Abstract: At present, smart mine construction generally faces problems such as imbalance between investment and output, lack of standards, low accuracy of core disaster early warning systems, insufficient technology integration, system silos, and insufficient utilization of data resources, which seriously restrict the in-depth application of intelligent technologies in mine safety prevention and control, production optimization, and operational decision-making. This study introduces the theoretical development of smart mine construction and the current status of technology integration and data governance, and points out that although smart mine construction has continuously evolved from digital mines and perceptual mines to intelligent mines and has achieved significant progress in technical architecture and system applications, it is still at the stage of system intelligence and has not yet realized truly comprehensive intelligence. Existing systems have prominent problems, including difficulties in comprehensive perception, deep interconnection, business collaboration, and data sharing, as well as limitations in intelligent decision-making. Based on an analysis of the core problems currently existing in smart mine construction in terms of technology integration, data governance, and ecosystem building, this study highlights the urgent need to promote smart mine upgrading and transformation through optimized technology integration and data governance, and proposes a three-stage upgrade pathway for smart mine construction, consisting of system integration and intelligent safety system development, full-process intelligent enhancement covering coal mining, tunneling, electromechanical systems, transportation, ventilation, and operation management, and the third stage focusing on the construction of large mining models, ecosystem collaboration, and emergent intelligence.