Recycle LAB - QR & E-Waste Management System

Feb 2025 - Feb 2025

Achievement: Top 5 in Karthavya National Level Hackathon at Jyothi Engineering College, Thrissur.

Use this repository to view the source code.

Overview

Welcome to the QR & E-Waste Management System, an integrated platform designed for QR code-based tracking and efficient e-waste repair management.

This system facilitates:

• Smart Waste Management: Integrating IoT, QR-based tracking, and ML-based forecasting.
• Full-bin Alert System: Using Arduino sensors to automate waste collection and reduce manual monitoring by 50%.
• Digital Inventory: QR-coded tracking for departmental waste, cutting data entry time by 60%.
• Analytics: Power BI dashboard for real-time visualization and ML models to predict monthly waste generation with 40% improved accuracy.
• Compliance: Ensuring 100% compliance with disposal regulations through certified recycling workflows.

Project Structure

This repository contains three main components:

1. QR MVP 🏷️

• A Node.js application that allows users to generate QR codes and store details in a CSV file.
• Users can also scan QR codes to retrieve and display stored data.
• Helps in tracking assets and managing inventory efficiently.

2. WMS 4 - E-Waste Generator Dashboard 🔧

• A React-based dashboard for entities generating e-waste.
• Enables businesses to track repair shops, request repairs, and manage e-waste disposal.
• Login System:
  • Username: abid
  • Password: abid
• Redirects to the Centre Dashboard for further processing after login.

3. Centre - Repair Center Dashboard 🏭

• A React-based dashboard used by repair centers to manage repair requests, sales, and inventory.
• Helps track incoming e-waste, accept/decline repair requests, and optimize workflow.
• Login Credentials:
  • Username: abin
  • Password: abin

4. Machine Learning Module 🤖

• A Flask-based web app performing Linear Regression, Decision Tree, and Random Forest analysis.
• Trained on data to generate predictive graphs.

Tech Stack

• Frontend: React
• Backend: Node.js
• ML/AI: Python, Flask, Scikit-learn (Linear Regression, Decision Tree, Random Forest)
• IoT: Arduino
• Analytics: Power BI