Information Mining Technologies to Enable Discovery of Actionable Intelligence to Facilitate Maritime Situational Awareness – I-MINE

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Authors
  1. St-Hilaire, M-O.
  2. Hadzagic, M.
Corporate Authors
Defence R&D Canada - Atlantic, Dartmouth NS (CAN);OODA Technologies Inc., Montreal, QUE. (CAN)
Abstract
Human operators trying to establish individual or collective maritime situational awareness often find themselves overloaded by huge amount of information obtained from multiple and possibly dissimilar sources. This kind of situation has also been identified within Maritime Forces Atlantic (MARLANT) and its supporting activities in the Regional Joint Operations Center (RJOC) East and West and the Marine Security Operations Centres (MSOCs) as its current information infrastructure (e.g. Global Position Warehouse (GPW)) faces a challenge of how to extract/discover valuable knowledge from the available large volumes of maritime traffic information usually stored in large databases. Applying data mining techniques to large sets of maritime traffic data to extract knowledge will facilitate vessel traffic analysis and management for maritime analysts as well as improved decision-making in the maritime domain. Since maritime traffic data differs from the data commonly mined in business domains, the selection of appropriate data mining tools is crucial for meaningful knowledge extraction. This report provides an extensive review and explores potential use of available information/ data mining technologies by maritime analysts to enable discovery of actionable intelligence to facilitate maritime situational awareness. The focus is on open source data mining tools, while the data is restricted to spatio-temporal maritime traffic data such as the Automated Identification System (AIS) da
Keywords
maritime situational awareness;data mining;AIS
Report Number
DRDC-RDDC-2014-C96 — Contract Report
Date of publication
01 Jan 2013
Number of Pages
86
DSTKIM No
CA039576
CANDIS No
800505
Format(s):
Electronic Document(PDF)

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