This study examines the prevalence of mobile phone use among motorcycle riders at signalized intersections in Marrakech, utilizing advanced computer vision techniques. Employing the YOLOv8 object detection model and the DeepSORT tracking algorithm, our approach effectively detects and tracks mobile phone usage in real-time traffic scenarios. By analyzing data from strategically placed cameras at high-traffic intersections, the research identifies patterns in mobile phone usage among motorcyclists and evaluates the impact on traffic safety. The findings highlight significant times of day for phone usage and offer insights into behavioral trends, providing a foundation for developing targeted interventions to enhance road safety.