Smart Garbage Monitoring and Waste Classification Using IoT and CNN

An intelligent waste management solution built to enhance smart city infrastructure. This project uses ultrasonic sensors to detect bin fill levels, gas sensors to monitor odor/emissions, and a camera module to capture images of incoming waste. The captured images are analyzed using a CNN model trained in Google Colab to classify waste into categories like biodegradable, non-biodegradable, or hazardous. Upon reaching capacity or identifying critical waste types, the system instantly notifies municipal authorities through a custom cloud-connected dashboard or mobile app, streamlining waste pickup and segregation processes.

What You’ll Receive with This Project Kit:

All Essential Project Components:
Includes ultrasonic distance sensor, MQ-series gas sensor, ESP32/NodeMCU, camera module, Wi-Fi/Bluetooth interface, and enclosure-friendly mounts.

Fully Functional Source Code:
Code for sensor readings, camera capture, cloud sync, and CNN-based image classification, ready for integration with models trained using Google Colab.

Step-by-Step Working Methods:
Illustrated guide with circuit connections, housing layout, data logging setup, model integration tutorial, and app/dashboard linkage.

100-Page Detailed Project Report (PDF):
Comprehensive report with smart waste management use-cases, CNN model architecture, real-time data results, and improvement roadmap for large-scale deployment.

Advanced Waste Monitoring Interface:
Cloud dashboard or mobile app to visualize waste type, bin levels, and gas emission alerts in real time. Enables proactive municipal response and optimized waste routing.