Optimizing Ore Drawing powered by Object Detection

Based on Patent Research | CN-117749996-A (2024)

Optimizing ore drawing is essential for safe and efficient mining operations. However, current manual processes are often dangerous, inefficient, and labor-intensive. This exposes workers to hazards, leading to accidents and reduced productivity. Computer vision, specifically object detection, offers a solution. It precisely identifies and locates specific targets, such as desired ore or potential obstructions, within real-time imagery. This capability enhances worker safety, streamlines operations, and improves overall efficiency by automating critical monitoring.

SOLUTION OVERVIEW

Manual Drawing Transformed by Smart Monitoring

In Mining and Quarrying, object detection technology directly addresses the challenges of hazardous, inefficient manual ore drawing. This capability uses cameras to capture real-time imagery of draw points and muck piles. Its process involves analyzing these images to precisely identify and classify specific targets, such as desired ore or potential obstructions. This automated system then provides immediate, accurate location data, enabling informed adjustments to operations and enhancing safety protocols for personnel.

The practical application of object detection enables continuous, automated monitoring, significantly reducing reliance on manual inspections in risky areas. It integrates seamlessly with existing mine management systems, providing valuable data for optimizing extraction and material handling. Consider it akin to having a tireless safety supervisor constantly observing every draw point, flagging potential hazards or blockages instantly. This technology contributes to substantial operational improvements, resource optimization, and more effective decision-making across mining sites.

HOW IT WORKS

Mine Images Yield Ore Insights

Capturing Live Visuals

High-resolution cameras are strategically placed at ore draw points and muck piles to continuously capture real-time video feeds. This constant visual input provides the essential raw data for the AI system's analysis.

Detecting Critical Elements

The AI system processes these live video streams using sophisticated object detection algorithms. It precisely identifies and classifies key targets, such as desired ore, large rocks, or potential obstructions within the drawing area.

Analyzing Operational Data

Following detection, the system analyzes the identified objects' positions, sizes, and movements. This analysis provides crucial contextual information about the material flow and potential issues at the draw point.

Delivering Actionable Intelligence

Based on its analysis, the system generates immediate, accurate location data and alerts regarding identified targets or hazards. This output provides real-time insights into the ore extraction process.

Guiding Smart Adjustments

These actionable insights are instantly communicated to operators and integrated with mine management or edge control systems. This enables automated adjustments to equipment, optimizing ore drawing and enhancing worker safety protocols.

Potential Benefits

Enhance Worker Safety

Automating monitoring of hazardous draw points drastically reduces manual inspections in risky areas. This minimizes worker exposure to dangers, preventing accidents and improving site safety protocols.

Optimize Resource Extraction

Object detection precisely identifies desired ore and obstructions in real-time. This enables informed, immediate adjustments to extraction operations, maximizing yield and minimizing waste efficiently.

Boost Operational Efficiency

By automating critical monitoring and providing accurate location data, the system streamlines ore drawing processes. It reduces labor-intensive tasks and enhances overall productivity across mining sites.

Enable Data-Driven Decisions

The system provides continuous, accurate data on draw point conditions and material flow. This empowers mine management with insights for optimizing extraction, handling, and strategic planning.

Implementation

1 Camera Installation. Strategically position and securely install high-resolution cameras at ore draw points. Ensure robust power and reliable network connectivity.

2 Data Acquisition. Collect diverse video data of ore and obstructions from the site. Accurately label these objects to prepare datasets for AI model training.

3 Model Development. Train the object detection model with labeled data. Configure the AI to precisely identify targets relevant to ore drawing operations.

4 System Integration. Integrate the trained AI model with existing mine management or edge control systems. Establish real-time data flow for actionable insights.

5 Calibration & Validation. Calibrate the integrated system for accurate detection and location reporting. Validate its performance against real-world ore drawing scenarios.

6 Operational Deployment. Deploy the AI system for continuous, automated monitoring. Monitor performance and leverage insights for optimizing ore drawing and safety.

Source: Analysis based on Patent CN-117749996-A "Underground intelligent ore drawing system for mine" (Filed: March 2024).