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False Alarm Filtering

By utilizing proprietary computer vision algorithms, Scylla AI video analytics triggers alerts only in case of validated threats, impressively minimizing false positives by up to 99.95%.

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How it works


Scylla False Alarm Filtering detects a person or vehicle in a single or a sequence of frames.


As soon as an object of interest is detected in the frame, an alert is formed and forwarded to security personnel.


By utilizing computer vision and artificial intelligence, Scylla False Alarm Filtering allows to impressively reduce the number of false positives by up to 99.95%.


The filtering algorithm can be configured to be sensitive only to certain areas of the frame as well as at predefined time slots.

What makes Scylla False Alarm Filtering stand out


Smart video analytics adds actionable intelligence on top of the hardware to help security personnel eliminate the overwhelming amount of false positives that inevitably cause noise fatigue, additional expenses and time loss.


Conventional motion detection-based surveillance cameras are inefficient for the most part as they trigger alerts each time anything moves on the video frame, be it a ceiling fan, foliage, shadow change, or an animal. Meanwhile, Scylla AI video analytics is highly sensitive to such events and alerts are triggered only if the object of interest is detected.


Deployed on premise Scylla False Alarm Filtering will operate 24/7 for your situational awareness.

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Video Surveillance False Alarm Filtering Technology Guide

We compiled a comprehensive guide to explain how advanced AI-powered solutions help to significantly reduce the number of false positives, improve operational productivity and cut costs.

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