Publication Type

Conference Proceeding Article

Publication Date

10-2017

Abstract

Target imaging and material identification play an important role in many real-life applications. This paper introduces TagScan, a system that can identify the material type and image the horizontal cut of a target simultaneously with cheap commercial of-the-shelf (COTS) RFID devices. The key intuition is that different materials and target sizes cause different amounts of phase and RSS (Received Signal Strength) changes when radio frequency (RF) signal penetrates through the target. Multiple challenges need to be addressed before we can turn the idea into a functional system including (i) indoor environments exhibit rich multipath which breaks the linear relationship between the phase change and the propagation distance inside a target; (ii) without knowing either material type or target size, trying to obtain these two information simultaneously is challenging; and (iii) stitching pieces of the propagation distances inside a target for an image estimate is non-trivial. We propose solutions to all the challenges and evaluate the system's performance in three different environments. TagScan is able to achieve higher than 94% material identification accuracies for 10 liquids and differentiate even very similar objects such as Coke and Pepsi. TagScan can accurately estimate the horizontal cut images of more than one target behind a wall.

Keywords

Horizontal cut imaging, Material identification, Multipath suppression, Phase and RSS measurements, RFID

Discipline

Databases and Information Systems | Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

Proceedings of the Annual International Conference on Mobile Computing and Networking: MobiCom 2017, Snowbird, United States, October 16-20

First Page

288

Last Page

300

ISBN

978-145034916-1

Identifier

10.1145/3117811.3117830

Publisher

Association for Computing Machinery

City or Country

Snowbird, United States

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

https://doi.org./10.1145/3117811.3117830

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