Selective Detection of Target Volatile Organic Compounds in Contaminated Air Using Sensor Array with Machine Learning: Aging Notes and Mold Smells in Simulated Automobile Interior Contaminant Gases

Selective Detection of Target Volatile Organic Compounds in Contaminated Air Using Sensor Array with Machine Learning: Aging Notes and Mold Smells in Simulated Automobile Interior Contaminant Gases

We investigated the selective detection of target volatile organic compounds (VOCs) which are age-related body odors (namely, 2-nonenal, pelargonic acid, and diacetyl) and a fungal odor (namely, acetic acid) in the presence of interference VOCs from car interiors (namely, <i>n</i>-decane...

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Bibliographic Details
Main Authors: Toshio Itoh, Yutaro Koyama, Woosuck Shin, Takafumi Akamatsu, Akihiro Tsuruta, Yoshitake Masuda, Kazuhisa Uchiyama
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Sensors
Subjects:
semiconductive-type gas sensor
age-related body odor
fungi odor
indoor-air contamination
machine learning
principal-component analysis (PCA)
Online Access:https://www.mdpi.com/1424-8220/20/9/2687

Internet

https://www.mdpi.com/1424-8220/20/9/2687

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