehicles plying thoroughfares requires consequently expanding parking areas in major destinations. In a school setting, where classrooms and academic facilities are an utmost concern, the provision and management of parking areas take a back seat. This study attempts to develop a vehicle parking monitoring and management system to provide convenience and accessibility to stakeholders of a target university in the Philippines. It seeks to optimize the utilization of parking spaces by providing information to vehicle owners on available parking slots, deliver data insights to the school administration for better management and planning, and contribute to the reduction of carbon emissions from cars roaming around looking for an available parking slot. A video camera or a recorded video clip of the parking area can be used as input into the Python programming language paired with OpenCV, a library of computer vision functions. After which, vehicle detection and tracking is performed using YOLOv8. The dedicated web application for management and monitoring is developed using HTML, CSS, and JavaScript complemented by Node.js, Bootstrap, and MongoDB. The study followed the Agile software development lifecycle methodology. The developed system proved to be successful in determining whether specific parking slots are occupied or not, therefore can guide users where to park their vehicles. Illegally parked cars can also be detected by the system. Furthermore, hourly, weekly, and monthly parking data can be generated for better parking management and planning.

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