Open-Pit Mines
Scene Introduction Demand Analysis Program Highlights Core Products Typical Case
Scene Introduction

The combination of steep slopes and complex geological conditions in mines, coupled with extreme weather and high-intensity mining, leads to frequent major accidents such as landslides, collapses, and dam failures. International standards explicitly require the implementation of multi-parameter automated monitoring to drive the transformation of mine safety towards "prevention." Ruhr IoT integrates "air, space, ground, and depth" three-dimensional sensing, AI big data, and mine intelligent agents to provide a full-stack solution from slope stability, environmental dust, and vehicle positioning to intelligent scheduling, ensuring safety is ever-present.

Demand Analysis
  • Slope Instability Due to Long-Term Excavation
    As mining time extends, the slope height and area continue to expand, the rock mass structure deteriorates, and disturbances such as blasting vibrations and rainwater infiltration cause the overall stability of the slope to decline, making it prone to landslides and collapses at any time.
  • Prominent Environmental Issues In Mining
    Mining damages mountains, forests, and even farmland, polluting the surrounding air with dust, endangering human health, and causing economic losses.
  • Safety Production Accidents Occur Frequently
    Employees' failed to comply with operating procedures, insufficient safety awareness, and low overall level of automation can easily lead to personnel injuries and equipment damage.
  • Unstable Loose Stockpiles in Spoil Heaps
    Spoil heaps with large heights, steep slopes, weak foundations, or the presence of groundwater are prone to landslides or debris flows.
Program Highlights
  • Full-Scale Monitoring
    The system intuitively displays historical changes and current status of monitoring data, providing clear and effective information for safe production.
  • Timely Alert Broadcast
    In case of emergencies, the system automatically issues sound, animation, and large-screen alarms, and pushes SMS/email messages to management personnel at different levels.
  • Adequate Data Analysis
    By combining data correlation analysis and video AI behavior recognition, the system optimizes the early warning model, improving accuracy and reducing false alarms and missed alarms.
  • Full-Process Production Monitoring
    AI cameras and smart safety helmets are deployed at key locations such as mining, processing, and storage yards to achieve full-process monitoring and early warning of abnormal personnel behavior.
  • Diversified Information Sharing
    A multi-level management platform is adopted to enable the sharing of monitoring information among reservoir areas, mining areas, management stations, and relevant municipal and provincial departments.
Core Products
Typical Case
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