AI perimeter surveillance applies computer vision to outdoor camera views to detect configured conditions at site boundaries, fences, gates and restricted outdoor areas.
Virtual perimeters and boundaries
Rather than treating the entire camera image as a security condition, BAV ONE allows teams to define polygons or lines within the calibrated camera scene. This reduces irrelevant events from activity outside the configured boundary.
Detection and filtering
Person and vehicle detection provides the object class. Direction filtering, object class selection and schedule windows reduce events from permitted activity. A vehicle entering through an authorized gate during business hours should not generate the same event as an unauthorized person crossing a perimeter at night.
Vision Policy for perimeter events
A perimeter Vision Policy combines the boundary crossing or zone presence with direction, object class, time schedule and duration before creating an event. Severity, evidence and escalation are configured per workflow.
Edge processing for remote sites
BAV Edge can run approved inference near remote or controlled sites and share policy-approved events and evidence. This is relevant for perimeter monitoring at sites with limited connectivity.
What AI perimeter surveillance does not do
AI perimeter surveillance can support earlier awareness and evidence for configured conditions. It does not prevent intrusion. Physical security and human response remain separate responsibilities.