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dc.contributorUniversitat Ramon Llull. La Salle
dc.contributor.authorNavarro Martín, Joan
dc.contributor.authorVidaña Vila, Ester
dc.contributor.authorAlsina Pagès, Rosa Maria
dc.contributor.authorHervás García, Marcos
dc.date.accessioned2020-03-25T16:19:55Z
dc.date.accessioned2023-10-02T06:44:25Z
dc.date.available2020-03-25T16:19:55Z
dc.date.available2023-10-02T06:44:25Z
dc.date.created2018-05
dc.date.issued2018-08
dc.identifier.urihttp://hdl.handle.net/20.500.14342/3444
dc.description.abstractAmbient Assisted Living (AAL) has become a powerful alternative to improving the life quality of elderly and partially dependent people in their own living environments. In this regard, tele-care and remote surveillance AAL applications have emerged as a hot research topic in this domain. These services aim to infer the patients’ status by means of centralized architectures that collect data from a set of sensors deployed in their living environment. However, when the size of the scenario and number of patients to be monitored increase (e.g., residential areas, retirement homes), these systems typically struggle at processing all associated data and providing a reasonable output in real time. The purpose of this paper is to present a fog-inspired distributed architecture to collect, analyze and identify up to nine acoustic events that represent abnormal behavior or dangerous health conditions in large-scale scenarios. Specifically, the proposed platform collects data from a set of wireless acoustic sensors and runs an automatic two-stage audio event classification process to decide whether or not to trigger an alarm. Conducted experiments over a labeled dataset of 7116 s based on the priorities of the Fundació Ave Maria health experts have obtained an overall accuracy of 94.6%.eng
dc.format.extent22 p.
dc.language.isoeng
dc.publisherMDPI
dc.relation.ispartofSensors. 2018, Vol. 18, No.8.
dc.rightsAttribution 4.0 International
dc.rights© L'autor/a
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceRECERCAT (Dipòsit de la Recerca de Catalunya)
dc.subject.otherAcústica
dc.subject.otherBiosensors
dc.titleReal-Time Distributed Architecture for Remote Acoustic Elderly Monitoring in Residential-Scale Ambient Assisted Living Scenarios
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscap
dc.identifier.doihttps://doi.org/10.3390/s18082492
dc.relation.projectIDinfo:eu-repo/grantAgreement/SUR del DEC/SGR/2017-SGR-977


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Attribution 4.0 International
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