Hospital PPE
EPI1 · Gown/coverall, mask, gloves, goggles and face shield in patient care areas
About this solution
Computer vision model trained by Neural to identify, on each worker, the presence or absence of Personal Protective Equipment — coveralls, gloves, safety glasses, masks and face shields — using the cameras already installed. Each non-compliance triggers an alert with photographic evidence and feeds safety metrics by area, shift and team.
- 1The cameras (RTSP/IP) send images to the on-premises or cloud inference server.
- 2The YOLO model detects people and each PPE item (or its absence) in milliseconds.
- 3A tracker associates detections with each worker to avoid duplicate alerts.
- 4Per-area rules define which PPE is mandatory (e.g. hard hat and vest on the construction site).
- 5Alerts with photos are sent to the safety officer (dashboard, email, WhatsApp, webhook).
Benefits
- Continuous 24/7 monitoring, without relying on in-person rounds.
- Photographic evidence of every occurrence for training and audits (occupational safety regulations, ISO 45001).
- Compliance metrics by area, shift and team for targeted preventive action.
- Fewer accidents, lost-time injuries and labor liabilities.
- Leverages the existing camera (CCTV) infrastructure.
More demos
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