Robust Spinning Sensing with Dual-RFID-Tags in Noisy Settings

Chunhui Duan, Lei Yang, Qiongzheng Lin, Yunhao Liu, Lei Xie

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)

Abstract

Conventional spinning inspection systems, equipped with separated sensors (e.g., accelerometer, laser, etc.) and communication modules, are either very expensive and/or suffering from occlusion and narrow field of view. The recently proposed RFID-based sensing solution draws much attention due to its intriguing features, such as being cost-effective, applicable to occluded objects, auto-identification, etc. However, this solution only works in quiet settings where both the reader and spinning object remain absolutely stationary, as their shaking would ruin the periodicity and sparsity of the spinning signal, making it impossible to be recovered. To overcome such limitation, this work introduces Tagtwins, a robust spinning sensing system that can work in noisy settings. It addresses the challenge by attaching dual RFID tags on the spinning surface and developing a new formulation of spinning signal that is shaking-resilient, even if the shaking involves unknown trajectories. Our main contribution lies in two newly developed techniques. First, we propose relative spinning signal using dual tags' readings and analytically demonstrate its feasibility in various settings. Second, we introduce dual compressive reading to inspect high-frequency spinning with relatively low reading rate of RFIDs. We have implemented Tagtwins with commercial RFID devices and evaluated it extensively. Experimental results show that Tagtwins can inspect the rotation frequency with high accuracy and robustness.

Original languageEnglish
Article number8509127
Pages (from-to)2647-2659
Number of pages13
JournalIEEE Transactions on Mobile Computing
Volume18
Issue number11
DOIs
Publication statusPublished - 1 Nov 2019

Keywords

  • dual-tag
  • RFID
  • robust
  • spinning sensing

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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