Year: 2025
Type: article
Abstract: : Individuals frequently disregard how important it is to wear helmets, which causes tragic accidents. A helmet reduces your risk of getting a serious brain injury and dying by deflecting most of the impact energy that would otherwise hit your head and brain during a tumble or collisions. In India, it is against the law to operate a motorbike or scooter without a helmet, which has increased fatalities as well as crashes. The existing system mostly relies on surveillance footage for keeping up with traffic violations, necessitating a close-up of the license plate by traffic police in the case that the motorcyclist lacks a helmet. Yet, this necessitates a substantial amount of personnel and time considering the high frequency of traffic violations and the rising everyday use of motorcycles. Imagine if there was an algorithm that monitored traffic infractions, such driving a motorbike with no a helmet, and, if any were identified, generate the license plate of the vehicle that committed the violation. Helmet and license plate is detected using a neural network is proposed in this paper. There will be two phases. Initially, we check to see if the riders are wearing helmets. If not, a second step is used to find their license plate. To identify unauthorized vehicles, we also look for license plates on passing vehicles. Keywords: Convolutional Neural Network, Helmet Detection, Machine Learning, Yolov8
DOI: 10.55041/ijsrem48029
Author: SAVARI JEEVA JEBASTIN P
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4410460964