Abstract :

The Growing Volume Of Municipal Solid Waste And Improper Disposal Practices Pose Significant Environmental, Economic, And Public Health Challenges. To Address These Issues, This Work Introduces A Smart Waste Handling And Recycling Guidance System Powered By Artificial Intelligence, Designed To Optimize Waste Segregation, Collection, And Recycling Decisions. The System Integrates Image-based Waste Recognition Using Machine Learning Models, Enabling Accurate Classification Of Materials Such As Plastic, Metal, Paper, And Organic Waste. Based On The Identified Category, The System Provides Real-time Disposal Recommendations And Recycling Guidance To Users Through An Interactive Interface. Additionally, The Platform Supports Data-driven Planning By Analyzing Waste Generation Patterns And Suggesting Optimized Collection Schedules For Waste Management Authorities. By Promoting Correct Segregation And Encouraging Recycling Behavior, The Proposed System Aims To Reduce Landfill Burden, Enhance Resource Recovery, And Support Sustainable Urban Waste Management Practices. Experimental Evaluation Demonstrates Improved Accuracy In Waste Identification And Efficiency In Handling Processes, Highlighting The System’s Potential As A Practical Solution For Smart Cities And Environmentally Conscious Communities. Keywords:Smart Waste Management, Recycling Guidance, Artificial Intelligence, Waste Segregation, Sustainability, Environmental Monitoring, Smart Bins, IoT Sensors, Machine Learning, Resource Optimization.

Published:

11-12-2025

Issue:

Vol. 25 No. 12 (2025)

Page Nos:

163-168

Section:

Articles

License:

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

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