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In Situ Detection of Aquatic Microplastics using Laser-Based Holographic Imaging and Deep Learning

CWSF · 2026 Environment & Climate Change Silver Medal

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Overview

The prevalence of microplastic pollution in aquatic environments is a significant global concern. However, quantifying microplastics using conventional laboratory-based methods is costly and labour-intensive, considerably limiting routine analysis. To overcome these constraints, I developed a field-portable, submersible, laser-based holographic imaging system for the in situ detection of microplastics. Digital holography was employed to facilitate high-detail, large depth-of-field imagery through an extensive water volume, achieving an optical resolution of <10 μm through optimization. Numerical algorithms were implemented to accurately reconstruct images and extract key morphological features of microparticles. Custom-trained AI models were developed to identify irregular-shaped microplastics in lake water, resulting in 94% detection accuracy. Performance was evaluated via real-world field trials at 10 bodies of water, yielding statistics on particle characteristics and concentrations. In addition to microplastics, various microorganisms were identified in situ, demonstrating the system’s versatility as an innovative, low-cost platform for robust, real-time monitoring of ecosystem health.

Awards (4)

  • Young Scientist Award
  • Challenge Award
  • Silver Medal
  • Selected for CWSF 2026

Competition history

  • CWSF 2026 Environment & Climate Change

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