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Cameras, events and the next step

Short notes about the aiVISION workflow. These are not reports of live product results.

Define the event first, then check footage, stream and response.

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Testing

Video analytics latency on real footage: how to test

Measure the path from a visible camera event to a signal and human review on the actual camera, network and notification workflow before acceptance.

Read →2026-10-02
Testing

Camera image quality for video analytics: practical guide

Assess lighting, focus, angle, movement and contrast before treating an existing camera view as usable evidence for a defined video event on site.

Read →2026-10-02
Testing

Night lighting and video analytics: assessment guide

Check infrared, shadows, reflections and movement before defining an after-hours event on an existing camera view and operating schedule on site.

Read →2026-10-02
Testing

Video analytics acceptance checklist for existing cameras

Use a video analytics acceptance checklist to test camera quality, event context, latency, review ownership and limits before expanding a custom workflow.

Read →2026-10-02
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aiVISION

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aiVISION is aiNOW's custom implementation service for video analytics on existing cameras.

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