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Artificial Intelligence can forecast gas-related incidents in coal mines within half an hour, according to a new study exploring how the technology can reduce the risk of disasters.

The study of coal mines in China compared 10 machine learning algorithms to see which AI method could make predictions about changes in methane gas levels 30 minutes in advance, and notify users of anomalies. "Comparative study of ten machine learning algorithms for short-term forecasting in gas warning systems" was published in the journal Scientific Reports.

Gas explosions or ignitions in underground mines pose significant risks, with almost 60% of coal mine accidents in China caused by methane gas.

China accounted for 46% of the world's coal production in 2020, and more than 3,200 coal mines in the country with high gas content at outburst-prone risk levels.

Author and Charles Darwin University (CDU) Faculty of Science and Technology Adjunct Associate Professor Niusha Shafiabady said the results showed out of the 10, four machine learning algorithms produced the best results.

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