Combining occupancy user profiles in a multi-user environment: An academic office case study

Andres Auquilla; Yannick De Bock; Ann Nowe; Joost Duflou

doi:10.1109/IE.2016.41

Combining occupancy user profiles in a multi-user environment: An academic office case study

Andres Auquilla
, Yannick De Bock
, Ann Nowe
, Joost Duflou

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

2 Scopus citations

Abstract

In a worldwide context, space heating is the largest energy consumer in commercial buildings, it accounts for 35% of the total energy consumed in the US. Energy efficient thermostats, that learn occupancy patterns and user preferences, haven been studied in literature. However, they are oriented to single-user environments, therefore, they are not applicable in offices where several users interact, i.e. multi-user environments. To expand the single-user techniques in order to cope with multi-user environments, two methods are proposed to derive the user's expected temperatures demands based on their occupancy profiles and individual preferences in terms of desired temperature and tolerance. This paper presents the implications of the implementation of such techniques by means of a case study of two users in an academic office. We observed that the proposed methods reduced the operational time up to 33% compared to a reference fixed schedule of 12 hours while maintaining user comfort. In conclusion, smart thermostats can also reduce energy consumption in multi-user environments while guaranteeing individual user expectations.

Original language	English
Title of host publication	Proceedings - 12th International Conference on Intelligent Environments, IE 2016
Editors	Stefano Chessa, Gordon Hunter, Tiina Kymalainen, Stefan Poslad, Stuart Middleton, Tony Huang, Antonio Coronato, Juan Carlos Augusto, Simon Egerton, Rui Loureiro
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	186-189
Number of pages	4
ISBN (Electronic)	9781509040568
DOIs	https://doi.org/10.1109/IE.2016.41
State	Published - 26 Oct 2016
Event	12th International Conference on Intelligent Environments, IE 2016 - London, United Kingdom Duration: 14 Sep 2016 → 16 Sep 2016

Publication series

Name	Proceedings - 12th International Conference on Intelligent Environments, IE 2016

Conference

Conference	12th International Conference on Intelligent Environments, IE 2016
Country/Territory	United Kingdom
City	London
Period	14/09/16 → 16/09/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

multi-user environment
occupancy prediction
smart thermostat
user profile

Access to Document

10.1109/IE.2016.41

Cite this

Auquilla, A., De Bock, Y., Nowe, A., & Duflou, J. (2016). Combining occupancy user profiles in a multi-user environment: An academic office case study. In S. Chessa, G. Hunter, T. Kymalainen, S. Poslad, S. Middleton, T. Huang, A. Coronato, J. C. Augusto, S. Egerton, & R. Loureiro (Eds.), Proceedings - 12th International Conference on Intelligent Environments, IE 2016 (pp. 186-189). Article 7723494 (Proceedings - 12th International Conference on Intelligent Environments, IE 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IE.2016.41

Auquilla, Andres ; De Bock, Yannick ; Nowe, Ann et al. / Combining occupancy user profiles in a multi-user environment : An academic office case study. Proceedings - 12th International Conference on Intelligent Environments, IE 2016. editor / Stefano Chessa ; Gordon Hunter ; Tiina Kymalainen ; Stefan Poslad ; Stuart Middleton ; Tony Huang ; Antonio Coronato ; Juan Carlos Augusto ; Simon Egerton ; Rui Loureiro. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 186-189 (Proceedings - 12th International Conference on Intelligent Environments, IE 2016).

@inproceedings{0f13673fb18245c8840c38dc3f3b5310,

title = "Combining occupancy user profiles in a multi-user environment: An academic office case study",

abstract = "In a worldwide context, space heating is the largest energy consumer in commercial buildings, it accounts for 35\% of the total energy consumed in the US. Energy efficient thermostats, that learn occupancy patterns and user preferences, haven been studied in literature. However, they are oriented to single-user environments, therefore, they are not applicable in offices where several users interact, i.e. multi-user environments. To expand the single-user techniques in order to cope with multi-user environments, two methods are proposed to derive the user's expected temperatures demands based on their occupancy profiles and individual preferences in terms of desired temperature and tolerance. This paper presents the implications of the implementation of such techniques by means of a case study of two users in an academic office. We observed that the proposed methods reduced the operational time up to 33\% compared to a reference fixed schedule of 12 hours while maintaining user comfort. In conclusion, smart thermostats can also reduce energy consumption in multi-user environments while guaranteeing individual user expectations.",

keywords = "multi-user environment, occupancy prediction, smart thermostat, user profile",

author = "Andres Auquilla and \{De Bock\}, Yannick and Ann Nowe and Joost Duflou",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 12th International Conference on Intelligent Environments, IE 2016 ; Conference date: 14-09-2016 Through 16-09-2016",

year = "2016",

month = oct,

day = "26",

doi = "10.1109/IE.2016.41",

language = "Ingl{\'e}s",

series = "Proceedings - 12th International Conference on Intelligent Environments, IE 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "186--189",

editor = "Stefano Chessa and Gordon Hunter and Tiina Kymalainen and Stefan Poslad and Stuart Middleton and Tony Huang and Antonio Coronato and Augusto, \{Juan Carlos\} and Simon Egerton and Rui Loureiro",

booktitle = "Proceedings - 12th International Conference on Intelligent Environments, IE 2016",

