通过物联网 (IoT) 和机器学习实现智能城市的智能停车
Mofadal Alymani1, Lenah Abdulaziz Almoqhem2, Dhuha Ahmed Alabdulwahab2
1Department of Computer and Network Engineering, College of Computing and Information Technology, Shaqra University, Shaqra, Saudi Arabia.
PeerJ. Computer science
|February 3, 2025
概括
这项研究引入了一个智能停车系统,使用自动车牌识别 (ANPR) 和机器学习来简化车辆访问和引导司机到可用地点,减少城市拥堵.
科学领域:
- 计算机科学 计算机科学
- 城市规划 城市规划
- 人工智能的人工智能
背景情况:
- 城市停车场短缺导致大量的燃料浪费和时间效率低下.
- 员工经常因为在工作中难以找到停车场而遇到延误.
- 安全人员手动验证车辆是耗时的.
研究的目的:
- 为智慧城市开发智能停车系统.
- 为了自动化车辆进入,并优化停车位利用率.
- 为了减少司机寻找停车所需的时间和精力.
主要方法:
- 实现用于车辆识别的光学字符识别 (OCR) 的自动车牌识别 (ANPR).
- 使用停车场内的摄像头来检测空置和占用空间.
- 开发一个中央数据库,用于实时的停车可用性数据.
主要成果:
- 通过自动识别车牌和数据库交叉引用,简化车辆进入.
- 在入口门的数字屏幕上实时显示可用停车位.
- 显著减少了司机寻找停车位的时间和精力.
结论:
- 拟议的系统有效地解决了城市停车场的挑战.
- 整合ANPR,OCR和机器学习可以提高停车管理.
- 这种解决方案有助于改善城市流动性和智能城市的发展.
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