Noninvasive Suspicious Liquid Detection Using Wireless Signals
Conventional liquid detection instruments are very expensive and not conducive to large-scale deployment. In this work, we propose a method for detecting and identifying suspicious liquids based on the dielectric constant by utilizing the radio signals at a 5G frequency band. There are three major e...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2019-09-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/19/19/4086 |
| id |
doaj-6ff2ac6923f54b6384ee4022a99a0725 |
|---|---|
| record_format |
Article |
| spelling |
doaj-6ff2ac6923f54b6384ee4022a99a07252020-11-25T02:01:02ZengMDPI AGSensors1424-82202019-09-011919408610.3390/s19194086s19194086Noninvasive Suspicious Liquid Detection Using Wireless SignalsJiewen Deng0Wanrong Sun1Lei Guan2Nan Zhao3Muhammad Bilal Khan4Aifeng Ren5Jianxun Zhao6Xiaodong Yang7Qammer H. Abbasi8School of Electronic Engineering, Xidian University, Xi’an 710071, ChinaSchool of Electronic Engineering, Xidian University, Xi’an 710071, ChinaSchool of Life Sciences and Technology, Xidian University, Xi’an 710126, ChinaSchool of Electronic Engineering, Xidian University, Xi’an 710071, ChinaSchool of Electronic Engineering, Xidian University, Xi’an 710071, ChinaSchool of Electronic Engineering, Xidian University, Xi’an 710071, ChinaSchool of Electronic Engineering, Xidian University, Xi’an 710071, ChinaSchool of Electronic Engineering, Xidian University, Xi’an 710071, ChinaSchool of Engineering, University of Glasgow, Glasgow G12 8QQ, UKConventional liquid detection instruments are very expensive and not conducive to large-scale deployment. In this work, we propose a method for detecting and identifying suspicious liquids based on the dielectric constant by utilizing the radio signals at a 5G frequency band. There are three major experiments: first, we use wireless channel information (WCI) to distinguish between suspicious and nonsuspicious liquids; then we identify the type of suspicious liquids; and finally, we distinguish the different concentrations of alcohol. The K-Nearest Neighbor (KNN) algorithm is used to classify the amplitude information extracted from the WCI matrix to detect and identify liquids, which is suitable for multimodal problems and easy to implement without training. The experimental result analysis showed that our method could detect more than 98% of the suspicious liquids, identify more than 97% of the suspicious liquid types, and distinguish up to 94% of the different concentrations of alcohol.https://www.mdpi.com/1424-8220/19/19/40865Gliquid detectionradio propagationdielectric constantWCI |
| collection |
DOAJ |
| language |
English |
| format |
Article |
| sources |
DOAJ |
| author |
Jiewen Deng Wanrong Sun Lei Guan Nan Zhao Muhammad Bilal Khan Aifeng Ren Jianxun Zhao Xiaodong Yang Qammer H. Abbasi |
| spellingShingle |
Jiewen Deng Wanrong Sun Lei Guan Nan Zhao Muhammad Bilal Khan Aifeng Ren Jianxun Zhao Xiaodong Yang Qammer H. Abbasi Noninvasive Suspicious Liquid Detection Using Wireless Signals Sensors 5G liquid detection radio propagation dielectric constant WCI |
| author_facet |
Jiewen Deng Wanrong Sun Lei Guan Nan Zhao Muhammad Bilal Khan Aifeng Ren Jianxun Zhao Xiaodong Yang Qammer H. Abbasi |
| author_sort |
Jiewen Deng |
| title |
Noninvasive Suspicious Liquid Detection Using Wireless Signals |
| title_short |
Noninvasive Suspicious Liquid Detection Using Wireless Signals |
| title_full |
Noninvasive Suspicious Liquid Detection Using Wireless Signals |
| title_fullStr |
Noninvasive Suspicious Liquid Detection Using Wireless Signals |
| title_full_unstemmed |
Noninvasive Suspicious Liquid Detection Using Wireless Signals |
| title_sort |
noninvasive suspicious liquid detection using wireless signals |
| publisher |
MDPI AG |
| series |
Sensors |
| issn |
1424-8220 |
| publishDate |
2019-09-01 |
| description |
Conventional liquid detection instruments are very expensive and not conducive to large-scale deployment. In this work, we propose a method for detecting and identifying suspicious liquids based on the dielectric constant by utilizing the radio signals at a 5G frequency band. There are three major experiments: first, we use wireless channel information (WCI) to distinguish between suspicious and nonsuspicious liquids; then we identify the type of suspicious liquids; and finally, we distinguish the different concentrations of alcohol. The K-Nearest Neighbor (KNN) algorithm is used to classify the amplitude information extracted from the WCI matrix to detect and identify liquids, which is suitable for multimodal problems and easy to implement without training. The experimental result analysis showed that our method could detect more than 98% of the suspicious liquids, identify more than 97% of the suspicious liquid types, and distinguish up to 94% of the different concentrations of alcohol. |
| topic |
5G liquid detection radio propagation dielectric constant WCI |
| url |
https://www.mdpi.com/1424-8220/19/19/4086 |
| work_keys_str_mv |
AT jiewendeng noninvasivesuspiciousliquiddetectionusingwirelesssignals AT wanrongsun noninvasivesuspiciousliquiddetectionusingwirelesssignals AT leiguan noninvasivesuspiciousliquiddetectionusingwirelesssignals AT nanzhao noninvasivesuspiciousliquiddetectionusingwirelesssignals AT muhammadbilalkhan noninvasivesuspiciousliquiddetectionusingwirelesssignals AT aifengren noninvasivesuspiciousliquiddetectionusingwirelesssignals AT jianxunzhao noninvasivesuspiciousliquiddetectionusingwirelesssignals AT xiaodongyang noninvasivesuspiciousliquiddetectionusingwirelesssignals AT qammerhabbasi noninvasivesuspiciousliquiddetectionusingwirelesssignals |
| _version_ |
1724959306769498112 |