基于低功耗嵌入式平台的实时停车位管理系统.
Kapyol Kim1, Jongwon Lee1, Incheol Jeong1
1Department of Computer Engineering, Gachon University, Seongnam 1342, Republic of Korea.
Sensors (Basel, Switzerland)
|November 27, 2025
概括
这项研究引入了一个基于边缘的智能停车系统,用于实时检测户外占用情况. 低功耗系统使用人工智能进行准确的车辆识别和管理,降低成本并实现动态定价.
科学领域:
- 计算机视觉 计算机视觉
- 嵌入式系统 嵌入式系统
- 人工智能的人工智能
背景情况:
- 传统的停车管理系统通常依赖于昂贵的传感器和大量维护.
- 实时占用数据对于有效的停车管理和动态定价策略至关重要.
研究的目的:
- 开发一个以边缘为中心的户外停车场管理系统,用于实时,槽级别的占用检测.
- 使用低功耗嵌入式设备创建一个具有成本效益和可扩展的智能停车基础设施.
主要方法:
- 构建了一个由13691张在各种条件下捕获的图像组成的数据集.
- 训练了一个基于YOLOv8的探测器来识别车辆.
- 实施了一个时间占用决策模块,具有平滑和阻塞强大的规则,以提高稳定性.
主要成果:
- 在AI-BOX边缘平台上实现了195ms和400ms的端到端延迟p50/p95.
- 在24小时运行期间,在3.35W (2.99FPS/W) 持续10FPS.
- 在恶劣的天气和夜间条件下表现出更好的稳定性.
结论:
- 拟议的基于边缘的系统为智能停车提供了灵活,可扩展和经济高效的解决方案.
- 与传统架构相比,降低了前期部署成本和定期维护.
- 通过与动态定价机制集成,实现自动化费用计算.
关键词:
在这里,我们可以看到AIAIAI.这是一个RTSP.这是一个YOLO YOLO.低功耗嵌入式低功耗嵌入式机器学习是机器学习.对象检测检测对象检测对象检测实时视频处理实时视频处理智能停车系统是一个智能停车系统.视频分析 视频分析更多相关视频
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