Disaggregating Building-Level Occupancy into Zone-Level Occupant Counts Using Sensor Fusion

Brodie W. Hobson; Tareq Abuimara; Araz Ashouri; H. Burak Gunay

doi:10.1007/978-981-19-9822-5_201

Disaggregating Building-Level Occupancy into Zone-Level Occupant Counts Using Sensor Fusion

Brodie W. Hobson
, Tareq Abuimara
, Araz Ashouri
, H. Burak Gunay

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

This paper outlines a methodology for disaggregating building-level occupancy data into zone-level occupant counts using opportunistic data from Wi-Fi access points, motion detectors, and CO₂ sensors via sensor fusion for a floor of an academic office building. The efficacy of different combinations of data for this purpose is explored and the occupant-count estimates from these different combinations of data are compared to one another. The impacts of different sensors, sensor grid densities, and their data on the occupant-count estimates are discussed. Historical CO₂ data are analysed to determine if instances of under- or over-occupancy as estimated by this methodology are reflected in the measured CO₂ trends where available. The results indicate that additional sensor data improves the disaggregation model’s ability to estimate which rooms are over-occupied, with the granularity of the Wi-Fi access point grid and inclusion of CO₂ data causing the largest increase in purported accuracy.

Original language	English
Title of host publication	Proceedings of the 5th International Conference on Building Energy and Environment
Editors	Liangzhu Leon Wang, Hua Ge, Mohamed Ouf, Zhiqiang John Zhai, Dahai Qi, Chanjuan Sun, Dengjia Wang
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	1913-1924
Number of pages	12
ISBN (Print)	9789811998218
DOIs	https://doi.org/10.1007/978-981-19-9822-5_201
Publication status	Published - 2023
Externally published	Yes
Event	5th International Conference on Building Energy and Environment, COBEE 2022 - Montreal, Canada Duration: Jul 25 2022 → Jul 29 2022

Publication series

Name	Environmental Science and Engineering
ISSN (Print)	1863-5520
ISSN (Electronic)	1863-5539

Conference

Conference	5th International Conference on Building Energy and Environment, COBEE 2022
Country/Territory	Canada
City	Montreal
Period	7/25/22 → 7/29/22

Keywords

Occupancy
Occupant-centric control
Sensor fusion
Space utilization
Ventilation

ASJC Scopus subject areas

Environmental Engineering
Information Systems

Access to Document

10.1007/978-981-19-9822-5_201

Cite this

Hobson, B. W., Abuimara, T., Ashouri, A., & Gunay, H. B. (2023). Disaggregating Building-Level Occupancy into Zone-Level Occupant Counts Using Sensor Fusion. In L. L. Wang, H. Ge, M. Ouf, Z. J. Zhai, D. Qi, C. Sun, & D. Wang (Eds.), Proceedings of the 5th International Conference on Building Energy and Environment (pp. 1913-1924). (Environmental Science and Engineering). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-9822-5_201

Disaggregating Building-Level Occupancy into Zone-Level Occupant Counts Using Sensor Fusion. / Hobson, Brodie W.; Abuimara, Tareq; Ashouri, Araz et al.
Proceedings of the 5th International Conference on Building Energy and Environment. ed. / Liangzhu Leon Wang; Hua Ge; Mohamed Ouf; Zhiqiang John Zhai; Dahai Qi; Chanjuan Sun; Dengjia Wang. Springer Science and Business Media Deutschland GmbH, 2023. p. 1913-1924 (Environmental Science and Engineering).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Hobson, BW, Abuimara, T, Ashouri, A & Gunay, HB 2023, Disaggregating Building-Level Occupancy into Zone-Level Occupant Counts Using Sensor Fusion. in LL Wang, H Ge, M Ouf, ZJ Zhai, D Qi, C Sun & D Wang (eds), Proceedings of the 5th International Conference on Building Energy and Environment. Environmental Science and Engineering, Springer Science and Business Media Deutschland GmbH, pp. 1913-1924, 5th International Conference on Building Energy and Environment, COBEE 2022, Montreal, Canada, 7/25/22. https://doi.org/10.1007/978-981-19-9822-5_201

