Efficient Methane Monitoring with Low-Cost Chemical Sensors and Machine Learning
We present a method to monitor methane at atmospheric concentrations with errors in the order of tens of parts per billion. We use machine learning techniques and periodic calibrations with reference equipment to quantify methane from the readings of an electronic nose. The results obtained demonstr...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-03-01
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| Series: | Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-3900/97/1/79 |
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