Real-Time Monitoring of Slope Displacement Under Rainfall Using a Stereo-Vision System

Abstract

Monitoring slope displacement under the influence of rainfall is crucial for assessing slope stability and mitigating landslide risks. This study proposes a stereo-vision system to accurately measure and analyze slope displacement caused by rainfall. The system captures high-resolution stereo images of the slope surface over time, generating 3D point clouds to track surface deformation. Advanced image processing techniques and 3D reconstruction algorithms are utilized to detect and quantify displacement at specific monitoring points. Unlike traditional contact-based sensors, the stereo-vision system provides a non-invasive, real-time, and high-precision measurement of displacement. The system is tested under controlled laboratory conditions, with rainfall simulated using a fogging nozzle system. Results demonstrate the effectiveness of the proposed approach in capturing subtle surface changes, enabling detailed analysis of deformation patterns. This method offers a cost-effective, scalable, and accurate solution for slope monitoring, providing essential insights for disaster prevention, geotechnical analysis, and early warning systems.