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dc.contributorUniversitat Ramon Llull. La Salle
dc.contributor.authorAlsina Pagès, Rosa Maria
dc.contributor.authorAlías Pujol, Francesc
dc.contributor.authorSocoró Carrié, Joan Claudi
dc.contributor.authorOrga Vidal, Ferran
dc.date.accessioned2020-03-25T18:00:13Z
dc.date.accessioned2023-10-02T06:43:35Z
dc.date.available2020-03-25T18:00:13Z
dc.date.available2023-10-02T06:43:35Z
dc.date.created2018-03
dc.date.issued2018-04
dc.identifier.urihttp://hdl.handle.net/20.500.14342/3435
dc.description.abstractOne of the main aspects affecting the quality of life of people living in urban and suburban areas is the continuous exposure to high road traffic noise (RTN) levels. Nowadays, thanks to Wireless Acoustic Sensor Networks (WASN) noise in Smart Cities has started to be automatically mapped. To obtain a reliable picture of the RTN, those anomalous noise events (ANE) unrelated to road traffic (sirens, horns, people, etc.) should be removed from the noise map computation by means of an Anomalous Noise Event Detector (ANED). In Hybrid WASNs, with master-slave architecture, ANED should be implemented in both high-capacity (Hi-Cap) and low-capacity (Lo-Cap) sensors, following the same principle to obtain consistent results. This work presents an ANED version to run in real-time on μ Controller-based Lo-Cap sensors of a hybrid WASN, discriminating RTN from ANE through their Mel-based spectral energy differences. The experiments, considering 9 h and 8 min of real-life acoustic data from both urban and suburban environments, show the feasibility of the proposal both in terms of computational load and in classification accuracy. Specifically, the ANED Lo-Cap requires around 16/ of the computational load of the ANED Hi-Cap, while classification accuracies are slightly lower (around 10%). However, preliminary analyses show that these results could be improved in around 4% in the future by means of considering optimal frequency selection.
dc.format.extent23 p.
dc.language.isoeng
dc.publisherMDPI
dc.relation.ispartofSensors. 2018, Vol.18, No.4
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.otherSoroll
dc.subject.otherSoroll urbà
dc.titleDetection of Anomalous Noise Events on Low-Capacity Acoustic Nodes for Dynamic Road Traffic Noise Mapping within an Hybrid WASN
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/s18041272
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/LIFE/LIFE13 ENV-IT-001254
dc.relation.projectIDinfo:eu-repo/grantAgreement/URL i SUR del DEC/Projectes recerca PDI/2017-URL-Proj-013
dc.relation.projectIDinfo:eu-repo/grantAgreement/SUR del DEC/SGR/2017-SGR-966
dc.relation.projectIDinfo:eu-repo/grantAgreement/SUR del DEC i FSE/FI/2017FI_B00243


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Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/
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