Intelligent Early Warning and Monitoring Solution for Mines

A comprehensive solution that prioritizes mine safety and integrates algorithms, computing power, and a unified platform to provide all-around safety protection for mining enterprises.

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Customer pain points

Smart Campus Solution IOC

Solution Architecture

Application Scenarios

Value of the plan

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Solution architecture

Application scenarios

7*24 hour AI video patrol and analysis of mines, providing real-time AI early warning and reporting of dangerous events and personnel violations. This includes AI video analysis such as: sleep detection, no hard hats, no reflective clothing, area intrusion, open flames, smoke, facial recognition, smoking, etc., as well as environmental exceeding warning.

Safety Helmet Wearing Detection

Real-time analysis of whether safety helmets are worn according to regulations, recording on-site video, identification, tracking, and alarm

Personnel Count Detection

When the mining face is shut down, count the number of personnel on the face. If the number of personnel exceeds the normal maintenance personnel, immediately alarm.

Fully Loaded Mine Car Detection

Detect whether the mine car is fully loaded. When a fully loaded mine car is detected in the monitoring area, trigger the detection and automatically save the time, location, and corresponding photos.

Phone Call Detection

Pre-set a no-phone zone in the monitoring scene. Real-time monitoring of whether anyone is making a phone call in this area. When detected, immediately alarm, link with the personnel location monitoring system, take screenshots as evidence, and remotely or on-site punish the relevant personnel.

Electronic Fence Detection

Set up a danger zone to monitor for unauthorized personnel entering restricted areas. Send an immediate alarm signal if detected.

Absence Detection

Automatically identify and monitor the on-duty status of personnel, detecting and alerting to absences 24/7.

Large Ore Detection

Detect large ore on conveyor belts. Trigger an alarm and automatically save the time, location, and corresponding photos when large ore is detected.

Self-Rescuer Detection

Real-time analysis, recording of on-site video, identification, tracking, and alarming of self-rescuers. If personnel are found not carrying self-rescuers as required, the system will automatically issue an alarm and save the time, location, and corresponding photos.

Solution Value

Fully Self-Developed

Multiple algorithms, constantly iterated and updated; independent algorithm team; nearly 200 self-developed algorithms; supports algorithm customization.

Flexible Deployment

Can be flexibly deployed according to needs: large platform (AI early warning and disposal cloud platform), small platform (embedded AI early warning system), quick response; host-built platform, quick deployment, plug and play.

Combination of Large and Small Models

Combines large and small models to improve algorithm accuracy.

Simple and Easy to Operate

User-friendly operation; interface constantly updated and iterated for better user experience.


Real-time monitoring and early warning	Emergency response and dispatch	Hidden danger investigation and risk assessment	Data statistics and analysis
Real-time AI monitoring of various parameters at the mine production site, including personnel location, equipment status, and environmental parameters. An anomaly immediately triggers a warning mechanism.	Emergency warning; the system can quickly respond and activate emergency plans to assist managers in accident dispatch and rescue operations.	Regular hidden danger investigation and risk assessment; through AI data analysis and model prediction, potential safety risks and risk points are identified.	Automatically generated safety reports quantify and close the loop on safety hazards and implementation status.