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dc.contributorUniversitat Ramon Llull. La Salle
dc.contributor.authorAlsina Pagès, Rosa Maria
dc.contributor.authorOrga Vidal, Ferran
dc.contributor.authorAlías Pujol, Francesc
dc.contributor.authorSocoró Carrié, Joan Claudi
dc.date.accessioned2020-03-27T15:23:34Z
dc.date.accessioned2023-10-02T06:41:50Z
dc.date.available2020-03-27T15:23:34Z
dc.date.available2023-10-02T06:41:50Z
dc.date.created2019-03
dc.date.issued2019-05
dc.identifier.urihttp://hdl.handle.net/20.500.14342/3417
dc.description.abstractTraffic noise is presently considered one of the main pollutants in urban and suburban areas. Several recent technological advances have allowed a step forward in the dynamic computation of road-traffic noise levels by means of a Wireless Acoustic Sensor Network (WASN) through the collection of measurements in real-operation environments. In the framework of the LIFE DYNAMAP project, two WASNs have been deployed in two pilot areas: one in the city of Milan, as an urban environment, and another around the city of Rome in a suburban location. For a correct evaluation of the noise level generated by road infrastructures, all Anomalous Noise Events (ANE) unrelated to regular road-traffic noise (e.g., sirens, horns, speech, etc.) should be removed before updating corresponding noise maps. This work presents the production and analysis of a real-operation environmental audio database collected through the 19-node WASN of a suburban area. A total of 156 h and 20 min of labeled audio data has been obtained differentiating among road-traffic noise and ANEs (classified in 16 subcategories). After delimiting their boundaries manually, the acoustic salience of the ANE samples is automatically computed as a contextual Signal-to-Noise Ratio (SNR) together with its impact on the A-weighted equivalent level ( ΔLAeq ). The analysis of the real-operation WASN-based environmental database is evaluated with these metrics, and we conclude that the 19 locations of the network present substantial differences in the occurrences of the subcategories of ANE, with a clear predominance of the noise of sirens, trains, and thunder.eng
dc.format.extent21 p.
dc.language.isoeng
dc.publisherMDPI
dc.relation.ispartofSensors. 2019, Vol. 19, No. 11
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 urbà
dc.subject.otherContaminació acústica
dc.titleA WASN-Based Suburban Dataset for Anomalous Noise Event Detection on Dynamic Road-Traffic Noise Mapping
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/s19112480
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/LIFE/LIFE13 ENV-IT-001254
dc.relation.projectIDinfo:eu-repo/grantAgreement/URL i La Caixa/Intensificació recerca PDI/2018-URL-IR2nQ-029
dc.relation.projectIDinfo:eu-repo/grantAgreement/URL i La Caixa/Intensificació recerca PDI/2018-URL-IR2nQ-038
dc.relation.projectIDinfo:eu-repo/grantAgreement/SUR del DEC i FSE/FI/2019_FI_B2_00168


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