Abstract
This chapter overviews maritime operational situations and underlying challenges that the automated processing of maritime mobility data would support with the detection of threats and abnormal activities. The maritime use cases and scenarios are geared on fishing activities monitoring, aligning with the European Union Maritime Security Strategy. Six scenarios falling under three use cases are presented together with maritime situational indicators expressing users’ needs when conducting operational tasks. This chapter also presents relevant data sources to be exploited for operational purposes in the maritime domain, and discusses the related big data challenges to be addressed by algorithmic solutions. An integrated dataset of heterogeneous sources for maritime surveillance is finally described, gathering 13 sources. This chapter concludes on the generation of specific datasets to be used for algorithms evaluation and comparison purposes.
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Acknowledgements
This work was supported by the project Big Data Analytics for Time-Critical Mobility Forecasting (datAcron), which has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 687591. The authors would like to thank Christophe Claramunt, Melita Hadzagic, LCdr Eric Reardon, Cdr Mike Ilteris, and Karna Bryan for their participation to the original ideas of the use cases and scenarios and cadets of the French Naval Academy for their participation in the design of scenario datasets.
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Ray, C., Jousselme, AL., Iphar, C., Zocholl, M., Camossi, E., Dréo, R. (2020). Mobility Data: A Perspective from the Maritime Domain. In: Vouros, G., et al. Big Data Analytics for Time-Critical Mobility Forecasting. Springer, Cham. https://doi.org/10.1007/978-3-030-45164-6_1
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DOI: https://doi.org/10.1007/978-3-030-45164-6_1
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