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In order to ensure the safety and quality of large-scale coal mining work, digital twin technology is used to optimize the design of remote intelligent monitoring methods for large-scale coal mines. Using digital twin technology to construct a virtual model of large-scale coal mines, determine the location of measurement points under this model, and remotely collect real-time operational data of large-scale coal mines. By extracting and matching data features, monitoring the operation status of large coal mines from two aspects: mining equipment and construction environment. Retrofitting a remote intelligent controller for large coal mines, using the monitoring results of operating status as the starting condition for the control program, to achieve remote intelligent monitoring tasks for large coal mines. By comparing with traditional monitoring methods, it can be concluded that the optimized design method significantly improves the monitoring performance of coal mining excavation equipment, reduces the monitoring errors of gas concentration and temperature in the environment by 0.34% and 0.19 ℃, and reduces the control errors by 0.09% and 0.145 ℃, respectively. At the same time, the monitoring range is expanded by 27.4%.