CYLGSPSep 30, 2020

Privacy Concerns Regarding Occupant Tracking in Smart Buildings

arXiv:2010.07028v14 citations
Originality Synthesis-oriented
AI Analysis

This work addresses privacy issues in smart building occupant tracking, which is an incremental improvement for building management and safety applications.

The paper compared occupant tracking methods for privacy concerns and proposed a method to anonymize gender information in vibration data, achieving similar localization accuracy while preserving privacy.

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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