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Alter is a video-based embedded solution for detecting drivers’ signs of fatigue and tendencies to fall asleep during driving in real-time. It works by capturing and analyzing critical features related to sleep and drowsiness over short but regular time intervals. These include micro-sleeps, eye-blinking, yawing opening, as well as head tilts and orientation. Using deep learning, the system has been trained to extract those features using a reference and well-established data sets of videos produced by subjects at various levels of fatigue tagged according to KSS (Karolinska Sleepiness Scale). 


A mounted camera continuously monitors driver’s face while driving
Sleep indicators of driver fatigue are extracted and analyzed for signs of fatigue
An alarm is set off with frequency and intensity proportional to the sleepiness state
Driver’s data can be captures for later assessment of driving performance



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