AI algorithm

Area Intrusion and Line Crossing Detection

AI detection for restricted-area intrusion, line crossing, perimeter protection, forbidden-zone entry, loitering, and abnormal stay events.

Area intrusion analysis converts a camera image into a defined operating rule. The site team sets the region, line, direction, target type, time schedule, and duration that matter for the location.

Rule Design

The system supports region rules, boundary lines, direction settings, schedules, target filters, and duration thresholds. It is commonly used for perimeter walls, equipment zones, storage areas, construction boundaries, and hazardous work areas.

Algorithm deployment notes

Defining an intrusion event from the camera view

Area intrusion and line-crossing analytics become useful when a site can define a boundary, a direction, a time period, and the response expected when a person or vehicle enters. The algorithm detects movement in the image; the operational rule gives that movement its meaning.

Draw rules around a physical reference

Use stable boundaries such as gates, doors, marked lanes, fence lines, machine barriers, loading zones, and corridor thresholds. The camera should see the approach path and the boundary clearly enough to distinguish entering, leaving, passing nearby, and remaining inside the area.

Add time, direction, and dwell logic

A line-crossing rule can specify the permitted direction. A region rule can use a schedule, minimum duration, object type, and repeat interval. These settings help separate ordinary use of a shared space from entry into a controlled zone or occupation of a protected route.

Make the alarm understandable later

Retain the camera name, location, time, rule ID, direction or region, snapshot, and related video where available. This allows operators to see which configured boundary was involved and whether the event is relevant to the site procedure.

Check seasonal and scene changes

Vegetation, shadows, rain, gates left open, parked vehicles, construction changes, and camera repositioning can alter a boundary view. Review the reference image after such changes and test the rule again before relying on it for continuous alerts.

Related planning: AI edge box integration for existing CCTV. The rule should be documented with its physical location and the authorised exception process.

Project inquiry

Tell us your camera environment and required AI analytics.

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