AI video analytics use case
AI safety compliance and PPE detection
Short answer
Safety compliance detection is video analytics that checks whether people follow site safety rules, most commonly whether required PPE such as hard hats and high-visibility vests is worn in designated zones. It flags violations in real time so supervisors can intervene, and keeps an event record for safety reviews, audits and training.
How safety compliance detection works
A person-detection model finds each worker, then a second model, or a model trained on both, checks for the presence of required equipment on that person, such as a helmet on the head or a vest on the torso. Rules define which items are required in which zone and during which shifts.
Other safety rules use the same building blocks, such as a person inside a hazardous zone that should be empty while machinery is running.
In OrionAlerts
In OrionAlerts, the AI runtime reads decoded frames from the same video engine that records the cameras, so detection runs on the streams you already record rather than on a parallel feed into a separate analytics appliance. Inference runs on the on-site Nebula OS node with GPU acceleration, and each event is written to the same record as the camera and site it came from. Alerts reach the dashboard, mobile app and email.
What affects reliability
Detection quality depends on the scene as much as the model. These are the factors to check during site survey and pilot.
- Person size in frame: PPE items are small, so workers need to appear large and clearly enough in the image.
- Camera angle: views from far above can hide helmets and vests; angled views from the side or front usually work better.
- Lighting: dim areas and strong backlight make colors and shapes of PPE harder to recognize.
- Site variation: PPE colors and styles differ by site, so detections are typically validated in a pilot before rollout.
What you need
No camera replacement is assumed. A typical OrionAlerts deployment needs:
- Existing IP cameras that expose video over ONVIF, RTSP or a supported vendor SDK. Compatibility is confirmed per camera model during solution design.
- An on-site Nebula OS node with GPU acceleration, sized per deployment to the channel count and the detections you run.
- Camera views that actually cover the area to be monitored, with zones and schedules defined for each rule.
- Optional: Orion Cloud for a central view of alerts and health across multiple sites, without uploading raw video.
Where it is used
This use case commonly applies in the industries below. Each industry page covers the risks, detections and modules that matter for that kind of site.
Solution
Which solution it belongs to
Safety Compliance Detection is part of AI Vision & Real-Time Alerts: turn live video into real-time AI alerts for safety, intrusion, PPE, and operational events.
Explore AI Vision & Real-Time AlertsFAQ
Safety Compliance Detection: common questions
What safety rules can video analytics check?
Most commonly, whether required PPE such as hard hats and high-visibility vests is worn in designated zones. Video analytics can also check presence rules, such as people entering hazardous or restricted areas during active hours. Which rules apply, and where, is agreed with the site's EHS team during solution design.
Can PPE rules differ between zones?
Yes. Rules are set per zone and schedule, so a production floor can require helmets and vests while a loading bay requires only vests and an office area requires nothing. Shift schedules can change the rules over the day, and each zone keeps its own record of violations for review.
How are safety alerts delivered?
In OrionAlerts, safety alerts reach the teams you configure, such as EHS supervisors, through the dashboard, mobile app and email. Each event is stored against the camera and site it came from, so violations can be reviewed later for safety meetings, audits and training, not only acted on in the moment.
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Plan this use case for your sites
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