Fundamental Analysis of Parking Occupancy Monitoring Systems: An Empirical Comparison of Ultrasonic Sensor and Computer Vision Methods: Fundamental Analysis of Parking Occupancy Monitoring Systems:

Abstract

Abstract— Urban parking inefficiencies contribute to approximately 30% of traffic congestion in major cities. This study compares two leading parking occupancy detection technologies ultrasonic sensors and computer vision under varying environmental conditions. Ultrasonic sensors use sound wave reflection to detect vehicle presence, while computer vision employs deep learning on video data to classify parking space occupancy. Evaluations were conducted in both simulated and real-world environments, considering factors such as lighting, weather, and vehicle density. Findings suggest that ultrasonic sensors offer consistency in enclosed areas, whereas computer vision performs better in open but visually dynamic environments. Additionally, a cost-benefit analysis reveals context-dependent advantages, with hybrid configurations offering the most reliable outcomes.