Traffic density estimation and mapping using IP-CCTV networks: A campus-based approach

Authors

• Roy Francis Navea, De La Salle University, Manila
• John Carl Bautista, De La Salle University, Manila
• Adrian Giuseppe Francis Fernan, De La Salle University, Manila
• Zendrel Gacuya, De La Salle University, Manila
• Adreenawatie Saidatul, University Malaysia Perlis

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Conference Proceeding

Source Title

AIP Conference Proceedings

Volume

2562

Issue

1

First Page

060006

Publication Date

2023

Abstract

Closed Circuit Television (CCTV) systems are widely used in monitoring and security surveillance applications to assess status and implement measures necessary to address problems and concerns. CCTV nowadays are visible in roads for monitoring and analyzing traffic behavior and conditions. Multiple cameras are utilized to capture the different angles of the road. This is useful in improving traffic management systems, determination of road traffic density, accident reviews, and in some advanced applications, contactless apprehension. Small to medium scale community areas like industrial parks, villages, hospitals, and even academic campuses require traffic monitoring systems. In this study, a network of IP-CCTV cameras was designed to capture vehicular movement, density, and road condition in a campus setting. The network is composed of eight IP-CCTV cameras processed by four Raspberry Pi computer boards in a 2:1 camera-to-computer ratio. A graphical user interface displays the video feed of the cameras, time customizable traffic report, and the road map visualization and notifications. All computer boards can send and receive data and can create visual traffic maps displayed in the user interface. Color-coding is used in the road segments to indicate light, moderate, or heavy traffic conditions. The vehicle detection accuracy of the system is 93% while its status notification accuracy is 84%. In a campus-based application, especially those with medical and health research institutes, this model suffices its requirements in monitoring, analyzing, basis for emergency rerouting, and improvements in traffic management.

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Recommended Citation

Navea, R., Bautista, J., Fernan, A., Gacuya, Z., & Saidatul, A. (2023). Traffic density estimation and mapping using IP-CCTV networks: A campus-based approach. AIP Conference Proceedings, 2562 (1), 060006. Retrieved from https://animorepository.dlsu.edu.ph/faculty_research/15401

Disciplines

Electrical and Computer Engineering

Keywords

Traffic monitoring—Equipment and supplies; Closed-circuit television

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