Fatigue Detection Using Raspberry Pi 3

Author:

Chellappa Akalya,Sushmanth Reddy Mandi,Ezhilarasie R,Kanimozhi Suguna S,Umamakeswari A

Abstract

Driver drowsiness is a primary cause of several highway calamities leads to severe physical injuries, loss of money, and loss of human life. The implementation of driver drowsiness detection in real-time will aid in avoiding major accidents. The system is designed for four-wheelers wherein the driver’s fatigue or drowsiness is detected and alerts the person. The proposed method will use 5-megapixel Raspbian camera that captures driver’s face and eyes and processes the images to detect driver’s fatigue. On the detection of drowsiness, the programmed system cautions the driver through an alarm to ensure vigilance. The proposed method constitutes of various stages to determine wakefulness of the driver. According to this output, the warning message is generated. Haar Cascade Classifiers is used to detect the blink duration of the driver and Eye Aspect Ratio (EAR) is calculated. Finally, the alert message along with car plate number is sent to the concerned person mobile with help of Ubidots cloud service and Twilio API. For this Raspberry Pi 3 with Raspbian (Linux Based) Operating System is used.  

Publisher

Science Publishing Corporation

Subject

Hardware and Architecture,General Engineering,General Chemical Engineering,Environmental Engineering,Computer Science (miscellaneous),Biotechnology

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2. Advanced Safety System with Computer Vision-Based Eye Movement and Heart Rate Monitoring;2024 International Conference on Smart Systems for Electrical, Electronics, Communication and Computer Engineering (ICSSEECC);2024-06-28

3. Based On Multitask Cascaded Convolutional Networks MTCNN, Implementation of Behavioral Drowsiness Detection System;2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI);2023-10-19

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