SmartSpectorAI: Roadside Parking Warning System for Congestion Prevention in Yogyakarta City

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Abstract
Traffic congestion has been a major problem in big cities, including Yogyakarta, with negative impacts including time, economic, and psychological losses. Based on data from the Yogyakarta Special Region Transportation Agency and Yogyakarta City Transportation Agency, analysis of congestion level data, and field observations, it was found that one of the main causes of congestion on the most congested roads in Yogyakarta City is vehicles parked on the side of the road. The proposed solution involves roadside parking detection and warning using surveillance cameras integrated with Artificial Intelligence (AI). The proposed system involves vehicle detection with pre-trained deep learning models, parking detection algorithms with Intersection over Union (IoU) tracking, and alerts that are forwarded to motorists as well as authorities such as the Transportation Department and local traffic police. The Yogyakarta CCTV dataset is used to test parking detection using various models, such as YOLOv5-medium, YOLOv5-large, YOLOv7-tiny, and Haar Cascade. The model evaluation shows that YOLOv5-large provides the highest accuracy of 86.1% with a processing speed of 5.5 Frames Per Second (FPS) to perform parking detection. With this proposed system, this research can contribute to solving congestion problems and improving traffic conditions in Yogyakarta City.

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