3RVision - See Your Products' Sustainable Future 🌱

"Every product tells a story of sustainability. With 3RVision, we help you write its next chapter via reuse, recycling and resale."

🧠 Introduction

3RVision is a comprehensive sustainability analysis platform that helps users make informed decisions about product lifecycle management. By analyzing product images, our platform provides detailed insights into how you can extend a product's life through three key sustainability pillars: reuse, recycle, and resale. Whether you're looking to dispose of items responsibly or make sustainable purchasing decisions, 3RVision guides you towards environmentally conscious choices.

🔍 Problem Statement

In today's consumer-driven world, we face several critical challenges:

• Lack of awareness about proper product disposal methods
• Difficulty in identifying recycling and reuse opportunities
• Limited access to local sustainability resources
• Environmental impact of improper product disposal
• Complex decision-making process for sustainable product lifecycle management

✅ Solution Overview

3RVision addresses these challenges through:

1. Image-Based Analysis

• Smart Capture: Take photos or upload product images
• Material Recognition: Advanced ML models identify product composition
• Lifecycle Analysis: Get detailed insights on:
  • Reuse potential and creative repurposing ideas
  • Recycling options and local facilities
  • Resale value and market opportunities
  • Biodegradability assessment

2. Browser Extension

• Quick Analysis: Get instant sustainability insights while browsing
• Seamless Integration: Works alongside your browsing experience
• Consistent Experience: Same analysis quality as the web platform
• Easy Access: One-click access to detailed sustainability information

3. Community Forum

• Share sustainability experiences
• Discuss eco-friendly practices
• Create and participate in polls
• Share images and tips
• Connect with like-minded individuals

🛠️ Tech Stack

Category	Technologies
Frontend	Next.js 15.2.4, React 19, TypeScript, TailwindCSS, Framer Motion, Three.js
Backend	Go (Golang), Gin Web Framework, AWS S3, MongoDB
Extension	JavaScript, Chrome Extension Manifest V3, Content Scripts
ML Component	Python, Computer Vision Models, Flask Server

🧩 Architecture

☘️ Installation

Prerequisites

• Node.js 18+
• Go 1.21+
• Python 3.10 or further
• Chrome/Edge browser
• AWS account
• MongoDB

Run Frontend

cd frontend
npm install
npm run dev

Run Backend

cd backend
go mod download
go run main.go

Run ML model

cd ml
py -3.10 -m venv myenv
source myenv/bin/activate  # For macOS/Linux
# OR
myenv\Scripts\activate  # For Windows
pip install --upgrade pip
pip install -r requirements.txt
# tensorflow-intel==2.18.0  ← not supported on macOS ARM (remove this line in requirements.txt)
python app.py or python3 app.py

#For conda environment
conda create --name myenv python=3.10
conda activate myenv          

Extension Setup

1. Open Chrome/Edge
2. Go to Extensions page
3. Enable Developer mode
4. Load unpacked extension from the extension directory

Environment Variables

Create .env files in respective directories:

Frontend (.env.local)

MONGODB_URI=your_mongodb_uri
JWT_SECRET=secret_key _for_JWT_tokens
EMAIL_USER=email_username
EMAIL_PASS=email_password
GEMINI_API_KEY=your_gemini_api_key

Backend (.env)

AWS_REGION=your_aws_region
AWS_ACCESS_KEY_ID=your_aws_access_key_id
AWS_SECRET_ACCESS_KEY=your_aws_secret_key
S3_BUCKET_NAME=your_bucket_name
GEMINI_API_KEY=your_api_key
FLASK_SERVER_URL=http://localhost:5001
PORT=8080

👥 Contributors

Khushi Agarawal
Arpit Srivastava
Naman Raj
Shreyansh Pathak

📄 License

This project is licensed under the MIT License.