Long term energy savings through user behaviour modeling in smart homes
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/28621 |
Resumo: | The Internet of Things (IoT) has enabled real-time monitoring of energy consumption in smart homes through sensors embedded in the surrounding environment. In the post-pandemic world, domestic energy management has gained importance due to increased work-from-home consumption, making data collection in a smart home a relevant IoT application with many potential energy savings. However, this information is difficult for most users to understand, and existing monitoring systems’ savings results degrade over time. To address these challenges, this study presents a novel approach for domestic energy consumption, production, and comfort perception using color-based dashboards enhanced for user feedback interaction. The approach includes the management of in-home appliances and comfort levels according to user preferences to attain long-term energy savings. The approach includes multiple appealing strategies such as 3D representation, mobile connectivity, utility integration, and dynamic information, to increase long-term engagement and provides quantitative data on energy savings achieved for one year, where the average energy consumption was reduced by 19%. It was found that the approach sustained user engagement over time, with users actively participating in energy conservation efforts. A community survey with 208 participants was also developed and studied where 69% of the enquired considered our approach more attractive than existing market solutions, and 79% considered it more useful than existing solutions. Regarding the real-time information presented on our approach, 81% of the participants strongly or totally agree that it can change users’ behaviors. |
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Long term energy savings through user behaviour modeling in smart homesIoTHome energy consumptionLong-term engagementUser behaviorSustainabilityThe Internet of Things (IoT) has enabled real-time monitoring of energy consumption in smart homes through sensors embedded in the surrounding environment. In the post-pandemic world, domestic energy management has gained importance due to increased work-from-home consumption, making data collection in a smart home a relevant IoT application with many potential energy savings. However, this information is difficult for most users to understand, and existing monitoring systems’ savings results degrade over time. To address these challenges, this study presents a novel approach for domestic energy consumption, production, and comfort perception using color-based dashboards enhanced for user feedback interaction. The approach includes the management of in-home appliances and comfort levels according to user preferences to attain long-term energy savings. The approach includes multiple appealing strategies such as 3D representation, mobile connectivity, utility integration, and dynamic information, to increase long-term engagement and provides quantitative data on energy savings achieved for one year, where the average energy consumption was reduced by 19%. It was found that the approach sustained user engagement over time, with users actively participating in energy conservation efforts. A community survey with 208 participants was also developed and studied where 69% of the enquired considered our approach more attractive than existing market solutions, and 79% considered it more useful than existing solutions. Regarding the real-time information presented on our approach, 81% of the participants strongly or totally agree that it can change users’ behaviors.IEEE2023-05-18T08:37:17Z2023-01-01T00:00:00Z20232023-05-18T09:37:17Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/28621eng2169-353610.1109/ACCESS.2023.3272888Mataloto, B.Ferreira, J.Resende, R.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:59:14Zoai:repositorio.iscte-iul.pt:10071/28621Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:31:03.049673Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Long term energy savings through user behaviour modeling in smart homes |
title |
Long term energy savings through user behaviour modeling in smart homes |
spellingShingle |
Long term energy savings through user behaviour modeling in smart homes Mataloto, B. IoT Home energy consumption Long-term engagement User behavior Sustainability |
title_short |
Long term energy savings through user behaviour modeling in smart homes |
title_full |
Long term energy savings through user behaviour modeling in smart homes |
title_fullStr |
Long term energy savings through user behaviour modeling in smart homes |
title_full_unstemmed |
Long term energy savings through user behaviour modeling in smart homes |
title_sort |
Long term energy savings through user behaviour modeling in smart homes |
author |
Mataloto, B. |
author_facet |
Mataloto, B. Ferreira, J. Resende, R. |
author_role |
author |
author2 |
Ferreira, J. Resende, R. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Mataloto, B. Ferreira, J. Resende, R. |
dc.subject.por.fl_str_mv |
IoT Home energy consumption Long-term engagement User behavior Sustainability |
topic |
IoT Home energy consumption Long-term engagement User behavior Sustainability |
description |
The Internet of Things (IoT) has enabled real-time monitoring of energy consumption in smart homes through sensors embedded in the surrounding environment. In the post-pandemic world, domestic energy management has gained importance due to increased work-from-home consumption, making data collection in a smart home a relevant IoT application with many potential energy savings. However, this information is difficult for most users to understand, and existing monitoring systems’ savings results degrade over time. To address these challenges, this study presents a novel approach for domestic energy consumption, production, and comfort perception using color-based dashboards enhanced for user feedback interaction. The approach includes the management of in-home appliances and comfort levels according to user preferences to attain long-term energy savings. The approach includes multiple appealing strategies such as 3D representation, mobile connectivity, utility integration, and dynamic information, to increase long-term engagement and provides quantitative data on energy savings achieved for one year, where the average energy consumption was reduced by 19%. It was found that the approach sustained user engagement over time, with users actively participating in energy conservation efforts. A community survey with 208 participants was also developed and studied where 69% of the enquired considered our approach more attractive than existing market solutions, and 79% considered it more useful than existing solutions. Regarding the real-time information presented on our approach, 81% of the participants strongly or totally agree that it can change users’ behaviors. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-05-18T08:37:17Z 2023-01-01T00:00:00Z 2023 2023-05-18T09:37:17Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/28621 |
url |
http://hdl.handle.net/10071/28621 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2169-3536 10.1109/ACCESS.2023.3272888 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
IEEE |
publisher.none.fl_str_mv |
IEEE |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799134872252448768 |