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Mobile crowdsensing approaches to address the COVID-19 pandemic in Spain

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Mobile crowdsensing approaches to address the COVID-19 pandemic in Spain

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dc.contributor.author Cecilia-Canales, José María es_ES
dc.contributor.author Cano, Juan-Carlos es_ES
dc.contributor.author Hernández-Orallo, Enrique es_ES
dc.contributor.author Tavares De Araujo Cesariny Calafate, Carlos Miguel es_ES
dc.contributor.author Manzoni, Pietro es_ES
dc.date.accessioned 2021-03-10T04:31:37Z
dc.date.available 2021-03-10T04:31:37Z
dc.date.issued 2020-07 es_ES
dc.identifier.uri http://hdl.handle.net/10251/163587
dc.description.abstract [EN] Mobile crowdsensing (MCS) is a technique where people with computing and sensing devices such as smartphones collectively share data that are of potential interest to the rest of society. MCS includes two different trends (i) mobile sensing, which shares raw data generated from the sensors that are embedded in mobile devices, and (ii) social sensing, which uses the information shared by people in online social networks (OSNs). In this study, the authors present the timeline evolution of the COVID¿19 pandemic in Spain, and summarise the MCS research efforts that are being undertaken by the Spanish community to address COVID¿19 outbreak. Indeed, the COVID¿19 pandemic is putting today's society at risk; lockdown and social distancing measures proposed by governments are dramatically affecting economies. In this regard, MCS tools can become a powerful solution to provide smart quarantine strategies in periods of a steep decrease of infections, or new outbreaks. es_ES
dc.description.sponsorship This work was partially supported by the Fundación Séneca del Centro de Coordinación de la Investigación de la Región de Murcia under Project 20813/PI/18, and by the Spanish Ministry of Science, Innovation and Universities under grants RTI2018-096384-B-I00 and RTC-2017-6389-5. es_ES
dc.language Inglés es_ES
dc.publisher Institution of Engineering and Technology es_ES
dc.relation.ispartof IET Smart Cities es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title Mobile crowdsensing approaches to address the COVID-19 pandemic in Spain es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1049/iet-smc.2020.0037 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/f SéNeCa//20813%2FPI%2F18/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//RTC-2017-6389-5/ES/PLANIFICACIÓN Y GESTIÓN DE RECURSOS HÍDRICOS A PARTIR DE ANÁLISIS DE DATOS DE IoT (WATERoT)/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-096384-B-I00/ES/SOLUCIONES PARA UNA GESTION EFICIENTE DEL TRAFICO VEHICULAR BASADAS EN SISTEMAS Y SERVICIOS EN RED/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI//RYC-2018-025580-I/ 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 Cecilia-Canales, JM.; Cano, J.; Hernández-Orallo, E.; Tavares De Araujo Cesariny Calafate, CM.; Manzoni, P. (2020). Mobile crowdsensing approaches to address the COVID-19 pandemic in Spain. IET Smart Cities. 2(2):1-6. https://doi.org/10.1049/iet-smc.2020.0037 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1049/iet-smc.2020.0037 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 6 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 2 es_ES
dc.description.issue 2 es_ES
dc.identifier.eissn 2631-7680 es_ES
dc.relation.pasarela S\425205 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.contributor.funder Fundación Séneca-Agencia de Ciencia y Tecnología de la Región de Murcia es_ES
dc.description.references World Health Organization:‘Novel coronavirus (2019‐ncov): Situation report 91’ [accessed 30‐April‐2020] es_ES
dc.description.references Instituto de Salud.Carlos.III:‘Situación de covid‐19 en españa’ [accessed 30‐April‐2020].https://covid19.isciii.es/ es_ES
dc.description.references LiR.RiversC.TanQ.et al.: ‘The demand for inpatient and ICU beds for COVID‐19 in the US: lessons from Chinese cities’ medRxiv 2020 pp.1–12 doi:10.1101/2020.03.09.20033241 es_ES
dc.description.references World Health Organization:‘Critical preparedness readiness and response actions for COVID‐19: interim guidance 22 March 2020’ es_ES
dc.description.references Kissler, S. M., Tedijanto, C., Goldstein, E., Grad, Y. H., & Lipsitch, M. (2020). Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period. Science, 368(6493), 860-868. doi:10.1126/science.abb5793 es_ES
dc.description.references International Labour Organization: ‘The socioeconomic impact of COVID‐19 in fragile settings: peace and social cohesion at risk’ https://www.ilo.org/global/topics/employment‐promotion/recovery‐and‐reconstruction/WCMS_741158/langen/index.htm [accessed 30‐April‐2020] 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 AdolphC.AmanoK.Bang JensenB.et al.: ‘Pandemic politics: timing state‐level social distancing responses to COVID‐19’ medRxiv 2020 es_ES


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