Abstract: In order to improve the ability and level of intelligent prevention and control on the hidden danger of coal spontaneous combustion fire,the near-field real-time collection,intelligent analysis and accurate early warning of coal spontaneous combustion index data are realized. By collecting fresh coal samples from multiple mining areas,the evolution characteristics of coal spontaneous combustion characteristic parameters were determined by means of coal spontaneous combustion temperature-programmed heating and spontaneous ignition tests. Combined with the characteristic points of the coal spontaneous combustion mechanism refinement index curve,a graded early warning model of the type I coal seam prone to spontaneous combustion is constructed,and the relevant early warning indicators and thresholds are determined. The ZDC7 mine fire intelligent monitoring and early warning system has been designed and developed,including mine intrinsically safe multi-parameter wireless sensor (GD7), mine intrinsically safe wireless monitoring host (ZDC7-Z),and intelligent management and control software platform. Mining multi-parameter sensors can independently collect data in the near field (CO, CH₄, CO₂, O₂, H₂S, temperature and humidity, differential pressure,etc.). In order to ensure that the ZDC7 system can be easily integrated into the underground industrial ring network of coal mines and effectively and stably ensure the transmission of data and information to multiple terminals (mobile phone APP,ground industrial computer,underground interactive interface,etc.),the bandshaped confined space energy efficient fault-tolerant topology control technology and the open wireless sensing network protocol standard adopted by the monitoring host can be used. In order to realize multi-source information fusion and self-processing,intelligently analyze the fire warning level and abnormal coal spontaneous combustion area situation prediction,an intelligent analysis and early warning module embedded in the intelligent management and control software platform is used,combined with deep learning and multiple regression analysis and other theories,and based on monitoring information. The preprocessing analysis of the method realizes the auxiliary decision support of the fire prevention and control technical scheme. As a mine fire intelligent monitoring and early warning system, it is embedded with a coal spontaneous combustion classification early warning and auxiliary decision-making model, which can sense the coal spontaneous combustion characteristic information online in real-time,and intelligently identify and assess the coal spontaneous combustion degree. Its on-site industrial tests and applications have been carried out,and its technical equipment conforms to the relevant national norms and standards for the construction of intelligent mines. The actual needs of coal mining enterprises for intelligent monitoring,early warning and prevention and control of mine fires have been met,and the green safe mining of coal mining enterprises is effectively guaranteed.