Project Background
Location and Institution: The project is implemented at the Rongtong Division of the China Industrial Internet Research Institute, located in Chaoyang District, Beijing.
Objective: To leverage artificial intelligence technology to enhance safety monitoring and management capabilities in industrial environments.
AI Algorithm Functions
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Safety Helmet Detection:
Using advanced image recognition technology, the system ensures that all personnel on site are wearing safety helmets. It monitors video feeds in real time and issues alerts when individuals are detected without helmets. -
Fire and Smoke Detection:
Cameras deployed throughout the industrial area continuously monitor for signs of smoke or open flames. This early detection capability is crucial for preventing fires and ensuring rapid response. -
Work Uniform Recognition:
By identifying specific work attire, the system verifies whether personnel are authorized to enter designated areas, thereby improving access control and workplace safety. -
Unauthorized Personnel Intrusion Detection:
The system detects and identifies unauthorized individuals entering restricted zones and immediately alerts management personnel. -
Sleep and Absence Detection:
Through behavioral pattern analysis, the system identifies potential safety risks such as employees sleeping or leaving their posts during working hours. -
Vehicle Intrusion Detection:
The system recognizes vehicles entering areas where they are not permitted and automatically issues an alarm. -
Video Fault Detection:
The platform continuously monitors the operational status of surveillance cameras to ensure the monitoring system remains stable and functional. -
Conveyor Belt Status Monitoring:
By analyzing real-time video footage, the system detects irregularities or faults in conveyor belt operation, helping to prevent accidents and equipment failures.
Implementation Outcomes
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Enhanced Safety: Real-time monitoring and AI-powered alerts have significantly reduced workplace accidents and potential risks.
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Improved Efficiency: Automated surveillance minimizes the need for manual inspection, increasing overall operational efficiency.
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Data-Driven Insights: Collected data supports deeper analysis, enabling continuous optimization of workflows and safety protocols.
Conclusion
The Safety Platform Project at the Rongtong Division of the China Industrial Internet Research Institute demonstrates the transformative potential of AI technology in industrial safety management. Through an integrated intelligent monitoring system, the project has not only improved workplace safety but also provided valuable insights and solutions for the future of intelligent industrial development.