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    Item type:Publication, Access status: with files ,
    Mining port operation information from AIS data
    (epubli, 2022-09)
    Steenari, Jussi
    ;
    Lwakatare, Lucy Ellen
    ;
    Nurminen, Jukka K.
    ;
    Talonen, Jaakko
    ;
    Manderbacka, Teemu
    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.
    Publicationtype: Conference Paper
      104  371
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    Item type:Publication, Access status: with files ,
    A peer-to-peer platform for decentralized logistics
    (epubli, 2017-10)
    Gallay, Olivier
    ;
    Korpela, Kari
    ;
    Tapio, Niemi
    ;
    Nurminen, Jukka K.
    We introduce a novel platform for decentralized logistics, the aim of which is to magnify and accelerate the impact offered by the integration of the most recent advances in Information and Communication Technologies (ICTs) to multi-modal freight operations. The essence of our peer-to-peer (P2P) framework distributes the management of the logistics operations to the multiple actors according to their available computational resources. As a result, this new approach prevents the dominant players from capturing the market, ensures equal opportunities for different size actors, and avoids vendor lock-in. The latest ICTs such as Industrial Data Space (IDS), Blockchain, and Internet-of-Things (IoT) are used as basic building blocks which, together, enable the creation of a trusted and integrated platform to manage logistics operations in a fully decentralized way. While IDS technology allows for secured data exchange between the different parties in the logistics chain, Blockchain technology handles transaction history and agreements between parties in a decentralized way. IoT enables the gathering of real-time data over the logistics network, which can be securely exchanged between the different parties and used for managing the decision-making related to the control of the freight transportation activities. The practicability and the potential of the proposed platform is demonstrated with two use cases, involving various actors in the logistics chains.
    Publicationtype: Conference Paper
      2602  3710