Driver’s Safety Technology Using Machine Learning

Abstract

Nowadays, machine learning is mostly used in personalized recommendation systems. The use of machine learning to model the complex user-item interaction function is a trend in the current recommendation domain. This study outlines research carried out in the realm of computer science and engineering to develop a system for detecting driver drowsiness. The main aim is to prevent majority of traffic accidents caused by driver fatigue and drowsiness, fire and smoke. Our proposed system provides a solution to the limited implementation of the various techniques such as machine learning and Arduino that are presented in our system. Therefore, our system implementation provides a realistic understanding of the system's operation and suggests improvements that could be done to increase the system's overall usefulness. To facilitate additional improvement in the aforementioned area and attain utility at better efficiency for a safer roadway, the report also presents a summary of the observations made by the authors.