Latency Benchmark Template for Edge AI Safety

Who this is for

For technical teams measuring latency in live safety AI pilots.

The buyer question

How should camera-to-alert latency be measured honestly?

Measure the whole path

Record the time from visible event to edge inference, event creation, VMS routing, local signal, and operator acknowledgement. Do not report only model time.

Separate lab and field numbers

A lab result is useful for engineering, but buyer-facing proof should come from the pilot environment with real streams and workflows. A model benchmarked on a clean dataset will not tell you what happens when the camera is backlit at 4pm or the VMS queue is backed up during a shift change.

Report conditions

Include camera count, stream resolution, edge node type, VMS path, network conditions, and event type so the number is interpretable.

How to use this with DHI

Use this page as a pre-pilot checklist. Pick one zone, one event type, one alert owner, and one review cadence. If the current cameras cannot support the workflow, fix the camera plan before expanding the deployment.