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Our system enhances security by automatically designating low-activity areas as restricted zones. Any object detected in these areas is considered a potential security threat and triggers immediate alerts to security personnel.
The system continuously analyzes object occurrences within a set time period and grid cell.
If the frequency falls below a predefined threshold, the area is automatically marked as restricted.
This threshold can be adjusted based on system requirements, making it adaptable to different environments.
By leveraging frequency analysis, the system can autonomously identify high-risk areas without requiring manual configuration.
This dynamic adaptation allows the system to adjust in real-time, ensuring accurate and efficient surveillance.
Compared to traditional rule-based systems, this approach significantly reduces false positives, ensuring that alerts are only triggered by genuine security threats.
The system¡¯s real-time responsiveness makes it effective in detecting evolving threats.
This automated, data-driven model enhances surveillance efficiency, making it scalable for large, high-risk environments such as airports, industrial sites, and city-wide surveillance networks.
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IEEE/ICACT20250047 Slide.08
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