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Odor Sensor System Using Chemosensitive Resistor Array and Machine Learning
- Source :
- IEEE Sensors Journal. 21:2077-2083
- Publication Year :
- 2021
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2021.
-
Abstract
- 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%.
- Subjects :
- Sensor system
Materials science
business.industry
010401 analytical chemistry
Channel data
Chip
Machine learning
computer.software_genre
01 natural sciences
Computer Science::Other
0104 chemical sciences
law.invention
Software
Odor
Electrical resistance and conductance
law
Artificial intelligence
Electrical and Electronic Engineering
Resistor
business
Instrumentation
computer
Subjects
Details
- ISSN :
- 23799153 and 1530437X
- Volume :
- 21
- Database :
- OpenAIRE
- Journal :
- IEEE Sensors Journal
- Accession number :
- edsair.doi...........91fc2286f84e8c5c4e8742512413bd45