Proposing Real-time Parking System for Smart Cities using Two Cameras

Abstract

Today, cars are becoming a popular means of life. This rapid development has resulted in an increasing demand for private parking. Therefore, finding a parking space in urban areas is extremely difficult for drivers. Another serious problem is that parking on the roadway has serious consequences like traffic congestion. As a result, various solutions are proposed to solve basic functions such as detecting a space or determining the position of the parking to orient the driver. In this paper, we propose a system that not only detects the space but also identifies the vehicle's identity based on their respective license plate. Our proposal system includes two cameras with two independent functions, Skyeye and LPR cameras, respectively. Skyeye module has function to detect and track vehicles while automatic license plate recognition system (ALPR) module detects and identifies license plates. Therefore, the system not only helps drivers to find suitable parking space but also manages and controls vehicles effectively for street parking. Besides, it is possible to detect offending vehicles parking on the roadway based on its identity. We also collect a set of data that correctly distributes for the context in order to increase the system's performance. The accuracy of proposal system is 99.48% that shows the feasibility of applying into real environments.