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Robust Occupant Detection Through Step-Induced Floor Vibration by Incorporating Structural Characteristics

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Dynamics of Coupled Structures, Volume 4

Abstract

The objective of this paper is to present an occupant detection method through step-induced structural vibration. Occupant detection enables various smart building applications such as space/energy management. Ambient structural vibration monitoring provides a non-intrusive sensing approach to achieve that. The main challenges for structural vibration based occupant footstep detection include that (1) the ambient structural vibration noise may overwhelm the step-induced vibration and (2) there are various other impulse-like excitations that look similar to footstep excitations in the sensing environment (e.g., door closing, chair dragging, etc.), which increase the false alarm rate for occupant detection. To overcome these challenges, a two-stage step-induced signal detection algorithm is developed to (1) incorporate the structural characteristics by selecting the dominant frequencies of the structure to increase the signal-to-noise ratio in the vibration data and thus improve the detection performance and (2) perform footstep classification on detected events to distinguish step-induced floor vibrations from other impulse excitations. The method is validated experimentally in two different buildings with distinct structural properties and noise characteristics, Carnegie Mellon University (CMU) campus building and Vincentian Nursing Home deployments in Pittsburgh, PA. The occupant footstep detection F1 score shows up to 4X reduction in detection error compared to traditional thresholding method.

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Acknowledgements

This work is partially supported by National Science Foundation (NSF) under awards CNS-1149611, Pennsylvania Infrastructure Technology Alliance (PITA), CMU-SYSU Collaborative Innovation Research Center (CIRC), Intel, Nokia, and Renault. The authors would also like to acknowledge Vincentian Nursing Home for providing deployment sites to conduct experiments and collect data.

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Authors and Affiliations

  1. Department of Civil and Environmental Engineering, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA, 15213, USA

    Mike Lam, Mostafa Mirshekari & Hae Young Noh

  2. Department of Electrical and Computer Engineering, Carnegie Mellon University, Building 23, Moffett Field, CA, 94035, USA

    Shijia Pan & Pei Zhang

Authors
  1. Mike Lam
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  2. Mostafa Mirshekari
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  3. Shijia Pan
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  4. Pei Zhang
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  5. Hae Young Noh
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Editors and Affiliations

  1. Engg Phys Dept 535 Engg Res Bldg, University of Wisconsin Madison, Madison, Wisconsin, USA

    Matt Allen

  2. MS 0557, Sandia National Laboratories, Albuquerque, New Mexico, USA

    Randall L. Mayes

  3. Lehrstuhl für Angewandte Mechanik, TU München, Garching, Bayern, Germany

    Daniel Rixen

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© 2016 The Society for Experimental Mechanics, Inc.

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Lam, M., Mirshekari, M., Pan, S., Zhang, P., Noh, H.Y. (2016). Robust Occupant Detection Through Step-Induced Floor Vibration by Incorporating Structural Characteristics. In: Allen, M., Mayes, R., Rixen, D. (eds) Dynamics of Coupled Structures, Volume 4. Conference Proceedings of the Society for Experimental Mechanics Series. Springer, Cham. https://doi.org/10.1007/978-3-319-29763-7_35

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  • DOI: https://doi.org/10.1007/978-3-319-29763-7_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-29762-0

  • Online ISBN: 978-3-319-29763-7

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