Motor vehicles are changing the way people live, but they are also putting a huge strain on urban traffic. In the majority of major cities, parking has become the number one problem for car owners to get around. The management efficiency of car parks directly affects the traffic of the whole city. In order to improve the management efficiency of the car park, this paper designs an intelligent parking management system based on ARM and ZigBee wireless sensor network. Firstly, according to the internal environment and economic cost of the car park, ultrasonic sensors are used to monitor whether the parking space is empty or not. The information collected by the ultrasonic sensors is transmitted to the ARM host controller through the ZigBee wireless sensor network, and the ARM host controller determines whether there are free parking spaces based on the collected information. Secondly, Faster R-CNN, a deep learning algorithm, is selected as the license plate recognition model, and the Faster R-CNNN is improved by the residual module. Finally, in order to extend the lifetime of the ZigBee wireless network, the ZigBee routing algorithm is investigated, and an improved routing algorithm based on energy averaging is proposed. The effectiveness of the improved routing algorithm is demonstrated by a simulation analysis through NS2. The test results show that the designed intelligent parking management system is able to complete the functions of parking space detection and license plate recognition normally, thus effectively improving the efficiency of the car park and providing great convenience to motorists.
CITATION STYLE
Xiang, Z., & Pan, J. (2022). Design of Intelligent Parking Management System Based on ARM and Wireless Sensor Network. Mobile Information Systems, 2022. https://doi.org/10.1155/2022/2965638
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