Too Late to Predict: The Challenge of Early Landslide Warning

Slope failure is one of the most dangerous operational risks in mining. Existing monitoring systems typically provide short prediction windows and limited analytical insight—leaving operations reactive and exposed to catastrophic losses.

SQE Solution

AI-Based r capable of detecting micro-movements in real time using high-resolution sensors, processed through NVIDIA GPU inference. The system enables long-term prediction and early warnings to prevent slope collapses.

COSMOS implements an AI-Based Monitoring

COSMOS is capable of detecting micro-movements in real time using high-resolution sensors, processed through NVIDIA GPU inference, enabling:

Near real-time monitoring of slope micro-shifts using precision sensors

Time-series prediction using machine learning & geotechnical modeling

Integration of external environmental indicators: rainfall, groundwater, seismic events

Analysis of internal geological factors: material type, structural layers, composition

Impact

Measurable Outcome

USD 5.0M Protected

Operational losses avoided from unexpected slope failures through early landslide warning

Geo-Risk Analysis · Slope Safety Team

≥50% cost reduction

Emergency response, evacuation, and recovery expenses significantly reduced through proactive slope failure alerts

Reactive → Predictive

From post-failure emergency response to long-term predictive insights for safer operations planning and stronger ESG compliance

Too Late to Predict: The Challenge of Early Landslide Warning