Open AccessDriver Drowsiness Detection System using Machine Learning
Author(s) -
M Charan
Publication year - 2021
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2021.33888
Subject(s) - computer science , artificial intelligence , face detection , android (operating system) , facial recognition system , bounding overwatch , process (computing) , computer vision , task (project management) , smart phone , phone , face (sociological concept) , real time computing , pattern recognition (psychology) , engineering , operating system , telecommunications , social science , linguistics , philosophy , systems engineering , sociology
We propose a Driver drowsiness detection system, the purposes of which are to prevent from dangerous cause and to avoid accidents. Since all the processes on image recognition performed on a smart phone, the system does not need to send images to a server and runs on an android smart phone in a real-time way. Automatic image-based recognition is a particularly challenging task. Traditional image analysis approaches have achieved low classification accuracy in the past, whereas deep learning approaches without human supervision real-time drowsiness detection. This model classifies whether the person’s eyes are opened or closed. To recognize the face, a user should have to adjust camera such a way that it covers his face first, and then the system starts recognition within the indicated bounding boxes. In addition, the system estimates the actions of the person. This recognition process is performed repeatedly about every second. We will implement this system as Web application effectively for real-time recognition.