A driver monitoring system that generates nuisance alerts gets disabled, and a disabled system detects nothing. That single fact drives the engineering: precision matters more than sensitivity, the infrared imaging has to work through sunglasses and at night, and the system has to know the difference between a fatigued driver and one performing a deliberate mirror check.
Detecting a closed eye in a well-lit frontal image is not difficult. Detecting it through polarised sunglasses, at night, with sunlight strobing through roadside trees, on a driver wearing a mask, at a seat position the calibration did not anticipate, while the cab vibrates — that is the engineering.
Near-infrared illumination is what makes it tractable. It penetrates many sunglass lenses, works in darkness without dazzling the driver, and is largely unaffected by the visible-light conditions outside. The remaining work is in the geometry: mounting position, field of view, and handling the range of body sizes and seating positions a real fleet contains.
Mounting positions, field of view, occlusion, vibration and power availability assessed across the actual vehicle mix, which is rarely uniform.
Real driving across day, night, weather and driver population, including the fatigue events the system exists to catch.
Per-vehicle geometry handled automatically, so installation does not depend on a technician's precision.
Escalation thresholds, in-cab feedback and what reaches the fleet office — agreed with drivers, not imposed on them.
A limited fleet run long enough to measure nuisance alert rate, which is the number that decides adoption.
Provisioning, over-the-air update, and ongoing monitoring of both detection and disablement rates.
Near-infrared illumination and imaging. NIR penetrates many sunglass lenses, works in complete darkness without dazzling the driver, and is largely independent of the visible-light conditions outside the vehicle.
Fatigue detection looks at eye closure duration, blink dynamics and head stability, which develop over time. Distraction detection looks at gaze direction and behaviour in the moment. They need different thresholds and different alert policies.
By fusing vehicle context with driver observation, so a head turn during an indicated lane change is read differently from the same head turn on a straight road, and by tuning for precision rather than maximum sensitivity. Nuisance alert rate is the metric that decides whether a system stays switched on.
That is a policy decision, and usually a regulated one. Systems can be configured to process on the device and retain nothing, to retain only event clips, or to retain more where the operator requires it and the legal basis exists.
Tell us the specification, the constraint and the deadline. Programmes that cross silicon, radio, embedded and AI are where Faststream is strongest.