Hobson BW, Abuimara T, Ashouri A, Gunay HB. Disaggregating Building-Level Occupancy into Zone-Level Occupant Counts Using Sensor Fusion. In Wang LL, Ge H, Ouf M, Zhai ZJ, Qi D, Sun C, Wang D, editors, Proceedings of the 5th International Conference on Building Energy and Environment. Springer Science and Business Media Deutschland GmbH. 2023. p. 1913-1924. (Environmental Science and Engineering). doi: 10.1007/978-981-19-9822-5_201

Hobson, Brodie W. ; Abuimara, Tareq ; Ashouri, Araz et al. / Disaggregating Building-Level Occupancy into Zone-Level Occupant Counts Using Sensor Fusion. Proceedings of the 5th International Conference on Building Energy and Environment. editor / Liangzhu Leon Wang ; Hua Ge ; Mohamed Ouf ; Zhiqiang John Zhai ; Dahai Qi ; Chanjuan Sun ; Dengjia Wang. Springer Science and Business Media Deutschland GmbH, 2023. pp. 1913-1924 (Environmental Science and Engineering).

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abstract = "This paper outlines a methodology for disaggregating building-level occupancy data into zone-level occupant counts using opportunistic data from Wi-Fi access points, motion detectors, and CO2 sensors via sensor fusion for a floor of an academic office building. The efficacy of different combinations of data for this purpose is explored and the occupant-count estimates from these different combinations of data are compared to one another. The impacts of different sensors, sensor grid densities, and their data on the occupant-count estimates are discussed. Historical CO2 data are analysed to determine if instances of under- or over-occupancy as estimated by this methodology are reflected in the measured CO2 trends where available. The results indicate that additional sensor data improves the disaggregation model{\textquoteright}s ability to estimate which rooms are over-occupied, with the granularity of the Wi-Fi access point grid and inclusion of CO2 data causing the largest increase in purported accuracy.",

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AU - Ashouri, Araz

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PY - 2023

Y1 - 2023

N2 - This paper outlines a methodology for disaggregating building-level occupancy data into zone-level occupant counts using opportunistic data from Wi-Fi access points, motion detectors, and CO2 sensors via sensor fusion for a floor of an academic office building. The efficacy of different combinations of data for this purpose is explored and the occupant-count estimates from these different combinations of data are compared to one another. The impacts of different sensors, sensor grid densities, and their data on the occupant-count estimates are discussed. Historical CO2 data are analysed to determine if instances of under- or over-occupancy as estimated by this methodology are reflected in the measured CO2 trends where available. The results indicate that additional sensor data improves the disaggregation model’s ability to estimate which rooms are over-occupied, with the granularity of the Wi-Fi access point grid and inclusion of CO2 data causing the largest increase in purported accuracy.

AB - This paper outlines a methodology for disaggregating building-level occupancy data into zone-level occupant counts using opportunistic data from Wi-Fi access points, motion detectors, and CO2 sensors via sensor fusion for a floor of an academic office building. The efficacy of different combinations of data for this purpose is explored and the occupant-count estimates from these different combinations of data are compared to one another. The impacts of different sensors, sensor grid densities, and their data on the occupant-count estimates are discussed. Historical CO2 data are analysed to determine if instances of under- or over-occupancy as estimated by this methodology are reflected in the measured CO2 trends where available. The results indicate that additional sensor data improves the disaggregation model’s ability to estimate which rooms are over-occupied, with the granularity of the Wi-Fi access point grid and inclusion of CO2 data causing the largest increase in purported accuracy.

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KW - Occupant-centric control

KW - Sensor fusion

KW - Space utilization

KW - Ventilation

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Disaggregating Building-Level Occupancy into Zone-Level Occupant Counts Using Sensor Fusion

Abstract

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Keywords

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