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CIoTVID: Towards an Open IoT-Platform for Infective Pandemic Diseases such as COVID-19.
Ramallo-González, Alfonso P; González-Vidal, Aurora; Skarmeta, Antonio F.
Afiliação
  • Ramallo-González AP; Department of Information and Communication Engineering, Faculty of Computer Science, University of Murcia, 30100 Murcia, Spain.
  • González-Vidal A; Department of Information and Communication Engineering, Faculty of Computer Science, University of Murcia, 30100 Murcia, Spain.
  • Skarmeta AF; Department of Information and Communication Engineering, Faculty of Computer Science, University of Murcia, 30100 Murcia, Spain.
Sensors (Basel) ; 21(2)2021 Jan 12.
Article em En | MEDLINE | ID: mdl-33445499
ABSTRACT
The factors affecting the penetration of certain diseases such as COVID-19 in society are still unknown. Internet of Things (IoT) technologies can play a crucial role during the time of crisis and they can provide a more holistic view of the reasons that govern the outbreak of a contagious disease. The understanding of COVID-19 will be enriched by the analysis of data related to the phenomena, and this data can be collected using IoT sensors. In this paper, we show an integrated solution based on IoT technologies that can serve as opportunistic health data acquisition agents for combating the pandemic of COVID-19, named CIoTVID. The platform is composed of four layers-data acquisition, data aggregation, machine intelligence and services, within the solution. To demonstrate its validity, the solution has been tested with a use case based on creating a classifier of medical conditions using real data of voice, performing successfully. The layer of data aggregation is particularly relevant in this kind of solution as the data coming from medical devices has a very different nature to that coming from electronic sensors. Due to the adaptability of the platform to heterogeneous data and volumes of data; individuals, policymakers, and clinics could benefit from it to fight the propagation of the pandemic.
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Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Processamento de Sinais Assistido por Computador / Internet das Coisas / COVID-19 Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Espanha

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Processamento de Sinais Assistido por Computador / Internet das Coisas / COVID-19 Tipo de estudo: Diagnostic_studies Limite: Humans Idioma: En Revista: Sensors (Basel) Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Espanha