}

Auquilla, A, De Bock, Y, Nowe, A & Duflou, J 2016, Combining occupancy user profiles in a multi-user environment: An academic office case study. in S Chessa, G Hunter, T Kymalainen, S Poslad, S Middleton, T Huang, A Coronato, JC Augusto, S Egerton & R Loureiro (eds), Proceedings - 12th International Conference on Intelligent Environments, IE 2016., 7723494, Proceedings - 12th International Conference on Intelligent Environments, IE 2016, Institute of Electrical and Electronics Engineers Inc., pp. 186-189, 12th International Conference on Intelligent Environments, IE 2016, London, United Kingdom, 14/09/16. https://doi.org/10.1109/IE.2016.41

Combining occupancy user profiles in a multi-user environment: An academic office case study. / Auquilla, Andres; De Bock, Yannick; Nowe, Ann et al.
Proceedings - 12th International Conference on Intelligent Environments, IE 2016. ed. / Stefano Chessa; Gordon Hunter; Tiina Kymalainen; Stefan Poslad; Stuart Middleton; Tony Huang; Antonio Coronato; Juan Carlos Augusto; Simon Egerton; Rui Loureiro. Institute of Electrical and Electronics Engineers Inc., 2016. p. 186-189 7723494 (Proceedings - 12th International Conference on Intelligent Environments, IE 2016).

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

TY - GEN

T1 - Combining occupancy user profiles in a multi-user environment

T2 - 12th International Conference on Intelligent Environments, IE 2016

AU - Auquilla, Andres

AU - De Bock, Yannick

AU - Nowe, Ann

AU - Duflou, Joost

PY - 2016/10/26

Y1 - 2016/10/26

N2 - In a worldwide context, space heating is the largest energy consumer in commercial buildings, it accounts for 35% of the total energy consumed in the US. Energy efficient thermostats, that learn occupancy patterns and user preferences, haven been studied in literature. However, they are oriented to single-user environments, therefore, they are not applicable in offices where several users interact, i.e. multi-user environments. To expand the single-user techniques in order to cope with multi-user environments, two methods are proposed to derive the user's expected temperatures demands based on their occupancy profiles and individual preferences in terms of desired temperature and tolerance. This paper presents the implications of the implementation of such techniques by means of a case study of two users in an academic office. We observed that the proposed methods reduced the operational time up to 33% compared to a reference fixed schedule of 12 hours while maintaining user comfort. In conclusion, smart thermostats can also reduce energy consumption in multi-user environments while guaranteeing individual user expectations.

AB - In a worldwide context, space heating is the largest energy consumer in commercial buildings, it accounts for 35% of the total energy consumed in the US. Energy efficient thermostats, that learn occupancy patterns and user preferences, haven been studied in literature. However, they are oriented to single-user environments, therefore, they are not applicable in offices where several users interact, i.e. multi-user environments. To expand the single-user techniques in order to cope with multi-user environments, two methods are proposed to derive the user's expected temperatures demands based on their occupancy profiles and individual preferences in terms of desired temperature and tolerance. This paper presents the implications of the implementation of such techniques by means of a case study of two users in an academic office. We observed that the proposed methods reduced the operational time up to 33% compared to a reference fixed schedule of 12 hours while maintaining user comfort. In conclusion, smart thermostats can also reduce energy consumption in multi-user environments while guaranteeing individual user expectations.

KW - multi-user environment

KW - occupancy prediction

KW - smart thermostat

KW - user profile

UR - http://ieeexplore.ieee.org/document/7723494/

U2 - 10.1109/IE.2016.41

DO - 10.1109/IE.2016.41

M3 - Contribución a la conferencia

AN - SCOPUS:84998785515

T3 - Proceedings - 12th International Conference on Intelligent Environments, IE 2016

SP - 186

EP - 189

BT - Proceedings - 12th International Conference on Intelligent Environments, IE 2016

A2 - Chessa, Stefano

A2 - Hunter, Gordon

A2 - Kymalainen, Tiina

A2 - Poslad, Stefan

A2 - Middleton, Stuart

A2 - Huang, Tony

A2 - Coronato, Antonio

A2 - Augusto, Juan Carlos

A2 - Egerton, Simon

A2 - Loureiro, Rui

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 14 September 2016 through 16 September 2016

ER -

Auquilla A, De Bock Y, Nowe A, Duflou J. Combining occupancy user profiles in a multi-user environment: An academic office case study. In Chessa S, Hunter G, Kymalainen T, Poslad S, Middleton S, Huang T, Coronato A, Augusto JC, Egerton S, Loureiro R, editors, Proceedings - 12th International Conference on Intelligent Environments, IE 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 186-189. 7723494. (Proceedings - 12th International Conference on Intelligent Environments, IE 2016). doi: 10.1109/IE.2016.41

Combining occupancy user profiles in a multi-user environment: An academic office case study

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this