Pregledni rad

Machine Learning Approaches to Maritime Anomaly Detection

Ines Obradović orcid.org/0000-0001-6035-0641 ; Sveučilište u Dubrovniku
Mario Miličević orcid.org/0000-0002-8877-4689 ; Sveučilište u Dubrovniku
Krunoslav Žubrinić ; Sveučilište u Dubrovniku

Sažetak

Topics related to safety in maritime transport have become very important over the past decades due to numerous maritime problems putting both human lives and the environment in danger. Recent advances in surveillance technology and the need for better sea traffic protection led to development of automated solutions for detecting anomalies. These solutions are based on generating normality models from data gathered on vessel movement, mostly from AIS. This paper provides a presentation of various machine learning approaches for anomaly detection in the maritime domain. It also addresses potential problems and challenges that could get in the way of successful automation of such systems.

Ključne riječi

maritime traffic; anomaly detection; situational awareness; machine learning; AIS

Hrčak ID:

130339

URI

https://hrcak.srce.hr/130339

Datum izdavanja:

9.12.2014.

Posjeta: 2.632 *