Perimeter protection is aimed at preventing people and vehicles from entering the territory. However, conventional surveillance systems do not classify the object well enough, resulting in false alarms constantly occurring.
Based on the deep learning algorithm, technologies have been created to distinguish people and cars from other objects, which removes false alarms, thereby making the security system effective and reliable.
IP cameras are now able to identify objects and classify them into three categories.
Human - alarm
Humans are the main offenders.
Vehicle - alarm
Vehicle tracking and number plate recognition.
Other - do nothing
Light, raindrops, cobwebs, leaf movement, animals, etc. no longer cause false alarms.
Recognition in any conditions
Overall accuracy rate over 99%.
Recognition of people and vehicles occurs nearly instantly.
Working in low light
Fast recognition even in low/insufficient light or in complete darkness.
The camera is given an intrusion / crossing zone and a person or a car crosses the border, the camera issues an appropriate signal.
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The accuracy of recognizing an object directly depends on the quality of the image from the camera - the higher the quality, the higher the accuracy.
We implement a full-fledged access control and / or time tracking system: