Manufacturing and industrial sites present complex visual monitoring requirements. AI video analytics can support two distinct categories: operational safety and monitoring, and visual quality inspection.
Operational safety and monitoring
BAV ONE can be configured for PPE detection, restricted-area monitoring, worker presence in hazardous zones, person and vehicle interactions, perimeter monitoring, occupancy and after-hours access. Each workflow requires validated camera conditions and a configured Vision Policy.
Visual quality inspection
Visual quality inspection uses computer vision to detect defects, verify presence or absence, count items, check orientation and verify process states. This requires use-case-specific training, validated datasets, appropriate camera positioning and lighting, and production acceptance criteria. The general surveillance model does not automatically perform manufacturing quality control.
Camera conditions in industrial environments
Industrial environments present challenges including dust, variable lighting, steam, vibration and occlusion. Camera placement, housing and maintenance affect detection reliability. A site assessment validates these conditions before deployment.
Edge AI for manufacturing
BAV Edge can run approved inference on-site, reducing dependence on video backhaul and supporting data-control requirements. This is particularly relevant for facilities with limited connectivity or strict data policies.
Starting a manufacturing pilot
Begin with a focused one-to-four camera pilot on a specific workflow, such as restricted-zone monitoring or PPE detection. Validate the camera conditions, Vision Policy and acceptance criteria before expanding.