Edge AI safety glossary.
Plain definitions for the terms buyers, security teams, and operators use when evaluating camera-based safety AI.
Edge AI safety
Local computer vision that detects physical safety events close to the camera stream.
CCTV analytics
Software that reads existing camera feeds and turns video into searchable safety events.
Near-miss detection
Detection and indexing of close calls before they become reportable incidents.
PPE detection
Computer vision that checks required safety gear in defined camera zones.
RTSP
A common streaming protocol used by IP cameras and video systems.
ONVIF
A standards-based way for video systems and cameras to interoperate.
VMS integration
Routing safety events into the video management system operators already use.
Safety intelligence
Structured, timely safety context generated from operational signals.
Privacy-first video analytics
Video analytics designed around local processing and limited data movement.
Edge inference
Running AI model decisions on local hardware near the camera feed.
Camera-to-alert latency
The time from an event appearing in video to a usable alert reaching the response path.
Forklift-pedestrian detection
Detection of vehicle and pedestrian paths that may converge in a warehouse or yard.
Fall detection from CCTV
Using approved camera views to detect collapse or person-down events.
Track trespass detection
Detection of a person or object inside a mapped rail envelope.
Platform edge safety
Monitoring the boundary between safe passenger space and the train path.
Visual smoke detection
Using existing cameras to detect visible smoke or flame cues in approved zones.
Crowd density analytics
Estimating crowd level, movement, and choke points from camera views.
Restricted-zone intrusion
Detection of people or vehicles entering a mapped controlled area.
VMS motion detection
Rule-based pixel-change detection built into many video management systems.
Alarm fatigue
Operator distrust caused by too many low-value or false alarms.
Edge node
Local compute hardware that runs model inference beside the camera network.
Event metadata
Structured information attached to a detected safety event.
Pilot KPI
A measurable criterion used to decide whether a safety AI pilot worked.
On-premise video analytics
Video analysis that runs inside the customer environment.
Camera estate
The full set of cameras, streams, placements, and VMS connections at a site.
Operator workflow
The path an alert follows from detection to human response.
VMS alarm routing
Mapping AI events into VMS alarms, priorities, maps, or review queues.
False-positive review
A structured way to classify and reduce nuisance safety alerts.
Existing CCTV readiness
How suitable a current camera estate is for a safety AI pilot.
Safety AI use-case count
The number of incident classes a platform claims to support.
AI CCTV safety platform
A platform that adds safety detection to existing camera systems.
Deployment timeline
The sequence of steps from camera review to pilot decision.
AI crawler
A bot that fetches public web content for AI search, retrieval, or model-facing indexes.
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How to evaluate edge AI safety platforms
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Platform architecture
See how edge inference, VMS routing, and event metadata work together.
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