Optimizing Perimeter Security via Orisol’s AI-Powered Safety Security Shield (SSS)

A footwear brand’s design and development center had long relied on a traditional system to create virtual fences for detecting unauthorized access or abnormal activities. However, this rule-based approach depended mainly on object , movement trajectory, and speed variations—without understanding semantic or behavioral context—resulting in frequent false alarms.

Common triggers such as moving tree shadows, light reflections, small animals, or rain often set off false alerts. Due to the high false-alarm rate, security staff found it difficult to distinguish real incidents from noise. Over time, confidence in the system declined, leading to partial or complete deactivation of the alert function.

To resolve this issue, the center implemented Orisol’s Safety Security Shield (SSS) equipped with AI-based image recognition technology. Powered by deep-learning models instead of traditional rule sets, SSS can accurately identify human presence, behavioral patterns, and abnormal activities. Based on field testing and site experience, the detection range of the electronic fence was optimized to 20–25 meters, ensuring reliable and stable monitoring performance.

According to test results, the traditional IVS system correctly identified only 2 out of every 10 alerts (20% accuracy), while the AI-driven system achieved a 90% accuracy rate with false alarms reduced to just 10%. This greatly reduced unnecessary interruptions and restored trust in the factory’s security system.

With the AI-powered model in place, security personnel can now respond quickly and confidently based on alert levels, improving both efficiency and reaction speed. The upgraded system transforms video surveillance from a reactive tool into a proactive, intelligent safeguard for smart factories.