Abstract: Microseismic monitoring technology plays a vital role in mine disaster early warning and prevention and control, with its core advantages being high spatial resolution and sensitivity. It can capture microseismic signals in real-time, achieve precise positioning, effectively identify potential instability zones, and provide comprehensive spatiotemporal coverage. However, the application of this technology faces challenges: complex and easily interfered microseismic signals make traditional methods struggle to achieve high-precision identification; sensor limitations in mine environments create monitoring blind spots; insufficient data processing capabilities, uncertain geological conditions, and imperfect early warning feedback mechanisms also affect application effectiveness. Future development directions include technical integration and intelligent optimization, construction of multi-source heterogeneous data fusion monitoring systems, deep application of artificial intelligence and machine learning, as well as cutting-edge exploration of quantum sensing and interdisciplinary integration. With improvements in sensor accuracy, data transmission efficiency, and intelligent algorithms, this technology will evolve toward high precision, full coverage, and intelligent development, providing support for mine safety production and driving the digital and smart transformation of safety management systems.