Paper Info
Title
Detecting Anomalous Behavior In Sea Traffic: A Study Of Analytical Strategies And Their Implications For Surveillance Systems
Abstract
Surveillance operators normally analyze vast amounts of sensor data in order to find conflict situations, and threatening or unusual activities while allowing the continuous flow of goods and people. Semi-automatic support may reduce the time needed for the detection of such situations, generating early warnings that can prevent accidents or provide time to prepare countermeasures. In order to provide adequate cognitive support for operators and guide the design of more efficient surveillance systems, this paper investigates the human analytical reasoning process of detecting anomalous behavior through a case study, the surveillance of sea areas. The analysis of data gathered during interviews and participant observations at three maritime control centers and the inspection of video recordings of real incidents lead to a characterization of operators' analytical processes. We suggest how to support these processes using data mining and visualization, and we derive recommendations for designers and developers of future maritime control systems.
Year
DOI
Venue
2014
10.1142/S021962201450045X
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
Keywords
Field
DocType
Anomaly detection, analytical reasoning, maritime traffic monitoring, decision making
Countermeasure,Data mining,Anomaly detection,Data analysis,Visualization,Analytic reasoning,Operator (computer programming),Control system,Mathematics,Anomalous behavior
Journal
Volume
Issue
ISSN
13
2
0219-6220
Citations 
PageRank 
References 
1
0.39
43
Authors
2
Name
Order
Citations
PageRank
Maria Riveiro113318.64
Göran Falkman217322.13