Abstract: Intelligent monitoring and early-warning of mining-induced geological disaster in metal mines is an essential technology ensuring mine safety and production. This paper provides a concise overview on the current state of this technology, focusing on the definition of geological disaster risks,types,monitoring methods,and early warning techniques specifically used in metal mining. It is pointed out that the quantitative analytical framework for assessing the susceptibility,vulnerability and risk of geological disasters in metal mines is still not comprehensive in terms of disaster risk definition. In terms of disaster risk monitoring and data fusion,the theories of collaborative monitoring with multi-sensing devices and data fusion are still not comprehensive. The intelligent adjustment of sensing device deployment plans based on risk conditions has not been achieved yet, which makes it difficult to ensure the spatiotemporal integrity and continuity of mechanical responses of disturbed rock masses. In terms of disaster risk early warning methodology,the combination of monitoring and simulation has become a trend for early warning of mining disasters. It should be further integrated with cloud computing,artificial intelligence and other technologies to establish a comprehensive theoretical system,so as to achieve real-time,dynamic,accurate and intelligent risk early warning for disasters. On this basis,based on the academic concept of " combining on-site monitoring and numerical simulation for early warning" ,this study puts forward an integrated disaster risk intelligent prediction and early warning method consisting of " geological disaster case matching,multi-source data mining,mechanical mechanism analysis,and expert system diagnosis" . Taking the monitoring and early warning of shallow buried cavity collapse and surface subsidence risks in Gongchangling Open-pit Mine as a background,the application and promotion of the proposed method are realized. Finally,it is pointed out that disaster risk intelligent monitoring and early warning technologies in metal mines face challenges in multi-source data fusion,disaster prediction model parameter selection,and completeness of early warning systems. High-performance dedicated intelligent sensing technologies and equipment for multiple disaster types,standardized data communication protocols and architectures,disaster intelligent early warning models combining monitoring and simulation,geological disaster monitoring and warning platforms and digital twin technologies are key the technologies to solve the above issues and will be major future development trends.