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

USD 4–5 Million Value Protected

Reduced operational losses through minimized downtime caused by unexpected slope failures

Higher Decision Confidence

Long-term predictive insights for operations planning

≥50% Cost Reduction

Lower emergency response, evacuation, and recovery expenses

Earlier Safety Intervention

Proactive alerts before failure escalation

CAPEX Loss Prevention

Avoided damage to equipment and critical slope infrastructure

Stronger ESG Compliance

Measurable improvements in risk and safety governance

Too Late to Predict: The Challenge of Early Landslide Warning