Project Overview:

The Smart Waste Management System is an IoT and AI-based solution that automates the monitoring, collection, and optimization of waste disposal in urban and rural areas. The system uses sensors to detect waste bin levels and transmits this data to a centralized server, where ML algorithms predict waste fill rates and suggest optimal collection routes for waste collection vehicles.

This project promotes cleaner cities, reduces manual monitoring, and enhances efficiency in garbage collection through intelligent route planning and predictions.

Technologies Used:

Hardware:

• Microcontroller: Arduino Uno / ESP32 / Raspberry Pi

• Sensors:

  • Ultrasonic Sensor (HC-SR04) – to measure waste bin fill level

  • GPS Module – to track bin location (optional)

  • GSM Module or Wi-Fi Module – to send data

• Power Supply: Battery/solar (optional)

Frontend:

• HTML, CSS, Bootstrap

• JavaScript (Google Maps API, Chart.js for graphs)

Backend:

• Option 1: PHP + MySQL

• Option 2: Node.js + MongoDB

• Option 3: Java Spring Boot + PostgreSQL

AI/ML:

• Python (pandas, scikit-learn, K-Means, Decision Trees)

• ML Models:

  • Predict bin fill time based on past data

  • Optimize garbage truck routes (route clustering using K-Means)

System Architecture:

1. Ultrasonic sensor detects fill level of garbage in real-time.

2. Microcontroller reads data and sends it to the backend server via Wi-Fi/GSM.

3. Server stores data in the database and runs an ML model to:

   • Predict when the bin will be full

   • Suggest optimized pickup routes

4. Web dashboard displays:

   • Real-time bin fill levels

   • Color-coded bin status (Green = empty, Red = full)

   • Smart maps showing optimized truck routes

5. Alerts are sent to authorities if bins are full or overflowing.