♻️ EcoBin: Intelligent AI Waste Management Ecosystem

Empowering Sustainability through Neural Intelligence. EcoBin is a cutting-edge, full-stack ecosystem designed to revolutionize personal waste management. By merging real-time AI computer vision with gamified incentives, we make responsible disposal an engaging, data-driven experience.

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📖 Table of Contents

• ✨ Key Features
• 🏗️ System Architecture
• 💻 Tech Stack
• 🚀 Quick Start
• 🛠️ Configuration
• 🛡️ Security & Privacy
• 🤝 Contributors
• 📜 License

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✨ Key Features

🔍 Real-Time AI Classification

• Neural Scanning Box: A high-precision "Laser Scanning" interface that crops and isolates objects from the background using real-time frame matrix transformations.
• Live Classification: Instant categorization into Biodegradable, Recyclable, or Non-Biodegradable with high-confidence auto-confirmation.
• Background Exclusion: Mathematical pixel-cropping logic ensures the AI focuses solely on the waste item, ignoring environmental clutter.

🎮 Gamified Eco-Impact

• EcoPoints System: Earn points for every successful scan and proper disposal.
• Global Leaderboards: Compete with other "Eco-Warriors" and track your rank in the community.
• Personal Dashboard: Comprehensive analytics on your recycling habits, streaks, and total impact.

🔐 Enterprise-Grade Backend

• JWT Security: Secure, stateless authentication with 24-hour session management.
• Admin Command Center: Dedicated administrative interface for managing classification rules, user logs, and system analytics.
• Robust Fallback: Intelligent keyword-matching taxonomy that takes over if the AI microservice experiences latency.

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🏗️ System Architecture

graph TD
    A[React Client] -->|Stream Frames| B(Vite Proxy)
    B -->|Base64 Payload| C{Spring Boot API}
    C -->|Analyze Image| D[Python AI Microservice]
    D -->|TensorFlow Inference| C
    C -->|Store Data| E[(PostgreSQL)]
    C -->|JWT Auth| F[Spring Security]
    A -->|Live Feedback| G[User Dashboard]

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💻 Tech Stack

Frontend (User Experience)

• Core: React 18, Vite (Fast HMR)
• State Management: Redux Toolkit (Global), React Query (Server-State)
• Styling: Tailwind CSS (Glassmorphism), Framer Motion (Fluid Animations)
• Icons: Lucide React

Backend (Business Logic)

• Framework: Spring Boot 3
• Security: Spring Security + JWT
• Persistence: Hibernate/JPA + PostgreSQL
• Utilities: Lombok, Maven

AI Engine (Neural Processing)

• Processing: Python, OpenCV (Image Matrixing)
• Model: TensorFlow/Keras (ecobin_model.keras)
• API Layer: Flask

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🚀 Quick Start

Prerequisites

• Node.js (v18+)
• Java JDK 17+
• Python 3.9+
• PostgreSQL Instance

1. Initialize the Neural Engine

cd Model
pip install -r requirements.txt
python app.py

2. Launch the Backend API

Configure your DB credentials in application.properties first.

cd EcoBin_Backend
# Run the provided startup script
./run_backend.bat
# OR via Maven
mvn spring-boot:run

3. Spin up the Frontend

cd EcoBin_Frontend
npm install
npm run dev

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🛠️ Configuration

The system relies on environment variables or application.properties:

Variable	Description
SPRING_DATASOURCE_URL	PostgreSQL Connection String
JWT_SECRET	256-bit Secure key for token signing
AI_MODEL_URL	Endpoint of the Flask Microservice
PORT	Backend server port (Default: 8080)

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🛡️ Security & Privacy

• Stateless Auth: All requests are protected via JWT.
• Data Integrity: Bcrypt password hashing for all user accounts.
• Frame Privacy: Captured frames for AI analysis are processed in-memory and subject to standard cleanup protocols.

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🤝 Contributors

This project is a collaborative effort:

• Ayush: Lead Developer (Frontend, Backend, & System Architecture)
• Akash: AI Model Development & Neural Engine Integration

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📜 License

Distributed under the MIT License. See LICENSE for more information.

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Developed with ❤️ by the EcoBin Team Contributing to a Greener Future, One Pixel at a Time.