RFlow-ID: Unobtrusive Workflow Recognition with COTS RFID

Links to Files

https://dl.acm.org/doi/10.1145/3144457.3144463

Permanent Link

https://doi.org/10.1145/3144457.3144463
 http://hdl.handle.net/11603/41995

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

Zhang, Jinshi, Qian Zhang, Dong Li, Run Zhao, and Dong Wang. "RFlow-ID: Unobtrusive Workflow Recognition with COTS RFID". 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): 333–42. https://doi.org/10.1145/3144457.3144463.

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

Workflow recognition is a key technique in the field of activity recognition with benefits of monitoring the step being performed in the workflow, detecting the missing step, and providing assistance to the performer of the workflow, among others. In this paper, we present an unobtrusive workflow recognition system called RFlow-ID, which is the first device-free, battery-free and privacy-preserving workflow recognition system based on RFID technique. RFlow-ID perceives the use and movement of associated objects in the workflow using fine-grained phase information extracted from low-level RF signal, and infers the most likely sequence of workflow activities via a VQ-HMM model. We implement RFlow-ID on COTS RFID devices and evaluate it through a common biomedical experiment. The results validate the high recognition accuracy and robustness of our system.