Top

Information Systems Frontiers

Published in:

01-08-2016

A complex event processing approach to detect abnormal behaviours in the marine environment

Authors: Fernando Terroso-Saenz, Mercedes Valdes-Vela, Antonio F. Skarmeta-Gomez

Published in: Information Systems Frontiers | Issue 4/2016

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Over the last years, many data-sources have become available to monitor the marine traffic. This has motivated the development of support systems to automatically detect vessels’ behaviours of interest. The present work states a novel approach in this domain following the Complex Event Processing (CEP) paradigm. As a proof of concept, a CEP-based system has been developed to timely detect a set of vessel’s abnormal behaviours by performing an event-based processing of Automatic Identification System data. Experiments based on real-world and synthetic data proved the suitability and feasibility of the proposal.

previous article A formulation of computational trust based on quantum decision theory

next article CHOOSE: Towards a metamodel for enterprise architecture in small and medium-sized enterprises

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

http://vesseltracker.com

Bomberger, N., Rhodes, B., Seibert, M., & Waxman, A. (2006). Associative learning of vessel motion patterns for maritime situation awareness. Information Fusion, 2006 9th International Conference on, 1–8.

Brinkhoff, T. (2002). A framework for generating network-based moving objects. Geoinformatica, 6(2), 153–180.CrossRef

Cugola, G., & Margara, A. (2012). Processing flows of information: From data stream to complex event processing. ACM Computing Surveys, 44(3), 15:1–15:62.CrossRef

Espertech (2013). Esper reference documentation, version 4.9.

Etzion, O., & Niblett, P. (2010). Event processing in action: Manning Publications.

Evensen, P., & Meling, H. (2012). AdScorer: an event-based system for near real-time impact analysis of television advertisements. In Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems; DEBS ’12 (pp. 85–94). New York, NY, USA: ACM.

Garagic, D., Rhodes, B. J., Bomberger, N. A., & Zandipour, M. (2009). Adaptive mixture-based neural network approach for higher-level fusion and automated behavior monitoring. In Communications, 2009. ICC’09, IEEE International Conference on (pp. 1–6) IEEE.

Guting, R. H., & Schneider, M. (2005). Moving object databases: Morgan Kaufmann Publishers.

Idiri, B., & Napoli, A (2012). The automatic identification system of maritime accident risk using rule-based reasoning. In System of Systems Engineering (SoSE), 2012 7th International Conference on (pp. 125–130): IEEE.

Kowalska, K., & Peel, L. (2012). Maritime anomaly detection using gaussian process active learning. In Information Fusion (FUSION), 2012 15th International Conference on (pp. 1164–1171): IEEE.

Kruger, M., Ziegler, J., & Heller, K (2012). A generic bayesian network for identification and assessment of objects in maritime surveillance. In Information Fusion (FUSION), 2012 15th International Conference on (pp. 2309–2316) IEEE.

Lane, R. O., Nevell, D. A., Hayward, S. D., & Beaney, T. W. (2010). Maritime anomaly detection and threat assessment. In Information Fusion (FUSION), 2010 13th Conference on (pp. 1–8): IEEE.

Luckham, D. (2011). Event processing for business: organizing the real-time enterprise. Wiley & Sons.

Mascaro, S., Korb, K. B., & Nicholson, A. E. (2010). Learning abnormal vessel behaviour from ais data with bayesian networks at two time scales: Tracks A Journal Of Artists Writings.

Meister, S. (2012) In Niedrite, L., Strazdina, R., & Wangler, B. (Eds.), Telemedical Events: Intelligent Delivery of Telemedical Values Using CEP and HL7 (Vol. 106 of Lecture Notes in Business Information Processing, pp. 1–13). Berlin: Springer.

Navigation Center-United States Coast Guard (2013). AIS messages.

Nuutinen, M., Savioja, P., & Sonninen, S. (2007). Challenges of developing the complex socio-technical system: realising the present, acknowledging the past, and envisaging the future of vessel traffic services. Applied Ergonomics, 38(5), 513– 24.CrossRef

Patiniotakis, I., Papageorgiou, N., Verginadis, Y., Apostolou, D., & Mentzas, G. (2013). Dynamic event subscriptions in distributed event based architectures. Expert Systems with Applications, 40(6), 1935–1946.CrossRef

Ristic, B., La Scala, B., Morelande, M., & Gordon, N (2008). Statistical analysis of motion patterns in AIS data: Anomaly detection and motion prediction. In Information Fusion, 2008 11th International Conference on (pp. 1–7) IEEE.

Roy, J. (2008). Anomaly detection in the maritime domain Vol. 6945. 69450W–69450W–14.

Roy, J. (2010). Rule-based expert system for maritime anomaly detection. In Proceedings of SPIE-The International Society for Optical Engineering, USA. 76662N–1, Vol. 7666.

Roy, J., & Davenport, M. (2009). Categorization of maritime anomalies for notification and alerting purpose. In NATO Workshop on Data Fusion and Anomaly Detection for Maritime Situational Awareness (pp. 15–17).

Terroso-Saenz, F., Valdes-Vela, M., Campuzano, F., Botia, J., & Skarmeta-Gomez, A. F. (2012). A complex event processing approach to perceive the vehicular context. Information Fusion, 0.

Terroso-Saenz, F., Valdes-Vela, M., Sotomayor-Martinez, C., Toledo-Moreo, R., & Gómez-Skarmeta, A. (2012). A cooperative approach to traffic congestion detection with complex event processing and VANET. IEEE Transactions on Intelligent Transportation Systems, 13(2), 914–929.CrossRef

Valdés-Vela, M., & Gomez-Skarmeta, A. F. (2010). Unified management of heterogeneous sensor for complex event processing. In Proceedings of the 4th International Symposium of Ubiq. Comp. & Amb. Intell.

van Laere, J., & Nilsson, M (2009). Evaluation of a workshop to capture knowledge from subject matter experts in maritime surveillance. In Information Fusion, 2009. FUSION’09, 12th International Conference on (pp. 171–178): IEEE.

Verginadis, Y., Papageorgiou, N., Patiniotakis, I., Apostolou, D., & Mentzas, G. (2012). A goal driven dynamic event subscription approach. In Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems; DEBS ’12 (pp. 81–84). New York, NY, USA: ACM.

Vespe, M., Visentini, I., Bryan, K., & Braca, P. (2012). Unsupervised learning of maritime traffic patterns for anomaly detection. In Data Fusion Target Tracking Conference (DF TT 2012): Algorithms Applications, 9th IET (pp. 1–5).

Will, J., Peel, L., & Claxton, C. (2011). Fast maritime anomaly detection using kd-tree gaussian processes: IMA Maths in Defence Conference.

Title: A complex event processing approach to detect abnormal behaviours in the marine environment
Authors: Fernando Terroso-Saenz
Mercedes Valdes-Vela
Antonio F. Skarmeta-Gomez
Publication date: 01-08-2016
Publisher: Springer US
Published in: Information Systems Frontiers / Issue 4/2016
Print ISSN: 1387-3326
Electronic ISSN: 1572-9419
DOI: https://doi.org/10.1007/s10796-015-9560-7

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Other articles of this Issue 4/2016

Guest editorial: web of things

A formulation of computational trust based on quantum decision theory

Semantic catalog of things, services, and data to support a wind data management facility

Assessing the role of IT-enabled process virtualization on green IT adoption

Identity management based on PCA and SVM

Properties that influence business process management maturity and its effect on organizational performance

Premium Partner