TagController: A Universal Wireless and Battery-free Remote Controller using Passive RFID Tags

Links to Files

https://dl.acm.org/doi/10.1145/3144457.3144498

Permanent Link

https://doi.org/10.1145/3144457.3144498
 http://hdl.handle.net/11603/42158

Collections

UMBC Computer Science and Electrical Engineering Department

Author/Creator

Author/Creator ORCID

https://orcid.org/0000-0002-3144-5104

Date

2017-11-07

Type of Work

conference papers and proceedings
Text

Department

Program

Citation of Original Publication

Li, Dong, Feng Ding, Qian Zhang, Run Zhao, Jinshi Zhang, and Dong Wang. "TagController: A Universal Wireless and Battery-Free Remote Controller Using Passive RFID Tags". Proceedings of the 14th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (New York, NY, USA), MobiQuitous 2017, (Nov 7, 2017): 166–75. https://doi.org/10.1145/3144457.3144498.

Rights

This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.

Subjects

Abstract

Innovative Human Machine Interface technologies are fundamentally reshaping the way people live, entertain and work. Passive RFID tags, benefiting from its wireless, inexpensive and battery-free sensing ability, are gradually being applied in new-style interaction interfaces, ranging from virtual touch screen to 3D mouse. This paper presents TagController, a universal wireless and battery-free remote controller with two types of interactive actions. The key insight is that the fine-grained phase information extracted from RF signals is capable of perceiving various actions. TagController can recognize 10 actions without any training or prestored profiles by executing a sequence of functional components, i.e. preprocessor, action detector and action recognizer. We have implemented TagController with COTS RFID devices and conducted substantial experiments in different scenarios. The results demonstrate that TagController can achieve an average recognition accuracy of 95.8% and 94.3% in the scenarios of one and two remote controllers, respectively, which promises its feasibility and robustness.