EcoVision

EcoVision is an innovative web application that uses AI to promote environmental sustainability by analyzing everyday objects in images and providing personalized eco-friendly tips.

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🌍 EcoVision: AI-Powered Sustainable Living Assistant

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EcoVision is an innovative AI-powered web application that promotes sustainable living by analyzing everyday objects in images and offering personalized eco-friendly recommendations.

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📸 Live Demo

🌐 Visit the live website to test EcoVision: https://ecovision-ai.netlify.app/
💻 Github repository: https://github.com/JimmyVS/EcoVision/

🚀 Project Overview

EcoVision addresses the growing need for accessible environmental education by making sustainability interactive, educational, and immediately actionable.

👁️‍🗨️ Problem Statement

Many people want to live more sustainably but lack the knowledge or guidance. EcoVision bridges this gap by analyzing everyday objects and providing real-time environmental tips.

💡 Features

🔍 AI-Powered Object Detection

  • Utilizes YOLOv8 for accurate real-time image analysis.

🌱 Eco-Tips Engine

  • Over 30+ categorized items.
  • Tips organized by:
    • Impact Level: High, Medium, Low
    • Action Type: Replace, Reduce, Recycle, Reuse
    • Item Category: Household, Electronics, Transport, etc.

🧠 Environmental Impact Scoring

  • Calculates environmental scores based on the image contents.

🎓 Educational Focus

  • Each tip includes scientific/environmental context and real-life impact.

📱 Intuitive Interface

  • Drag-and-drop file uploads
  • Real-time visual feedback
  • Fully responsive for desktop and mobile

🧰 Tech Stack

🔗 Backend

  • Python
  • Flask, Flask-CORS
  • Ultralytics YOLOv8
  • PIL, NumPy

🖥 Frontend

  • HTML5, CSS3, JavaScript (ES6+)
  • Responsive Design (Flexbox + Grid)

🤖 AI/ML

  • YOLOv8 (pretrained on COCO dataset)
  • Real-time object detection
  • Actionable recommendation generation

🛠 Development Tools

  • RESTful API
  • Drag-and-drop support
  • Cross-platform functionality
  • Error handling and user feedback

🌎 Environmental Impact

✅ Educates users on sustainable practices
✅ Promotes Reduce, Reuse, Recycle
✅ Increases awareness of item-specific environmental impact
✅ Supports eco-friendly decision-making

🧪 Innovation & Highlights

  • ⚡ Real-time object detection using cutting-edge AI
  • 📊 Scalable impact scoring and eco-database
  • 🌐 Built-in educational context for each item
  • 💡 Clean, modern interface for easy engagement

📈 Future Enhancements

  • 👥 Community-driven tip sharing
  • 📅 Sustainability tracking + goal setting
  • 🗺️ Integration with local recycling/donation centers
  • 📱 Native mobile app
  • 🧠 Machine learning for personalized tips

🧱 Challenges Faced

  • Balancing Accuracy and Speed: Running object detection in real-time with meaningful recommendations, while keeping the app responsive, required optimizing both model loading and result parsing.
  • Frontend-Backend Communication Across Hosts: Hosting the frontend on Netlify while developing the backend locally introduced CORS and cross-origin communication issues, which had to be solved for demo consistency.

🧪 Getting Started

# Clone the repository
git clone https://github.com/JimmyVS/EcoVision.git
cd EcoVision

# Run the python server and open the website.
# This is done automatically by opening the open.bat
start open.bat

🖼️ Demo Instructions

  1. Go to the Live Demo
  2. Upload an image with everyday objects.
  3. Click Analyze Image.
  4. Get eco-tips + impact score in real-time.

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🤝 Contributing

Pull requests are welcome! For major changes, please open an issue first to discuss what you'd like to change.

📜 License

This project is licensed under the MIT License. See LICENSE for more information.

🧠 Acknowledgements

  • Ultralytics YOLOv8
  • COCO Dataset
  • Netlify for live preview

Note: This repository is created to showcase the project for the Hackboro Hackathon 2025.

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