Efficient Methane Monitoring with Low-Cost Chemical Sensors and Machine Learning

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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Bibliographic Details
Main Authors: Guillem Domènech-Gil, Nguyen Thanh Duc, J. Jacob Wikner, Jens Eriksson, Donatella Puglisi, David Bastviken
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Proceedings
Subjects:
methane
electronic nose
environmental monitoring
machine learning
gas sensors
low-cost
Online Access:https://www.mdpi.com/2504-3900/97/1/79
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