EcoCycle360

EcoCycle360 is a sustainability-driven web platform designed to encourage recycling by offering customers reward points and leaderboard rankings for submitting recyclable materials. The collected materials — such as plastic, e-waste, paper, books, clothes, glass, and metal — are then supplied to recycling companies. This creates a win–win model, where customers are rewarded for their contributions and companies build a stronger brand image while supporting environmental goals.

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Project Structure

EcoCycle360/
│
├── admin/         # Admin dashboard (React)
├── customer/      # Customer portal (React)
├── backend/       # Node.js/Express backend API
├── ML_api/        # Python Flask ML API for CO₂ prediction
├── Model/         # ML model, dataset, and simulation scripts

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Features

Admin Dashboard (admin/)

• Customer Management: View, search, and manage customer profiles and activity.
• Order Management: Track and manage placed orders and recycling returns.
• Analytics Dashboard: Visualize key metrics (customers, orders, recyclables, CO₂ savings) with charts and graphs.
• In-Mall Submission: Admins can submit recyclables on behalf of customers.
• Authentication: Secure admin login and registration.

Customer Portal (customer/)

• User Registration & Login: Secure sign-up and sign-in for customers.
• Order Placement: Customers can place orders for recyclable items.
• Checkout Flow: Multi-step checkout with address, payment, and order confirmation.
• Leaderboard: See eco-score and CO₂ savings compared to peers.
• Performance Dashboard: Visual feedback on recycling performance and rewards (EcoCoins).
• Profile Management: View and update personal details.

Backend API (backend/)

• RESTful API: Built with Node.js and Express, provides endpoints for authentication, users, orders, recyclables, and analytics.
• PostgreSQL Database: Stores users, orders, recycling data, and more.
• Authentication: JWT-based authentication for secure access.
• Integration with ML API: For CO₂ savings prediction.

Machine Learning API (ML_api/ & Model/)

• Flask API: Receives recycling data and predicts CO₂ savings using a trained ML model.
• Model Training: Scripts and datasets for training and updating the eco-impact prediction model.

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Technologies Used

• Frontend: React, Vite, Tailwind CSS, Zustand (state management), React Router
• Backend: Node.js, Express, PostgreSQL, JWT, dotenv
• ML API: Python, Flask, scikit-learn, pandas
• DevOps: Vite, ESLint, environment variable management

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How It Works

1. Customers register and log in to the portal, place orders, and submit recyclables.
2. Admins manage users, orders, and recyclables through a dedicated dashboard.
3. Recycling Data is sent to the ML API, which predicts CO₂ savings and returns results to the backend.
4. Leaderboards and performance dashboards motivate users to recycle more by showing their impact and rewards.
5. All data is securely stored and managed in a PostgreSQL database.

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Getting Started

Prerequisites

• Node.js & npm
• Python 3.x
• PostgreSQL