Artificial Intelligence Enhanced Waste Sorting and Classification System for Urban Recycling


Year : 2025 | Volume : 15 | Issue : 01 | Page : 23-32
    By

    Boovaneswari S,

  • Varalakshmi I,

  • Sarathi S,

  • Sriram P,

  1. Student, Department of Computer Science Engineering, Manakula Vinayagar Institute of Technology,, Kalitheerthalkuppam, Puducherry, India
  2. Student, Department of Computer Science Engineering, Manakula Vinayagar Institute of Technology, Kalitheerthalkuppam, Puducherry,, India
  3. Student, Department of Computer Science Engineering, Manakula Vinayagar Institute of Technology, Kalitheerthalkuppam, Puducherry, India
  4. Student, Department of Computer Science Engineering, Manakula Vinayagar Institute of Technology, Kalitheerthalkuppam, Puducherry, India

Abstract

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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.

Keywords: Intelligent waste management, artificial intelligence (AI), machine learning (ML), optimization, route optimization, waste forecasting, waste categorization, urban sustainability, resource efficiency

[This article belongs to Current Trends in Signal Processing (ctsp)]

How to cite this article:
Boovaneswari S, Varalakshmi I, Sarathi S, Sriram P. Artificial Intelligence Enhanced Waste Sorting and Classification System for Urban Recycling. Current Trends in Signal Processing. 2025; 15(01):23-32.
How to cite this URL:
Boovaneswari S, Varalakshmi I, Sarathi S, Sriram P. Artificial Intelligence Enhanced Waste Sorting and Classification System for Urban Recycling. Current Trends in Signal Processing. 2025; 15(01):23-32. Available from: https://journals.stmjournals.com/ctsp/article=2025/view=0


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Regular Issue Subscription Original Research
Volume 15
Issue 01
Received 08/01/2025
Accepted 13/01/2025
Published 14/02/2025
126

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