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In order to solve the problem of low safety in coal mine underground construction, an improved RBF data fusion algorithm is used to optimize the design of coal mine underground safety monitoring methods. Install gas, temperature and humidity sensors and equipment in the underground environment of coal mines, and install them at the designated measurement points. Using the improved RBF data fusion algorithm to collect and process sensing data, based on the data fusion results, considering environmental parameters such as gas concentration, temperature and humidity, and mine pressure, the monitoring results of coal mine underground safety are obtained. Considering the real-time location of underground personnel in the coal mine, determine the direction of underground safety monitoring, and use the designed safety monitor to achieve underground safety monitoring work driven by the safety monitoring results. Through effectiveness testing experiments, it can be concluded that compared with traditional monitoring methods, the optimized design method reduces gas and temperature monitoring errors by 1.005mg/m, respectively 3 And 5.65 ℃, while the safety monitoring range has been significantly expanded.