The automatic identification system of maritime accident risk using rule-based reasoning

Idiri, Bilal; Napoli, Aldo

doi:10.1109/sysose.2012.6384140

Cited by 13 publications

(8 citation statements)

References 5 publications

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“…tuggingSpeed is a simple fluent expressing the intervals during which a vessel is said to be sailing at tugging speed (see Table 3). According to rule (8), two vessels are said to be engaged in tugging if one of them is a tug boat, neither of them is a pilot boat, and, for at least V Tug time-points, they are close to each other and sail at tugging speed.…”

Section: Tuggingmentioning

confidence: 99%

Composite Event Recognition for Maritime Monitoring

Pitsikalis

Artikis

Dreo

et al. 2019

Proceedings of the 13th ACM International Conference on Distributed and Event-Based Systems

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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.

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Section: Tuggingmentioning

confidence: 99%

Composite Event Recognition for Maritime Monitoring

Pitsikalis

Artikis

Dreo

et al. 2019

Proceedings of the 13th ACM International Conference on Distributed and Event-Based Systems

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“…Their model incorporates the position, course, and speed of the ships in each route to identify the collision candidates. Son et al (2012) suggested a fuzzy algorithm to estimate collision risk among multiple ships in Korea using real-time AIS data, while Idiri and Napoli (2012) proposed a rule-based method applied to the movements of ships under changing sea conditions which would give an identification of the risks in real-time and potentially trigger an alarm to help prioritize interventions.…”

Section: Collision and Grounding Risk Assessmentmentioning

confidence: 99%

Past, present, and future of the satellite-based automatic identification system: areas of applications (2004–2016)

Fournier

Hilliard²,

Rezaee

et al. 2018

WMU J Marit Affairs

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In 2016, the world shipping fleet grew by 3.5%. Even if the annual growth rate remains at its lowest since 2013, the global situation is still in overcapacity (UNCTAD 2016). Ninety percent of global trade, by volume, is done by sea. Monitoring this fleet helps with vessel navigation, informing to help avoid critical situations such as collisions, accidents leading to oil pollution, grounding, or ships in distress, but also because traffic management in congested areas is essential. For system wide management, in regions such as MPAs (marine protected areas), conservation is the key factor, and movements can be monitored and analyzed in order to determine illegal or suspicious activities, or in order to limit and/or divert traffic, to mitigate the risks to species subject to protection. It is among these efforts that the automatic identification system (AIS) can play a key role. Since 2004, this VHF transceiver-based reporting system, imposed by the International Maritime Organization (IMO), has shifted from a traditional vessel identification device to a tool used in a wide variety of applications. The most common uses are safety and security; these issues are quite visible in the media and may touch more people on a global scale (e.g., piracy, oil spills). Over the years, AIS has become, especially with the emergence of the satellite-based capture of the signal in 2011, a widely used tool for developing applications such as fisheries monitoring, marine conservation, air pollution forecasting and modeling, ballast water monitoring, invasive species transport, and many more. In this paper, we propose to review the peerreviewed publications related to the uses and applications of the AIS.

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“…CEP component comprises a set of rules and knowledge to detect a predefined group of anomalies on the basis of the receiving event attribute which are the same in [31][32][33]. The rule base specifies how to infer complex events from the event stream.…”

Section: Lida-e Enginementioning

confidence: 99%

A Novel Complex Event Processing Engine for Intelligent Data Analysis in Integrated Information Systems

Wang

Zhou

Ali

et al. 2016

International Journal of Distributed Sensor Networks

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Novel and effective engines for data analysis in integrated information systems are urgently required by diverse applications, in which massive business data can be analyzed to enable the capturing of various situations in real time. The performance of existing engines has limited capacity of data processing in distributed computing. Although Complex Event Processing (CEP) has enhanced the capacity of data analysis in information systems, it is still a big challenging task since events are rapidly increasing in diverse applications. In this paper, a lightweight intelligent data analysis system with a novel CEP engine named LIDA-E is introduced, which employs the knowledge base with rules and an event processing algorithm for analysis. Event models as well as operators support the rules for event selection and aggregation. These operators and rules have been utilized for constructing new CEP system architecture which combines expressiveness and efficiency in analysis. It adopts the agents and filter conception explicitly to provide the event transmission mechanism efficiently. Finally, the comparison between the proposed engine and the existing engine shows that LIDA-E has 48.65% averagely reduced time cost in different tests. The experimental results demonstrate that the developed architecture has better performance in both transmitting and analyzing a large number of events.

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The automatic identification system of maritime accident risk using rule-based reasoning

Abstract: To cite this version:Bilal Idiri, Aldo Napoli. The automatic identification system of maritime accident risk using rulebased reasoning. 7th International Conference on System Of Systems Engineering - IEEE SOSE 2012, Jul 2012, Genoa, Italy. pp.125-130, 2012, <10.1109/SYSoSE.2012

Cited by 13 publications

References 5 publications

Composite Event Recognition for Maritime Monitoring

Composite Event Recognition for Maritime Monitoring

Past, present, and future of the satellite-based automatic identification system: areas of applications (2004–2016)

A Novel Complex Event Processing Engine for Intelligent Data Analysis in Integrated Information Systems

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