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The improper disposal and management of waste pose significant global challenges, contributing to environmental degradation. Manual waste segregation methods are labour-intensive and error-prone, leading to inefficient recycling. This article explores the potential of AI-based image analysis and machine learning to enhance garbage segregation accuracy. Employing computer vision and pattern recognition, the goal is to create an automated system that identifies and categorizes diverse waste types based on their visual features, revolutionizing waste management with efficient sorting and environmental conservation.

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Optimizing Garbage Segregation Through AI-Based Image Analysis and Machine Learning: An Exploratory Study of Classification Algorithms

  • 会议论文

  • 发表日期：

    2025年

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  • Bimmarolu Shanthi,
  • Renuka Kuntala,
  • K. Venkata Balamurali Krishna,
  • Peddi Niranjan Reddy,
  • Mruthyunjayam Allakonda,
  • Gujjula Anjareddy

摘要

The improper disposal and management of waste pose significant global challenges, contributing to environmental degradation. Manual waste segregation methods are labour-intensive and error-prone, leading to inefficient recycling. This article explores the potential of AI-based image analysis and machine learning to enhance garbage segregation accuracy. Employing computer vision and pattern recognition, the goal is to create an automated system that identifies and categorizes diverse waste types based on their visual features, revolutionizing waste management with efficient sorting and environmental conservation.