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Design of the Model for Indoor Location Prediction Using IMU of Smartphone Based on Beacon

  • Jae-Gwang Lee
  • Seoung-Hyeon Lee
  • Jae-Kwang Lee
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 789)

Abstract

IPS (Indoor positioning system) is a system that measures the user’s position in the room. Since IPS can’t use GPS (Global Positioning System), various researches are under way focusing on indoor location accuracy. IPS may also be unable to measure indoors because of signal loss, blind spots, etc. To solve this problem, Beacon’s RSSI signal is linearized using BITON algorithm and Kalman filter is applied. In addition, the position is predicted even when the signal is lost by measuring the instantaneous direction and the moving distance using the sensor of the smartphone. Therefore, in this paper, we propose a room location prediction model that can improve user’s position accuracy and detect user’s position in case of signal loss using Beacon and smartphone sensor.

Keywords

Beacon Kalman filter Geomagnetic sensor IPS Indoor location prediction 

Notes

Acknowledgements

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A3B03036130).

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Jae-Gwang Lee
    • 1
  • Seoung-Hyeon Lee
    • 2
  • Jae-Kwang Lee
    • 1
  1. 1.Department of Computer Engineering Hannam UniversityDaejeonKorea
  2. 2.Information Security Research DivisionETRIDaejeonKorea

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