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Providing personalized energy management and awareness services for energy efficiency in smart buildings

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dc.contributor.authorFotopoulou, Eleni
dc.contributor.authorZafeiropoulos, Anastasios
dc.contributor.authorSimsek, Umutcan
dc.contributor.authorGonzález Vidal, Aurora
dc.contributor.authorTsiolis, George
dc.contributor.authorGouvas, Panagiotis
dc.contributor.authorLiapis, Paris
dc.contributor.authorFensel, Anna
dc.contributor.authorSkarmeta Gómez, Antonio
dc.contributor.authorTerroso Sáenz, Fernando
dc.contributor.departmentIngeniería de la Información y las Comunicaciones
dc.contributor.otherFacultades de la UMU::Facultad de Informática
dc.date.accessioned2026-02-18T12:05:48Z
dc.date.available2026-02-18T12:05:48Z
dc.date.copyright© 2017 by the authors
dc.date.issued2017-09-07
dc.description.abstractConsidering that the largest part of end-use energy consumption worldwide is associated with the buildings sector, there is an inherent need for the conceptualization, specification, implementation, and instantiation of novel solutions in smart buildings, able to achieve significant reductions in energy consumption through the adoption of energy efficient techniques and the active engagement of the occupants. Towards the design of such solutions, the identification of the main energy consuming factors, trends, and patterns, along with the appropriate modeling and understanding of the occupants’ behavior and the potential for the adoption of environmentally-friendly lifestyle changes have to be realized. In the current article, an innovative energy-aware information technology (IT) ecosystem is presented, aiming to support the design and development of novel personalized energy management and awareness services that can lead to occupants’ behavioral change towards actions that can have a positive impact on energy efficiency. Novel information and communication technologies (ICT) are exploited towards this direction, related mainly to the evolution of the Internet of Things (IoT), data modeling, management and fusion, big data analytics, and personalized recommendation mechanisms. The combination of such technologies has resulted in an open and extensible architectural approach able to exploit in a homogeneous, efficient and scalable way the vast amount of energy, environmental, and behavioral data collected in energy efficiency campaigns and lead to the design of energy management and awareness services targeted to the occupants’ lifestyles. The overall layered architectural approach is detailed, including design and instantiation aspects based on the selection of set of available technologies and tools. Initial results from the usage of the proposed energy aware IT ecosystem in a pilot site at the University of Murcia are presented along with a set of identified open issues for future research.
dc.formatapplication/pdf
dc.format.extent21
dc.identifier.citationSensors, 2017, Vol. 17(9), 2054
dc.identifier.doihttps://doi.org/10.3390/s17092054
dc.identifier.eissn1424-8220
dc.identifier.urihttp://hdl.handle.net/10201/207503
dc.languageeng
dc.publisherMDPI
dc.relationThis work is supported by the European Commission Research Programs through the Entropy Project under Contract H2020-649849.
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/17/9/2054
dc.rightsAttribution 4.0 International*
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectBehavioral change
dc.subjectPersonalized recommendations
dc.subjectEnergy analytics
dc.subjectBehavioral analytics;
dc.subjectBig data analytics
dc.subjectInternet of Things
dc.subjectIoT
dc.subjectDrools
dc.subjectRules management system
dc.subjectSemantic reasoning
dc.subjectEnergy efficiency
dc.subject.odsNo relacionado con ningún objetivo de desarrollo sostenible
dc.titleProviding personalized energy management and awareness services for energy efficiency in smart buildings
dc.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dspace.entity.typePublicationes
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relation.isAuthorOfPublication04e7e654-2e93-49b7-89d8-6a351be20dd3
relation.isAuthorOfPublication.latestForDiscoverycf8009bf-6088-449d-9f79-a516af312945
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