aiVISION / NOTES
Short notes about the aiVISION workflow. These are not reports of live product results.
Define the event first, then check footage, stream and response.
Discuss your scenario →Define a forklift and pedestrian proximity event from an existing camera, then route its context to a human reviewer without claiming incident prevention.
Read →WorkflowBuild a human-reviewed manufacturing safety event from existing cameras by defining one zone, one visible condition and one acceptance record.
Read →TestingCheck infrared, shadows, reflections and movement before defining an after-hours event on an existing camera view and operating schedule on site.
Read →WorkflowDefine one office or property entrance event with an existing camera, schedule, reviewer and response record, without claiming identity or intent from video.
Read →ArchitectureUse ONVIF S, T and M as interface evidence, then test the actual camera, firmware, stream and event path before video analytics implementation.
Read →WorkflowWrite a restricted-zone entry rule for an existing camera, test the boundary and stream, and keep human review visible before adding more events.
Read →WorkflowConnect a visible retail queue condition to a team action with existing cameras, a time rule and human review, while keeping sales claims outside the evidence.
Read →InfrastructureCheck camera access, codec, timestamps, network behavior and stream stability before implementing a video analytics workflow on an existing camera.
Read →TestingUse a video analytics acceptance checklist to test camera quality, event context, latency, review ownership and limits before expanding a custom workflow.
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