 |
While traditional CCTV intrusion detection systems provide a basic level of security, they come with several limitations.
First, manual rule configuration is complex and inefficient, requiring significant effort from security teams.
"Second, users must input multiple parameters for each camera, making setup and maintenance time-consuming.
Lastly, in large-scale environments, managing multiple cameras simultaneously is challenging and inefficient, leading to operational bottlenecks.
To address these limitations, a more advanced solution is required.
An AI-driven intrusion detection system can automate rule configuration and improve detection accuracy.
Efficient processing of large-scale CCTV data is essential for real-time surveillance in complex environments.
Automated configuration and adaptive learning will make the system more user-friendly, eliminating the need for manual intervention while ensuring optimal security performance.
In the next section, I will introduce our proposed approach that leverages AI and deep learning for enhanced intrusion detection.
|
IEEE/ICACT20250047 Slide.04
[Big Slide]