A Review on Driver Drowsiness Detection Systems Using Image Processing and AI Techniques

Abstract: Because of its close connection to road safety, driver fatigue detection has become a major area of study in intelligent transportation systems. Drivers who are tired or distracted cause hundreds of accidents each year. This review research looks closely at the methods, difficulties, and most recent developments in the field of real-time sleepiness detection. Recent developments like as Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are contrasted with more conventional physiological, behavioural, and vehicle-based approaches. The study evaluates sensor modalities, comparative studies, performance measures, and real-world applications, highlighting both current inadequacies and accomplishments. In order to increase resilience, the study also looks into hybrid.