Artificial intelligence for modeling and reducing microplastic in marine environments: A review of current evidence

Marine microplastic pollution presents a critical environmental challenge, affecting ecosystems, wildlife, and human health as millions of tons of plastic waste enter oceans each year. Microplastics, due to their small size, are difficult to detect and accumulate widely in marine environments, where they integrate into the food web. Artificial Intelligence (AI) offers promising advancements for modeling, detecting, and mitigating the effects of microplastics in marine ecosystems. This narrative review examines recent developments in AI applications for addressing microplastic pollution. The review focuses on AI-driven modeling for predicting microplastic flows, intelligent waste detection systems that utilize remote sensing and autonomous robotics, and AI-based interventions aimed at reducing microplastic release. AI-driven models enhance the accuracy of predicting microplastic accumulation zones, supporting targeted clean-up efforts and informed policy-making. Advanced detection systems provide real-time monitoring over extensive areas, while AI-based filtration and material innovation technologies help reduce microplastic pollution at the source. AI holds significant potential to mitigate marine microplastic pollution, yet challenges such as data availability, model refinement, and global collaboration remain. Future research should focus on enhancing AI models, refining detection systems, and encouraging international data-sharing and cooperation. Collaboration across sectors is essential to fully leverage AI's potential in safeguarding marine ecosystems from microplastic pollution.