INSTRUCTOR: A Tool for Analyzing Anomalous Ship Trajectories Using Clustering Algorithms

• Cláudio V. Ribeiro Fluminense Federal University
• Aline Paes Fluminense Federal University
• Daniel de Oliveira Fluminense Federal University

DOI: https://doi.org/10.5753/sbbd_estendido.2023.233222

Abstract

Thousands of vessels circulate daily and the number of incidents is significant, and such occurrences are associated with trajectories considered anomalous. The agents responsible for maritime surveillance need to be supported by visual analysis of the situation to indicate these occurrences, especially in advance. In this article, we present the INSTRUCTOR tool, which allows the visual analysis of anomalous vessel trajectories using multiple clustering algorithms (e.g. DBSCAN, K-Means, Birch, Spectral Clustering and Ensembles). The INSTRUCTOR can be obtained at GitHub repository and has been evaluated by experts from the Brazilian Navy through specific questionnaires with a test script.

Keywords: Data clustering, Trajectory detection

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