Workplace Safety AI Monitoring

We detect hard hats, safety vests, gloves, safety glasses, and harnesses in real time across multiple camera feeds. Each worker gets a compliance status, and violations trigger immediate alerts to shift supervisors.

We define virtual geofences around hazardous areas, equipment exclusion zones, and authorized-only sections. When someone enters a restricted zone, the system logs the event and sends an alert within seconds.

Our models identify fall events by analyzing body posture transitions in real time. When a fall is detected, the system sends instant alerts to safety officers and logs the exact timestamp and camera location for incident response.

We create pedestrian-vehicle collision prevention zones using camera-based tracking. The system monitors distance between workers and moving vehicles, triggering warnings when proximity thresholds are breached.

Our visual detection models identify smoke and flame patterns earlier than traditional heat or particle sensors. We train on facility-specific backgrounds to reduce false positives from steam, dust, or welding operations.

We build shift-level safety compliance scoring dashboards that aggregate PPE adherence, zone violations, and incident counts. Trend analysis surfaces patterns across shifts, areas, and time periods for proactive safety management.

Multi-stream video analytics pipeline for concurrent camera processing.

High-performance edge GPU for running multiple safety models simultaneously.

Standard industrial camera protocols for flexible deployment.

Lightweight messaging for real-time alert distribution to multiple subscribers.

Real-time compliance visualization and historical trend analysis.

Model optimization for maximum inference speed on NVIDIA hardware.

Fine-tuned detection models for PPE, posture, and zone compliance.

Configurable alert routing to SMS, email, PA systems, and dashboards.

Incident clip extraction and archival for investigation and compliance.