Advancing microplastic pollution management in aquatic environments through artificial intelligence

Abstract

The rising infiltration of microplastics (MPs) into aquatic environments is a complex and alarming threat jeopardizing marine biodiversity, destabilizing entire ecosystems, and endangering human health. Traditional methods for identifying and characterizing microplastics are often manual, requiring significant time and effort due to the small size, diverse shapes, and varying sources of microplastics. By integrating artificial intelligence (AI) with traditional environmental approaches, we can make significant progress in mitigating the influence of microplastics on aquatic ecosystems and health of humans. This review emphasizes the goals, benefits, results, and key insights of emerging robotics and various AI models across three critical areas: collection and sorting of microplastic waste, characterization of microplastic waste to determine its abundance, size and chemical composition and predicting and monitoring microplastic degradation. Several countries and organizations are using AI technologies to address microplastic pollution through innovative projects and supportive policies. The review aims to highlight these successful initiatives focused on monitoring, prevention, and cleanup of microplastics in aquatic environments. Further, challenges and future research opportunities on integrating robotics and AI technologies in mitigating microplastic pollution have also been discussed.

Keywords: Artificial intelligence; Characterization; Degradation; Microplastics; Sorting.