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 proceedingConference contribution

    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 languageEnglish
    Title of host publicationISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    ISBN (Electronic)9781538683279
    DOIs
    Publication statusPublished - May 2019
    Event18th International Symposium on Olfaction and Electronic Nose, ISOEN 2019 - Fukuoka, Japan
    Duration: May 26 2019May 29 2019

    Publication series

    NameISOEN 2019 - 18th International Symposium on Olfaction and Electronic Nose, Proceedings

    Conference

    Conference18th International Symposium on Olfaction and Electronic Nose, ISOEN 2019
    Country/TerritoryJapan
    CityFukuoka
    Period5/26/195/29/19

    All Science Journal Classification (ASJC) codes

    • Signal Processing
    • Instrumentation

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