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

November 1, 2019·
Chunhui Duan
Chunhui Duan
Corresponding author
,
Lei Yang
,
Qiongzheng Lin
,
Yunhao Liu
,
Lei Xie
· 2 min read
Type
Publication
IEEE Transactions on Mobile Computing, 18(11), 2647-2659
Status
Peer-reviewed
publications

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.

Citation

C. Duan, L. Yang, Q. Lin, Y. Liu, and L. Xie, “Robust Spinning Sensing with Dual-RFID-Tags in Noisy Settings,” IEEE Transactions on Mobile Computing(TMC), vol. 18, no. 11, pp. 2647-2659, 2019.

中文引用(GB/T 7714)

Duan C, Yang L, Lin Q, et al. Robust Spinning Sensing with Dual-RFID-Tags in Noisy Settings[J]. IEEE Transactions on Mobile Computing(TMC), 2019, 18(11): 2647-2659.

Chunhui Duan
Authors
Chunhui Duan (she/her)
Associate Professor
I am Chunhui Duan (段春晖), currently an Associate Professor (tenure-track) in School of Computer Science and Technology, Beijing Institute of Technology. Previously, I worked as a postdoc research fellow at Tsinghua University. I received the B.S. and Ph.D. degrees from the School of Software at Tsinghua University, in 2013 and 2018 respectively, supervised by Prof. Yunhao Liu.

My research interests include RFID, Internet-of-Things, indoor localization, wireless sensing, etc.