Système de détection de la somnolence basé sur l'apprentissage profond (Deep Learning

Abstract

As part of our project, we developed an intelligent system aimed at detecting driver drowsiness in real time, in order to reduce road accidents caused by loss of concentration while driving. This system relies on artificial intelligence and image processing techniques to analyze the driver’s facial features, particularly eye movements, using a camera. The system was designed using the Python programming language, relying on several libraries such as OpenCV and TensorFlow, along with modern development tools and technologies. It triggers instant (audio) alerts when the driver’s eyes remain closed for a certain period, helping to restore attention and prevent potential risks. The main objective of this project is to provide a practical and effective solution that can be integrated into modern vehicles or used as a standalone application. This solution aims to improve road safety and reduce the number of accidents, especially during long trips and nighttime driving. We believe that this system represents an important step forward in the development of intelligent driving systems and the enhancement of road safety