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Whitepaper
2026-07-02
7 min read

Latency Benchmark Template for Edge AI Safety

DHI Safety Operations
Edge AI Architecture
Reviewed by: DHI Engineering

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.

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.

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Coordinate a 30-day architecture review and live camera validation based on the protocol described in "latency benchmark template for edge ai safety" for your facility.

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Best follow-up: bring the current workflow that "Latency Benchmark Template for Edge AI Safety" is supposed to improve.