Marine pollution represents a significant threat to the sustainable use of ocean resources and is increasing globally. Consequently, multidimensional and sustainable ocean governance frameworks have placed growing emphasis on the prevention, reduction, and elimination of marine pollution. In recent years, artificial intelligence (AI) has been increasingly adopted as an effective tool for monitoring, assessing, and managing marine pollution. This review aimed to highlight the role of artificial intelligence in addressing marine pollution. The efforts of scientists in employing and leveraging the advantages of AI to tackle the issue of marine pollution were examined. It was found that AI, supported by machine learning, has been applied to predict, locate, manage, and control marine environmental pollution. Recent research has clearly demonstrated the significant role of AI in advancing marine pollution studies, enhancing analytical accuracy, and fostering sustainable coastal management. These applications can be summarized in several fields, including water quality assessment; monitoring and detecting pollutants such as oil, marine litter and microbial contaminants; predictive modeling; study of emerging pollutants like microplastics (MP); and decision support to assist policymakers with risk evaluations and interventions based on real-time detection or projected scenarios. In conclusion, managing marine pollution with AI faces complexities due to natural factors influencing marine ecosystems. While AI is still in the experimental phase in controlling marine pollution, it holds great promise for addressing this issue despite challenges such as limited expertise and data-related constraints. Advances in algorithms, data collection, and computing power are expected to enhance monitoring and mitigation efforts.
Ghani et al. (Thu,) studied this question.