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

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.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.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.2020.0037S1622World Health Organization:‘Novel coronavirus (2019‐ncov): Situation report 91’ [accessed 30‐April‐2020]Instituto de Salud.Carlos.III:‘Situación de covid‐19 en españa’ [accessed 30‐April‐2020].https://covid19.isciii.es/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:10.1101/2020.03.09.20033241World Health Organization:‘Critical preparedness readiness and response actions for COVID‐19: interim guidance 22 March 2020’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.abb5793International 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]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:10.1145/2794400AdolphC.AmanoK.Bang JensenB.et al.: ‘Pandemic politics: timing state‐level social distancing responses to COVID‐19’ medRxiv 202