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dc.contributorUniversitat Ramon Llull. La Salle
dc.contributor.authorAlsina Pagès, Rosa Maria
dc.contributor.authorSocoró Carrié, Joan Claudi
dc.contributor.authorAlías Pujol, Francesc
dc.date.accessioned2020-07-06T12:24:44Z
dc.date.accessioned2023-07-13T09:52:05Z
dc.date.available2020-07-06T12:24:44Z
dc.date.available2023-07-13T09:52:05Z
dc.date.issued2017-11-13
dc.identifier.urihttp://hdl.handle.net/20.500.14342/2894
dc.description.abstractOne of the main aspects affecting the life of people living in urban and suburban areas is their continued exposure to high road traffic noise (RTN) levels, traditionally measured by specialists working on the field. Nowadays, the deployment of Wireless Acoustic Sensor Networks (WASN) has allowed to automate noise mapping in Smart Cities. In order to obtain a reliable picture of the RTN levels affecting citizens, those anomalous noise events (ANE) unrelated to road traffic should be removed from the noise map computation. For this purpose, an Anomalous Noise Event Detector (ANED) designed to differentiate in real-time between RTN and ANE should be developed to run on the low-cost acoustic sensors of the WASN. In this work, the viability of implementing the ANED algorithm to run on low-capacity (LowCap) μ controller-based acoustic sensors developed within the DYNAMAP project is presented, after being designed and implemented for the high-capacity sensors. The algorithm is based on the comparison between RTN and ANE spectral differences using real-life acoustic data from both suburban and urban scenarios. The results show significant spectral differences between RTN and ANE classes in both environments, after being parametrized using Gammatone Cepstral Coefficients. However, further research should be conducted to determine the most discriminant subbands, which should be taken into account for the implementation of the ANED LowCap version.eng
dc.format.extent8 p.cat
dc.language.isoengcat
dc.publisher4th International Electronic Conference on Sensors and Applicationscat
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.otherSoroll urbàcat
dc.subject.otherCirculació -- Sorollcat
dc.subject.otherContaminació acústicacat
dc.titleDetecting Anomalous Noise Events on Low-Capacity Acoustic Sensor in Dynamic Road Traffic Noise Mappingcat
dc.typeinfo:eu-repo/semantics/articlecat
dc.typeinfo:eu-repo/semantics/publishedVersioncat
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscapcat
dc.identifier.doihttps://doi.org/10.3390/ecsa-4-04897cat
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/LIFE/LIFE13 ENV-IT-001254cat
dc.relation.projectIDinfo:eu-repo/grantAgreement/SUR del DEC/SGR/2014-SGR-0590cat
dc.relation.projectIDinfo:eu-repo/grantAgreement/URL i SUR del DEC/Projectes recerca PDI/2017-URL-Proj-013cat


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Attribution 4.0 International
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