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All Journal Journal of Systems Engineering and Information Technology
Rico Aditya Utama
Gunadarma University
Computer Science & IT

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Implementation Counting and Yolo Object Detection Methods for Identification Degree of Road Saturation Rico Aditya Utama
Journal of Systems Engineering and Information Technology (JOSEIT) Vol 1 No 1 (2022): March 2022
Publisher : Ikatan Ahli Informatika Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (637.479 KB) | DOI: 10.29207/joseit.v1i1.1965

Abstract

Identification of road conditions such as congestion at this time still requires manual efforts in getting results. The congestion parameters certainly need to be monitored, especially in crowded areas and big city business centers, such as on Jalan Jendral Sudirman, Central Jakarta. Many parameters to identify the level of road congestion, one of them is by observing the value of the degree of road saturation. The purpose of this study is to propose a system that can calculate the value of the degree of saturation quickly and accurately using a camera. The method that is being proposed is to combine the Computer Vision with YOLO Object Detector techniques based on Deep Learning and the Object Counting method to get the value of traffic flow in the observed area. The results obtained by this system are quite good, this is supported by the error value obtained by the system around 3-4%.
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