Configured Camera Zones
Draw a polygon over the relevant part of a stable camera view and validate object scale and occlusion.
BAV ONE Computer Vision Operating System · Turn existing cameras into programmable AI sensors
Explore the platformBAV ONE Computer Vision Operating System · Turn existing cameras into programmable AI sensors
Explore the platformDefine a camera polygon and operating rule so presence becomes relevant only under approved conditions.
How it works
Each stage remains observable and can be validated independently.
Draw a polygon over the relevant part of a stable camera view and validate object scale and occlusion.
Specify which object matters, when the zone is restricted and how long presence must continue before an event.
Use assessed restricted-zone rules for schools, factories, warehouses and critical infrastructure without assuming the same policy applies everywhere.
Capability, compatibility and performance depend on the camera scene, approved models, infrastructure and acceptance criteria. Human review remains appropriate for critical decisions.
Related guidance
Frequently asked questions
Usually not without review. Each view has different geometry, lighting, operating schedules and response ownership.
Yes. BAV ONE supports assessed edge, on-premises, cloud and hybrid architectures. The selected design depends on camera access, compute, bandwidth, data-control and operational requirements.
No. Compatibility depends on stream access, protocol, resolution, frame rate, camera angle, lighting, network conditions and the selected use case. Bharat AI Vision validates these factors before rollout.
Begin with a camera and workflow assessment, then validate a focused one-to-four-camera pilot against agreed operating conditions and acceptance criteria.
Validate before rollout
Map the operating requirement, assess compatible streams and validate a focused workflow before expanding.