🦺 AI-Powered PPE Detection & Safety Compliance System

An intelligent AI-based Personal Protective Equipment (PPE) detection system designed to enhance worker safety at construction and industrial sites by automatically identifying whether workers are wearing mandatory safety gear and alerting supervisors in real time.

🚀 Project Overview

This system uses Computer Vision and Deep Learning to monitor live camera feeds and detect whether individuals are wearing required PPE such as helmets, safety goggles, gloves, or protective caps. If a person is detected without proper PPE, the system immediately: Captures the individual’s image Highlights the violation with a bounding box Sends an email alert with the captured image to the respective site manager Once the person complies and wears the PPE, the bounding box is automatically removed, ensuring continuous and adaptive monitoring.

🎯 Key Objectives

Prevent workplace accidents and injuries Automate PPE compliance monitoring Reduce manual safety audits Enable fast response to safety violations

🧠 How the System Works 1️⃣ Live Video Monitoring

Cameras continuously monitor the construction site Each video frame is processed in real time

2️⃣ PPE Detection & Classification

AI model detects individuals in the frame PPE items (helmet, goggles, etc.) are identified System determines compliance or violation

3️⃣ Violation Alert Mechanism

If PPE is missing: Bounding box is drawn around the person Image snapshot is captured Email alert is sent to the site manager Alerts include visual proof for quick action

4️⃣ Continuous Tracking & Compliance Update

The system tracks the same individual If PPE is worn later: Bounding box is removed Violation is cleared No duplicate alerts for the same person

📧 Email Notification System

Automatic alerts to managers/supervisors Includes captured image of violation Timestamp and detection details Helps enforce safety protocols instantly

📊 Dashboard & Monitoring (Optional Extension)

Live safety status monitoring PPE compliance statistics Historical violation records Camera and site management

🏗️ Tech Stack (High-Level)

Backend: FastAPI/ Django Computer Vision: OpenCV Deep Learning: CNN / YOLO-based object detection AI/ML: PPE classification models Notification: Email (SMTP / API-based)

🔐 Security & Privacy

Role-based access to safety dashboards Secure image handling Minimal data retention Designed for industrial compliance use

🏭 Use Cases

Construction sites Manufacturing plants Industrial safety monitoring Smart workplace environments

🌱 Future Enhancements

Multi-camera worker tracking PPE compliance analytics dashboard Mobile alerts and SMS notifications Cloud-based deployment Integration with attendance and access systems

👨‍💻 Author

Jayesh Naidu Machine Learning Engineer | Computer Vision Specialist Focused on AI-driven safety, real-time monitoring, and applied deep learning systems

⭐ Impact

This project contributes directly to saving lives by enforcing PPE compliance and reducing workplace accidents through intelligent automation.