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There is currently a need for automated tools that use complex machine learning algorithms to help in sustainability. In this field, it is essential to create mechanisms to identify and separate organic matter from non-organic matter to help separate and reuse waste. This paper presents an electronic device that uses gas sensors controlled by a microcontroller, capable of sending data to an application that can identify organic food matter with a satisfactory degree of certainty using a machine learning algorithm. This device can be used in garbage cans, facilitating the correct disposal of organic food matter for later reuse.

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Electronic Devices Using Machine Learning to Identify Organic Material

  • 会议论文

  • 发表日期：

    2026年

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  • Almir Silva da Silveira,
  • André Carlos Teixeira Vasconcelos,
  • Jorge Eugenio Medeiros,
  • João Roberto de Toledo Quadros

摘要

There is currently a need for automated tools that use complex machine learning algorithms to help in sustainability. In this field, it is essential to create mechanisms to identify and separate organic matter from non-organic matter to help separate and reuse waste. This paper presents an electronic device that uses gas sensors controlled by a microcontroller, capable of sending data to an application that can identify organic food matter with a satisfactory degree of certainty using a machine learning algorithm. This device can be used in garbage cans, facilitating the correct disposal of organic food matter for later reuse.