RESUMO
Microplastics have been detected from water and soil systems extensively, with increasing evidence indicating their detrimental impacts on human and animal health. Concerns surrounding microplastic pollution have spurred the development of advanced collection and characterization methods for studying the size, abundance, distribution, chemical composition, and environmental impacts. This paper offers a comprehensive review of artificial intelligence (AI)-empowered technologies for the collection and characterization of microplastics. A framework is presented to streamline efforts in utilizing emerging robotics and machine learning technologies for collecting, processing, and characterizing microplastics. The review encompasses a range of AI technologies, delineating their principles, strengths, limitations, representative applications, and technology readiness levels, facilitating the selection of suitable AI technologies for mitigating microplastic pollution. New opportunities for future research and development on integrating robots and machine learning technologies are discussed to facilitate future efforts for mitigating microplastic pollution and advancing AI technologies.
