Intelligent control of underground mine ventilation processes based on deep learning and real-time sensor data analysis
The study proposes an intelligent approach aimed at collecting and preprocessing multi-parameter sensor data, detecting hazardous situations, forecasting the state of the mine atmosphere, and adaptively controlling fan operating modes based on deep learning models and the analysis of real-time sensor data.