Autonomous Worker Safety & PPE Compliance Monitoring in Heavy Plants
A primary steel manufacturing mill operating high-risk melt shops, rolling mills, and heavy material handling yards equipped with 250 existing CCTV security cameras.
Run on Arjuna · Plant Operations & Safety
The challenge
Worker safety non-compliance (missing hard hats, high-visibility vests, safety goggles, or thermal suits) caused high workplace injury rates.
Safety officers could not monitor 250 video feeds manually in real time, catching safety violations only after accidents occurred.
Installing specialized AI safety cameras across the 50-acre plant was cost-prohibitive.
How Arjuna solves it
Retrofit RTSP CCTV Stream Ingestion
Arjuna connects to all 250 existing CCTV camera RTSP video streams without requiring hardware replacements.
Real-Time PPE Detection Models
Applies deep learning vision models to detect hard hats, safety vests, eye protection, and heat shielding gear in real time under low-light and dusty mill conditions.
Immediate Safety Violation Alerting
Flags non-compliant personnel instantly, sending visual alert clips to floor supervisor mobile devices and control room monitors.
Automated Audio Horn Interlocking
Triggers localized warning horns or halts automated crane movement if workers enter hazardous hot-metal zones without required gear.
Safety Compliance Analytics Cockpit
Generates shift-by-shift safety compliance heatmaps and compliance trend reports for EHS directors.
The outcome
- PPE compliance rates increased
- 0%PPE compliance rates increased
- reduction in lost-time workplace injury incidents
- 0%reduction in lost-time workplace injury incidents
PPE compliance rates increased from 68% to 99.4% within 30 days of deployment.
72% reduction in lost-time workplace injury incidents.
Zero capital expenditure spent on new cameras by retrofitting 100% of existing CCTV infrastructure.
Representative scenario: a modelled industry situation showing how this accelerator applies. Figures are projections, not a named client result.
Capabilities used
Every accelerator is assembled from the same capability layer, so a workflow you adopt here shares its foundation with the rest of the portfolio.
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