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Opportunities and Challenges in Relation to Big Data Analytics for the Shipping and Port Industries

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Smart Ports and Robotic Systems

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Abstract

The so-called “Fourth (stage of the) Industrial Revolution,” also termed as “Industry 4.0” in the wider literature, is associated with cutting-edge technology applications like Artificial Intelligence (AI), Big Data Analytics (BDA), Cloud Computing, and Internet of Things (IoT), which are already influencing the paradigm of operations within the shipping and port industries. Today, all computer systems on-board a ship or supporting facilities ashore, as well as the numerous information technology (IT) applications related to ship and port management activities are heavily reliant upon real-time data to effectively fulfill their allocated tasks. Truly vast quantities of data, commonly referred to as “Big Data” (BD), are created; the issue of how to effectively manage all the associated information is clearly standing out. Using software tools for extracting and processing the “right” information and deploying advanced algorithms to perform the relevant statistical analysis, becomes the obvious solution. This chapter, which follows a qualitative approach along with a Strengths, Weaknesses, Opportunities and Challenges (SWOC) analysis matrix, is aiming to identify and briefly discuss the most relevant tools and techniques that are associated with BDA. It will also highlight the need for effective BD management, in order to fully exploit the opportunity of improving—or even optimizing—the conduct of maritime transport activities and port operations.

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Authors and Affiliations

  1. Maritime Safety and Environmental Administration, World Maritime University, Malmo, Sweden

    Dimitrios Dalaklis

  2. Department of Shipping, Trade and Transport, University of the Aegean, Chios, Hellas, Greece

    Nikitas Nikitakos & Dimitrios Papachristos

  3. National and Kapodistrian University of Athens, Athens, Greece

    Dimitrios Papachristos

  4. Henley Business School, University of Reading, Reading, UK

    Angelos Dalaklis

Authors
  1. Dimitrios Dalaklis
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  2. Nikitas Nikitakos
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  3. Dimitrios Papachristos
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  4. Angelos Dalaklis
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Corresponding author

Correspondence to Dimitrios Dalaklis .

Editor information

Editors and Affiliations

  1. WMU-Sasakawa-Global Ocean Institute, World Maritime University, Malmö, Skåne Län, Sweden

    Tafsir Matin Johansson

  2. World Maritime University, Malmö, Sweden

    Dimitrios Dalaklis

  3. The City Law School, City, University of London, London, UK

    Jonatan Echebarria Fernández

  4. WMU-Sasakawa-Global Ocean Institute, World Maritime University, Malmö, Sweden

    Aspasia Pastra

  5. University of Aberdeen, Aberdeen, UK

    Mitchell Lennan

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Dalaklis, D., Nikitakos, N., Papachristos, D., Dalaklis, A. (2023). Opportunities and Challenges in Relation to Big Data Analytics for the Shipping and Port Industries. In: Johansson, T.M., Dalaklis, D., Fernández, J.E., Pastra, A., Lennan, M. (eds) Smart Ports and Robotic Systems . Studies in National Governance and Emerging Technologies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-031-25296-9_14

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