Odor Sensor System Using Chemosensitive Resistor Array and Machine Learning

被引：11

作者：

Yatabe, Rui ^{[1
]}

Shunori, Atsushi ^{[2
]}

Wyszynski, Bartosz ^{[3
]}

Hanai, Yosuke ^{[2
]}

Nakao, Atsuo ^{[2
]}

Nakatani, Masaya ^{[2
]}

Oki, Akio ^{[2
]}

Oka, Hiroaki ^{[2
]}

Washio, Takashi ^{[4
]}

Toko, Kiyoshi ^{[3
,5
]}

机构：

[1] Kyushu Univ, Fac Informat Sci & Elect Engn, Fukuoka 8190395, Japan

[2] Ind Solut Co, Panason Corp, Osaka 5718506, Japan

[3] Kyushu Univ, Res & Dev Ctr Sense Devices 5, Fukuoka 8190395, Japan

[4] Osaka Univ, Inst Sci & Ind Res, Osaka 5670047, Japan

[5] Kyushu Univ, Inst Adv Study, Fukuoka 8190395, Japan

来源：

IEEE SENSORS JOURNAL | 2021年 / 21卷 / 02期

关键词：

Annealing; Resistors; Sensor phenomena and characterization; Sensor systems; Resistance; Chemical sensors; GC materials; carbon black; odor sensor; artificial olfaction; chemical sensor; sensor array; odor discrimination; Weka; CARBON-BLACK; GAS SENSOR;

D O I：

10.1109/JSEN.2020.3016678

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this study, we developed an odor sensor system using chemosensitive resistors, which outputted multichannel data. Mixtures of gas chromatography stationary materials (GC materials) and carbon black were used as the chemosensitive resistors. The interaction between the chemosensitive resistors and gas species shifted the electrical resistance of the resistors. Sixteen different chemosensitive resistors were fabricated on an odor sensor chip. In addition, a compact measurement instrument was fabricated. Sixteen channel data were obtained from the measurements of gas species using the instrument. The data were analyzed using machine learning algorithms available on Weka software. As a result, the sensor system successfully identified alcoholic beverages. Finally, we demonstrated the classification of restroom odor in a field test. The classification was successful with an accuracy of 97.9%.

引用

页码：2077 / 2083

页数：7

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