PPE Detection System

AI-powered Personal Protective Equipment (PPE) detection systems use computer vision and CCTV to monitor, detect, and alert in real-time when workers fail to wear mandatory safety gear like helmets, masks, vests, or gloves. These automated systems reduce violations by up to 73%, enhance workplace safety compliance, and provide audit-ready data for industries like construction, manufacturing, and healthcare

Key Features

Deep Learning Model YOLOv11 architecture for fast and accurate object detection
High Precision 90%+ detection accuracy with adjustable confidence thresholds
Web Interface Streamlit-based application
Multi-Source Processing Processes images and videos
Automated Reports Generates detailed compliance reports

Technical Specifications

Specification	Detail
Model:	YOLO11
Framework:	PyTorch
Language:	Python 3.8+
Dataset:	Roboflow
Computer Vision:	OpenCV
Interface:	Streamlit Web App

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