Researchers at Australia’s Edith Cowan University (ECU) have invented a computer-based tracking system that employs a basic camera to identify drivers who are too impaired by alcohol to drive safely.

This technology relies on a machine learning system that examines different facial features, along with head position and the driver's gaze direction, to assess their level of intoxication.

The researchers utilized MiX by Powerfleet, a fleet management application that typically tracks driver behavior, to train their tool. This is the very first solution to use a conventional RGB camera to detect levels of alcohol intoxication based on signs of impairment on drivers’ faces.

4. The research experiment began by categorizing participants into three groups based on their level of alcohol intoxication: sober, slightly intoxicated, and severely intoxicated. They were then observed driving on a simulator, and the recorded images were subsequently inputted into the machine learning system developed by the researchers.