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JACIII Vol.15 No.9 pp. 1287-1298
doi: 10.20965/jaciii.2011.p1287
(2011)

Paper:

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Using Radio Frequency Identification for Indoor Location Identification Based on Power Level, Signal Strength and Fuzzy Method

Rung-Ching Chen, Yu-Cheng Lin, Sheng-Ling Huang,
and Qiangfu Zhao

Chaoyang University of Technology, 168 Jifeng E. Rd., Wufeng District, Taichung 41349, Taiwan, R.O.C.

Received:
April 12, 2011
Accepted:
August 24, 2011
Published:
November 20, 2011
Creative Commons License
Keywords:
RFID, indoor position location, RSS, power level, fuzzy set theory
Abstract
In recent years, there has been a dramatic proliferation of research concerned with Radio Frequency Identification (RFID). RFID technologies are getting considerable attention not only from academic research but also from the applications for enterprise. One of the most important application issues prevailing throughout the last few decades of RFID application research is the indoor position location. Many researchers have used varied technologies to perform the action of indoor position location tracking. In our research, we propose a new method using RFID tags to perform indoor position location tracking. This method uses Received Signal Strength (RSS) to collect signal strengths from reference tags beforehand, and then uses the signal strengths to set up Power Level areas of range by reference tags. Next, using the signal strengths from the reference tags we match signal strengths with track tags. Finally, when the track tags are set up in indoor environments, they can find the position of neighboring reference tags by using the fuzzy set theory and an arithmetic mean to calculate the position location values; with this method we are able to break figures down to track tag position locations. We conducted this experiment to prove that our methodology can provide better accuracy than the LANDMARC system.
Cite this article as:
R. Chen, Y. Lin, S. Huang, and Q. Zhao, “Using Radio Frequency Identification for Indoor Location Identification Based on Power Level, Signal Strength and Fuzzy Method,” J. Adv. Comput. Intell. Intell. Inform., Vol.15 No.9, pp. 1287-1298, 2011.
Data files:
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