Smart IUU Detection: Leveraging AI for Sustainable Fisheries Management

Illegal, Unreported, and Unregulated (IUU) fishing poses significant threats to marine ecosystems, economic stability, and global food security. This paper presents a novel AI-driven IUU tracker that integrates machine learning techniques with advanced maritime monitoring systems to detect and mitigate unauthorized fishing activities. By leveraging satellite data, vessel tracking information, and behavioral pattern analysis, the proposed model identifies suspicious activities with high accuracy and real-time capabilities. This solution not only enhances regulatory enforcement but also supports sustainable fisheries management by addressing a critical global challenge. Experimental results demonstrate the system’s effectiveness in diverse maritime scenarios, paving the way for scalable and reliable IUU mitigation strategies.

Key Words:  IUU Fishing, Machine Learning, Geospatial Analytics, Satellite Imagery, Real-Time Monitoring, AIS Data, Anomaly Detection, Marine Protection, Risk Assessment, Fisheries Management