Alymani Mofadal, Almoqhem Lenah Abdulaziz, Alabdulwahab Dhuha Ahmed, Alghamdi Abdulrahman Abdullah, Alshahrani Hussain, Raza Khalid
Department of Computer and Network Engineering, College of Computing and Information Technology, Shaqra University, Shaqra, Saudi Arabia.
Department of Computer Science, College of Computing and Information Technology, Shaqra University, Shaqra, Saudi Arabia.
PeerJ Comput Sci. 2025 Jan 15;11:e2544. doi: 10.7717/peerj-cs.2544. eCollection 2025.
With the escalating number of vehicles and the lack of parking spaces, the issue of parking has become a significant problem in major cities as it is a daily occurrence for educational institutions, companies, and government facilities, resulting in fuel wastage and time inefficiencies. In their work lives, employees often face problems when parking their cars in the work parking area. Finding a space for their vehicle can take a lot of time and effort, leading to late arrival for work. On the other hand, security guards have difficulty entering their employees' cars. In this context, our proposed system attempts to address this pressing issue, which consists of two parts: one is a camera at the parking gate that recognizes the license plate using the Automatic Number Plate Recognition (ANPR) algorithm, where the camera captures the license plate and outputs the plate number using the optical character recognition (OCR) technique. After that, the resulting data is cross-referenced with database records for seamless entry authentication. This eliminates the need for security personnel to verify vehicle identities or stickers manually, streamlining access procedures. The second part is a camera in the car parks that distinguishes between vacant and available parking spaces and stores the data collected by the camera in the centralized database, enabling the real-time display of the nearest available parking spots on digital screens at entrance gates, significantly reducing the time and effort spent in locating parking spaces. Through this innovative solution, we aim to enhance urban mobility and alleviate the challenges associated with urban parking congestion, thereby resolving the problem of intelligent parking for smart cities with the help of machine learning.
随着车辆数量的不断增加以及停车位的短缺，停车问题已成为大城市的一个重大问题，因为教育机构、公司和政府设施每天都面临停车难题，这导致了燃油浪费和时间效率低下。在工作生活中，员工在工作停车场停车时经常遇到问题。为车辆找到停车位可能需要花费大量时间和精力，导致上班迟到。另一方面，保安难以进入员工的车辆。在此背景下，我们提出的系统试图解决这一紧迫问题，该系统由两部分组成：一是停车场入口处的摄像头，它使用自动车牌识别（ANPR）算法识别车牌，摄像头捕捉车牌并使用光学字符识别（OCR）技术输出车牌号。之后，将所得数据与数据库记录进行交叉核对，以实现无缝的入口认证。这消除了保安人员手动验证车辆身份或贴纸的需要，简化了进入程序。第二部分是停车场内的摄像头，它区分空车位和可用车位，并将摄像头收集的数据存储在中央数据库中，从而能够在入口处的数字屏幕上实时显示最近的可用停车位，显著减少寻找停车位所花费的时间和精力。通过这种创新解决方案，我们旨在提高城市交通流动性，缓解与城市停车拥堵相关的挑战，从而借助机器学习解决智慧城市的智能停车问题。
