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IoT-based COVID-19 diagnosing and monitoring systems: a survey

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dc.contributor.authorAnjum, Nasreen
dc.contributor.authorAlibakhshikenari, Mohammad
dc.contributor.authorRashid, Junaid
dc.contributor.authorJabeen, Fouzia
dc.contributor.authorAsif, Amna
dc.contributor.authorMohamed, Ehab Mahmoud
dc.contributor.authorFalcone Lanas, Francisco Javier
dc.contributor.departmentIngeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzareneu
dc.contributor.departmentInstitute of Smart Cities - ISCen
dc.contributor.departmentIngenierĆ­a ElĆ©ctrica, ElectrĆ³nica y de ComunicaciĆ³nes_ES
dc.date.accessioned2023-01-20T09:58:38Z
dc.date.available2023-01-20T09:58:38Z
dc.date.issued2022
dc.date.updated2023-01-20T09:30:29Z
dc.description.abstractTo date, the novel Coronavirus (SARS-CoV-2) has infected millions and has caused the deaths of thousands of people around the world. At the moment, five antibodies, two from China, two from the U.S., and one from the UK, have already been widely utilized and numerous vaccines are under the trail process. In order to reach herd immunity, around 70% of the population would need to be inoculated. It may take several years to hinder the spread of SARS-CoV-2. Governments and concerned authorities have taken stringent measurements such as enforcing partial, complete, or smart lockdowns, building temporary medical facilities, advocating social distancing, and mandating masks in public as well as setting up awareness campaigns. Furthermore, there have been massive efforts in various research areas and a wide variety of tools, technologies and techniques have been explored and developed to combat the war against this pandemic. Interestingly, machine learning (ML) algorithms and internet of Things (IoTs) technology are the pioneers in this race. Up till now, several real-time and intelligent IoT-based COVID-19 diagnosing, and monitoring systems have been proposed to tackle the pandemic. In this article we have analyzed a wide range of IoTs technologies which can be used in diagnosing and monitoring the infected individuals and hotspot areas. Furthermore, we identify the challenges and also provide our vision about the future research on COVID-19.en
dc.description.sponsorshipDr. Mohammad Alibakhshikenari acknowledges support from the CONEX-Plus programme funded by Universidad Carlos III de Madrid and the European Unionā€™s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 801538. Additionally, this work was supported by Project RTI2018-095499-B-C31, funded by the Ministerio de Ciencia, InnovaciĆ³n y Universidades, Gobierno de EspaƱa (MCIU/AEI/FEDER, UE).en
dc.format.mimetypeapplication/pdfen
dc.identifier.citationAnjum, N., Alibakhshikenari, M., Rashid, J., Jabeen, F., Asif, A., Mohamed, E. M., & Falcone, F. (2022). Iot-based covid-19 diagnosing and monitoring systems: A survey. IEEE Access, 10, 87168-87181. https://doi.org/10.1109/ACCESS.2022.3197164en
dc.identifier.doi10.1109/ACCESS.2022.3197164
dc.identifier.issn2169-3536
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/44610
dc.language.isoengen
dc.publisherIEEEen
dc.relation.ispartofIEEE Access 2022, 10 (87168)en
dc.relation.projectIDinfo:eu-repo/grantAgreement/European Commission/Horizon 2020 Framework Programme/801538en
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de InvestigaciĆ³n CientĆ­fica y TĆ©cnica y de InnovaciĆ³n 2017-2020/RTI2018-095499-B-C31/ES/en
dc.relation.publisherversionhttps://doi.org/10.1109/ACCESS.2022.3197164
dc.rightsThis work is licensed under a Creative Commons Attribution 4.0 License.en
dc.rights.accessRightsAcceso abierto / Sarbide irekiaes
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectArtificial intelligence (AI)en
dc.subjectCoronavirusen
dc.subjectCOVID-19 pandemicen
dc.subjectInternet of Things (IoTs)en
dc.subjectMachine learning algorithmsen
dc.titleIoT-based COVID-19 diagnosing and monitoring systems: a surveyen
dc.typeArtĆ­culo / Artikuluaes
dc.typeinfo:eu-repo/semantics/articleen
dc.type.versionVersiĆ³n publicada / Argitaratu den bertsioaes
dc.type.versioninfo:eu-repo/semantics/publishedVersionen
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relation.isAuthorOfPublication69667b5c-e390-42d4-bc71-9f256c1b7b85
relation.isAuthorOfPublication.latestForDiscovery69667b5c-e390-42d4-bc71-9f256c1b7b85

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