Open AccessBig Data for Anomaly Detection in Maritime Surveillance: Spatial AIS Data Analysis for Tankers
Author(s) -
Dominik Filipiak,
Milena Stróżyna,
Krzysztof Węcel,
Witold Abramowicz
Publication year - 2018
Publication title -
zeszyty naukowe akademii marynarki wojennej/zeszyty naukowe - akademia marynarki wojennej im. bohaterów westerplatte
Language(s) - English
Resource type - Journals
eISSN - 2300-5300
pISSN - 0860-889X
DOI - 10.2478/sjpna-2018-0024
Subject(s) - anomaly detection , big data , computer science , volume (thermodynamics) , anomaly (physics) , data mining , condensed matter physics , physics , quantum mechanics
The paper presents results of spatial analysis of huge volume of AIS data with the goal to detect predefined maritime anomalies. The maritime anomalies analysed have been grouped into: traffic analysis, static anomalies, and loitering detection. The analysis was carried out on data describing movement of tankers worldwide in 2015, using sophisticated algorithms and technology capable of handling big data in a fast and efficient manner. The research was conducted as a follow-up of the EDA-funded SIMMO project, which resulted in a maritime surveillance system based on AIS messages enriched with data acquired from open Internet sources.