一种基于人工视觉的新占用指数模型,用于增强海管理
Mireia Sempere-Tortosa1, Ignacio Toledo2, Diego Marcos-Jorquera3
1Department of Computer Science and Artificial Intelligence, University of Alicante, Carretera Sant Vicent del Raspeig s/n, 03690, Alicante, Spain.
Journal of environmental management
|October 8, 2024
概括
这项研究引入了一种新的海管理方法,使用人工视觉计算占用率和距离指数. 该系统有效地监控人群密度和空间分布,以优化海使用.
科学领域:
- 环境管理环境管理
- 计算机视觉 计算机视觉
- 公共卫生 公共卫生
背景情况:
- 有效的海管理需要监控用户密度和社会距离.
- 监测海占用率的传统方法往往是人工和劳动密集型的.
- 对海使用和人群分布的实时数据的需求对于公共安全和资源分配至关重要.
研究的目的:
- 开发和验证一个新的实时海占用监测系统.
- 引入过度拥挤指数 (Iocr) 和距离指数 (Idis),结合成一个占用指数 (Iocu).
- 评估系统在管理海容量和确保足够的社会距离方面的有效性.
主要方法:
- 利用摄像头和计算机视觉算法 (YOLOX,ByteTrack) 进行自动的人口计数和距离测量.
- 开发并整合过度拥挤指数 (Iocr) 和距离指数 (Idis) 成为统一的占用指数 (Iocu).
- 实现了一个功能原型,用于实时计算和显示海占用指数.
主要成果:
- 过度拥挤指数 (Iocr) 显示了与密度的反向关系,在最大容量时接近零.
- 发现距离指数 (Idis) 低 (0.18) 即使在靠近海岸线的中等密度,表明未能达到2米的距离.
- 综合占用率指数 (Iocu) 实现了0.31的值,验证了综合指数方法.
结论:
- 拟议的人工视觉系统准确地监测了海用户的数量和分布.
- 开发的指数为基于实时占用率的有效海管理提供了有价值的工具.
- 这项技术使主动和数据驱动的决策能够优化海利用和公共安全.
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