Document Open Access Logo

A Stream Reasoning System for Maritime Monitoring

Authors Georgios M. Santipantakis, Akrivi Vlachou, Christos Doulkeridis, Alexander Artikis, Ioannis Kontopoulos, George A. Vouros

PDF
Thumbnail PDF

File

LIPIcs.TIME.2018.20.pdf
  • Filesize: 0.7 MB
  • 17 pages

Document Identifiers

Author Details

Georgios M. Santipantakis
  • University of Piraeus, Karaoli and Dimitriou 80, 18534 Piraeus, Greece
Akrivi Vlachou
  • University of Piraeus, Karaoli and Dimitriou 80, 18534 Piraeus, Greece
Christos Doulkeridis
  • University of Piraeus, Karaoli and Dimitriou 80, 18534 Piraeus, Greece
Alexander Artikis
  • Department of Maritime Studies, University of Piraeus, Greece, Institute of Informatics & Telecommunications, NCSR "Demokritos", Ag. Paraskevi, Greece
Ioannis Kontopoulos
  • Institute of Informatics & Telecommunications, NCSR "Demokritos", Ag. Paraskevi, Greece
George A. Vouros
  • University of Piraeus, Karaoli and Dimitriou 80, 18534 Piraeus, Greece

Cite As Get BibTex

Georgios M. Santipantakis, Akrivi Vlachou, Christos Doulkeridis, Alexander Artikis, Ioannis Kontopoulos, and George A. Vouros. A Stream Reasoning System for Maritime Monitoring. In 25th International Symposium on Temporal Representation and Reasoning (TIME 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 120, pp. 20:1-20:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018) https://doi.org/10.4230/LIPIcs.TIME.2018.20

Abstract

We present a stream reasoning system for monitoring vessel activity in large geographical areas. The system ingests a compressed vessel position stream, and performs online spatio-temporal link discovery to calculate proximity relations between vessels, and topological relations between vessel and static areas. Capitalizing on the discovered relations, a complex activity recognition engine, based on the Event Calculus, performs continuous pattern matching to detect various types of dangerous, suspicious and potentially illegal vessel activity. We evaluate the performance of the system by means of real datasets including kinematic messages from vessels, and demonstrate the effects of the highly efficient spatio-temporal link discovery on performance.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Activity recognition and understanding
Keywords
  • event pattern matching
  • Event Calculus

Metrics

  • Access Statistics
  • Total Accesses (updated on a weekly basis)
    0
    PDF Downloads
    0
    Metadata Views

References

  1. E. Alevizos, A. Skarlatidis, A. Artikis, and G. Paliouras. Probabilistic complex event recognition: A survey. ACM Comput. Surv., 50(5):71:1-71:31, 2017. URL: http://dx.doi.org/10.1145/3117809.
  2. Alexander Artikis and Marek J. Sergot. Executable specification of open multi-agent systems. Logic Journal of the IGPL, 18(1):31-65, 2010. Google Scholar
  3. Alexander Artikis, Marek J. Sergot, and Georgios Paliouras. An event calculus for event recognition. IEEE Trans. Knowl. Data Eng., 27(4):895-908, 2015. Google Scholar
  4. H. Beck, M. Dao-Tran, and T. Eiter. LARS: A Logic-Based Framework for Analytic Reasoning over Streams. Technical Report INFSYS RR-1843-17-03, Institute of Information Systems, TU Vienna, 2017. Google Scholar
  5. Iliano Cervesato and Angelo Montanari. A calculus of macro-events: Progress report. In Proceedings of TIME, pages 47-58, 2000. Google Scholar
  6. L. Chittaro and A. Montanari. Efficient temporal reasoning in the cached event calculus. Computational Intelligence, 12(3):359-382, 1996. Google Scholar
  7. G. Cugola and A. Margara. Processing flows of information: From data stream to complex event processing. ACM Computing Surveys, 44(3):15, 2012. Google Scholar
  8. Gianpaolo Cugola and Alessandro Margara. TESLA: a formally defined event specification language. In Proceedings of DEBS, pages 50-61, 2010. Google Scholar
  9. C. Dousson and P. Le Maigat. Chronicle recognition improvement using temporal focusing and hierarchisation. In Proceedings of IJCAI, pages 324-329, 2007. Google Scholar
  10. Bilal Idiri and Aldo Napoli. The automatic identification system of maritime accident risk using rule-based reasoning. In Proceedings of SoSE, pages 125-130, 2012. Google Scholar
  11. Robert Isele, Anja Jentzsch, and Christian Bizer. Efficient multidimensional blocking for link discovery without losing recall. In Proceedings of WebDB, 2011. Google Scholar
  12. Robert A. Kowalski and Marek J. Sergot. A logic-based calculus of events. New Generation Comput., 4(1):67-95, 1986. Google Scholar
  13. R. Miller and M. Shanahan. Some alternative formulations of the event calculus. In Computational Logic: Logic Programming and Beyond, LNAI 2408, pages 452-490. Springer, 2002. Google Scholar
  14. M. Montali, F. M. Maggi, F. Chesani, P. Mello, and W. M. P. van der Aalst. Monitoring business constraints with the event calculus. ACM TIST, 5(1):17:1-17:30, 2013. Google Scholar
  15. Markus Nentwig, Michael Hartung, Axel-Cyrille Ngonga Ngomo, and Erhard Rahm. A survey of current link discovery frameworks. Semantic Web, 8(3):419-436, 2017. Google Scholar
  16. Axel-Cyrille Ngonga Ngomo. ORCHID - reduction-ratio-optimal computation of geo-spatial distances for link discovery. In Proceedings of ISWC, pages 395-410, 2013. Google Scholar
  17. Axel-Cyrille Ngonga Ngomo and Sören Auer. LIMES - A time-efficient approach for large-scale link discovery on the web of data. In Proceedings of IJCAI, pages 2312-2317, 2011. Google Scholar
  18. A. Paschke. ECA-RuleML: An approach combining ECA rules with temporal interval-based KR event/action logics and transactional update logics. Technical Report 11, Technische Universität München, 2005. Google Scholar
  19. Adrian Paschke and Martin Bichler. Knowledge representation concepts for automated SLA management. Decision Support Systems, 46(1), 2008. Google Scholar
  20. K. Patroumpas, E. Alevizos, A. Artikis, M. Vodas, N. Pelekis, and Y. Theodoridis. Online event recognition from moving vessel trajectories. GeoInformatica, 21(2):389-427, 2017. Google Scholar
  21. T. Przymusinski. On the declarative semantics of stratified deductive databases and logic programs. In Foundations of Deductive Databases and Logic Programming. Morgan, 1987. Google Scholar
  22. Mohamed Ahmed Sherif, Kevin Dreßler, Panayiotis Smeros, and Axel-Cyrille Ngonga Ngomo. Radon - rapid discovery of topological relations. In Proceedings of AAAI, pages 175-181, 2017. Google Scholar
Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2024 Schloss Dagstuhl – LZI GmbH About DROPS Imprint Privacy Contact