Physical Security
How AI video analytics cut false alarms by 96%
Wind, rain, cats and headlights used to trigger most alarm call-outs. Here is how modern analytics and human verification changed the maths.
SAMO Operations Center · · 6 min read
For decades, the biggest cost of an alarm system was not the hardware. It was the false alarms: guards dispatched to find a fox, a flapping banner or a spider on a lens. Most monitoring centres still see nine false activations for every real one.
What changed
Deep-learning analytics now run directly on cameras and recorders. Instead of reacting to any change in pixels, they classify what they see: person, vehicle, animal, or nothing at all.
- Object classification filters out animals, weather and lighting changes
- Virtual tripwires and zones only fire when a person crosses a real boundary
- Thermal cameras keep working in fog and total darkness
- Every remaining alert is verified by an operator on video before dispatch
AI decides what deserves a human's attention. A human decides what deserves a response.
What it means for you
Fewer wasted call-outs, faster response to the real ones, and police who take your alarms seriously because they are always verified. It also makes monitoring affordable for sites that could never justify a guard on patrol.
Doing it lawfully
Video analytics process personal data, so GDPR applies. Run a DPIA, use privacy masking on public areas, keep retention short and documented, and avoid facial recognition unless you have a clear lawful basis.