Resource type
Comparisons.
How running detection on site compares with cloud analytics and with wearables, with the trade-offs stated.
Comparison8 min read
Edge AI vs Cloud AI for Forklift Safety
Compare local inference and cloud analytics for forklift-pedestrian conflict, blind-corner alerts, and near-miss capture.
Comparison9 min read
AI Fall Detection CCTV vs Wearable Fall Detection
Compare camera-based person-down detection and wearable fall detection by coverage, adoption, privacy, and response workflow.
Comparison8 min read
DHI vs Cloud Workplace Safety AI
A neutral architecture comparison between DHI's local inference model and cloud-first workplace safety analytics.
Use the guide, then validate it on your cameras.
Don't let the guide be the end of it. Take the checklist, a clear deployment path, and a direct line to ask implementation questions.
The checklist is built for operators evaluating a live pilot in the next 30 days.
- Book a demoSee the flow on a real operating scenario and scope a pilot around one facility or corridor.
- See deployment architectureReview camera ingest, edge inference, alert routing, and what stays on-premises.
- Get the implementation checklistDownload the deployment checklist buyers use before green-lighting an industrial AI pilot.
- Talk to an engineerBring camera count, VMS constraints, latency expectations, and privacy requirements to a technical review.