DESIGN OF TRAFFIC AMERCEMENT AUTOMATION USING COMPUTER VISION
Chirag Suthar1, Chirantan Banerjee2, Gaurav Mourya3, Ishan Makharia4, .Nagraj M.Lutimath5
1Student, 2Student, 3Student, 4Student, 5Associate Professor
Department of Computer Science and Engineering
Dayananda Sagar Academy of Technology and Management, Bengaluru, Karnataka, India
Abstract: Traffic rule violations, such as speeding, not wearing a proper protective helmet, and running red lights, are a major contributor to the high number of road accidents in India. According to National Crime Records Bureau data, over 1.5 lakh people lose their lives in road accidents across the country every year, an average of 426 daily or 18 every hour. To address this issue, we propose an automated system for collecting traffic fines using machine learning techniques. The system utilizes object detection to identify vehicles that have violated traffic rules, using video surveillance cameras. It then extracts the number plate and an encrypted QR code of the vehicle, which can be used to retrieve the vehicle owner's phone number and other details. These details are stored on a server, and the system sends three reminders for payment within a fixed time window. If the fine is not paid, the vehicle's registration with the RTO (Regional Transport Office) is automatically cancelled and it is no longer allowed on the road. This system aims to improve the efficiency and accuracy of the traffic fine collection process, while also reducing errors and the possibility of bribery. The use of machine learning techniques and video surveillance cameras allows for continuous monitoring of traffic, reducing the need for large numbers of traffic police to manually monitor the roads. The extraction of the QR code and vehicle owner's details also makes it easier to track and verify transactions, ensuring that the correct fine is being paid by the right individual. The automatic cancellation of the vehicle's registration if the fine is not paid serves as a deterrent for individuals attempting to evade paying their fines. In summary, our proposed system utilizes advanced technology to automate the traffic fine collection process, improving efficiency and accuracy while also reducing the possibility of bribery and errors.y.
