ERFS: Enhanced RSSI value Filtering Schema for Localization in Wireless Sensor Networks

  • Seung-chan Shin
  • Byung-rak Son
  • Won-geun Kim
  • Jung-gyu Kim
Part of the IFIP – The International Federation for Information Processing book series (IFIPAICT, volume 264)


In this research, we have suggested the Localization Algorithm using Probable Filtering Schema of RSSI without additional hardwares. The existing method has been filtering with only average and feedback of received RSSI values. This method was not considering about the variation of RSSI when obstacles are moving at indoor environment. In this research, we have suggested the probable filtering algorithm which is considered factors of errors at indoor environment and we have demonstrated the superiority of this algorithm through the examination. It presents 14.66% and 11.65% improved accuracy than the existing filtering algorithm.


Sensor Node Wireless Sensor Network Location Information Indoor Environment Distance Estimation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© IFIP International Federation for Information Processing 2008

Authors and Affiliations

  • Seung-chan Shin
    • 1
  • Byung-rak Son
    • 1
  • Won-geun Kim
    • 1
  • Jung-gyu Kim
    • 1
  1. 1.Department of Information Communication EngineeringDaegu UniversityRepublic of Korea

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