Intelligent Vehicle Driver Face and Conscious Recognition

Abstract

The car manufacturing industry faces pressing issues of vehicle theft and driver conscious related accidents. This study introduces AI-powered computer applications to tackle these challenges, aiming to enhance security and safety in the automotive sector. The study developing two distinct models—one for driver identification via facial recognition prior to ignition, and another for continuous driver state monitoring during travel—this research aims to bolster vehicle security and enhance driver safety. Two carefully curated data sets consisting of images of four individuals were used to train and validate the models, one for facial recognition and the other for conscious and unconscious driver detection. The models achieved accuracy rates exceeding 99%, and cross-validation confirmed their reliability, with consistent performance showing accuracy ranging from 95% to 100%. The study underscores the potential of AI to revolutionize vehicle security and driver safety mechanisms. The implementation of these models promises to significantly curtail the incidence of car theft and the risk of accidents cause by driver un conscious, heralding a new era of ethical and advanced automotive technologies.