TY - JOUR
T1 - WiEps
T2 - Measurement of Dielectric Property with Commodity WiFi Device - An Application to Ethanol/Water Mixture
AU - Song, Hang
AU - Wei, Bo
AU - Yu, Qun
AU - Xiao, Xia
AU - Kikkawa, Takamaro
N1 - Funding Information:
Manuscript received March 3, 2020; revised May 5, 2020; accepted May 28, 2020. Date of publication June 1, 2020; date of current version December 11, 2020. This work was supported in part by the Japan Society for the Promotion of Science KAKENHI under Grant 20K14740, and in part by NSFC under Grant 61271323. (Corresponding authors: Bo Wei; Hang Song.) Hang Song, Qun Yu, and Xia Xiao are with the Tianjin Key Laboratory of Imaging and Sensing Microelectronic Technology, School of Microelectronics, Tianjin University, Tianjin 300072, China (e-mail: songhang168@tju.edu.cn).
Publisher Copyright:
© 2014 IEEE.
PY - 2020/12
Y1 - 2020/12
N2 - WiFi signal has become accessible everywhere, providing high-speed data transmission experience. Besides the communication service, channel state information (CSI) of the WiFi signals is widely employed for numerous Internet-of-Things (IoT) applications. Recently, most of these applications are based on the analysis of the microwave reflections caused by the physical movement of the objective. In this article, a novel contactless wireless sensing technique named WiEps is developed to measure the dielectric properties of the material, exploiting the transmission characteristics of the WiFi signals. In WiEps, the material under test is placed between the transmitter antenna and receiver antenna. A theoretical model is proposed to quantitatively describe the relationship between CSI data and dielectric properties of the material. During the experiment, the phase and amplitude of the transmitted WiFi signals are extracted from the measured CSI data. The parameters of the theoretical model are calculated using measured data from the known materials. Then, WiEps is utilized to estimate the dielectric properties of unknown materials. The proposed technique is first applied to the ethanol/water mixtures. Then, additional liquids are measured for further verification. The estimated permittivities and conductivities show good agreement with the actual values, with the average error of 4.0% and 8.9%, respectively, indicating the efficacy of WiEps. By measuring the dielectric property, this technique is promising to be applied to new IoT applications using ubiquitous WiFi signals, such as food engineering, material manufacturing process monitoring, and security check.
AB - WiFi signal has become accessible everywhere, providing high-speed data transmission experience. Besides the communication service, channel state information (CSI) of the WiFi signals is widely employed for numerous Internet-of-Things (IoT) applications. Recently, most of these applications are based on the analysis of the microwave reflections caused by the physical movement of the objective. In this article, a novel contactless wireless sensing technique named WiEps is developed to measure the dielectric properties of the material, exploiting the transmission characteristics of the WiFi signals. In WiEps, the material under test is placed between the transmitter antenna and receiver antenna. A theoretical model is proposed to quantitatively describe the relationship between CSI data and dielectric properties of the material. During the experiment, the phase and amplitude of the transmitted WiFi signals are extracted from the measured CSI data. The parameters of the theoretical model are calculated using measured data from the known materials. Then, WiEps is utilized to estimate the dielectric properties of unknown materials. The proposed technique is first applied to the ethanol/water mixtures. Then, additional liquids are measured for further verification. The estimated permittivities and conductivities show good agreement with the actual values, with the average error of 4.0% and 8.9%, respectively, indicating the efficacy of WiEps. By measuring the dielectric property, this technique is promising to be applied to new IoT applications using ubiquitous WiFi signals, such as food engineering, material manufacturing process monitoring, and security check.
KW - Channel state information (CSI)
KW - WiFi signal
KW - dielectric property measurement
KW - microwave propagation
KW - wireless senssing
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U2 - 10.1109/JIOT.2020.2999210
DO - 10.1109/JIOT.2020.2999210
M3 - Article
AN - SCOPUS:85097841222
SN - 2327-4662
VL - 7
SP - 11667
EP - 11677
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 12
M1 - 9105044
ER -