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Ȩ Ȩ > ¿¬±¸¹®Çå > ¿µ¹® ³í¹®Áö > TIIS (Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ)

TIIS (Çѱ¹ÀÎÅͳÝÁ¤º¸ÇÐȸ)

Current Result Document : 5 / 13 ÀÌÀü°Ç ÀÌÀü°Ç   ´ÙÀ½°Ç ´ÙÀ½°Ç

ÇѱÛÁ¦¸ñ(Korean Title) A Location Tracking System using BLE Beacon Exploiting a Double-Gaussian Filter
¿µ¹®Á¦¸ñ(English Title) A Location Tracking System using BLE Beacon Exploiting a Double-Gaussian Filter
ÀúÀÚ(Author) Jae Gu Lee   Jin Kim   Seon Woo Lee   Young Woong Ko  
¿ø¹®¼ö·Ïó(Citation) VOL 11 NO. 02 PP. 1162 ~ 1179 (2017. 02)
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(Korean Abstract)
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(English Abstract)
In this paper, we propose indoor location tracking method using RSSI(Received Signal Strength Indicator) value received from BLE(Bluetooth Low Energy) beacon. Due to the influence of various external environmental factors, it is very difficult to improve the accuracy in indoor location tracking. In order to solve this problem, we propose a novel method of reducing the noise generated in the external environment by using a double Gaussian filter. In addition, the value of the RSSI signal generated in the BLE beacon is different for each device. In this study, we propose a method to allocate additional weights in order to compensate the intensity of signal generated in each device. This makes it possible to improve the accuracy of indoor location tracking using beacons. The experiment results show that the proposed method effectively decrease the RSSI deviation and increase location accuracy. In order to verify the usefulness of this study, we compared the Kalman filter algorithm which is widely used in signal processing. We further performed additional experiments for application area for indoor location service and find that the proposed scheme is useful for BLE-based indoor location service.
Å°¿öµå(Keyword) Indoor localization   BLE   RSSI   Gaussian filter   Friis   Triangulation  
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