Features:

1. Intelligent Speed Control

   • Utilizes a proprietary explosion-proof camera designed for mining to capture coal flow information, based on intelligent machine vision flow detection algorithms.
   • Implements variable frequency speed control with high, medium, low, and idle speeds according to the actual conveyor belt load, achieving energy-saving objectives.
   • Automatically identifies the conveyor load through camera detection, selecting the appropriate transmission mode within specific thresholds to optimize energy consumption.

2. Coal Quantity Detection

   • Collects coal flow data using an in-house developed explosion-proof camera for mining, underpinned by intelligent machine vision flow detection algorithms.
   • Identifies and marks the transported coal quantity, calculating the load through algorithmic processing.

3. Foreign Object Detection

   • Transitions from manual inspections or fixed camera monitoring to intelligent inspection robots in key underground areas of coal mines.
   • Intelligent inspection reliably collects real-time video and environmental data from underground coal mine sites, enabling management to make timely control decisions based on data analysis.
   • Detects and analyzes abnormal events in specific conveyor monitoring areas, providing timely, intelligent, and accurate video monitoring and alarm services for underground coal mines.

4. Monorail Inspection

   • Monitors underground monorail systems in coal mines using intelligent detection, capturing real-time video and operational data of monorails.
   • Detects whether personnel are properly using the monorail, ensuring compliance with safety protocols. Alerts management in case of any violations.

5. Smoke and Flame Detection

   • Uses intelligent video analysis and deep learning neural networks to identify smoke and flames within monitored areas.
   • Tracks the dynamic progression of smoke and flames from none to presence, small to large, and vice versa, providing real-time analysis and alarms without relying on other sensors.
   • Offers a high recognition accuracy of ≥95% and a false alarm rate of less than 2%.

6. Crossing/Intrusion Detection in Critical Areas

   • Continuously monitors the safety status of work area perimeters using intelligent video analysis and deep learning neural networks.
   • Management can define critical zones, with the system recording and alerting whenever someone crosses into or traverses these dangerous zones.
   • Ensures a recognition accuracy of ≥95% and a false alarm rate of less than 2%.

7. Safety Helmet and Apparel Detection

   • Monitors the safety gear compliance of personnel entering work areas, ensuring correct wearing of helmets and protective clothing.
   • The system will block access to the work area if proper safety gear is not detected, alerting management for necessary action.

8. Conveyor Belt Misalignment Detection

   • Leverages intelligent video analysis and deep learning neural networks to detect misalignment in coal conveyors.
   • Alerts and records when the belt deviates from its designated path, promptly notifying management for corrective action.
   • Maintains a recognition accuracy of ≥95% and a false alarm rate of less than 2%.