Mining port operation information from AIS data

Jussi Steenari*, Lucy Lwakatare, Jukka K. Nurminen, Jaakko Talonen, Teemu Manderbacka

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    Abstract

    Purpose: Ports play a vital role in global trade and commerce. While there is an abundance of analytical studies related to ship operations, less work is available about port operations and infrastructure. Information about them can be complicated and expensive to acquire, especially when done manually. We use an analytical machine learning approach on Automatic Identification System (AIS) data to understand how ports operate.

    Methodology: This paper uses the DBSCAN algorithm on AIS data gathered near the Port of Brest, France to detect clusters representing the port’s mooring areas. In addition, exploratory data analyses are per formed on these clusters to gain additional insights into the port infrastructure and operations.

    Findings: From Port of Brest, our experiment results identified seven clusters that had defining characteristics, which allowed them to be identified, for example, as dry docks. The clusters created by our approach appear to be situated in the correct places in the port area when inspected visually.

    Originality: This paper presents a novel approach to detecting potential mooring areas and how to analyse characteristics of the mooring areas. Similar clustering methods have been used to detect anchoring spots, but this study provides a new approach to getting information on the clusters.
    Original languageEnglish
    Title of host publicationProceedings of the Hamburg International Conference of Logistics (HICL)
    EditorsWolfgang Kersten, Carlos Jahn, Thorsten Blecker, Christian M. Ringle
    PublisherEpubli GmbH
    Pages657-678
    Number of pages22
    ISBN (Electronic)978-3-756541-95-9
    DOIs
    Publication statusPublished - 21 Sept 2022
    MoE publication typeA4 Article in a conference publication
    Event16th Hamburg International Conference of Logistics (HICL) 2022 - online - Online
    Duration: 21 Sept 202223 Sept 2022

    Publication series

    SeriesProceedings of the Hamburg International Conference of Logistics (HICL)
    Volume33
    ISSN2635-4430

    Conference

    Conference16th Hamburg International Conference of Logistics (HICL) 2022 - online
    Period21/09/2223/09/22

    Keywords

    • Port Logistics

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