LH upgrades AI smart monitoring system for retaining wall safety

Korea Land and Housing Corporation said Monday it will upgrade its "AI smart measurement system" — which combines AI and digital twin technology — and strengthen proactive safety management for retaining walls and slopes.

The AI smart measurement system uses high-precision sensors installed on retaining walls to measure displacement, tilt and other structural changes in real time. AI then analyzes the accumulated data and immediately flags any anomalies.

The system can detect subtle changes in structures that are difficult to assess with the naked eye and quickly identify warning signs, enabling early prevention of casualties and property damage.

LH has selected retaining walls requiring priority management from among all LH-managed retaining walls and slopes nationwide, installing the smart measurement system at 80 sites and conducting real-time safety monitoring.

LH plans to enhance the system's core functions to improve the accuracy of hazard detection while further strengthening its round-the-clock monitoring capabilities.

With the risk of sudden heavy rainfall and heavy snowfall growing throughout the year due to shifting weather patterns, LH will have AI comprehensively learn and analyze measurement data and rainfall patterns during disaster situations to secure what it calls a "72-hour golden window before an accident." Through repeated learning, the system will be able to proactively predict warning signs and issue alerts up to three days — 72 hours — before an incident occurs.

For more precise risk analysis, LH will incorporate a digital twin-based three-dimensional visualization control function. The feature renders field conditions as a 3D model in a virtual environment and calculates structural cross-section simulations and risk scores in real time, allowing engineers to intuitively grasp even minor hazards in a three-dimensional view.

LH will also add electrical resistivity testing when analyzing conditions behind retaining walls, enabling a comprehensive assessment of internal structural conditions that are difficult to judge from measurement data alone and improving the accuracy of risk diagnosis.

"Our goal is to actively adopt cutting-edge technologies such as AI and data analytics in safety management and, through continuous technological advancement, detect warning signs faster and more accurately," said Lee Sang-jo, head of LH's Smart Safety Management Division. "We will keep strengthening our safety management framework to protect public safety."

Meanwhile, LH announced in June that it had completed construction of "Neulbom A-Eye," an AI-based real-time safety management system, and begun operations.