Machine Learning for Smart Building Applications: Review and Taxonomy

dc.contributor.authorDjenouri, Djamel
dc.contributor.authorLaidi, Roufaida
dc.contributor.authorDjenouri, Youcef
dc.contributor.authorBalasingham, Ilangko
dc.date.accessioned2019-04-05T16:21:44Z
dc.date.available2019-04-05T16:21:44Z
dc.date.issued2019-03
dc.description.abstractThe use of machine learning (ML) in smart building applications is reviewed in this paper. We split existing solutions into two main classes, occupant-centric vs. energy/devices centric. The first class groups solutions that use ML for aspects related to the occupants, including (1) occupancy estimation and identification, (2) activity recognition, and (3) estimating preferences and behavior. The second class groups solutions that use ML to estimate aspects related either to energy or devices. They are divided into three categories, (1) energy profiling and demand estimation, (2) appliances profiling and fault detection, and (3) inference on sensors. Solutions in each category are presented, discussed and compared, as well as open perspectives and research trends. Compared to related state-of-the-art survey papers, the contribution herein is to provide a comprehensive and holistic review from the ML perspectives rather than architectural and technical aspects of existing building management systems. This is by considering all types of ML tools, buildings, and several categories of applications, and by structuring the taxonomy accordingly. The paper ends with a summary discussion of the presented works, with focus on lessons learned, challenges, open and future directions of research in this field.fr_FR
dc.identifier.issn0360-0300fr_FR
dc.identifier.urihttp://dl.cerist.dz/handle/CERIST/937
dc.publisherACMfr_FR
dc.relation.ispartofseriesACM Computing Surveys (CSUR), 52(2);24
dc.relation.pages24:1--24:36fr_FR
dc.structureRéseaux de capteurs et Applicationsfr_FR
dc.subjectMachine learning, Smart buildings, Smart cities, Internet of Thingsfr_FR
dc.titleMachine Learning for Smart Building Applications: Review and Taxonomyfr_FR
dc.typeArticle
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