• DocumentCode
    2717138
  • Title

    Intelligent Information Processing of WSN Based on Vague Sets Theory and Applied in Control of Coal Mine Monitoring

  • Author

    Tian Yi-ming ; Huang You-rui ; Huang Yi-qing

  • Author_Institution
    Coll. of Electr. & Inf. Eng., Anhui Univ. of Sci. & Technol., Huainan
  • Volume
    2
  • fYear
    2008
  • fDate
    3-4 Aug. 2008
  • Firstpage
    649
  • Lastpage
    652
  • Abstract
    To overcome the disadvantage of the imperfect and uncertain data and redundancy node, reduce energy efficiency of communications and data processing, an optimization model based on agent distributed computation is proposed. In this model, vague set theory is used to optimize and reduce data. Furthermore, it is applied to intelligent information processing of wireless sensor networks (WSN) as clusters shape. Meanwhile, in the real-time demonstration of coal mine monitoring, the analysis indicate that this method may optimize the node scale and make node automatic gain and transmit effective minimum information, through carrying on the data analysis to each cluster, reducing the knowledge, choosing the decision rule, realize the energy efficiency optimization. At last, a practical project verifies its effectiveness.
  • Keywords
    computerised monitoring; fuzzy set theory; mining industry; optimisation; wireless sensor networks; agent distributed computation; automatic gain; coal mine monitoring control; data processing; intelligent information processing; optimization model; redundancy node; uncertain data; vague sets theory; wireless sensor network; Communication system control; Data processing; Distributed computing; Energy efficiency; Information processing; Intelligent networks; Monitoring; Optimization methods; Set theory; Wireless sensor networks; Information Processing; Vague Sets; WSN;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computing, Communication, Control, and Management, 2008. CCCM '08. ISECS International Colloquium on
  • Conference_Location
    Guangzhou
  • Print_ISBN
    978-0-7695-3290-5
  • Type

    conf

  • DOI
    10.1109/CCCM.2008.221
  • Filename
    4609768