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dc.contributorUniversitat Ramon Llull. La Salle
dc.contributor.authorNavarro Martín, Joan
dc.contributor.authorAlsina Pagès, Rosa Maria
dc.contributor.authorHervás García, Marcos
dc.date.accessioned2020-03-25T18:28:09Z
dc.date.accessioned2023-10-02T06:43:12Z
dc.date.available2020-03-25T18:28:09Z
dc.date.available2023-10-02T06:43:12Z
dc.date.created2017-04
dc.date.issued2017-05
dc.identifier.urihttp://hdl.handle.net/20.500.14342/3431
dc.description.abstractHuman life expectancy has grown over the last century, which has driven governments to increase the efforts on caring about the eldest population. Therefore, modern trends take advantage of latest advances in technology to remotely monitor those people with special needs at their home, increasing their life quality and with less impact on their social lives. This paper presents an acoustic event detection platform for assisted living that tracks patients’ status by automatically identifying and analyzing the acoustic events happening in a house. Specifically, we have taken benefit of a Jetson TK1, with its NVIDIA Graphical Processing Unit, to process the acoustic data and identify a closed number of events in order to inform the care system. This is a proof of concept conducted with data of only one acoustic sensor, but we plan in the future to deploy a sensor network in several places in the house.eng
dc.format.extent8 p.
dc.language.isoeng
dc.publisherIFSA
dc.relation.ispartofSensors & Transducers Journal. 2017. Vol.212, No.5 (Maig)
dc.rights© L'autor/a
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceRECERCAT (Dipòsit de la Recerca de Catalunya)
dc.subject.otherAcústica
dc.subject.otherSoroll
dc.titleHome Sound: a GPU-based Platform for Massive Data Acquisition and Processing for Acoustic Ambient Assisted Living Applications for Behavior Monitoring
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscap
dc.relation.projectIDinfo:eu-repo/grantAgreement/SUR del DEC/SGR/2014-SGR-0590
dc.relation.projectIDinfo:eu-repo/grantAgreement/SUR del DEC/SGR/2014-SGR-589


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