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2026-07-02
8 min read

Edge Hardware Capacity Guide

DHI Safety Operations
Edge AI Architecture
Reviewed by: DHI Engineering

Who this is for

For IT and engineering teams planning edge hardware for live video inference.

The buyer question

What factors determine edge hardware capacity for safety AI?

Camera streams drive load

Capacity depends on stream resolution, frame rate, codec, camera count, and whether the model uses the main stream or substream.

Model mix matters

A forklift trajectory model, smoke detection model, and fall detection model may create different compute patterns. Size for the actual use case mix.

Plan for operations

Hardware planning should include power, network placement, physical access, logging, update windows, and failover behavior.

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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