一起或单独：使用无线指纹检测组移动性
Together or Alone: Detecting Group Mobility with Wireless Fingerprints
摘要：
本文提出了一种新的方法来检测人群走“在一起”（组移动性），以及人走“单独”（个人运动）使用无线信号。我们利用多个无线嗅探器来普遍收集人的移动数据与移动设备和识别相似性和基于无线指纹的组移动性。我们提出了一种方法，首先将嗅探器收集的无线数据包转换为人们的无线指纹。然后，该方法确定组的流动性，找到在某些时间（动态/静态）和动态的人的空间相关性的人的状态。为了评估我们的方法的可行性，我们进行了现实世界的实验，收集数据，从10个参与者携带蓝牙低功耗（BLE）信标在办公室环境中为期两周的时间。所提出的方法捕获空间相关性与95%和群体流动性与79%的准确率平均。利用所提出的方法，我们成功地1）检测群体和个人的运动和2）生成社交网络的基础上的群体移动特性。
英文摘要：
This paper proposes a novel approach for detecting groups of people that walk "together" (group mobility) as well as the people who walk "alone" (individual movements) using wireless signals. We exploit multiple wireless sniffers to pervasively collect human mobility data from people with mobile devices and identify similarities and the group mobility based on the wireless fingerprints. We propose a method which initially converts the wireless packets collected by the sniffers into people's wireless fingerprints. The method then determines group mobility by finding the statuses of people at certain times (dynamic/static) and the space correlation of dynamic people. To evaluate the feasibility of our approach, we conduct real world experiments by collecting data from 10 participants carrying Bluetooth Low Energy (BLE) beacons in an office environment for a two-week period. The proposed approach captures space correlation with 95% and group mobility with 79% accuracies on average. With the proposed approach we successfully 1) detect the groups and individual movements and 2) generate social networks based on the group mobility characteristics.
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。
