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Vol. 32, No. 8(2), S&M2292

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Sensors and Materials
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Sensors and Materials, Volume 29, Number 4 (2017)
Copyright(C) MYU K.K.
pp. 387-395
S&M1331 Research Paper of Special Issue
https://doi.org/10.18494/SAM.2017.1520
Published: April 19, 2017

Improving Radio Frequency Identification-Based Localization Accuracy Using Computer-Vision-Assisted Sensor Deployment Technology [PDF]

Rong-Shue Hsiao, Chun-Hao Kao, Hsin-Piao Lin, and Kai-Wei Ke

(Received August 30, 2016; Accepted January 6, 2017)

Keywords: sensor deployment, computer vision, indoor localization, RFID, genetic algorithm

Radio frequency identification (RFID) technology is one of the promising technologies enabling the realization of the Internet of Things. However, the current major application is limited to using its identification ability. The number of applications will be increased if we can enable RFID technology to have the capability of accurate localization. In this paper, we propose a new sensor deployment method for improving the passive RFID localization accuracy. The proposed method integrates computer vision technology while employing a genetic algorithm to find the appropriate locations to deploy RFID reader antennas. The proposed method was applied to a fingerprinting-based indoor localization system. The result showed that the localization accuracy can be effectively improved by selecting the appropriate deployment locations of RFID reader antennas.

Corresponding author: Rong-Shue Hsiao


Cite this article
Rong-Shue Hsiao, Chun-Hao Kao, Hsin-Piao Lin, and Kai-Wei Ke, Improving Radio Frequency Identification-Based Localization Accuracy Using Computer-Vision-Assisted Sensor Deployment Technology, Sens. Mater., Vol. 29, No. 4, 2017, p. 387-395.



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