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  2. Fatigue detection software - Wikipedia

    en.wikipedia.org/wiki/Fatigue_detection_software

    Various real-time operator drowsiness detection systems use PERCLOS assessment and proprietary developed software to determine the onset of fatigue. Each technology developer use a unique set-up and combination of hardware to improve the accuracy and ability to track eye movement, eyelid behaviour, head and face poses under all possible ...

  3. Driver drowsiness detection - Wikipedia

    en.wikipedia.org/wiki/Driver_drowsiness_detection

    Volvo Cars: Driver Alert Control [23] In 2007, Volvo Cars launched the world's first Driver Drowsiness Detection system, Driver Alert Control. The system monitors the car's movements and assesses whether the vehicle is being driven in a controlled or uncontrolled way. If the system detects a high risk of the driver being drowsy, the driver is ...

  4. Smart Eye - Wikipedia

    en.wikipedia.org/wiki/Smart_Eye

    AIS uses Smart Eye's automotive grade DMS software that analyzes subtle changes in a driver's head movements, eye gaze, and facial expressions to detect early signs of drowsiness and distraction in real time. AIS promptly alerts drivers at the earliest possible point, to prevent road accidents and promote safe driving behavior.

  5. Optalert - Wikipedia

    en.wikipedia.org/wiki/Optalert

    Optalert's fatigue monitoring system uses infra-red light to measures a driver’s levels of alertness continuously and objectively in real time. It is the first validated system that provides early warning signs of drowsiness. [2] It includes a pair of glasses connected to a small computer processor in the vehicle.

  6. Drowsy driving statistics and facts 2024 - AOL

    www.aol.com/finance/drowsy-driving-statistics...

    Statistics show an estimated 17.6 percent of fatal car crashes between 2017 and 2021 involved a drowsy driver (AAA Foundation). The majority of drowsy-driving crashes happen between midnight and 6 ...

  7. Affectiva - Wikipedia

    en.wikipedia.org/wiki/Affectiva

    The AI uses an optical sensor like a webcam or smartphone camera to identify a human face in real-time. [17] Then, computer vision algorithms identify key features on the face, which are analyzed by deep learning algorithms to classify facial expressions. These facial expressions are then mapped back to emotions.

  8. Advanced driver-assistance system - Wikipedia

    en.wikipedia.org/wiki/Advanced_driver-assistance...

    Driver drowsiness detection aims to prevent collisions due to driver fatigue. [16] The vehicle obtains information, such as facial patterns, steering movement, driving habits, turn signal use, and driving velocity, to determine if the driver's activities correspond with drowsy driving. [ 17 ]

  9. Vehicle safety technology - Wikipedia

    en.wikipedia.org/wiki/Vehicle_safety_technology

    These systems were created in order to prevent lane swerving and possible driver drowsiness accidents. To alert the driver of a lane departure, systems can do employ one or more of a seat vibration, the illumination of a warning signal, and warning sounds (either a small sound or a verbal warning from system technologies. These systems do not ...