International Journal of Science, Engineering and TechnologyAuthors: Associate Professor K.V.S.S Ramakrishna, Gurram Anantha Lakshmi, Nalleboina Sravnathi, Naru Venkata Gayathri, Puli Durga
Abstract: The rise of city populations and vehicle numbers per city have led to serious traffic jams and frequent disobeying of traffic laws. Most of the time, authorities use traditional traffic monitoring systems that require manually checking or using sensors to detect the problem, and these may not work well and can be easily forgotten by humans. This research aims to design an intelligent traffic monitoring system using the latest ML and computer vision techniques to identify different traffic violations and get the vehicle license plate number(s) without any human intervention and in real time. The system not only detects red-light running, speeding, and lane crossing but also identifies the responsible vehicles using object detection algorithms (like YOLO or Faster R-CNN) on the video footages captured by the surveillance cameras. The use of OCR for reading license plates after getting the region of the license plate by image processing using deep learning models is also proposed in this system The proposed solution significantly upgrades faithful, timely, and effortless traffic monitoring, thus providing the road safety officers with the necessary tools to keep the roads safe, reduce accidents, and increase the execution of the law with a minimum of human effort.
