research-article

ThermoCoach: Reducing Home Energy Consumption with Personalized Thermostat Recommendations

Authors:

Devika Pisharoty,

Mark W. Newman,

Kamin WhitehouseAuthors Info & Claims

BuildSys '15: Proceedings of the 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments

Pages 201 - 210

https://doi.org/10.1145/2821650.2821671

Published: 04 November 2015 Publication History

Abstract

Thermostats have the potential for tremendous impact on global energy consumption, but unfortunately they are often not used effectively. In this paper, we present a new system called ThermoCoach that improves thermostat usability by giving personalized and actionable recommendations for thermostat use. The system senses human occupancy patterns in a home and emails the household suggested setpoint schedules that can be modified or activated with the click of a button. We performed a randomized controlled trial by deploying over 600 devices in 40 homes from 12 weeks to compare ThermoCoach with a manually programmable thermostat and the Nest learning thermostat. Results indicate that ThermoCoach saves 4.7% more energy than a manually programmable thermostat and 12.4% more energy than the Nest learning thermostat while significantly improving comfort over both approaches.

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Cited By

Luo MZheng QZhao YZhao FZhou X(2023)Developing occupant-centric smart home thermostats with energy-saving and comfort-improving goalsEnergy and Buildings10.1016/j.enbuild.2023.113579299(113579)Online publication date: Nov-2023
https://doi.org/10.1016/j.enbuild.2023.113579
Ham SKarava PBilionis IBraun J(2022)A scalable and practical method for disaggregating heating and cooling electrical usage using smart thermostat and smart metre dataJournal of Building Performance Simulation10.1080/19401493.2022.203235215:2(251-267)Online publication date: 7-Feb-2022
https://doi.org/10.1080/19401493.2022.2032352
Ham SKarava PBilionis IBraun J(2021)Real-time model for unit-level heating and cooling energy prediction in multi-family residential housingJournal of Building Performance Simulation10.1080/19401493.2021.196849514:4(420-445)Online publication date: 25-Aug-2021
https://doi.org/10.1080/19401493.2021.1968495
Show More Cited By

Index Terms

ThermoCoach: Reducing Home Energy Consumption with Personalized Thermostat Recommendations

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cover image ACM Conferences

BuildSys '15: Proceedings of the 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments

November 2015

264 pages

ISBN:9781450339810

DOI:10.1145/2821650

General Chair:
David Culler
University of California, Berkeley, USA
,
Program Chairs:
Yuvraj Agarwal
Carnegie Mellon University, USA
,
Rahul Mangharam
University of Pennslyvania, USA

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 04 November 2015

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National Science Foundation

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BuildSys '15

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BuildSys '15: The 2nd ACM International Conference on Embedded Systems for Energy-Efficient Built Environments

November 4 - 5, 2015

Seoul, South Korea

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BuildSys '15 Paper Acceptance Rate 20 of 66 submissions, 30%;

Overall Acceptance Rate 148 of 500 submissions, 30%

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Cited By

Luo MZheng QZhao YZhao FZhou X(2023)Developing occupant-centric smart home thermostats with energy-saving and comfort-improving goalsEnergy and Buildings10.1016/j.enbuild.2023.113579299(113579)Online publication date: Nov-2023
https://doi.org/10.1016/j.enbuild.2023.113579
Ham SKarava PBilionis IBraun J(2022)A scalable and practical method for disaggregating heating and cooling electrical usage using smart thermostat and smart metre dataJournal of Building Performance Simulation10.1080/19401493.2022.203235215:2(251-267)Online publication date: 7-Feb-2022
https://doi.org/10.1080/19401493.2022.2032352
Ham SKarava PBilionis IBraun J(2021)Real-time model for unit-level heating and cooling energy prediction in multi-family residential housingJournal of Building Performance Simulation10.1080/19401493.2021.196849514:4(420-445)Online publication date: 25-Aug-2021
https://doi.org/10.1080/19401493.2021.1968495
Ham SKarava PBilionis IBraun J(2021)A data-driven model for building energy normalization to enable eco-feedback in multi-family residential buildings with smart and connected technologyJournal of Building Performance Simulation10.1080/19401493.2021.192875514:4(343-365)Online publication date: 29-May-2021
https://doi.org/10.1080/19401493.2021.1928755
Trivedi ABovornkeeratiroj PBreda JShenoy PTaneja JIrwin D(2021)Phone-based ambient temperature sensing using opportunistic crowdsensing and machine learningSustainable Computing: Informatics and Systems10.1016/j.suscom.2020.10047929(100479)Online publication date: Mar-2021
https://doi.org/10.1016/j.suscom.2020.100479
Breda JTrivedi AWijesundara CBovornkeeratiroj PIrwin DShenoy PTaneja J(2019)Hot or NotProceedings of the 6th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3360322.3360856(41-50)Online publication date: 13-Nov-2019
https://dl.acm.org/doi/10.1145/3360322.3360856
Cardell-Oliver RSarkar C(2019)BuildSenseACM Transactions on Sensor Networks10.1145/334117115:3(1-23)Online publication date: 9-Aug-2019
https://dl.acm.org/doi/10.1145/3341171
Kuijer LGiaccardi EMandryk RHancock MPerry MCox A(2018)Co-performanceProceedings of the 2018 CHI Conference on Human Factors in Computing Systems10.1145/3173574.3173699(1-13)Online publication date: 21-Apr-2018
https://dl.acm.org/doi/10.1145/3173574.3173699
Goulden MSpence AWardman JLeygue C(2018)Differentiating ‘the user’ in DSR: Developing demand side response in advanced economiesEnergy Policy10.1016/j.enpol.2018.07.013122(176-185)Online publication date: Nov-2018
https://doi.org/10.1016/j.enpol.2018.07.013
Law MThirani MRollins SJoshi ABanerjee N(2018)Understanding Home Energy Saving RecommendationsPersuasive Technology10.1007/978-3-319-78978-1_25(297-309)Online publication date: 3-Apr-2018
https://doi.org/10.1007/978-3-319-78978-1_25
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