Concealed Geohazard Risks and the Operation of Artificial Intelligence Technology

Geohazard monitoring technology constitutes a critical approach for disaster risk prevention and control. This paper systematically reviews innovative applications and challenges of optical fiber sensing, radar remote sensing, artificial intelligence (AI), and related technologies in geohazard monitoring. By analyzing the mechanisms and case studies of distributed optical fiber sensors (DOFS), SBAS-InSAR, UAV remote sensing, and deep learning models, this study reveals the pivotal role of multi-source data fusion and intelligent algorithms in early warning systems for landslides, rockfalls, and other geological hazards. The research identifies existing bottlenecks, including insufficient adaptability to complex environments and limited model interpretability. Future breakthroughs are proposed through interdisciplinary technology integration, adaptive algorithm optimization, and sensor material innovation. This paper provides theoretical foundations and technical references for advancing the intelligence and integration of geohazard monitoring technologies.