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Guide
2026-07-02
9 min read

On-Premise Video Analytics for Privacy-Sensitive Facilities

DHI Safety Operations
Edge AI Architecture
Reviewed by: DHI Engineering

Who this is for

For privacy, legal, IT, and security reviewers at facilities where video movement needs strict control.

The buyer question

How can a facility evaluate video analytics without losing control of raw footage?

Define approved camera zones

The review should start with the camera zones allowed for safety analytics, the event types allowed in each zone, and the teams allowed to receive events.

Separate metadata from footage

Structured event metadata is not the same as continuous video export. The architecture should explain what moves, when it moves, and who approves clips.

Document retention and access

A pilot should define retention, access, audit trails, and clip approval before live alerting begins.

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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Validate "on-premise video analytics for privacy-sensitive facilities" on your live feeds.

Coordinate a 30-day architecture review and live camera validation based on the protocol described in "on-premise video analytics for privacy-sensitive facilities" for your facility.

Get the implementation checklist

Best follow-up: bring the current workflow that "On-Premise Video Analytics for Privacy-Sensitive Facilities" is supposed to improve.