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dc.contributor.authorRuiz Jiménez, María Dolores 
dc.contributor.authorGómez Romero, Juan 
dc.contributor.authorFernández Basso, Carlos Jesús 
dc.contributor.authorMartín Bautista, María José 
dc.date.accessioned2025-01-15T11:32:29Z
dc.date.available2025-01-15T11:32:29Z
dc.date.issued2022
dc.identifier.urihttps://hdl.handle.net/10481/99239
dc.description.abstractThe enormous quantity of data handled by building management systems are key to develop more efficient energy operational systems. However, the inability of current systems to take benefit from the generated data may waste good opportunities of improving building performance. Big Data appears as a suitable framework to sustain the management system and conduct future prospective analysis. In this article, we present a Big Data-based architecture for the efficient management of buildings. The different Big Data components are involved not only in the data acquisition phase, but also in the implementation of algorithms capable of analyzing massive data collected from very heterogeneous sources. They also enable fast computations that can help the generation of optimal operational plan generations to improve the building functioning. The proposed architecture has been effectively introduced in four different-purpose buildings, demonstrating that Big Data can help during the energy cycle of the building.es_ES
dc.language.isoenges_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleBig data architecture for building energy management systemses_ES
dc.typejournal articlees_ES
dc.relation.projectIDEnergy IN TIME EeB.NMP.2013-4es_ES
dc.rights.accessRightsopen accesses_ES
dc.identifier.doihttps://doi.org/10.1109/TII.2021.3130052
dc.type.hasVersionAMes_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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