DHI uses edge compute such as NVIDIA Jetson-class hardware to run safety inference close to the camera, protect response time, and keep raw video inside the local environment.
Integration proof
The integration page should answer what connects, what data moves, what the operator sees, and what has to be validated before pilot launch.
Integration target
DHI uses edge compute such as NVIDIA Jetson-class hardware to run safety inference close to the camera, protect response time, and keep raw video inside the local environment.
Camera workflow
Jetson-class edge hardware gives DHI the local inference layer needed for forklift conflict, track trespass, fall detection, smoke detection, and crowd monitoring without continuously streaming footage to a remote service.
Event routing
The edge node reads approved camera streams inside the site environment.
Deployment check
Start with the camera count and incident class that matter most before planning a full estate rollout.
Security posture
Raw video stays on the site network while DHI routes safety metadata into the existing operator workflow.
Fit
Jetson-class edge hardware gives DHI the local inference layer needed for forklift conflict, track trespass, fall detection, smoke detection, and crowd monitoring without continuously streaming footage to a remote service.
The node plan depends on how many streams run at once and which detection models are active.
Industrial sites should confirm power, mounting, heat, dust, and maintenance access before install.
Compute should sit on a network path that can read camera streams and send events to the VMS with low latency.
Event flow
These pages should make the data path simple enough for IT, security operations, and safety leadership to review together.
The edge node reads approved camera streams inside the site environment.
DHI models classify safety events on local hardware without waiting on cloud inference.
Only the structured event, timestamp, confidence, and camera reference move into the alert workflow.
Pilot checklist
A strong integration page should help the buyer self-qualify before the first technical call.
Start with the camera count and incident class that matter most before planning a full estate rollout.
Power, mounting, heat, network distance, and maintenance access affect where edge compute belongs.
A useful pilot records frame rate, alert latency, event volume, and operator response.
Review DHI edge compute, camera ingest, and VMS event routing.
Why safety decisions tied to movement need local inference.
What to check before choosing a safety AI platform.
Bring your camera list, VMS version, alarm workflow, and pilot zones. We will map where DHI fits and what has to be tested first.
No raw video has to leave your site for an integration review.
See the flow on a real operating scenario and scope a pilot around one facility or corridor.
Review camera ingest, edge inference, alert routing, and what stays on-premises.
Download the deployment checklist buyers use before green-lighting an industrial AI pilot.
Bring camera count, VMS constraints, latency expectations, and privacy requirements to a technical review.