.png){kind=icon}
.png){kind=icon}
Return
Large artificial intelligence models for coal mining: Development, applications and challenges
.png){kind=icon}
PRE
AI
DOI：10.1007/s12613-026-3492-8.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Large-scale artificial intelligence (AI) models are increasingly shaping safety, efficiency, and sustainability in the mining industry. This paper reviews the development, applications, and challenges of domain-specific large AI models in coal mining. These models integrate heterogeneous multimodal data—text, images, video, audio, design data, point clouds, and time series—within multi-layered architectures encompassing infrastructure, data resources, algorithms, application services, and security. Application platforms supporting knowledge services, visual analysis, and intelligent scheduling demonstrate practical improvements in operational decision-making. Despite these advances, deployment faces challenges including fragmented data, limited labeled datasets, few-/zero-shot scenarios, industry-specific adaptation, robustness and interpretability, weak causal reasoning, edge computing limitations, cost–benefit trade-offs, and compatibility issues. Overcoming these barriers requires coordinated progress in data governance, model design, and industry standardization.
Keywords:
large artificial intelligence models
domain-specific large language models
multimodal data
coal mining applications
Journal
IF:
7.2
Papers:
3.0K
Citations:
8.6K