Integration of social behavioral modeling for energy optimization in smart environments

Simone Silvestri; D. A. Baker; Valeria Dolce

doi:10.1145/3055601.3055618

Integration of social behavioral modeling for energy optimization in smart environments

Simone Silvestri, D. A. Baker, Valeria Dolce

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

8 Scopus citations

Abstract

A key requirement for success of smart home energy management systems is understanding the user's psychological perception of a smart environments, and the design of control strategies that specifically take into account such dimensions in system operation. We discuss how our research develops psychological models and integrates them with optimization and machine learning techniques to realize social and behavioral aware energy optimization methodologies for smart homes.

Original language	English
Title of host publication	Proceedings - 2017 2nd International Workshop on Social Sensing, SocialSens 2017 (part of CPS Week)
Pages	97
Number of pages	1
ISBN (Electronic)	9781450349772
DOIs	https://doi.org/10.1145/3055601.3055618
State	Published - Apr 18 2017
Event	2nd International Workshop on Social Sensing, SocialSens 2017 - Pittsburgh, United States Duration: Apr 21 2017 → …

Publication series

Name	Proceedings - 2017 2nd International Workshop on Social Sensing, SocialSens 2017 (part of CPS Week)

Conference

Conference	2nd International Workshop on Social Sensing, SocialSens 2017
Country/Territory	United States
City	Pittsburgh
Period	4/21/17 → …

Bibliographical note

Publisher Copyright:
© 2017 ACM.

Keywords

Energy management
Smart living
Social-behavioral models

ASJC Scopus subject areas

Signal Processing
Computer Networks and Communications

Access to Document

10.1145/3055601.3055618

Cite this

Silvestri, S., Baker, D. A., & Dolce, V. (2017). Integration of social behavioral modeling for energy optimization in smart environments. In Proceedings - 2017 2nd International Workshop on Social Sensing, SocialSens 2017 (part of CPS Week) (pp. 97). (Proceedings - 2017 2nd International Workshop on Social Sensing, SocialSens 2017 (part of CPS Week)). https://doi.org/10.1145/3055601.3055618

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abstract = "A key requirement for success of smart home energy management systems is understanding the user's psychological perception of a smart environments, and the design of control strategies that specifically take into account such dimensions in system operation. We discuss how our research develops psychological models and integrates them with optimization and machine learning techniques to realize social and behavioral aware energy optimization methodologies for smart homes.",

keywords = "Energy management, Smart living, Social-behavioral models",

author = "Simone Silvestri and Baker, {D. A.} and Valeria Dolce",

note = "Publisher Copyright: {\textcopyright} 2017 ACM. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; 2nd International Workshop on Social Sensing, SocialSens 2017 ; Conference date: 21-04-2017",

year = "2017",

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doi = "10.1145/3055601.3055618",

language = "English",

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Silvestri, S, Baker, DA & Dolce, V 2017, Integration of social behavioral modeling for energy optimization in smart environments. in Proceedings - 2017 2nd International Workshop on Social Sensing, SocialSens 2017 (part of CPS Week). Proceedings - 2017 2nd International Workshop on Social Sensing, SocialSens 2017 (part of CPS Week), pp. 97, 2nd International Workshop on Social Sensing, SocialSens 2017, Pittsburgh, United States, 4/21/17. https://doi.org/10.1145/3055601.3055618

Integration of social behavioral modeling for energy optimization in smart environments. / Silvestri, Simone; Baker, D. A.; Dolce, Valeria.
Proceedings - 2017 2nd International Workshop on Social Sensing, SocialSens 2017 (part of CPS Week). 2017. p. 97 (Proceedings - 2017 2nd International Workshop on Social Sensing, SocialSens 2017 (part of CPS Week)).

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

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AU - Baker, D. A.

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AB - A key requirement for success of smart home energy management systems is understanding the user's psychological perception of a smart environments, and the design of control strategies that specifically take into account such dimensions in system operation. We discuss how our research develops psychological models and integrates them with optimization and machine learning techniques to realize social and behavioral aware energy optimization methodologies for smart homes.

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KW - Smart living

KW - Social-behavioral models

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ER -

Integration of social behavioral modeling for energy optimization in smart environments

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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