Abstract: The monitoring alarming or early warning of five major hazards in coal mines are initially achieved in China. The hazards include gas, fire, water damage, roof and dust. However, the level of intelligence is relatively low, and it does not have the capability to self-analyzing and making decisions. Under the framework of the concept of intelligent mines, the connotation of intelligent hazard early warning for coal mine is elaborated. The four features of intelligent hazard early warning are proposed: accurate perception data, intelligent early warning models, collaborative early warning and hazard prevention, and efficient emergency decision-making. The overall architecture of intelligent hazard early warning for coal mine is designed. It consists of four layers: perception control layer, transmission layer, storage analysis layer, and application layer. It can achieve intelligent early warning and control of various hazards. It adopts the data processing principles of unified standards, unified collection, unified storage, unified analysis, and unified presentation. It can achieve multi-source heterogeneous data sharing and deep mining utilization for intelligent hazard early warning, so as to solve problems such as isolated data island and data chimney. Based on the overall architecture of intelligent hazard early warning for coal mine, an intelligent hazard early warning business process has been designed to provide reference for intelligent hazard early warning design. The key technologies of intelligent hazard early warning of coal mine are summarized. The key technologies include precise monitoring and early warning of gas, fire, water damage, roof and dust, and intelligent hazard fusion early warning technology. The difficulties and development directions of each key technology are analyzed. Taking intelligent hazard early warning platform of Qinglongsi Coal Mine as an example, the application effects of intelligent hazard early warning technology in monitoring, hazard early warning, emergency rescue and hierarchical control are demonstrated. It is proposed to conduct in-depth research on precise hazard perception technology and equipment, multi field coupling hazard mechanism, and self-learning and adaptive technology of warning models to achieve intelligent hazard early warning in advanced stages.