Identifying and Combating Unlawful Fishing Activities: A Classification-Based Approach

Illegal, unreported, and unregulated (IUU) fishing has become a very profitable business, with nearly $23.5 billion worth of fish stolen from the world’s oceans. Every year business grows efficiently, Illegal is one big back steps in this business. Furthermore, many populations are pushed to extinction. This paper proposes illegal detection using data analytics machine learning techniques. The primary was gathered Global Fishing Watch (GFW) analyzed find whether vessels used for or legal based on sensors attached vessel GFW found location data, type vessel, speed vessel. Even available trying solve problem globally difficult task. By these classification models (Logistic Regression, SVM, KNN, Naïve Bayes, XG Boost, Decision Tree, Random Forest Classifier), we can predict take necessary actions against boats.