BAV ONE Computer Vision Operating System · Turn existing cameras into programmable AI sensors
Explore the platformExplore focused BAV ONE workflows for detection, tracking, zones, boundaries, counting, dwell and alerts. Each solution is validated against the camera scene and operating policy.
BAV ONE solution
Person detection provides a person class and bounding box for configured video scenes; it is not facial recognition and does not establish identity.
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Convert tracked movement across calibrated lines or zones into entry, exit and occupancy analytics without promising unvalidated counting accuracy.
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Define what constitutes an intrusion for a specific camera, zone, schedule and accountable response workflow.
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Apply explicit virtual boundaries and site rules to compatible outdoor camera views while retaining human-led response for critical events.
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Use tracked movement across a calibrated virtual line to create directional operational events.
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Support operational awareness of occupancy and density without claiming unvalidated crowd-behavior prediction.
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Detection alone does not need to create an alert. BAV ONE evaluates operational context and a configured Vision Policy first.
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Associate detections over consecutive frames within one camera to understand movement without claiming cross-camera identity tracking.
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Define a camera polygon and operating rule so presence becomes relevant only under approved conditions.
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Dwell is a time-and-zone measurement. Business policy—not the model—determines whether that duration matters.
Explore solutionFrom visual data to enterprise intelligence
Start with the operating condition, camera view and response workflow—then validate models and infrastructure.