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All Journal Journal of Information Systems and Informatics
Rizki Juliansyah
IPB University
Computer Science & IT

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Development of a Real-Time Traffic Density Detection Website Using YOLOv8-Based Digital Image Processing with OpenCV Rizki Juliansyah; Muhammad Aqil Musthafa Ar Rachman; Muhammad Al Amin; Aisya Tyanafisya; Nurrizkyta Aulia Hanifah; Endang Purnama Giri; Gema Parasti Mindara
Journal of Information System and Informatics Vol 6 No 4 (2024): December
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51519/journalisi.v6i4.912

Abstract

This study introduces a real-time traffic density monitoring system utilizing YOLOv8-based digital image processing to improve traffic management efficiency. By leveraging YOLOv8’s enhanced speed and precision, the system detects and classifies five types of vehicles and displays traffic data through a web interface developed with OpenCV and Flask. Key implementation features include real-time video streaming and accurate detection metrics, with the system achieving 96% Precision, 84% Recall, and an F1 Score of 90% during field testing in Bogor. This indicates the system’s potential for minimizing manual traffic monitoring and aiding traffic authorities in making data-driven decisions. The research also discusses the system’s integration into urban traffic management and its scalability for diverse environments.
Co-Authors Aisya Tyanafisya Endang Purnama Giri Gema Parasti Mindara Muhammad Al Amin Muhammad Aqil Musthafa Ar Rachman Nurrizkyta Aulia Hanifah