MSense: Towards Mobile Material Sensing with a Single Millimeter-Wave Radio

61Citations
Citations of this article
45Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Target material sensing in ubiquitous contexts plays an important role in various applications. Recently, a few wireless sensing systems have been proposed for material identification. Yet, prior work usually requires to capture the signals penetrating a target (with devices set up on both sides of the target) or to instrument the target (e.g., by attaching an RFID tag), relies on multiple transceivers, and/or involves unexplainable feature engineering. In this paper, we explore the feasibility of material identification by analyzing only the signals reflected off the target, rather than those penetrating it, with a single RF radio. We present mSense, a mobile material sensing system using a single millimeter-wave (mmWave) radio. At the core of mSense is the insight that different materials reflect RF signals in distinct ways. We propose a novel and easy-to-measure material reflection feature that quantitatively characterizes the material's reflectivity. A set of techniques are then devised to achieve accurate and robust material identification despite various factors, including device mobility, hardware defects of commodity mmWave radios, environmental interferences, and etc. Experiments using commercial mmWave networking chipsets demonstrate an average accuracy of 93% in categorizing five common types of materials: Aluminum, ceramic, plastic, wood, and water, regardless of their different sizes and thicknesses. The accuracy retains about 90% even in mobile scenarios (i.e., a user holds and moves the radio to perform sensing), which shows the great potential of mSense for mobile applications. A case study on 21 daily objects of various materials, shapes, and textures over different days further validates the performance in differentiating real-life objects.

References Powered by Scopus

Understanding and modeling of WiFi signal based human activity recognition

930Citations
N/AReaders
Get full text

Whole-home gesture recognition using wireless signals

915Citations
N/AReaders
Get full text

Soli: Ubiquitous gesture sensing with millimeter wave radar

835Citations
N/AReaders
Get full text

Cited by Powered by Scopus

A Survey of mmWave-Based Human Sensing: Technology, Platforms and Applications

79Citations
N/AReaders
Get full text

GaitCube: Deep Data Cube Learning for Human Recognition with Millimeter-Wave Radio

50Citations
N/AReaders
Get full text

MmWrite: Passive Handwriting Tracking Using a Single Millimeter-Wave Radio

47Citations
N/AReaders
Get full text

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Wu, C., Zhang, F., Wang, B., & Liu, K. J. R. (2020). MSense: Towards Mobile Material Sensing with a Single Millimeter-Wave Radio. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 4(3). https://doi.org/10.1145/3411822

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 14

64%

Researcher 5

23%

Professor / Associate Prof. 2

9%

Lecturer / Post doc 1

5%

Readers' Discipline

Tooltip

Computer Science 18

67%

Engineering 7

26%

Economics, Econometrics and Finance 1

4%

Agricultural and Biological Sciences 1

4%

Save time finding and organizing research with Mendeley

Sign up for free