The system continuously monitors heart rate, heart rate variability (HRV), core body temperature, movement patterns, and activity levels. Additional metrics can include respiratory rate, skin temperature, and environmental data depending on the wearable device deployed. All data is analyzed in real-time to detect patterns indicating fatigue, heat stress, cardiac anomalies, or physical strain.

Human Condition Monitoring by Aatmunn integrates with multiple wearable form factors including wristbands, smart watches, in-ear monitors, chest straps, and sensor-equipped helmets. We support devices from leading manufacturers including Bodytrak, SlateSafety, Blackline, and others. The platform is device-agnostic, allowing you to choose wearables that best fit your operational environment and comfort requirements.

Initial deployment typically takes 2-4 weeks depending on site size and complexity. This includes wearable device provisioning, SPANR platform configuration, supervisor training, and baseline data collection. Workers can be equipped and actively monitored within the first week. Our implementation team works alongside your safety managers to ensure smooth rollout with minimal disruption to daily work.

All biometric data is encrypted end-to-end and stored in SOC 2 compliant infrastructure. Individual health data is only accessible to authorized personnel based on role-based permissions you configure. Workers can view their own health metrics through a personal dashboard. The system focuses on safety alerts rather than performance monitoring, and data usage complies with GDPR and applicable privacy regulations.

When worker biometrics exceed safe thresholds, the system triggers multi-level alerts. The worker receives immediate notification on their device (visual, audio, or haptic depending on device type). Supervisors receive real-time alerts with worker location, condition severity, and recommended actions. For critical alerts, safety teams and medical personnel can be notified simultaneously. All alerts are logged for compliance documentation and incident investigation.

Yes. SPANR provides open APIs and pre-built integrations for leading EHS platforms, incident management systems, CMMS tools, and access control systems. Biometric data and alerts can flow automatically into your existing workflows. We also support custom integrations for proprietary systems. Integration typically doesn't require replacing any current safety tools.

Our fatigue detection algorithms analyze multiple physiological indicators simultaneously, including heart rate variability patterns, activity levels, and historical baseline data. The system uses machine learning models trained on extensive industrial worker datasets. Detection accuracy exceeds 85% for identifying elevated fatigue risk before performance impairment occurs. Accuracy improves over time as the system learns individual worker baselines and patterns.