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http://dx.doi.org/10.6109/jkiice.2018.22.11.1442

RFID Indoor Location Recognition with Obstacle Using Neural Network  

Lee, Jong-Hyun (Department of Electronic Engineering, Incheon National University)
Lee, Kang-bin (Department of Electronic Engineering, Incheon National University)
Hong, Yeon-chan (Department of Electronic Engineering, Incheon National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.22, no.11, 2018 , pp. 1442-1447 More about this Journal
Abstract
Since the indoor location recognition system using RFID is a method for predicting the indoor position, an error occurs due to the surrounding environment such as an obstacle. In this paper, we plan to reduce errors using back propagation neural networks. The neural network adjusts and trains the connection values between the layers to reduce the error between the actual position of the object with the reader and the expected position of the object through the experiment. In this paper, we propose a method that uses the median method and the radiation method as input to the neural network. Among the two methods, we want to find out which method is more effective in recognizing the actual position in an environment with obstacles and reduce the error. Consequently, the method using the median has less error, and we confirmed that the more the number of data, the smaller the error.
Keywords
Indoor location; Median value; Obstacle environment; RFID; Radiation pattern;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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