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Exploring Temporal Analytics in Fog-Cloud Architecture for Smart Office HealthCare

Bhatia, Munish ; Sood, Sandeep K.

Mobile networks and applications, 2019-08, Vol.24 (4), p.1392-1410 [Periódico revisado por pares]

New York: Springer US

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  • Título:
    Exploring Temporal Analytics in Fog-Cloud Architecture for Smart Office HealthCare
  • Autor: Bhatia, Munish ; Sood, Sandeep K.
  • Assuntos: Cloud computing ; Communications Engineering ; Computer architecture ; Computer Communication Networks ; Computing time ; Electrical Engineering ; Engineering ; Health care ; Information storage ; Information technology ; Internet of Things ; IT in Business ; Networks ; Personal health ; Working hours
  • É parte de: Mobile networks and applications, 2019-08, Vol.24 (4), p.1392-1410
  • Descrição: Ever since the boost realized in Information and Communication Technology (ICT), market is flooded with high-end multi-tasking devices, presenting a real-time computational environment for technologies like Internet of Things (IoT). With computation at user-end, it provides a fog-based computing paradigm to generate time senstive results, which along with cloud storage presents a comprehensive Fog-Cloud computing paradigm. Because of these reasons, the work presented in this paper focuses on utilizing the potential of IoT Technology to provide a novel Fog-Cloud architecture for efficient healthcare services in smart office. Specifically, a Fog-Cloud architecture has been proposed to monitor and analyze various health attributes of a person during his working hours. Moreover, the framework indulges various activities in the ambient office environment with the purpose of analyzing it for health severity. In order to realize this, a probabilistic measure, named as Severity Index (SI) is defined to evaluate the adverse effects of different activities on personal health. Finally, an application scenario of temporal healthcare predictive monitoring and alert generation is discussed to depict the ideology of Smart Office Healthcare. In order to validate the system, an experimental implmentation is performed on heterogenous datasets. The results obtained in comparison to state-of-the-art techniques show that the proposed model is highly efficient and accurate for providing appropriate healthcare environment during working hours of a person in a smart office.
  • Editor: New York: Springer US
  • Idioma: Inglês
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  • Realização: ABCD-USP USP   Logos de Redes Sociais: Freepik

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