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Increasing maritime situation awareness via trajectory detection, enrichment and recognition of events

: Vouros, G.A.; Vlachou, A.; Santipantakis, G.; Doulkeridis, C.; Pelekis, N.; Georgiou, H.; Theodoridis, Y.; Patroumpas, K.; Alevizos, E.; Artikis, A.; Fuchs, G.; Mock, M.; Andrienko, G.; Andrienko, N.; Claramunt, C.; Ray, C.; Camossi, E.; Jousselme, A.-L.


Luaces, M.R.:
Web and wireless geographical information systems : 16h International Symposium, W2GIS 2018. Proceedings : A Coruña, May 21-22, 2018
Cham: Springer International Publishing, 2018 (Lecture Notes in Computer Science 10819)
ISBN: 978-3-319-90052-0 (Print)
ISBN: 978-3-319-90053-7 (Online)
International Symposium on Web and Wireless Geographical Information Systems (W2GIS) <16, 2018, A Coruña>
Fraunhofer IAIS ()

The research presented in this paper aims to show the deployment and use of advanced technologies towards processing surveillance data for the detection of events, contributing to maritime situation awareness via trajectories’ detection, synopses generation and semantic enrichment of trajectories. We first introduce the context of the maritime domain and then the main principles of the big data architecture developed so far within the European funded H2020 datAcron project. From the integration of large maritime trajectory datasets, to the generation of synopses and the detection of events, the main functions of the datAcron architecture are developed and discussed. The potential for detection and forecasting of complex events at sea is illustrated by preliminary experimental results.