论文标题

关于智能建筑中乘员跟踪的隐私问题

Privacy Concerns Regarding Occupant Tracking in Smart Buildings

论文作者

Kessler, Ellis, Masiane, Moeti, Abdelhalim, Awad

论文摘要

在过去十年中,对建筑物内的居民的跟踪已成为一个有趣的话题。乘员跟踪已用于公共安全,节能和营销领域。已经证明了各种方法可以跟踪建筑物外部和内部的人们;包括GPS,使用监视摄像机的基于视觉的跟踪以及使用传感器(例如加速度计)的基于振动的跟踪。在这项工作中,将那些用于跟踪乘员的主要系统进行比较,并与他们提供的有关居住者所在的细节以及各自的隐私问题以及收集到的跟踪信息的可识别性与特定人员的可识别方式形成对比。我们讨论了一项案例研究,该案例研究使用了最近进行的弗吉尼亚理工大学的古德温厅(Goodwin Hall)上安装的振动传感器,表明可以实现与当前方法相似的乘员定位准确性,并突出显示振动信号数据集中的识别信息量。最后,提出了一种转换振动数据以保护乘员隐私的方法,并在数据集上进行了测试。结果表明,我们提出的方法成功地导致了匿名的占用者的性别信息,该信息以前可以从振动数据中识别出来,同时最小化影响了无匿名化的本地化精度。

Tracking of occupants within buildings has become a topic of interest in the past decade. Occupant tracking has been used in the public safety, energy conservation, and marketing fields. Various methods have been demonstrated which can track people outside of and inside buildings; including GPS, visual-based tracking using surveillance cameras, and vibration-based tracking using sensors such as accelerometers. In this work, those main systems for tracking occupants are compared and contrasted for the levels of detail they give about where occupants are, as well as their respective privacy concerns and how identifiable the tracking information collected is to a specific person. We discuss a case study using vibrations sensors mounted in Virginia Tech's Goodwin Hall that was recently conducted, demonstrating that similar levels of accuracy in occupant localization can be achieved to current methods, and highlighting the amount of identifying information in the vibration signals dataset. Finally, a method of transforming the vibration data to preserve occupant privacy was proposed and tested on the dataset. The results indicate that our proposed method has successfully resulted in anonymizing the occupant's gender information which was previously identifiable from the vibration data, while minimally impacting the localization accuracy achieved without anonymization.

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