• DocumentCode
    2524980
  • Title

    The Multiplicity of Intelligent Agent Based Healthcare Sensor Decision Network

  • Author

    Dai, Zhifeng ; Sun, Baolin ; Zhang, Qifei

  • Author_Institution
    Sch. of Comput., Hubei Univ. of Econ., Wuhan, China
  • fYear
    2009
  • fDate
    11-13 June 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    With the emerging awareness of health care, this paper addresses the challenging research issue of healthcare sensor decision. On light of the technology combination of WSN, MAS and RST, and its contribution to the framework of healthcare sensor decision network, this work further studies the multiplicity of intelligent agent based healthcare sensor decision network, and proposes the hierarchical model DHMASDN and its corresponding agent layer built healthcare sensor decision network, attribute layer built healthcare sensor decision network and rule layer built healthcare sensor decision network. Furthermore, the tutorial algorithm and results are also given based on rule layer built healthcare sensor decision network. And as expected, the presented model, algorithm and illustrative results are demonstrated to be more helpful to enhance the integrality and reliability of healthcare sensor decision network than those of previous related works.
  • Keywords
    health care; hierarchical systems; intelligent sensors; multi-agent systems; reliability; rough set theory; wireless sensor networks; agent layer built; healthcare sensor decision network; hierarchical model; integrality; intelligent agent; multiagent system; multiplicity; reliability; rough set theory; rule layer built; wireless sensor network; Computer networks; Diseases; Intelligent agent; Intelligent networks; Intelligent sensors; Medical services; Sensor fusion; Sensor phenomena and characterization; Sensor systems; Wireless sensor networks;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-2901-1
  • Electronic_ISBN
    978-1-4244-2902-8
  • Type

    conf

  • DOI
    10.1109/ICBBE.2009.5163634
  • Filename
    5163634