Distracted Driver Detection Using AI (International Journal of Scientific Research in Science and Technology, 2025)
Driver distraction has emerged as one of the leading causes of road accidents in recent years, posing a significant threat to public safety. Tackling this critical issue has become a priority for researchers worldwide, leading to the development of various methodologies aimed at detecting and mitigating driver distraction. Among these, deep learning and machine learning techniques have become increasingly prominence due to their ability to analyze complex visual data and accurately classify driver behaviors.Traditional approaches to distracted driver detection typically rely on processing the entire image as input. However, this method can be inefficient and often introduces noise, as only processes the segmented ROI to classify driver behavior as distracted or attentive. This method enhances detection precision, reduces computational overhead, and is suitable for real-time applications. By integrating segmentation and classification, the model provides a robust and efficient solution for safer road environments through advanced deep learning techniques.