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All Journal IAES International Journal of Artificial Intelligence (IJ-AI)
Dimas Dwi Budiarjo
Universitas Semarang
Computer Science & IT Engineering

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The implementation of intelligent systems in automating vehicle detection on the road Susanto Susanto; Dimas Dwi Budiarjo; Aria Hendrawan; Prind Triajeng Pungkasanti
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 3: September 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i3.pp571-575

Abstract

Indonesia is a country with a high population, especially in big cities. The road always crowded with various types of vehicles. Sometimes the growth of vehicles is not matched by road construction. During peak hours, too many vehicles can cause traffic jams on the road. The road is needed to be widened to accommodate the number of vehicles that pass each day. In order for road widening to be precise at locations that frequently occur in traffic jams, data on the number and classification of vehicles passing is required. Therefore, a system that can calculate and recognize the type of vehicle that passes is needed. The development of various studies on artificial intelligence especially about object detection can classify and calculate the type of vehicle. In this study, the authors used the you only look once (YOLO) object detection system using a convolution neural network (CNN) method to classify and count vehicles that pass automatically. The author uses a dataset of 600 images with 4 classes which are car, truck, bus, and motorbikes that pass through the road. The results showed that the YOLO object detection system can recognize objects consistently with accuracy more than 80% on CCTV video that installed on the road.
Co-Authors Aria Hendrawan, Aria Prind Triajeng Pungkasanti, Prind Triajeng Susanto Susanto