Understanding the energy behavior of building occupants through the chronology of their energy interactions

Danielle Preziuso; Gregory Kaminski; Philip Odonkor

doi:10.1115/DETC2021-69953

Understanding the energy behavior of building occupants through the chronology of their energy interactions

Danielle Preziuso
, Gregory Kaminski
, Philip Odonkor

Stevens Institute of Technology

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

Abstract

The energy consumption of buildings has traditionally been driven by the consumption habits of building occupants. However, with the proliferation of smart building technologies and appliances, automated machine decisions are beginning to impart their influence on building energy behavior as well. This is giving rise to a disconnect between occupant energy behavior and the overall energy consumption of buildings. Consequently, researchers can no longer leverage building energy consumption as a proxy for understanding human energy behavior. This paper addresses this problem by exploiting the habitual and sequential nature of human energy consumption. By studying the chronology of human energy actions, the results of this work present a promising new approach for non-intrusively learning about human energy behavior directly from building energy demand data.

Original language	English
Title of host publication	47th Design Automation Conference (DAC)
ISBN (Electronic)	9780791885383
DOIs	https://doi.org/10.1115/DETC2021-69953
State	Published - 2021
Event	47th Design Automation Conference, DAC 2021, Held as Part of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2021 - Virtual, Online Duration: 17 Aug 2021 → 19 Aug 2021

Publication series

Name	Proceedings of the ASME Design Engineering Technical Conference
Volume	3A-2021

Conference

Conference	47th Design Automation Conference, DAC 2021, Held as Part of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2021
City	Virtual, Online
Period	17/08/21 → 19/08/21

UN SDGs

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

SDG 7 Affordable and Clean Energy

Keywords

Energy analysis
Gaussian mixture models
Human energy behavior

Access to Document

10.1115/DETC2021-69953

Cite this

@inproceedings{972253e86da04f3e9e0a7c3377adcbaa,

title = "Understanding the energy behavior of building occupants through the chronology of their energy interactions",

abstract = "The energy consumption of buildings has traditionally been driven by the consumption habits of building occupants. However, with the proliferation of smart building technologies and appliances, automated machine decisions are beginning to impart their influence on building energy behavior as well. This is giving rise to a disconnect between occupant energy behavior and the overall energy consumption of buildings. Consequently, researchers can no longer leverage building energy consumption as a proxy for understanding human energy behavior. This paper addresses this problem by exploiting the habitual and sequential nature of human energy consumption. By studying the chronology of human energy actions, the results of this work present a promising new approach for non-intrusively learning about human energy behavior directly from building energy demand data.",

keywords = "Energy analysis, Gaussian mixture models, Human energy behavior",

author = "Danielle Preziuso and Gregory Kaminski and Philip Odonkor",

note = "Publisher Copyright: Copyright {\textcopyright} 2021 by ASME.; 47th Design Automation Conference, DAC 2021, Held as Part of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2021 ; Conference date: 17-08-2021 Through 19-08-2021",

year = "2021",

doi = "10.1115/DETC2021-69953",

language = "English",

series = "Proceedings of the ASME Design Engineering Technical Conference",

booktitle = "47th Design Automation Conference (DAC)",

}

Preziuso, D, Kaminski, G & Odonkor, P 2021, Understanding the energy behavior of building occupants through the chronology of their energy interactions. in 47th Design Automation Conference (DAC)., V03AT03A014, Proceedings of the ASME Design Engineering Technical Conference, vol. 3A-2021, 47th Design Automation Conference, DAC 2021, Held as Part of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2021, Virtual, Online, 17/08/21. https://doi.org/10.1115/DETC2021-69953

Understanding the energy behavior of building occupants through the chronology of their energy interactions. / Preziuso, Danielle; Kaminski, Gregory; Odonkor, Philip.
47th Design Automation Conference (DAC). 2021. V03AT03A014 (Proceedings of the ASME Design Engineering Technical Conference; Vol. 3A-2021).

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

TY - GEN

T1 - Understanding the energy behavior of building occupants through the chronology of their energy interactions

AU - Preziuso, Danielle

AU - Kaminski, Gregory

AU - Odonkor, Philip

PY - 2021

Y1 - 2021

N2 - The energy consumption of buildings has traditionally been driven by the consumption habits of building occupants. However, with the proliferation of smart building technologies and appliances, automated machine decisions are beginning to impart their influence on building energy behavior as well. This is giving rise to a disconnect between occupant energy behavior and the overall energy consumption of buildings. Consequently, researchers can no longer leverage building energy consumption as a proxy for understanding human energy behavior. This paper addresses this problem by exploiting the habitual and sequential nature of human energy consumption. By studying the chronology of human energy actions, the results of this work present a promising new approach for non-intrusively learning about human energy behavior directly from building energy demand data.

AB - The energy consumption of buildings has traditionally been driven by the consumption habits of building occupants. However, with the proliferation of smart building technologies and appliances, automated machine decisions are beginning to impart their influence on building energy behavior as well. This is giving rise to a disconnect between occupant energy behavior and the overall energy consumption of buildings. Consequently, researchers can no longer leverage building energy consumption as a proxy for understanding human energy behavior. This paper addresses this problem by exploiting the habitual and sequential nature of human energy consumption. By studying the chronology of human energy actions, the results of this work present a promising new approach for non-intrusively learning about human energy behavior directly from building energy demand data.

KW - Energy analysis

KW - Gaussian mixture models

KW - Human energy behavior

UR - https://www.scopus.com/pages/publications/85119994540

UR - https://www.scopus.com/pages/publications/85119994540#tab=citedBy

U2 - 10.1115/DETC2021-69953

DO - 10.1115/DETC2021-69953

M3 - Conference contribution

AN - SCOPUS:85119994540

T3 - Proceedings of the ASME Design Engineering Technical Conference

BT - 47th Design Automation Conference (DAC)

T2 - 47th Design Automation Conference, DAC 2021, Held as Part of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2021

Y2 - 17 August 2021 through 19 August 2021

ER -

Understanding the energy behavior of building occupants through the chronology of their energy interactions

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

Other files and links

Fingerprint

Cite this