Multichannel Odor Sensor System using Chemosensitive Resistors and Machine Learning

Atsushi Shunori; Rui Yatabe; Bartosz Wyszynski; Yosuke Hanai; Atsuo Nakao; Masaya Nakatani; Akio Oki; Hiroaki Oka; Takashi Washio; Kiyoshi Toko

doi:10.1109/ISOEN.2019.8823511

Multichannel Odor Sensor System using Chemosensitive Resistors and Machine Learning

Atsushi Shunori, Rui Yatabe, Bartosz Wyszynski, Yosuke Hanai, Atsuo Nakao, Masaya Nakatani, Akio Oki, Hiroaki Oka, Takashi Washio, Kiyoshi Toko

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Citations (Scopus)

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	https://doi.org/10.1109/ISOEN.2019.8823511
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/Territory	Japan
City	Fukuoka
Period	5/26/19 → 5/29/19

All Science Journal Classification (ASJC) codes

Signal Processing
Instrumentation

Access to Document

10.1109/ISOEN.2019.8823511

Cite this

Shunori, A., Yatabe, R., Wyszynski, B., Hanai, Y., Nakao, A., Nakatani, M., Oki, A., Oka, H., Washio, T., & Toko, K. (2019). Multichannel Odor Sensor System using Chemosensitive Resistors and Machine Learning. In ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings [8823511] (ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISOEN.2019.8823511

Multichannel Odor Sensor System using Chemosensitive Resistors and Machine Learning. / Shunori, Atsushi; Yatabe, Rui; Wyszynski, Bartosz et al.

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

Shunori, A, Yatabe, R, Wyszynski, B, Hanai, Y, Nakao, A, Nakatani, M, Oki, A, Oka, H, Washio, T & Toko, K 2019, Multichannel Odor Sensor System using Chemosensitive Resistors and Machine Learning. in ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings., 8823511, ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings, Institute of Electrical and Electronics Engineers Inc., 18th International Symposium on Olfaction and Electronic Nose, ISOEN 2019, Fukuoka, Japan, 5/26/19. https://doi.org/10.1109/ISOEN.2019.8823511

Shunori A, Yatabe R, Wyszynski B, Hanai Y, Nakao A, Nakatani M et al. Multichannel Odor Sensor System using Chemosensitive Resistors and Machine Learning. In 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). https://doi.org/10.1109/ISOEN.2019.8823511

Shunori, Atsushi ; Yatabe, Rui ; Wyszynski, Bartosz et al. / Multichannel Odor Sensor System using Chemosensitive Resistors and Machine Learning. ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. (ISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings).

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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.",

author = "Atsushi Shunori and Rui Yatabe and Bartosz Wyszynski and Yosuke Hanai and Atsuo Nakao and Masaya Nakatani and Akio Oki and Hiroaki Oka and Takashi Washio and Kiyoshi Toko",

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AU - Hanai, Yosuke

AU - Nakao, Atsuo

AU - Nakatani, Masaya

AU - Oki, Akio

AU - Oka, Hiroaki

AU - Washio, Takashi

AU - Toko, Kiyoshi

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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.

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Multichannel Odor Sensor System using Chemosensitive Resistors and Machine Learning

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