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This project focuses on developing an advanced system for waste classification, aimed at categorizing various types of waste while also assessing their degradability. Leveraging the convolutional neural network algorithm VGG16, the system facilitates both image-based classification and real-time camera streaming for efficient waste management. Also, the system incorporates multi-class methods for the ultimate detection and classification of different waste materials. After the materials have undergone classification, the system triggers alerts that make it very useful in practices of waste management.

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Predicting Waste Variation: Incorporating Neural Networks for Automated Sorting Under Dynamic Environmental Conditions

  • 会议论文

  • 发表日期：

    2025年

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  • P. Latha,
  • D. Janani,
  • P. Monigaa,
  • M. Mythili

摘要

This project focuses on developing an advanced system for waste classification, aimed at categorizing various types of waste while also assessing their degradability. Leveraging the convolutional neural network algorithm VGG16, the system facilitates both image-based classification and real-time camera streaming for efficient waste management. Also, the system incorporates multi-class methods for the ultimate detection and classification of different waste materials. After the materials have undergone classification, the system triggers alerts that make it very useful in practices of waste management.