Multi-room occupancy estimation through adaptive gray-box models

A. Ebadat; G. Bottegal; M. Molinari; D. Varagnolo; B. Wahlberg; H. Hjalmarsson; K.H. Johansson

doi:10.1109/CDC.2015.7402794

Multi-room occupancy estimation through adaptive gray-box models

A. Ebadat, G. Bottegal, M. Molinari, D. Varagnolo, B. Wahlberg, H. Hjalmarsson, K.H. Johansson

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

10 Citations (Scopus)

Abstract

We consider the problem of estimating the occupancy level in buildings using indirect information such as CO2 concentrations and ventilation levels. We assume that one of the rooms is temporarily equipped with a device measuring the occupancy. Using the collected data, we identify a gray-box model whose parameters carry information about the structural characteristics of the room. Exploiting the knowledge of the same type of structural characteristics of the other rooms in the building, we adjust the gray-box model to capture the CO2 dynamics of the other rooms. Then the occupancy estimators are designed using a regularized deconvolution approach which aims at estimating the occupancy pattern that best explains the observed CO2 dynamics. We evaluate the proposed scheme through extensive simulation using a commercial software tool, IDA-ICE, for dynamic building simulation.

Original language	English
Title of host publication	2015 IEEE 54th Annual Conference on Decision and Control (CDC) December 15-18, 2015. Osaka, Japan
Place of Publication	New York
Publisher	Institute of Electrical and Electronics Engineers
Pages	3705-3711
Number of pages	7
ISBN (Electronic)	978-1-4799-7886-1
DOIs	https://doi.org/10.1109/CDC.2015.7402794
Publication status	Published - 8 Feb 2015
Externally published	Yes
Event	54th IEEE Conference on Decision and Control (CDC 2015) - "Osaka International Convention Center", Osaka, Japan Duration: 15 Dec 2015 → 18 Dec 2015 Conference number: 54 http://www.cdc2015.ctrl.titech.ac.jp/

Conference

Conference	54th IEEE Conference on Decision and Control (CDC 2015)
Abbreviated title	CDC 2015
Country/Territory	Japan
City	Osaka
Period	15/12/15 → 18/12/15
Internet address	http://www.cdc2015.ctrl.titech.ac.jp/

Keywords

CO2 dynamics
Maximum Likelihood
Occupancy estimation
building automation
inference

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10.1109/CDC.2015.7402794

http://www.mendeley.com/research/multiroom-occupancy-estimation-through-adaptive-graybox-models

Cite this

Ebadat, A., Bottegal, G., Molinari, M., Varagnolo, D., Wahlberg, B., Hjalmarsson, H., & Johansson, K. H. (2015). Multi-room occupancy estimation through adaptive gray-box models. In 2015 IEEE 54th Annual Conference on Decision and Control (CDC) December 15-18, 2015. Osaka, Japan (pp. 3705-3711). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CDC.2015.7402794

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title = "Multi-room occupancy estimation through adaptive gray-box models",

abstract = "We consider the problem of estimating the occupancy level in buildings using indirect information such as CO2 concentrations and ventilation levels. We assume that one of the rooms is temporarily equipped with a device measuring the occupancy. Using the collected data, we identify a gray-box model whose parameters carry information about the structural characteristics of the room. Exploiting the knowledge of the same type of structural characteristics of the other rooms in the building, we adjust the gray-box model to capture the CO2 dynamics of the other rooms. Then the occupancy estimators are designed using a regularized deconvolution approach which aims at estimating the occupancy pattern that best explains the observed CO2 dynamics. We evaluate the proposed scheme through extensive simulation using a commercial software tool, IDA-ICE, for dynamic building simulation.",

keywords = "CO2 dynamics, Maximum Likelihood, Occupancy estimation, building automation, inference",

author = "A. Ebadat and G. Bottegal and M. Molinari and D. Varagnolo and B. Wahlberg and H. Hjalmarsson and K.H. Johansson",

year = "2015",

month = feb,

day = "8",

doi = "10.1109/CDC.2015.7402794",

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booktitle = "2015 IEEE 54th Annual Conference on Decision and Control (CDC) December 15-18, 2015. Osaka, Japan",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

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Ebadat, A, Bottegal, G, Molinari, M, Varagnolo, D, Wahlberg, B, Hjalmarsson, H & Johansson, KH 2015, Multi-room occupancy estimation through adaptive gray-box models. in 2015 IEEE 54th Annual Conference on Decision and Control (CDC) December 15-18, 2015. Osaka, Japan. Institute of Electrical and Electronics Engineers, New York, pp. 3705-3711, 54th IEEE Conference on Decision and Control (CDC 2015), Osaka, Japan, 15/12/15. https://doi.org/10.1109/CDC.2015.7402794

Multi-room occupancy estimation through adaptive gray-box models. / Ebadat, A.; Bottegal, G.; Molinari, M. et al.
2015 IEEE 54th Annual Conference on Decision and Control (CDC) December 15-18, 2015. Osaka, Japan. New York: Institute of Electrical and Electronics Engineers, 2015. p. 3705-3711.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Multi-room occupancy estimation through adaptive gray-box models

AU - Ebadat, A.

AU - Bottegal, G.

AU - Molinari, M.

AU - Varagnolo, D.

AU - Wahlberg, B.

AU - Hjalmarsson, H.

AU - Johansson, K.H.

N1 - Conference code: 54

PY - 2015/2/8

Y1 - 2015/2/8

N2 - We consider the problem of estimating the occupancy level in buildings using indirect information such as CO2 concentrations and ventilation levels. We assume that one of the rooms is temporarily equipped with a device measuring the occupancy. Using the collected data, we identify a gray-box model whose parameters carry information about the structural characteristics of the room. Exploiting the knowledge of the same type of structural characteristics of the other rooms in the building, we adjust the gray-box model to capture the CO2 dynamics of the other rooms. Then the occupancy estimators are designed using a regularized deconvolution approach which aims at estimating the occupancy pattern that best explains the observed CO2 dynamics. We evaluate the proposed scheme through extensive simulation using a commercial software tool, IDA-ICE, for dynamic building simulation.

AB - We consider the problem of estimating the occupancy level in buildings using indirect information such as CO2 concentrations and ventilation levels. We assume that one of the rooms is temporarily equipped with a device measuring the occupancy. Using the collected data, we identify a gray-box model whose parameters carry information about the structural characteristics of the room. Exploiting the knowledge of the same type of structural characteristics of the other rooms in the building, we adjust the gray-box model to capture the CO2 dynamics of the other rooms. Then the occupancy estimators are designed using a regularized deconvolution approach which aims at estimating the occupancy pattern that best explains the observed CO2 dynamics. We evaluate the proposed scheme through extensive simulation using a commercial software tool, IDA-ICE, for dynamic building simulation.

KW - CO2 dynamics

KW - Maximum Likelihood

KW - Occupancy estimation

KW - building automation

KW - inference

U2 - 10.1109/CDC.2015.7402794

DO - 10.1109/CDC.2015.7402794

M3 - Conference contribution

SP - 3705

EP - 3711

BT - 2015 IEEE 54th Annual Conference on Decision and Control (CDC) December 15-18, 2015. Osaka, Japan

PB - Institute of Electrical and Electronics Engineers

CY - New York

T2 - 54th IEEE Conference on Decision and Control (CDC 2015)

Y2 - 15 December 2015 through 18 December 2015

ER -

Multi-room occupancy estimation through adaptive gray-box models

Abstract

Conference

Keywords

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