What it means
Near-miss detection identifies events where people, vehicles, or hazards came close enough to reveal a repeat safety pattern. In warehouses, that often means forklift conflict, blocked walkways, sudden stops, or unsafe crossings.
Why it matters
Close calls often disappear after the shift. Turning them into clips and records gives safety teams a way to fix repeat zones before an injury happens.
Evaluation questions
- How is a near miss defined for the pilot?
- Can events be grouped by zone, shift, and camera?
- Can supervisors review clips without searching raw footage manually?
Continue exploring.
- GuideWarehouse near-miss detection guidePlan a near-miss detection pilot around existing CCTV.
- SolutionWarehouse safety AISee how near misses fit into a warehouse safety program.
- PlatformPlatform architectureReview how DHI runs inference, event routing, and camera ingest.
- GuideEdge AI safety evaluation guideUse a structured checklist to evaluate platform fit before a pilot.
- PricingPricing and pilot scopeUnderstand what changes the final pilot and rollout scope.
Validate near-miss detection in a real pilot.
Use your current cameras, VMS, and response workflow to test whether the concept works in one defined zone.
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.