A Framework for Occupancy Tracking in a Building via Structural Dynamics Sensing of Footstep Vibrations
Counting the number of occupants in building areas over time—occupancy tracking—provides valuable information for responding to emergencies, optimizing thermal conditions or managing personnel. This capability is distinct from tracking individual building occupants as they move within a building, ha...
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Online Access: | http://journal.frontiersin.org/article/10.3389/fbuil.2017.00065/full |
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doaj-7ee264f45c91454599545af56229acce2020-11-24T23:41:36ZengFrontiers Media S.A.Frontiers in Built Environment2297-33622017-11-01310.3389/fbuil.2017.00065273391A Framework for Occupancy Tracking in a Building via Structural Dynamics Sensing of Footstep VibrationsJeffrey D. Poston0R. Michael Buehrer1Pablo A. Tarazaga2Wireless@VT, Electrical and Computer Engineering Department, Virginia Tech, Blacksburg, VA, United StatesWireless@VT, Electrical and Computer Engineering Department, Virginia Tech, Blacksburg, VA, United StatesVT-SIL, Mechanical Engineering Department, Virginia Tech, Blacksburg, VA, United StatesCounting the number of occupants in building areas over time—occupancy tracking—provides valuable information for responding to emergencies, optimizing thermal conditions or managing personnel. This capability is distinct from tracking individual building occupants as they move within a building, has lower complexity than conventional tracking algorithms require, and avoids privacy concerns that tracking individuals may pose. The approach proposed here is a novel combination of data analytics applied to measurements from a building’s structural dynamics sensors (e.g., accelerometers or geophones). Specifically, measurements of footstep-generated structural waves provide evidence of occupancy in a building area. These footstep vibrations can be distinguished from other vibrations, and, once identified, the footsteps can be located. These locations, in turn, form the starting point of estimating occupancy in an area. In order to provide a meaningful occupancy count, however, it is first necessary to associate discrete footsteps with individuals. The proposed framework incorporates a tractable algorithm for this association task. The proposed algorithms operate online, updating occupancy count over time as new footsteps are detected. Experiments with measurements from a public building illustrate the operation of the proposed framework. This approach offers an advantage over others based on conventional technologies by avoiding the cost of a separate sensor system devoted to occupancy tracking.http://journal.frontiersin.org/article/10.3389/fbuil.2017.00065/fullsmart buildingstructural dynamicsoccupancytrackingvibration |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jeffrey D. Poston R. Michael Buehrer Pablo A. Tarazaga |
spellingShingle |
Jeffrey D. Poston R. Michael Buehrer Pablo A. Tarazaga A Framework for Occupancy Tracking in a Building via Structural Dynamics Sensing of Footstep Vibrations Frontiers in Built Environment smart building structural dynamics occupancy tracking vibration |
author_facet |
Jeffrey D. Poston R. Michael Buehrer Pablo A. Tarazaga |
author_sort |
Jeffrey D. Poston |
title |
A Framework for Occupancy Tracking in a Building via Structural Dynamics Sensing of Footstep Vibrations |
title_short |
A Framework for Occupancy Tracking in a Building via Structural Dynamics Sensing of Footstep Vibrations |
title_full |
A Framework for Occupancy Tracking in a Building via Structural Dynamics Sensing of Footstep Vibrations |
title_fullStr |
A Framework for Occupancy Tracking in a Building via Structural Dynamics Sensing of Footstep Vibrations |
title_full_unstemmed |
A Framework for Occupancy Tracking in a Building via Structural Dynamics Sensing of Footstep Vibrations |
title_sort |
framework for occupancy tracking in a building via structural dynamics sensing of footstep vibrations |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Built Environment |
issn |
2297-3362 |
publishDate |
2017-11-01 |
description |
Counting the number of occupants in building areas over time—occupancy tracking—provides valuable information for responding to emergencies, optimizing thermal conditions or managing personnel. This capability is distinct from tracking individual building occupants as they move within a building, has lower complexity than conventional tracking algorithms require, and avoids privacy concerns that tracking individuals may pose. The approach proposed here is a novel combination of data analytics applied to measurements from a building’s structural dynamics sensors (e.g., accelerometers or geophones). Specifically, measurements of footstep-generated structural waves provide evidence of occupancy in a building area. These footstep vibrations can be distinguished from other vibrations, and, once identified, the footsteps can be located. These locations, in turn, form the starting point of estimating occupancy in an area. In order to provide a meaningful occupancy count, however, it is first necessary to associate discrete footsteps with individuals. The proposed framework incorporates a tractable algorithm for this association task. The proposed algorithms operate online, updating occupancy count over time as new footsteps are detected. Experiments with measurements from a public building illustrate the operation of the proposed framework. This approach offers an advantage over others based on conventional technologies by avoiding the cost of a separate sensor system devoted to occupancy tracking. |
topic |
smart building structural dynamics occupancy tracking vibration |
url |
http://journal.frontiersin.org/article/10.3389/fbuil.2017.00065/full |
work_keys_str_mv |
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