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Indoor Geofencing Based on Sensorless Motion Sensing and Fingerprint Self-Updating

  • Kun ZhaoEmail author
  • Wei Xi
  • Zhiping Jiang
  • Zhi Wang
  • Hui He
  • Tao Li
  • Xiaobin Zhang
  • Jizhong Zhao
Article
  • 33 Downloads

Abstract

Indoor location is definitively a key feature with immense value especial for geofencing. The received signal strength (RSS) fingerprinting based methodology is widely adopted to determine his/her proximity to that particular region. Its dynamic nature and maintain overhead remain a primary challenge. In this paper, we propose a hybrid electronic geofence approach that combines self-updating RSS fingerprints based localization and Channel State Information (CSI) motion detection. Multidimensional matching and filtering principle achieves fingerprints self-updating and improves the localization accuracy. CSI-based speed estimation reduces localization frequency and overhead. Our extensive real-world experiment results show that the proposed indoor geofencing method works well for more than 30 days without manual Wi-Fi fingerprints updating.

Keywords

CSI-RSS collaboration Mobile device management Multi-dimensional RSS Self-update 

Notes

Acknowledgements

We thank the valuable comments from our reviewers and editors. This work was supported by National Key R&D Program of China 2017YFB1003000, NSFC Grant No.61751211, 61572-396, 61772413, 61672424, National Science and Technology Major Project of the Ministry of Science and Technology of China JZ-20150910, and ShaanXi Provincial Natural Science Foundation (No.2017JM6109).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Kun Zhao
    • 1
    Email author
  • Wei Xi
    • 1
  • Zhiping Jiang
    • 2
  • Zhi Wang
    • 1
  • Hui He
    • 1
  • Tao Li
    • 3
  • Xiaobin Zhang
    • 1
  • Jizhong Zhao
    • 1
  1. 1.Xi’an Jiaotong UniversityXi’anChina
  2. 2.Xidian UniversityXi’anChina
  3. 3.Arizona State UniversityTempeUSA

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