Mining port operation information from AIS data

Jussi Steenari (Corresponding author), Lucy Lwakatare, Jukka K. Nurminen, Jaakko Talonen, Teemu Manderbacka

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 Sep 2022
MoE publication typeA4 Article in a conference publication
Event16th Hamburg International Conference of Logistics (HICL) 2022 - online - Online
Duration: 21 Sep 202223 Sep 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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