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Odor Sensor System Using Chemosensitive Resistor Array and Machine Learning
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DOI：10.1109/JSEN.2020.3016678.png)
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Abstract
En 中文
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%.
Keywords:
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
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