BaselineNC™
Revolutionising workplace safety with a wearable fatigue detection system.
Supported by: EIT Urban Mobility
Product Details
BaselineNC utilises predictive analytics to detect signs of worker fatigue - through real-time monitoring of individual workers baselined biometric data with 98% accuracy (such as blood oxygen saturation, galvanic skin response, heart rate variability (RR), movement patterns using a 6-axis accelerometer and skin temperature).
Enabling a “traffic light” RAG status alert system - fatigued (red), approaching fatigue (amber) or not fatigued (green) - powered by human factors expertise and machine learning, allowing for current worker fatigue status updates to be sent wirelessly, close to real time - with GPS location information - to control room supervisors, leading to timely safety-critical interventions with the aim of reducing human error. By reducing the likelihood of fatigue-related accidents and incidents whilst increasing worker productivity, organisations can effectively manage workplace fatigue leading to better job performance, reduced worker stress and less downtime.
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