Data-driven monitoring system for ground reinforcement using advanced visualization techniques

Slope stability monitoring aims to prevent damage caused by slope failure. Although various methods have been proposed to track overall slope behavior, these approaches often overlook embedded reinforcements that play a critical role in maintaining slope stability. Therefore, this study proposes a method to visualize and monitor the status of embedded reinforcements to enhance current slope stability monitoring practices. To intuitively understand the status of the embedded reinforcement, reinforcement information and measured data were integrated into a Building Information Model (BIM) using Dynamo for visualization. In laboratory-scale slope models subjected to 150 mm/h rainfall, embedded strain gauges captured deformation leading to localized shear failure, validating the proposed method. These strain data were automatically imported into BIM, where color-coded elements highlighted ‘Safe’, ‘Warning’, and ‘Danger’. This proof-of-concept establishes a scalable digital-twin workflow for proactive maintenance and decision-making, enhancing the resilience and sustainability of slope-reinforced infrastructure. Additionally, this approach is expected to enhance the sustainability of various infrastructure structures through disaster prevention, including structural reinforcement and ground reinforcement of roads, bridges, and tunnels over slopes. • Integrated real-time strain data with BIM to monitor embedded reinforcements. • Automated reinforcement modeling and status updates via Dynamo scripts. • Visualize reinforcement status with color-coded digital twins. • Lab-scale rainfall failure tests verified the visualization of reinforcement states.