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Proceedings Paper

BOES: Building Occupancy Estimation System using sparse ambient vibration monitoring
Author(s): Shijia Pan; Amelie Bonde; Jie Jing; Lin Zhang; Pei Zhang; Hae Young Noh
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Paper Abstract

In this paper, we present a room-level building occupancy estimation system (BOES) utilizing low-resolution vibration sensors that are sparsely distributed. Many ubiquitous computing and building maintenance systems require fine-grained occupancy knowledge to enable occupant centric services and optimize space and energy utilization. The sensing infrastructure support for current occupancy estimation systems often requires multiple intrusive sensors per room, resulting in systems that are both costly to deploy and difficult to maintain. To address these shortcomings, we developed BOES. BOES utilizes sparse vibration sensors to track occupancy levels and activities. Our system has three major components. 1) It extracts features that distinguish occupant activities from noise prone ambient vibrations and detects human footsteps. 2) Using a sequence of footsteps, the system localizes and tracks individuals by observing changes in the sequences. It uses this tracking information to identify when an occupant leaves or enters a room. 3) The entering and leaving room information are combined with detected individual location information to update the room-level occupancy state of the building. Through validation experiments in two different buildings, our system was able to achieve 99.55% accuracy for event detection, less than three feet average error for localization, and 85% accuracy in occupancy counting.

Paper Details

Date Published: 10 April 2014
PDF: 16 pages
Proc. SPIE 9061, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2014, 90611O (10 April 2014); doi: 10.1117/12.2046510
Show Author Affiliations
Shijia Pan, Carnegie Mellon Univ. (United States)
Amelie Bonde, Carnegie Mellon Univ. (United States)
Jie Jing, Tsinghua Univ. (China)
Lin Zhang, Tsinghua Univ. (China)
Pei Zhang, Carnegie Mellon Univ. (United States)
Hae Young Noh, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 9061:
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2014
Jerome P. Lynch; Kon-Well Wang; Hoon Sohn, Editor(s)

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