AI-DRIVEN WASTE SORTING AND CLASSIFICATION FOR SMART URBAN RECYCLING

Archana Balkrishna, Yadav (2025) AI-DRIVEN WASTE SORTING AND CLASSIFICATION FOR SMART URBAN RECYCLING. Manuscripts on the Artificial Intelligence and Digital Research, 2 (1). pp. 1-9. ISSN 3064-8807

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Abstract

This study explores the potential of Artificial Intelligence (AI) and Machine Learning (ML) to enhance waste management efficiency within urban environments. Rapid urbanization has resulted in a surge of municipal waste, which current systems often struggle to manage effectively. The proposed AI-enhanced waste sorting and classification system aims to optimize waste collection routes and accurately forecast waste generation trends, thereby reducing operational costs, fuel consumption, and traffic congestion. Additionally, AI-driven image recognition and sorting algorithms improve waste classification accuracy, ensuring recyclable materials are efficiently identified and redirected away from landfills, thus promoting sustainability. By leveraging real-time and historical data, the system dynamically adjusts resource allocation and collection schedules to meet the varying needs of different urban areas. Results indicate significant gains in waste management efficiency and resource optimization, positioning this AI-driven system as a substantial advancement in sustainable urban waste management.

Item Type:	Article
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Divisions:	Postgraduate > Master's of Islamic Education
Depositing User:	Journal Editor
Date Deposited:	12 Feb 2025 05:20
Last Modified:	12 Feb 2025 05:34
URI:	http://eprints.umsida.ac.id/id/eprint/15376

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