When preventing an industrial fatality or a train strike, a two-second network delay is a physical liability. Here is why serious safety requires edge-native compute.
Architecture Validation
This comparison frames the technical debt and physical risk of cloud streaming in high-stakes environments.
Deployment tradeoff
This comparison exists to answer the physical consequence of where inference happens, not just the marketing difference between two product categories.
Latency question
The page explains why cloud delay changes the outcome when a train approaches or a forklift enters a blind corner.
Privacy question
The privacy row answers a real blocker from enterprise IT and union review, not a hypothetical SEO talking point.
Failure-mode question
The reliability row covers what happens when the connection drops and whether local alarms still fire.
ROI question
This page frames bandwidth, false urgency, and operator response time as business costs, not only technical specs.
Cloud forces video to travel off-premises causing critical round-trip delays. Edge inferences raw pixels the moment they hit the local node.
Streaming 30 HD cameras to the cloud cripples enterprise networks. Edge processing means only text logs and tiny alert-clips leave the facility.
"We can't send camera feeds to the cloud — IT blocked it." We hear this in every enterprise deal. With edge compute, raw video never leaves your VLAN. GDPR and union negotiations become trivial.
If the fiber connection is cut, cloud AI stops alarming. Dhi's edge nodes continue triggering local VMS sirens independently.
Bring your current camera throughput and network path. We will pressure-test whether cloud streaming or local inference fits the actual safety response your facility requires.
Most enterprise pilots start with a latency audit and a 5-camera Edge Node trial.
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.