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Use case · Security

Perimeter intrusion detection

Your fence line is already on camera. Make those cameras raise the alarm instead of just recording the break-in.

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The problem

Why it keeps happening.

Perimeter cameras at most sites are forensic tools, useful for finding out what happened after the theft or trespass. Motion-based alarms drown security teams in false positives from animals, weather, and headlights until the alerts get ignored.

Remote assets (substations, pump stations, laydown yards) are the most exposed and the least watched.

The rule

Written the way you'd say it.

In plain English
“Alert security when someone crosses the perimeter line after hours.”
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How it runs

  1. 01

    Use the fence-line views you have

    Existing perimeter and gate cameras connect over ONVIF/RTSP. Remote sites run the same detection with offline buffering when connectivity drops.

  2. 02

    Detect people and vehicles, not motion

    Person and vehicle detection ignores the swaying branches and wildlife that make motion alarms useless. Alerts mean something is actually there.

  3. 03

    Schedule the enforcement

    After-hours rules arm automatically; delivery windows and known patterns are excluded. Escalation goes to guards, the control room, or a monitoring provider.

  4. 04

    Respond with evidence in hand

    Each alert carries the sealed clip and location. Responders see what and where before they move, and the record stands up afterwards.

Measure

What's measured.

  • Crossings per perimeter segment, after hours
  • Alerts confirmed against alerts dismissed
  • Response time per site

What it’s worth

  • Theft and trespass interrupted instead of investigated
  • Guard hours focused by real alerts, not sensor noise
  • Remote assets covered without staffing them
  • Sealed evidence for police reports and insurance claims

Estimate your ROI for your own operation, in about two minutes.

Comply

The evidence.

  • A clip and frame of the event, sealed with the device’s own key the moment it happens
  • The rule that fired, the zone and camera, and the time
  • The vision-language model’s verdict on the alert, with its reason
  • Who saw it, who acted, and when, in the audit log
FloFusion · alert review
An alert in FloFusion: the frame, the review choices, and the device seal and evidence check both verified

Common questions

How are false alarms kept low?

Detection looks for people and vehicles, not motion, and rules add zones, schedules and dwell. A vision-language model checks each alert before your team reviews it.

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What about sites with no reliable connectivity?

FloFrame detects on site and keeps working through outages. Alerts and their sealed evidence go up when the link returns, over outbound HTTPS on port 443 only.

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More use cases

The use-case library

See it on your own cameras.

A pilot on the cameras you already own, with success criteria agreed up front.

Book a demoTry it in the Rule Playground