Article | Proceedings of The 60th SIMS Conference on Simulation and Modelling SIMS 2019, August 12-16, Västerås, Sweden | Building occupation modelling using motion sensor data Linköping University Electronic Press Conference Proceedings
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Title:
Building occupation modelling using motion sensor data
Author:
Nils-Olav Skeie: Department of Electrical Engineering, Information Technology and Cybernetics, University of South-Eastern Norway, Porsgrunn, Norway Jørund Martinsen: Department of Electrical Engineering, Information Technology and Cybernetics, University of South-Eastern Norway, Porsgrunn, Norway
DOI:
https://doi.org/10.3384/ecp2017043
Download:
Full text (pdf)
Year:
2019
Conference:
Proceedings of The 60th SIMS Conference on Simulation and Modelling SIMS 2019, August 12-16, Västerås, Sweden
Issue:
170
Article no.:
007
Pages:
43-50
No. of pages:
8
Publication type:
Abstract and Fulltext
Published:
2020-01-24
ISBN:
978-91-7929-897-5
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press, Linköpings universitet


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In smart building environments, both office and residential buildings, it is important to have some information about the use and occupation. Today this is normally solved by a fixed time schedule meaning the occupants must adapt to the system, not the other way around. This paper discuss the usage of a top hat probability models, based on a four weeks history from inexpensive sensor devices, for prediction of the occupation in the next week. The model was divided into seven groups, one group for each of day of the week. A software system, based on several modules, was developed. One module was used to record the information from the motion sensors and stored the data as historical data. One module was used to create the model, and another module was used to prediction of occupation for the next days, up to a week. The models are working satisfactory as long as the behavior patterns are similar for the training and prediction period. However, the models are sensitive to changes in the daily behavior pattern of the occupants, like holidays or taking a day off.

Keywords: probability model, building occupation, PIR sensor devices, motion sensor devices, building occupation prediction

Proceedings of The 60th SIMS Conference on Simulation and Modelling SIMS 2019, August 12-16, Västerås, Sweden

Author:
Nils-Olav Skeie, Jørund Martinsen
Title:
Building occupation modelling using motion sensor data
DOI:
10.3384/ecp2017043
References:

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Proceedings of The 60th SIMS Conference on Simulation and Modelling SIMS 2019, August 12-16, Västerås, Sweden

Author:
Nils-Olav Skeie, Jørund Martinsen
Title:
Building occupation modelling using motion sensor data
DOI:
https://doi.org10.3384/ecp2017043
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Last updated: 2019-11-06