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Evaluation of a New Energy-Based Human Tracking Method in a Smart Building Using Floor Vibration Measurements

Conference paper
Part of the Conference Proceedings of the Society for Experimental Mechanics Series book series (CPSEMS)

Abstract

Tracking occupants in an indoor environment has applications in intruder detection, emergency response and evacuation (e.g., locating an occupant in a burning building), and energy saving (through activity-based control of building lighting and HVAC system). In this document, we show that tracking occupants in an indoor environment can be done using the floor vibration caused by occupant footstep impacts. In order to track an occupant, each footstep impact location must first be estimated. For that purpose, we evaluate the performance of a newly developed energy-based localization (multilateration) method for the case of localizing occupant footsteps in a real-life operational smart building. The new method is based on the fact that the energy of the impact-generated wave will be attenuated as the wave travels away from the impact location. Localization is achieved using a network of vibration sensors (accelerometers) placed underneath the walking floor, which provides a non-intrusive and tamper-proof localization system. The new method has small computational time and requires a relatively small sensor data sampling rate. It is anticipated that the new method will have a smaller footstep localization error compared to conventional time of flight/arrival methods. Occupant tracking experiments show that the new method has a promisingly small localization error.

Keywords

Occupant tracking Underfloor accelerometers Sensor networks Floor vibrations Multilateration 

Notes

Acknowledgements

The authors are thankful for the support and collaborative efforts provided by our sponsors VTI Instruments, PCB Piezotronics, Inc.; Dytran Instruments, Inc.; and Oregano Systems. The authors are particularly thankful for the support provided by the College of Engineering at Virginia Tech through Ed Nelson and Dean Richard Benson as well as Capital Project Manager Todd Shelton. The authors would also like to acknowledge the collaboration with Gilbane, Inc.; in particular members David Childress and Eric Hotek. We are especially thankful to the Hashemite University of Jordan and the Student Engineering Council at Virginia Tech for their financial support. The authors would also like to recognize the support provided by the John R. Jones III faculty fellowship. The work was conducted under the patronage of the Virginia Tech Smart Infrastructure Laboratory and its members.

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Copyright information

© The Society for Experimental Mechanics, Inc. 2019

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringVirginia TechBlacksburgUSA
  2. 2.Department of Mechanical EngineeringVirginia Tech Smart Infrastructure Lab (VTSIL)BlacksburgUSA

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