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dc.contributor.authorAntón, Miguel Ángel
dc.contributor.authorOrdieres-Meré, Joaquín
dc.contributor.authorSaralegui, Unai
dc.contributor.authorSun, Shengjing
dc.date.accessioned2019-07-22T12:00:20Z
dc.date.available2019-07-22T12:00:20Z
dc.date.issued2019
dc.identifier.citationAntón, Miguel Ángel, Joaquín Ordieres-Meré, Unai Saralegui, and Shengjing Sun. “Non-Invasive Ambient Intelligence in Real Life: Dealing with Noisy Patterns to Help Older People.” Sensors 19, no. 14 (July 14, 2019): 3113. doi:10.3390/s19143113.en
dc.identifier.issn1424-3210en
dc.identifier.urihttp://hdl.handle.net/11556/745
dc.description.abstractThis paper aims to contribute to the field of ambient intelligence from the perspective of real environments, where noise levels in datasets are significant, by showing how machine learning techniques can contribute to the knowledge creation, by promoting software sensors. The created knowledge can be actionable to develop features helping to deal with problems related to minimally labelled datasets. A case study is presented and analysed, looking to infer high-level rules, which can help to anticipate abnormal activities, and potential benefits of the integration of these technologies are discussed in this context. The contribution also aims to analyse the usage of the models for the transfer of knowledge when different sensors with different settings contribute to the noise levels. Finally, based on the authors’ experience, a framework proposal for creating valuable and aggregated knowledge is depicted.en
dc.description.sponsorshipThis research was partially funded by Fundación Tecnalia Research & Innovation, and J.O.-M. also wants to recognise the support obtained from the EU RFCS program through project number 793505 ‘4.0 Lean system integrating workers and processes (WISEST)’ and from the grant PRX18/00036 given by the Spanish Secretaría de Estado de Universidades, Investigación, Desarrollo e Innovación del Ministerio de Ciencia, Innovación y Universidades.en
dc.language.isoengen
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)en
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.titleNon-Invasive Ambient Intelligence in Real Life: Dealing with Noisy Patterns to Help Older Peopleen
dc.typearticleen
dc.identifier.doi10.3390/s19143113en
dc.rights.accessRightsopenAccessen
dc.subject.keywordsSmart buildingen
dc.subject.keywordsIoTen
dc.subject.keywordsMachine learningen
dc.subject.keywordsAmbient intelligenceen
dc.subject.keywordsAmbient assisted livingen
dc.identifier.essn1424-8220en
dc.issue.number14en
dc.journal.titleSensorsen
dc.page.initial3113en
dc.volume.number19en


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