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Understanding the limitations of eco-feedback: a one-year long-term study

dc.contributor.authorPereira, Lucas
dc.contributor.authorQuintal, Filipe
dc.contributor.authorBarreto, Mary
dc.contributor.authorNunes, Nuno J.
dc.date.accessioned2022-08-04T10:15:11Z
dc.date.available2022-08-04T10:15:11Z
dc.date.issued2013
dc.description.abstractFor the last couple of decades the world has been witnessing a change in habits of energy consumption in domestic environments, with elec tricity emerging as the main source of energy consumed. The effects of these changes in our eco-system are hard to assess, therefore encouraging researchers from different fields to conduct studies with the goal of understanding and im proving perceptions and behaviors regarding household energy consumption. While several of these studies report success in increasing awareness, most of them are limited to short periods of time, thus resulting in a reduced knowledge of how householders will behave in the long-term. In this paper we attempt to reduce this gap presenting a long-term study on household electricity consump tion. We deployed a real-time non-intrusive energy monitoring and eco feedback system in 12 families during 52 weeks. Results show an increased awareness regarding electricity consumption despite a significant decrease in interactions with the eco-feedback system over time. We conclude that after one year of deployment of eco-feedback it was not possible to see any significant increase or decrease in the household consumption. Our results also confirm that consumption is tightly coupled with independent variables like the house hold size and the income-level of the families.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationPereira, L., Quintal, F., Barreto, M., & Nunes, N. J. (2013, July). Understanding the limitations of eco-feedback: a one-year long-term study. In International Workshop on Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Data (pp. 237-255). Springer, Berlin, Heidelberg. DOI: 10.1007/978-3-642-39146-0_21pt_PT
dc.identifier.doi10.1007/978-3-642-39146-0_21pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.13/4508
dc.language.isoengpt_PT
dc.publisherSpringerpt_PT
dc.relationAMBIENT INTELLIGENT SERVICES: FROM FICTION TO REALITY
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/pt_PT
dc.subjectEco-feedbackpt_PT
dc.subjectElectric energy consumptionpt_PT
dc.subjectSustainabilitypt_PT
dc.subject.pt_PT
dc.subjectFaculdade de Ciências Exatas e da Engenhariapt_PT
dc.subjectEscola Superior de Tecnologias e Gestãopt_PT
dc.titleUnderstanding the limitations of eco-feedback: a one-year long-term studypt_PT
dc.typeconference object
dspace.entity.typePublication
oaire.awardTitleAMBIENT INTELLIGENT SERVICES: FROM FICTION TO REALITY
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/OE/SFRH%2FBD%2F77856%2F2011/PT
oaire.citation.endPage255pt_PT
oaire.citation.startPage237pt_PT
oaire.citation.titleInternational Workshop on Human-Computer Interaction and Knowledge Discovery in Complex, Unstructured, Big Datapt_PT
oaire.citation.volume7947pt_PT
oaire.fundingStreamOE
person.familyNameQuintal
person.familyNameBarreto
person.familyNameNunes
person.givenNameFilipe
person.givenNameMary
person.givenNameNuno
person.identifier1333903
person.identifier1379802
person.identifier.ciencia-idEC10-568D-FB0A
person.identifier.ciencia-idDE1D-5AAF-B0A9
person.identifier.orcid0000-0002-3525-142X
person.identifier.orcid0000-0002-9619-4254
person.identifier.orcid0000-0002-2498-0643
person.identifier.ridC-8682-2018
person.identifier.ridC-9134-2018
person.identifier.ridM-4006-2013
person.identifier.scopus-author-id6504228821
person.identifier.scopus-author-id50361028500
person.identifier.scopus-author-id8704415000
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typeconferenceObjectpt_PT
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