DETECTION DROWINESS WHILE DRIVING USING RASPBERRY PI
Keywords:
ADAS, EBCMAbstract
Drowsiness and the Fatigue of drivers are among the significant cause of road accidents. Every year they increases the amount of deaths and fatalities injuries globally. In this paper a module for Advanced Driver Assistance System (ADAS); this system deals with the automation driver drowsiness detection based on visual information and Artificial Intelligence. We propose an algorithm to locate, track, and analyze both the drivers face and eyes to measure of drowsiness associated with slow eye closure. The video will be recorded using the webcam to see the transition from awake to fatigue and finally, drowsy. The designed system deals with detecting the face area of the image captured from the video. The purpose of using the face area so it can narrow down to detect eyes and mouth within the face area. Once+ the face is found the eyes and mouth are found by creating the eye for left and right eye detection and also mouth detection. The parameters of the eyes and mount detection are created within the face image.
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Copyright (c) 2023 Thanniru Pavan Vinayak, Gugulothu Sai Dhanush, Nallagorla Sowmya , Mamidi Sri Vidhya (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
