Title: Coal mine artificial intelligence technology and scenario applications

Authors: Wen Cui; Yuting Zhou; Zhou Zheng; Hao Gu; Mujtaba Asad; Xiaolin Huang; He Jiang

Addresses: School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China ' School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China ' School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China ' School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China ' School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China ' School of Automation and Intelligent Sensing, Shanghai Jiao Tong University, Shanghai 200240, China ' School of Information and Control Engineering, China University of Mining and Technology, Xuzhou, 221116, China

Abstract: Addressing coal mine safety requirements, we systematically analyse the efficacy of artificial intelligence (AI) technologies in underground operations. By integrating audio-visual technology, an intelligent solution covering core scenarios including safety monitoring, mining optimisation, and equipment maintenance is established. The results confirm that video technology dynamically monitors gas concentrations, detects roadway deformations, and intelligently controls mining equipment, while audio technology identifies equipment fault signatures and geological acoustic patterns, significantly improving real-time early warning capabilities. This integrated system significantly improves operational safety, production efficiency, and intelligentisation levels, providing an effective pathway for smart coal mine construction.

Keywords: scenario applications; coal mine; artificial intelligence; audio-visual technology; intelligentisation levels.

DOI: 10.1504/IJSCIP.2026.154735

International Journal of System Control and Information Processing, 2026 Vol.5 No.1, pp.49 - 78

Received: 31 Jul 2025
Accepted: 30 Dec 2025
Published online: 12 Jul 2026 *

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