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Large-scale decimeter-level indoor tracking using a single access point: demo abstract

Published:16 November 2020Publication History

ABSTRACT

Existing indoor location systems do not easily scale at low cost while maintaining high accuracy. We present EasiTrack, an indoor tracking system that achieves decimeter accuracy using a single commodity WiFi Access Point (AP) under Non-Line-Of-Sight conditions and can deploy at scale with (almost) zero cost. We build a fully functional real-time system with a satellite-like architecture, which enables EasiTrack to support an unlimited number of clients. We have demonstrated EasiTrack in a number of different scenarios to track both humans and machines. The results reveal that EasiTrack achieves a decimeter median accuracy and a <2m maximum error and supports a broad coverage of 50 m×60 m using a single AP.

References

  1. Chenshu Wu, Feng Zhang, Yusen Fan, and K J Ray Liu. 2019. RF-based inertial measurement. In ACM SIGCOMM. 117--129.Google ScholarGoogle Scholar
  2. Chenshu Wu, Feng Zhang, Beibei Wang, and K J Ray Liu. 2019. EasiTrack: Decimeter-Level Indoor Tracking With Graph-Based Particle Filtering. IEEE Internet of Things Journal 7, 3 (2019), 2397--2411.Google ScholarGoogle ScholarCross RefCross Ref
  3. Feng Zhang, Chen Chen, Beibei Wang, Hung-Quoc Lai, Yi Han, and K J Ray Liu. 2018. WiBall: A time-reversal focusing ball method for decimeter-accuracy indoor tracking. IEEE Internet of Things Journal 5, 5 (2018), 4031--4041.Google ScholarGoogle Scholar

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  1. Large-scale decimeter-level indoor tracking using a single access point: demo abstract

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      • Published in

        cover image ACM Conferences
        SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor Systems
        November 2020
        852 pages
        ISBN:9781450375900
        DOI:10.1145/3384419

        Copyright © 2020 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 16 November 2020

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        Overall Acceptance Rate174of867submissions,20%
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