The way people interact in daily life is a challenging phenomenon to be captured and studied without altering the natural rhythm of the interactions. We investigate the development of automated tools that may provide information to the researchers that analyse interactions among humans. One important requirement of these tools is that should not interfere with the subjects under observation, in order to avoid any alteration in the subject’s normal behaviour. Our approach is based on the detection of proximity among groups of people that is obtained using commercial wearable wireless tags based on Bluetooth Low Energy (BLE) and a novel algorithm called Remote Detection of Human Proximity (ReD-HuP) that analyses the wireless signal of tags and produce the proximity information. The algorithm, which has been validated against the ground truth of an experimental dataset, achieves an accuracy of 95.91% and an F-Score of 95.79%.

中文翻译：

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通过蓝牙低功耗信标远程检测室内环境中的社交互动

人们在日常生活中进行交互的方式是一个具有挑战性的现象，需要加以捕捉和研究，而不会改变交互的自然节奏。我们调查了自动工具的开发，这些工具可能会为分析人与人之间相互作用的研究人员提供信息。这些工具的一项重要要求是，不得干扰被观察者，以免改变其正常行为。我们的方法基于使用基于蓝牙低功耗（BLE）的商业可穿戴无线标签和一种称为“人类近距离远程检测”（ReD-HuP）的新颖算法（可分析人群的无线信号）获得的人群之间的接近度检测。标记并产生邻近信息。该算法