Abstract :

This Project Presents An AI-Based Smart Waste Segregation And Monitoring System That Uses Artificial Intelligence And Deep Learning Techniques To Automatically Identify And Classify Different Types Of Waste. The System Enhances Waste Management By Accurately Segregating Waste Into Categories Such As Plastic, Paper, Metal, Glass, Cardboard, Food Organics, Textile, Vegetation, And Miscellaneous Trash. It Ensures Efficient Waste Disposal, Reduces Human Effort, And Supports Environmental Sustainability Through Intelligent Decisionmaking. The System Uses Camera-based Image Acquisition Or Uploaded Images Along With Computer Vision Techniques To Classify Waste Using A Trained Convolutional Neural Network (CNN) Model. After Classification, The System Displays The Predicted Waste Category With A Confidence Score, Stores Prediction History, And Provides Monitoring And Reporting Features. Traditional Waste Segregation Methods Rely On Manual Sorting, Which Is Time-consuming, Laborintensive, Error-prone, And Often Results In Improper Waste Disposal And Increased Environmental Pollution.

Published:

29-7-2026

Issue:

Vol. 26 No. 7 (2026)

Page Nos:

1398-1405

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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