REAL TIME HELMET DETECTION USING YOLO

Abstract

Real-time worker helmet detection is an AI-powered computer vision system that ensures workplace safety by automatically identifying whether workers are wearing helmets in live video streams using deep learning models like YOLO and RCNN. Designed for industries such as construction, manufacturing, and mining, the system offers features like instant safety alerts, high-accuracy detection under challenging conditions, continuous monitoring with violation logging, and a Flask-based web interface for remote supervision. It supports scalable, low-latency deployment on edge or cloud platforms and can be customized for other PPE detection, offering a cost-effective solution that minimizes manual supervision while enhancing compliance and safety.