用智能手机收集的蓝牙数据集用于室内环境中的近距离检测
Michele Girolami1, Davide La Rosa1, Paolo Barsocchi1
1Institute of Information Science and Technologies, National Research Council, (ISTI-CNR), Via G. Moruzzi, 1, 56124, Pisa, Italy.
Data in brief
|February 29, 2024
概括
这项研究引入了一个新的数据集,用于在博物馆环境中使用蓝牙信标信号进行近距离检测. 这些数据有助于开发用于识别用户接近感兴趣点 (POI) 的算法.
科学领域:
- 计算机科学 计算机科学
- 无处不在的计算 无处不在的计算
- 人与计算机的交互
背景情况:
- 近距离检测对于室内环境中的上下文感知应用至关重要.
- 现有的数据集可能无法完全捕捉现实世界博物馆导航和用户交互的复杂性.
- 蓝牙低能 (BLE) 信标为室内定位和近距离传感提供了可行的技术.
研究的目的:
- 为近距离检测研究提供一个新的数据集.
- 促进开发和评估用于识别室内环境中用户接近感兴趣点 (POI) 的算法.
- 提供一个现实的数据集,以解释用户路径和设备类型的变化.
主要方法:
- 进行了一项数据收集实验,涉及32个博物馆参观.
- 使用智能手机收集蓝牙信标消息 (接收信号强度 - RSS).
- 多种智能手机机型号和游客路径通过10个不同的艺术品.
- 建立了详细的基本真相,包括每次艺术品参观的开始和结束时间.
主要成果:
- 创建了一个包括RSS值,时间,艺术品标识符和基本真相注释在内的综合数据集.
- 数据集捕捉了博物馆中遇到的现实环境条件.
- 能够研究不同用户行为和设备特征下的近距离检测算法.
结论:
- 发布的数据集为研究人员和行业专业人士提供了宝贵的资源.
- 它支持使用商用智能手机技术自动检测人员和兴趣点的近距离检测算法的进步.
- 加快室内定位和上下文感知系统领域的原型设计和开发.
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