SMART HELMET & TRIPLE RIDING DETECTION USING IOT &ML

Abstract

Violations in traffic laws are very common in a highly populated country like India. The accidents associated with these violations cause a huge loss to life and property. Since utilization of bikes is high, mishaps associated with bikes are additionally high contrasted with different vehicles. One of the main causes of these is not using motorcycle helmets. So we propose an approach called Smart helmet detection and triple riding detection using ML and IOT using deep learning which automatically sends challan or send an SMS for individuals in case of identification of bicycle riders without headgear and who are triple riding utilizing surveillance videos in real-time. The proposed approach initially recognizes motorcycle riders utilizing background subtraction and object segmentation. At that point we utilize object classifier to classify violators. Since wearing helmet is critical while driving, our main aim is to decrease the danger of injuries in case of accident. By detecting the motorcyclists without helmets, triple riding or other violations we can therefore increase their safety while on road. Hence by automating we reduce the workload on the traffic control team and will be able to share the evidence with the team efficiently to impose fines on violators. In recent years, the rise in road accidents and vehicle thefts has become a serious concern, urging the need for innovative solutions to enhance road safety and vehicle security. This paper presents a novel approach combining helmet detection and biometric-based vehicle security using machine learning techniques to address these issues. This system provides two steps of security in first step it validates triple riding in second step it identifies helmet wearing. If any one of these two will fail then vehicle will not start or stop. This proposed project title is helmet detection and biometric based vehicle security using machine learning with Arduino and ESP32 camera.