Real-Time Maritime Traffic Anomaly Detection Based on Sensors and History Data Embedding

The automated identification system of vessel movements receives a huge amount of multivariate, heterogeneous sensor data, which should be analyzed to make a proper and timely decision on vessel movements. The large number of vessels makes it difficult and time-consuming to detect abnormalities, thu...

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Detalles Bibliográficos
Autores principales: Venskus, Julius, Treigys, Povilas, Bernatavičienė, Jolita, Tamulevičius, Gintautas, Medvedev, Viktor
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749247/
https://www.ncbi.nlm.nih.gov/pubmed/31480449
http://dx.doi.org/10.3390/s19173782

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749247/
https://www.ncbi.nlm.nih.gov/pubmed/31480449
http://dx.doi.org/10.3390/s19173782

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