The paper is a position statement that reviews unsupervised maritime behavior change detection challenges and suggests applying TICC, without reporting any experiments or results.
Composite Event Recognition for Maritime Monitoring
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abstract
Maritime monitoring systems support safe shipping as they allow for the real-time detection of dangerous, suspicious and illegal vessel activities. We present such a system using the Run-Time Event Calculus, a composite event recognition system with formal, declarative semantics. For effective recognition, we developed a library of maritime patterns in close collaboration with domain experts. We present a thorough evaluation of the system and the patterns both in terms of predictive accuracy and computational efficiency, using real-world datasets of vessel position streams and contextual geographical information.
fields
cs.LG 1years
2019 1verdicts
UNVERDICTED 1representative citing papers
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Unsupervised Behavior Change Detection in Multidimensional Data Streams for Maritime Traffic Monitoring
The paper is a position statement that reviews unsupervised maritime behavior change detection challenges and suggests applying TICC, without reporting any experiments or results.