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Event Processing for Maritime Situational Awareness

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Big Data Analytics for Time-Critical Mobility Forecasting

Abstract

Numerous illegal and dangerous activities take place at sea, including violations of ship emission rules, illegal fishing, illegal discharges of oil and garbage, smuggling, piracy and more. We present our efforts to combine two stream reasoning technologies for detecting such activities in real time: a formal, computational framework for composite maritime event recognition, based on the Event Calculus, and an industry-strong maritime anomaly detection service, capable of processing daily real-world data volumes.

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Acknowledgements

This work was supported by the datACRON and the INFORE projects, which have received funding from the European Union’s Horizon 2020 research and innovation programme, under grant agreements No 687591 and No 825070.

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Correspondence to Alexander Artikis .

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Pitsikalis, M., Bereta, K., Vodas, M., Zissis, D., Artikis, A. (2020). Event Processing for Maritime Situational Awareness . 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_9

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  • DOI: https://doi.org/10.1007/978-3-030-45164-6_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-45163-9

  • Online ISBN: 978-3-030-45164-6

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