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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 |