Scholarlink

This paper proposes an innovative AI-based system for automated domestic waste segregation. Utilizing Teachable Machine and MobileNet, the system accurately categorizes waste into dry and wet components, laying the foundation for sustainable waste management practices. Embedded in a Raspberry Pi 4, the system integrates real-time image processing with various sensors to streamline the sorting process. While the model has been simulated due to budgetary constraints, future implementation envisions real-world application. Potential advancements include expanding the dataset, enabling multi-category waste classification, and exploring low-power alternatives. This research contributes to the evolving landscape of smart waste management, addressing environmental sustainability and the pressing need for automated, efficient waste segregation at the domestic level.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Proposing an AI-Enabled Waste Segregation System for Domestic Settings

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Devnarayan G. Rao,
  • G. Sangeetha,
  • J. Sandeep,
  • C. S. Sreeja,
  • Agnes Nalini Vincent,
  • Teena Mary

摘要

This paper proposes an innovative AI-based system for automated domestic waste segregation. Utilizing Teachable Machine and MobileNet, the system accurately categorizes waste into dry and wet components, laying the foundation for sustainable waste management practices. Embedded in a Raspberry Pi 4, the system integrates real-time image processing with various sensors to streamline the sorting process. While the model has been simulated due to budgetary constraints, future implementation envisions real-world application. Potential advancements include expanding the dataset, enabling multi-category waste classification, and exploring low-power alternatives. This research contributes to the evolving landscape of smart waste management, addressing environmental sustainability and the pressing need for automated, efficient waste segregation at the domestic level.