The execution of monotonous tasks that require high levels of attention is increasingly common due to automation and technological development. When such tasks have critical roles in guaranteeing the safety of work environments – such as in industrial control rooms and airport traffic control towers –, it is essential that operators retain adequate levels of alertness, so that demands for action are fulfilled. This paper presents a model for the detection of drowsiness based on processing video streams of a person’s face. Different from intrusive methods based on biological approach Drowsiness detection relies on automatic face detection and evaluation of the Eye Aspect Ratio, which allows monitoring user’s alertness state by classification with Support Vector Machine