Abstract
In this study, we have fabricated multichannel odor sensor using chemosensitive resistors. The chemosensitive resistors were made from complex of carbon black and gas chromatography stationary materials (GC materials). The electrical resistance of the chemosensitive resistor changed by sensing gas species. We have fabricated an odor sensor chip, which had 16 types of chemosensitive resistors. In addition, we developed a measurement instrument with compact size. The odor sensor chip was embedded in the instrument to construct an odor sensor system. The sensor system outputted the data of 16 channels if sensing gas species. The data have been analyzed using machine learning algorithms that were available on software Weka. As a result, it was successful to identify alcohol beverages by sensing their odor using the sensor system.
| Original language | English |
|---|---|
| Title of host publication | ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781538683279 |
| DOIs | |
| Publication status | Published - May 2019 |
| Event | 18th International Symposium on Olfaction and Electronic Nose, ISOEN 2019 - Fukuoka, Japan Duration: May 26 2019 → May 29 2019 |
Publication series
| Name | ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings |
|---|
Conference
| Conference | 18th International Symposium on Olfaction and Electronic Nose, ISOEN 2019 |
|---|---|
| Country | Japan |
| City | Fukuoka |
| Period | 5/26/19 → 5/29/19 |
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All Science Journal Classification (ASJC) codes
- Signal Processing
- Instrumentation
Cite this
Multichannel Odor Sensor System using Chemosensitive Resistors and Machine Learning. / Shunori, Atsushi; Yatabe, Rui; Wyszynski, Bartosz; Hanai, Yosuke; Nakao, Atsuo; Nakatani, Masaya; Oki, Akio; Oka, Hiroaki; Washio, Takashi; Toko, Kiyoshi.
ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8823511 (ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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TY - GEN
T1 - Multichannel Odor Sensor System using Chemosensitive Resistors and Machine Learning
AU - Shunori, Atsushi
AU - Yatabe, Rui
AU - Wyszynski, Bartosz
AU - Hanai, Yosuke
AU - Nakao, Atsuo
AU - Nakatani, Masaya
AU - Oki, Akio
AU - Oka, Hiroaki
AU - Washio, Takashi
AU - Toko, Kiyoshi
PY - 2019/5
Y1 - 2019/5
N2 - In this study, we have fabricated multichannel odor sensor using chemosensitive resistors. The chemosensitive resistors were made from complex of carbon black and gas chromatography stationary materials (GC materials). The electrical resistance of the chemosensitive resistor changed by sensing gas species. We have fabricated an odor sensor chip, which had 16 types of chemosensitive resistors. In addition, we developed a measurement instrument with compact size. The odor sensor chip was embedded in the instrument to construct an odor sensor system. The sensor system outputted the data of 16 channels if sensing gas species. The data have been analyzed using machine learning algorithms that were available on software Weka. As a result, it was successful to identify alcohol beverages by sensing their odor using the sensor system.
AB - In this study, we have fabricated multichannel odor sensor using chemosensitive resistors. The chemosensitive resistors were made from complex of carbon black and gas chromatography stationary materials (GC materials). The electrical resistance of the chemosensitive resistor changed by sensing gas species. We have fabricated an odor sensor chip, which had 16 types of chemosensitive resistors. In addition, we developed a measurement instrument with compact size. The odor sensor chip was embedded in the instrument to construct an odor sensor system. The sensor system outputted the data of 16 channels if sensing gas species. The data have been analyzed using machine learning algorithms that were available on software Weka. As a result, it was successful to identify alcohol beverages by sensing their odor using the sensor system.
UR - http://www.scopus.com/inward/record.url?scp=85072958674&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85072958674&partnerID=8YFLogxK
U2 - 10.1109/ISOEN.2019.8823511
DO - 10.1109/ISOEN.2019.8823511
M3 - Conference contribution
AN - SCOPUS:85072958674
T3 - ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings
BT - ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -