SURVEY ON AI-Based Driver Drowsiness Detection And Alert System

K.B.Keerthana Jessleena; A.Chandupriya; D Jhansi; B. Amaranthareddy; J.Pavan; M.Thanigavel

SURVEY ON AI-Based Driver Drowsiness Detection And Alert System

Authors: K.B.Keerthana Jessleena, A.Chandupriya, D Jhansi, B. Amaranthareddy, J.Pavan, M.Thanigavel

Unique Paper ID: 177965
Volume: 11
Issue: 12
PageNo: 1754-1759

Keywords: Driver fatigue fatigue detection eye blink drowsiness Raspberry pi open cv Face detection Driver monitoring system Alarm.

Abstract:
In recent years driver fatigue is one of the major causes of road accidents in the world. A through way of measuring driver fatigue is measuring the state of the driver drowsiness. So it is very important to detect the fatigue of the driver to save life and property. This prototype is a real time system which captures image continuously and measures the state of the eye according to the specified algorithm and gives warning. This system works by means of monitoring the driver's eyes and sounding an alarm if he or she will become drowsy. The system designed in this way is a non-intrusive real-time monitoring system. The priority is to enhance motive force safety without being intrusive. When the driver's eyes are closed for an extended period of time, an alert sound is generated to notify him in order to certify that the driver is taking certain steps to avoid falling asleep. The output of the system proposed in the paper on Deep learning technology of Dlib which uses CNN (Convolutional Neural Network) as its base algorithm for accurate detection, OpenCV, and Raspberry Pi environments with a mounted camera for the same, show that system achieves good result when it comes to drowsiness detection, reducing the overall number of accidents on the streets. It fully complies with the system's needs and objectives. The structure has reached an unwavering state in which every bug has been eliminated.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 12
PageNo: 1754-1759

SURVEY ON AI-Based Driver Drowsiness Detection And Alert System

Available:https://ijirt.org/Article?manuscript=177965

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Journal no 47859

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