A Study on Autonomic Analysis for Servicing Intelligent Gas Safety Management Based on RFID/USN

RFID/USN 기반 지능형 가스안전관리 서비스를 위한 자율적 분석 연구

  • Published : 2008.12.31

Abstract

As RFID/USN technology is used in the latest industry trend, the information analysis paradigm shifts to intelligence service environment. The intelligent service includes autonomic operation, which select activity by defining itself to the status of industry facilities. Furthermore, information analysis based on IT used to frequently data mining for detecting the meaning information and deriving new pattern. This paper suggest self-classifying of context-aware by applying data mining in gas facilities for serving the intelligent gas safety management. We modify data algorithm for fitting the domain of gas safety, construct context-aware model by using the proposed algorithm, and demonstrate our method. As the accuracy of our model is improved over 90%, the our approach can apply to intelligent gas safety management based on RFID/USN environments.

Keywords

RFID/USN;data mining;intelligent service;context-aware model;gas safety management

References

  1. 박승민, "센서 네트워크 노드 플랫폼 및 운영체제 기술 동향", 전자통신동향분석, 제21권, 제1호, 2006
  2. Oil & Natural Gas Projects(Transmission, Distribution, and Refining, NETL, 2005
  3. M. Goeble and L. Gruenwald, "A Survey of Data Mining and Knowledge Discovery Software Tools", ACM SIGKDD Explorations, Vol. 1, No. 1, pp. 20-33, 1999
  4. G. Zangl and J. Hannerer, "Data Mining Applications in the Petroleum Industry", IBM Round Oak Publishing, 2003
  5. B. Heile, "Emerging Standards: Where does ZigBee fit", ZigBee Alliance, 2004
  6. Weka Public Mining Software tool, [http://www.cs.waikato.ac.nz/weka]
  7. A. Ganek and T. Corbi, "The Dawning of the Autonomic Computing Era", IBM Systems Journal, Vol. 42, No. 1, pp. 55-18, 2003
  8. D. Moorel, "Statistics Concepts and Controversies", W. H. Freemand and Company, 2001
  9. 한국전산원, "USN 기술동향 분석", 2005
  10. S. Elnaffar, P. Martin,and R. Horman "Automatically Classifying Database Workloads", CKIM Conference, pp. 622-624, 2002