Abstract: Aiming at the prominent problems in intelligent coal mine construction, including high investment with low return ratio, advanced technologies with poor adaptability, and high system complexity with low practicality, a five-in-one technical evolution path featuring methodology priority, data foundation establishment, equipment empowerment, system collaboration and intelligent decision-making is constructed based on the engineering practice of Kekagai newly-built coal mine. A differentiated construction methodology centered on a five-level maturity model is established. Following the principles of business-driven development, standard prioritization, phased iteration and integrated innovation, customized upgrading paths ranging from Level 1 disordered stage to Level 5 optimized stage are formulated for various types of coal mines. The intelligent transformation cost per ton of coal is markedly cut, yielding remarkable economic benefits. A seven-dimensional data governance framework complying with national standards and a Software Defined Control (SDC) architecture are developed. The unified standards, interfaces and platforms are realized via the whole-process mode of source data collection, centralized storage, standardized governance and cross-domain sharing. An information technology innovation architecture composed of virtualization layer, domestic real-time operating system and hardware abstraction layer is designed, enabling the transfer of equipment control rights from manufacturers to mine operators. Based on the Viable System Model (VSM), a three-loop intelligent collaborative operation model is proposed. Combined with low-code development paradigm and Lego-style development concept, a dedicated coal mine component library containing over 200 reusable modules covering six major fields is built. This approach effectively improves information technology response efficiency and module reusability, shortens development cycles and reduces external IT outsourcing dependence. A large-scale model for coal mine safety production management is constructed, which integrates production monitoring, equipment perception, risk early warning and decision optimization functions. The prediction accuracy of potential safety hazards is greatly enhanced, and losses caused by safety accidents are substantially reduced. The comprehensive platform has reached Level 4 intelligent maturity with high coverage of autonomous system decision-making, providing valuable references for intelligent transformation of the coal industry.