BeSense：利用WiFi渠道数据和计算智能进行行为分析
BeSense: Leveraging WiFi Channel Data and Computational Intelligence for Behavior Analysis
摘要：
不断发展的信息技术逐渐将人与计算机紧密地联系在一起。理解用户行为成为许多领域的关键推动因素，例如与久坐相关的医疗保健、人机交互（HCI）和情感计算。传统的基于传感器和基于视觉的用户行为分析方法通常是突兀的，阻碍了它们在现实世界中的使用。因此，在本文中，我们首先引入WiFi信号作为一种新的来源，而不是传感器和视觉，用于非侵入性的用户行为分析。然后，我们设计了BeSense，一个非接触式行为分析系统，利用WiFi信道状态信息（CSI）的信号处理和计算智能。我们在商品低成本WiFi设备上原型化BeSense，并评估其在现实环境中的性能。实验结果验证了该方法在用户行为识别中的有效性。
英文摘要：
The ever evolving informatics technology has gradually bounded human and computer in a compact way. Understanding user behavior becomes a key enabler in many fields such as sedentary-related healthcare, human-computer interaction (HCI) and affective computing. Traditional sensor-based and vision-based user behavior analysis approaches are obtrusive in general, hindering their usage in realworld. Therefore, in this article, we first introduce WiFi signal as a new source instead of sensor and vision for unobtrusive user behaviors analysis. Then we design BeSense, a contactless behavior analysis system leveraging signal processing and computational intelligence over WiFi channel state information (CSI). We prototype BeSense on commodity low-cost WiFi devices and evaluate its performance in realworld environments. Experimental results have verified its effectiveness in recognizing user behaviors.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
