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<p>Microplastics are widespread in aquatic environments, and their quantification remains difficult. This study presents the <i>zero plastic</i> prototype, an open source AI-assisted imaging system designed for microplastic detection. The prototype device uses flow-imaging microscopy to capture particles in the 3–200 <InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\mu\)</EquationSource> </InlineEquation>m range and applies an AI-based segmentation pipeline for image analysis. Laboratory validation was carried out using polystyrene microspheres in the 3–20 <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\mu\)</EquationSource> </InlineEquation>m range, prepared under reproducible conditions. Comparison with scanning electron microscopy showed agreement for spherical particles larger than 3 <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\mu\)</EquationSource> </InlineEquation>m. The results define the prototype’s performance under controlled laboratory conditions for polystyrene microspheres and provide a basis for future development toward use in environmental monitoring.</p>

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Zero-plastic: AI-assisted sensing for microplastic assessment

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年2月26日

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  • Bruna de Vargas Guterres,
  • Everson da Silva Flores,
  • Marcelo de Gomensoro Malheiros,
  • Paula Alice Bezerra Barros,
  • Thiago Alves Teixeira,
  • Cristiana Lima Dora,
  • Luis Henrique da Silva Poersch,
  • Wilson Francisco Britto Wasielesky Junior,
  • Marcelo Rita Pias

摘要

Microplastics are widespread in aquatic environments, and their quantification remains difficult. This study presents the zero plastic prototype, an open source AI-assisted imaging system designed for microplastic detection. The prototype device uses flow-imaging microscopy to capture particles in the 3–200 \(\mu\) m range and applies an AI-based segmentation pipeline for image analysis. Laboratory validation was carried out using polystyrene microspheres in the 3–20 \(\mu\) m range, prepared under reproducible conditions. Comparison with scanning electron microscopy showed agreement for spherical particles larger than 3 \(\mu\) m. The results define the prototype’s performance under controlled laboratory conditions for polystyrene microspheres and provide a basis for future development toward use in environmental monitoring.