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A Critical Review on Artificial Intelligence—Based Microplastics Imaging Technology: Recent Advances, Hot-Spots and Challenges

Author

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  • Yan Zhang

    (School of Materials and Environmental Engineering, Fujian Polytechnic Normal University, Fuzhou 350300, China)

  • Dan Zhang

    (School of Big Data and Artificial Intelligence, Fujian Polytechnic Normal University, Fuzhou 350300, China
    Fujian Provincial Key Laboratory of Coastal Basin Environment, Fujian Polytechnic Normal University, Fuzhou 350300, China)

  • Zhenchang Zhang

    (College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China)

Abstract

Due to the rapid artificial intelligence technology progress and innovation in various fields, this research aims to use science mapping tools to comprehensively and objectively analyze recent advances, hot-spots, and challenges in artificial intelligence-based microplastic-imaging field from the Web of Science (2019–2022). By text mining and visualization in the scientific literature we emphasized some opportunities to bring forward further explication and analysis by (i) exploring efficient and low-cost automatic quantification methods in the appearance properties of microplastics, such as shape, size, volume, and topology, (ii) investigating microplastics water-soluble synthetic polymers and interaction with other soil and water ecology environments via artificial intelligence technologies, (iii) advancing efficient artificial intelligence algorithms and models, even including intelligent robot technology, (iv) seeking to create and share robust data sets, such as spectral libraries and toxicity database and co-operation mechanism, (v) optimizing the existing deep learning models based on the readily available data set to balance the related algorithm performance and interpretability, (vi) facilitating Unmanned Aerial Vehicle technology coupled with artificial intelligence technologies and data sets in the mass quantities of microplastics. Our major findings were that the research of artificial intelligence methods to revolutionize environmental science was progressing toward multiple cross-cutting areas, dramatically increasing aspects of the ecology of plastisphere, microplastics toxicity, rapid identification, and volume assessment of microplastics. The above findings can not only determine the characteristics and track of scientific development, but also help to find suitable research opportunities to carry out more in-depth research with many problems remaining.

Suggested Citation

  • Yan Zhang & Dan Zhang & Zhenchang Zhang, 2023. "A Critical Review on Artificial Intelligence—Based Microplastics Imaging Technology: Recent Advances, Hot-Spots and Challenges," IJERPH, MDPI, vol. 20(2), pages 1-30, January.
    • Handle: RePEc:gam:jijerp:v:20:y:2023:i:2:p:1150-:d:1029443
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    References listed on IDEAS

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