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Accurate Ambient Noise Assessment Using Smartphones

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Accurate Ambient Noise Assessment Using Smartphones

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dc.contributor.author Zamora-Mero, Willian Jesus es_ES
dc.contributor.author Tavares de Araujo Cesariny Calafate, Carlos Miguel es_ES
dc.contributor.author Cano, Juan-Carlos es_ES
dc.contributor.author Manzoni, Pietro es_ES
dc.date.accessioned 2018-05-14T04:18:53Z
dc.date.available 2018-05-14T04:18:53Z
dc.date.issued 2017 es_ES
dc.identifier.uri http://hdl.handle.net/10251/101891
dc.description.abstract [EN] Nowadays, smartphones have become ubiquitous and one of the main communication resources for human beings. Their widespread adoption was due to the huge technological progress and to the development of multiple useful applications. Their characteristics have also experienced a substantial improvement as they now integrate multiple sensors able to convert the smartphone into a flexible and multi-purpose sensing unit. The combined use of multiple smartphones endowed with several types of sensors gives the possibility to monitor a certain area with fine spatial and temporal granularity, a procedure typically known as crowdsensing. In this paper, we propose using smartphones as environmental noise-sensing units. For this purpose, we focus our study on the sound capture and processing procedure, analyzing the impact of different noise calculation algorithms, as well as in determining their accuracy when compared to a professional noise measurement unit. We analyze different candidate algorithms using different types of smartphones, and we study the most adequate time period and sampling strategy to optimize the data-gathering process. In addition, we perform an experimental study comparing our approach with the results obtained using a professional device. Experimental results show that, if the smartphone application is well tuned, it is possible to measure noise levels with a accuracy degree comparable to professional devices for the entire dynamic range typically supported by microphones embedded in smartphones, i.e., 35 95 dB. es_ES
dc.description.sponsorship This work was partially supported by the “Programa Estatal de Investigación, Desarrollo e InnovaciOn Orientada a Retos de la Sociedad, Proyecto TEC2014-52690-R”, the “Universidad Laica Eloy Alfaro de Manabí” and the “Programa de Becas SENESCYTde la República del Ecuador.”
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Sensors es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Crowdsensing es_ES
dc.subject Smartphone es_ES
dc.subject Noise sensing es_ES
dc.subject Dynamic range es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title Accurate Ambient Noise Assessment Using Smartphones es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/s17040917 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TEC2014-52690-R/ES/INTEGRACION DEL SMARTPHONE Y EL VEHICULO PARA CONECTAR CONDUCTORES, SENSORES Y ENTORNO A TRAVES DE UNA ARQUITECTURA DE SERVICIOS FUNCIONALES/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors es_ES
dc.description.bibliographicCitation Zamora-Mero, WJ.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Manzoni, P. (2017). Accurate Ambient Noise Assessment Using Smartphones. Sensors. 17(4):1-18. doi:10.3390/s17040917 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/s17040917 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 18 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 17 es_ES
dc.description.issue 4 es_ES
dc.identifier.eissn 1424-8220 es_ES
dc.identifier.pmid 28430126 en_EN
dc.identifier.pmcid PMC5426841 en_EN
dc.relation.pasarela S\336197 es_ES
dc.contributor.funder Ministerio de Economía, Industria y Competitividad es_ES
dc.description.references Noise European Environment Agencyhttp://www.eea.europa.eu/themes/noise/intro es_ES
dc.description.references Zannin, P. H. T., Ferreira, A. M. C., & Szeremetta, B. (2006). Evaluation of Noise Pollution in Urban Parks. Environmental Monitoring and Assessment, 118(1-3), 423-433. doi:10.1007/s10661-006-1506-6 es_ES
dc.description.references Kanjo, E. (2009). NoiseSPY: A Real-Time Mobile Phone Platform for Urban Noise Monitoring and Mapping. Mobile Networks and Applications, 15(4), 562-574. doi:10.1007/s11036-009-0217-y es_ES
dc.description.references Assessment and management of environmental noise (EU Directive)http://eur-lex.europa.eu/eli/dir/2002/49/oj es_ES
dc.description.references Commission Directive (EU) 2015/ 996 of 19 May 2015http://eur-lex.europa.eu/eli/dir/2015/996/oj es_ES
dc.description.references Lane, N., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., & Campbell, A. (2010). A survey of mobile phone sensing. IEEE Communications Magazine, 48(9), 140-150. doi:10.1109/mcom.2010.5560598 es_ES
dc.description.references Ganti, R., Ye, F., & Lei, H. (2011). Mobile crowdsensing: current state and future challenges. IEEE Communications Magazine, 49(11), 32-39. doi:10.1109/mcom.2011.6069707 es_ES
dc.description.references Guo, B., Wang, Z., Yu, Z., Wang, Y., Yen, N. Y., Huang, R., & Zhou, X. (2015). Mobile Crowd Sensing and Computing. ACM Computing Surveys, 48(1), 1-31. doi:10.1145/2794400 es_ES
dc.description.references Maisonneuve, N., Stevens, M., Niessen, M. E., & Steels, L. (2009). NoiseTube: Measuring and mapping noise pollution with mobile phones. Environmental Science and Engineering, 215-228. doi:10.1007/978-3-540-88351-7_16 es_ES
dc.description.references Rana, R., Chou, C. T., Bulusu, N., Kanhere, S., & Hu, W. (2015). Ear-Phone: A context-aware noise mapping using smart phones. Pervasive and Mobile Computing, 17, 1-22. doi:10.1016/j.pmcj.2014.02.001 es_ES
dc.description.references Kardous, C. A., & Shaw, P. B. (2014). Evaluation of smartphone sound measurement applications. The Journal of the Acoustical Society of America, 135(4), EL186-EL192. doi:10.1121/1.4865269 es_ES
dc.description.references Le Prell, C., Nast, D., & Speer, W. (2014). Sound level measurements using smartphone «apps»: Useful or inaccurate? Noise and Health, 16(72), 251. doi:10.4103/1463-1741.140495 es_ES
dc.description.references Sonometer PCE322Ahttp://www.pce-iberica.es/medidor-detalles-tecnicos/instrumento-de-ruido/sonometro-con-logger-de-datos-sl-322.htm es_ES
dc.description.references Kardous, C. A., & Shaw, P. B. (2016). Evaluation of smartphone sound measurement applications (apps) using external microphones—A follow-up study. The Journal of the Acoustical Society of America, 140(4), EL327-EL333. doi:10.1121/1.4964639 es_ES
dc.description.references Zamora, W., Calafate, C. T., Cano, J.-C., & Manzoni, P. (2016). A Survey on Smartphone-Based Crowdsensing Solutions. Mobile Information Systems, 2016, 1-26. doi:10.1155/2016/9681842 es_ES
dc.description.references Electroacoustics—Sound level meters—Part 1: Specificationshttps://webstore.iec.ch/publication/5708 es_ES
dc.description.references Samsung Galaxy S7 edge SM-G935T Complimentary Teardown Report with Additional Commentaryhttp://www.techinsights.com/about-techinsights/overview/blog/samsung-galaxy-s7-edge-teardown/ es_ES


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