Project Background
In today’s rapidly advancing digital era, the Anhui Suzhou Public Resources Trading Center faces growing demands for improved safety management and operational efficiency. To address these challenges, the center decided to adopt artificial intelligence technology and implement an advanced video analysis system.
Project Objectives
The main goals of the project include:
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Fire and Smoke Detection: Timely identification of potential fire hazards within the trading center to ensure public safety.
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Sleep and Absence Detection: Monitoring staff activity to maintain work efficiency and service quality.
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Facial Recognition: Enhancing visitor management and employee attendance tracking to improve both security and administrative efficiency.
Technical Implementation
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Fire and Smoke Detection:
The system employs deep learning algorithms to analyze surveillance footage and detect signs of smoke or flame in real time. When an anomaly is detected, the system automatically triggers an alarm and notifies both management and fire safety personnel. -
Sleep and Absence Detection:
Using human posture recognition and behavioral analysis technology, the system monitors staff presence and alertness. If an employee is detected sleeping or away from their post, the system records the event and alerts management. -
Facial Recognition:
The system integrates high-precision facial recognition technology for visitor registration, employee attendance, and access control. This enhances entry security while streamlining visitor management and attendance processes.
Implementation Steps
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System Deployment: Install high-definition smart cameras in key locations to ensure comprehensive coverage.
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Software Integration: Integrate the AI video analysis system with the existing monitoring infrastructure to optimize data processing workflows.
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Data Management: Utilize a cloud-based platform for data storage and analysis to ensure system stability and reliability.
Expected Outcomes
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Effectively prevent and respond to fire and other emergencies, greatly improving public safety.
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Enhance work efficiency and service quality through active monitoring of staff attendance and alertness.
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Simplify visitor management and attendance tracking, improving overall administrative efficiency.
Conclusion
The Anhui Suzhou Public Resources Trading Center Video Analysis System Project represents a major enhancement in safety and management processes, showcasing a successful application of AI technology in the public service sector. By implementing this system, the trading center not only strengthens security but also provides a valuable model of intelligent, data-driven management for other public institutions to follow.