Mining Safety Through Artificial Intelligence: A Survey
Authors
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Resources Valorisation, Environment and Sustainable Development Research Team (RVESD), Department of Mines, Mines School of Rabat, Av Hadj Ahmed Cherkaoui, Agdal, BP 753, Rabat - 10090 ,MA
Oumaima Otmani -
Resources Valorisation, Environment and Sustainable Development Research Team (RVESD), Department of Mines, Mines School of Rabat, Av Hadj Ahmed Cherkaoui, Agdal, BP 753, Rabat - 10090 ,MASaad Soulaimani
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Resources Valorisation, Environment and Sustainable Development Research Team (RVESD), Department of Mines, Mines School of Rabat, Av Hadj Ahmed Cherkaoui, Agdal, BP 753, Rabat - 10090 ,MAKhalil Abdessamad
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Compagnie manière des Guemassa, BP 469, Marrakech ,MARmiki Amina
DOI:
https://doi.org/10.18311/jmmf/2024/44846Keywords:
Artificial Intelligence, Mine Ventilation, Monitoring Systems, Underground Mine Hazards, Workers SafetyAbstract
The challenges workers face in underground mines are numerous and hazardous, with potential threats to their safety and well-being. Mining accidents are caused by various factors, including hardware errors and environmental deficiencies. In response to these hazards, the mining industry has made significant efforts to improve safety through the implementation of advanced technologies. Artificial Intelligence (AI) technology has been notably integrated into mine ventilation systems in recent years. A ventilation network in a mine is a sophisticated system with many interdependent processes, some of which present difficulties for deterministic simulation techniques. This paper aims to discuss major hazards caused by ventilation and provide an overview of various AI advances in mine ventilation to monitor various environmental parameters such as gas concentrations and heat.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Accepted 2024-08-12
Published 2024-09-04
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