Drowsiness Detection System

Abstract

This project focuses on developing a drowsiness detection system using machine learning that can detect signs of driver fatigue by analysing facial features, specifically the eyes' blinking pattern. The system aims to improve road safety and prevent accidents by alerting drivers when they show signs of drowsiness, allowing them to take appropriate measures. The project uses an iterative development model that includes the phases of the software development life cycle, such as planning, analysis and design, implementation, testing, deployment, and evaluation. The project's final deliverables include a detection system using machine learning, data collection, a Google Collab file/Jupyter, web applications, a processed dataset, report generation, a real-time notification system, and a manual guide. The beneficiaries of this project are drivers and the public, and the goal is to make roads safer, especially for people who drive long distances or at odd hours of the day or who are sleep deprived.