Survey on Traffic Violation Prediction using Deep Learning Based on Helmets with Number Plate Recognition

Nowadays, the most widely used mode of transportation is two-wheelers. Both bike riders and pillions are strongly encouraged to wear helmet. A significant application and developing field of study in machine learning and image processing, object tracking in video surveillance is of considerable interest to many academics. Object detection is the process of identifying the existence of items in a scene using a bounding box and the types or categories of the objects that have been placed. This study reviews tracking methods, classifies them into several sorts, and emphasizes the most significant and practical methods. Finally, this study analyzes potential study directions after reviewing general tactics as a part of the literature review on various approaches. This study uses an image processing system to identify motorcycle riders without helmets. Additionally, utilize the OCR method to extract user information from images of license plates and classify them using OCR. then figure out the fine amount. Making SMS services inform customers in order to avoid motor-bike accidents is the final step. The performance of the proposed framework is assessed in terms of precision and speed.