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Spatiotemporal Data Analytics for the Maritime Industry

In: Maritime Informatics

Author

Listed:
  • Patrick Schmitt

    (BearingPoint GmbH)

  • Marcin Lukasz Bartosiak

    (Università di Pavia)

  • Torbjörn Rydbergh

    (Marine Benchmark)

Abstract

Having the right information at the right time is a key ingredient to creating value for any business, and the maritime industry is no different. From optimising vessels routes and preparing ports for efficient operations to reducing pollution and saving the environment, data analytics makes a difference for various maritime industry stakeholders. With the streams of digital data coming from pervasive sensors and transmitters, it is possible to track the position of almost any object in space and time, thus, supporting situational awareness to improve efficiency of sea operations. Spatiotemporal data merges both geospatial and temporal data points, which make it particularly useful in the maritime context but also challenging from the analytical point of view. This chapter presents the state of the art in spatiotemporal analytics and provides an overview of its practical applications in the maritime industry. The described scenarios are (1) long-term route planning, (2) environment preservation, (3) collision avoidance, (4) cargo tracking and (5) port call optimisation.

Suggested Citation

  • Patrick Schmitt & Marcin Lukasz Bartosiak & Torbjörn Rydbergh, 2021. "Spatiotemporal Data Analytics for the Maritime Industry," Progress in IS, in: Mikael Lind & Michalis Michaelides & Robert Ward & Richard T. Watson (ed.), Maritime Informatics, pages 335-353, Springer.
    • Handle: RePEc:spr:prochp:978-3-030-50892-0_20
    DOI: 10.1007/978-3-030-50892-0_20
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