Driver Drowsiness Detection System Using Machine Learning

EasyChair Preprint 8010

Abstract

This feature is used for the safety of the peoples from the accidents. This work shows the development of ADAS ( advance driving assistance system) this focus on the driver drowsiness detection is main aim to alert the driver from the drowsiness state to avoid road accidents. In this we use the Machine Learning to predict the condition and emotions of the driver that will improve the safety on the roads. We use the CNN for this project that will effectively detect the driver fatigue status using driver images. In this project we can use the Electrocardiogram (ECG) for the psychological system to detect drowsiness. Artificial Intelligence means system can automatically learns as well as improve without being programmed. We also use the various machine learning techniques like OpenCv, Keras, tensorflow.

Keyphrases: Artificial Intelligence, CNN, machine learning

@booklet{EasyChair:8010,
  author    = {Dushyant Parashar and Abhishek Jadaun},
  title     = {Driver Drowsiness Detection System             Using Machine Learning},
  howpublished = {EasyChair Preprint 8010},
  year      = {EasyChair, 2022}}