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Vessel Profile Indicators using Fuzzy Logic Reasoning and AIS

Authors:
Konstantinos Chatzikokolakis
Dimitrios Zissis
Giannis Spiliopoulos

Keywords: AIS; Maritime Domain Awareness; Anomaly Detection; Fuzzy Logic System.

Abstract:
Early vessel profiling and risk assessment is a critical component of advanced maritime tracking systems, required by a number of maritime stakeholders including custom controls, port authorities, coastguards and others. This paper reports on the development of a fuzzy logic reasoning tool for generating maritime vessel profile indicators through the Automatic Identification System (AIS). The report describes the need and the underlying statistical methods applied, which are based on Fuzzy Logic Reasoning, for finding potential profile indicators and classifying vessels to a degree of “risk”, thus requiring further examination and monitoring. Under conservative assumptions, some preliminary results about the probabilities and boundaries of potential indicators are presented and discussed.

Pages: 95 to 100

Copyright: Copyright (c) IARIA, 2018

Publication date: November 18, 2018

Published in: conference

ISSN: 2308-4278

ISBN: 978-1-61208-676-7

Location: Athens, Greece

Dates: from November 18, 2018 to November 22, 2018