• DocumentCode
    3192782
  • Title

    BodyCloud: Integration of Cloud Computing and body sensor networks

  • Author

    Fortino, Giancarlo ; Pathan, M. ; Di Fatta, Giuseppe

  • Author_Institution
    DEIS, Univ. of Calabria, Rende, Italy
  • fYear
    2012
  • fDate
    3-6 Dec. 2012
  • Firstpage
    851
  • Lastpage
    856
  • Abstract
    Spatially distributed sensor nodes can be used to monitor systems and humans conditions in a wide range of application domains. A network of body sensors in a community of people generates large amounts of contextual data that requires a scalable approach for storage and processing. Cloud computing can provide a powerful, scalable storage and processing infrastructure to perform both online and offline analysis and mining of body sensor data streams. This paper presents BodyCloud, a system architecture based on Cloud Computing for the management and monitoring of body sensor data streams. It incorporates key concepts such as scalability and flexibility of resources, sensor heterogeneity, and the dynamic deployment and management of user and community applications.
  • Keywords
    body sensor networks; cloud computing; data mining; health care; patient monitoring; BodyCloud; body sensor data stream management; body sensor data stream mining; body sensor data stream monitoring; body sensor networks; cloud computing; community applications; contextual data; healthcare scenario; offline analysis; online analysis; processing infrastructure; resource flexibility; resource scalability; sensor heterogeneity; spatially distributed sensor nodes; storage infrastructure; user dynamic deployment; user management; Biomedical monitoring; Cloud computing; Computer architecture; Medical services; Monitoring; Real-time systems; Wireless sensor networks; Body Sensors; Cloud Computing; Data Mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing Technology and Science (CloudCom), 2012 IEEE 4th International Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    978-1-4673-4511-8
  • Electronic_ISBN
    978-1-4673-4509-5
  • Type

    conf

  • DOI
    10.1109/CloudCom.2012.6427537
  • Filename
    6427537