Estimating Occupancy from Measurements and Knowledge Using the Bayesian Network for Energy Management
Joint Authors
Amayri, Manar
Ploix, Stephane
Kazmi, Hussain
Ngo, Quoc-Dung
Safadi, E. L. Abed E. L.
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-04-10
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
A general approach is proposed to determine occupant behavior (occupancy and activity) in offices and residential buildings in order to use these estimates for improved energy management.
Occupant behavior is modelled with a Bayesian network in an unsupervised manner.
This algorithm makes use of domain knowledge gathered via questionnaires and recorded sensor data for motion detection, power, and hot water consumption as well as indoor CO2 concentration.
Different case studies have been investigated with diversity according to their context (available sensors, occupancy or activity feedback, complexity of the environment, etc.).
Furthermore, experiments integrating occupancy estimation and hot water production control show that energy efficiency can be increased by roughly 5% over known optimal control techniques and more than 25% over rule-based control while maintaining the same occupant comfort.
American Psychological Association (APA)
Amayri, Manar& Ploix, Stephane& Kazmi, Hussain& Ngo, Quoc-Dung& Safadi, E. L. Abed E. L.. 2019. Estimating Occupancy from Measurements and Knowledge Using the Bayesian Network for Energy Management. Journal of Sensors،Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1191485
Modern Language Association (MLA)
Amayri, Manar…[et al.]. Estimating Occupancy from Measurements and Knowledge Using the Bayesian Network for Energy Management. Journal of Sensors No. 2019 (2019), pp.1-12.
https://search.emarefa.net/detail/BIM-1191485
American Medical Association (AMA)
Amayri, Manar& Ploix, Stephane& Kazmi, Hussain& Ngo, Quoc-Dung& Safadi, E. L. Abed E. L.. Estimating Occupancy from Measurements and Knowledge Using the Bayesian Network for Energy Management. Journal of Sensors. 2019. Vol. 2019, no. 2019, pp.1-12.
https://search.emarefa.net/detail/BIM-1191485
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1191485