E-Waste Deconstructor — Digital Twin

Developed by: DhanushN2005
Date: September 2025

A smart, automated e-waste processing system that uses computer vision and digital twin simulation to classify electronic waste, estimate hazardous levels, and provide safe deconstruction suggestions in real time. :contentReference[oaicite:1]{index=1}

🧠 Project Overview

E-waste contains hazardous materials and poses environmental and health risks if not handled properly. This project combines YOLO-based object detection, hazard prediction, and a digital twin simulation to:

✔ Identify and classify e-waste items
✔ Predict hazardous levels
✔ Generate automated safe deconstruction recommendations
✔ Simulate and monitor the deconstruction workflow in real time This solution bridges real-world deconstruction processes with simulation to improve safety and efficiency in electronic waste management. :contentReference[oaicite:2]{index=2}

🚀 Features

• 🔍 YOLO-powered Object Detection
  Detects and classifies electronic waste components using computer vision. :contentReference[oaicite:3]{index=3}
• ⚠️ Hazard Level Estimation
  Predicts the hazardous severity of detected e-waste items to guide handling decisions. :contentReference[oaicite:4]{index=4}
• 🧪 Digital Twin Simulation
  Runs autonomous simulations of the deconstruction process for monitoring and analysis. :contentReference[oaicite:5]{index=5}
• 📊 Web Dashboard Interface
  Visual interface for real-time detection and simulation status (HTML files included). :contentReference[oaicite:6]{index=6}

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🗂 Repository Structure

By Dhanush N