Abstract: With the steady progress of intelligent mine construction and the acceleration of the implementation of digital transformation of coal enterprises, the demand for digital business applications of coal mine users is growing exponentially. This puts forward higher requirements for the efficiency of business application development. The traditional development model of application systems in the coal industry relies excessively on professional manufacturers. It has problems, such as long implementation cycles, high implementation costs and low resource reuse rates. It is difficult to meet the management requirements of coal mine users for rapid development of business applications. To solve the above problems, a design scheme of intelligent mine low code industrial IoT platform using the "model driven" development mode is proposed. Based on microservices technology, the platform architecture including the data acquisition layer, data processing layer, data storage layer, data release layer, human-computer interaction and application layer is designed. The operation platform at each level resolves the corresponding functions of the development platform configuration through a resolution engine. By designing data encoding and master data specifications, platform internal data interaction specifications, platform interfaces and services, a unified technical system has been established. The unified supervision of various IoT monitoring objects on coal mine operation sites is achieved. By developing a low code component toolbox, a series of common functions and business logic that originally needed to be customized and developed in various monitoring system software for coal mines are uniformly encapsulated. It forms directly reusable components that can adapt to different types of monitoring system applications in coal mines. This provides users with a visual development environment for intelligent mining application software development by dragging and dropping components and configuring parameters. The application results indicate that this platform can provide a rapid development platform for coal mine monitoring systems, meeting the daily needs of coal mine users for emergency customized task development.