IoT-based Driver's Doziness Detection

Manish Mokal; Aaman Sayyad; Anushka Patil; Rutuksha Kedari; Charusheela Pandit

Abstract

A couple of lakh injuries have happened because of numerous factors, including terrible usage, avoiding protection, motive force fatigue, and so forth. According to statistics, driver indolence constitutes 40% of injuries. Internet of things (IoT) can assist in decreasing the number of accidents. To resolve this problem, a machine for motive force doziness detection is presented in this article. This device uses a system learning algorithm to usually monitor the driver's eye movements and activates a buzzer if any signs and symptoms of doziness are visible on the driver's face. Here, a small safety digicam with a snap function is applied to examine the driving force's face and check the eyes for symptoms of drowsiness. The sensor for alcohol will hit upon the inebriated driver and sound an alarm to prevent him from operating a car. This development can reduce accidents and improve protection.

Abstract

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