A System for Real-time On-street Parking Detection and Visualization on an Edge Device

In recent years, street parking in prohibited areas has become a serious social problem, particularly in metropolitan and tourist areas where there are many on-street parked cars. In addition, because on-street parking can cause traffic congestion and accidents, real-time detection is considered necessary. In previous studies, fixed-point cameras have been mainly used for traffic control; however, a major disadvantage of these systems is their limited detection area. In this study, we developed a system that can detect and visualize on-street parking in real-time using video data captured by dashboard cameras, which have become widely used in recent years. We created a learned model to detect on-street parking and to recognize cars using an edge device. By displaying the location information of on-street parked cars on a map, their location can be visualized. This system could be used to obtain statistical data for crackdowns on on-street parking and to identify areas where on-street parking occurs.