Now showing items 1-7 of 7

    • Context for maritime situation awareness 

      Jousselme, Anne-Laure; Bryan, Karna (CMRE, 2019/06)
      Effective maritime situation awareness (MSA) relies on high-level information fusion tasks that benefit from a formal approach to context-based reasoning. This chapter discusses the relative notion of context through the ...
    • Data-driven detection and context-based classification of maritime anomalies 

      Pallotta, Giuliana; Jousselme, Anne-Laure (CMRE, 2019/06)
      Discovering anomalies at sea is one of the critical tasks of Maritime Situational Awareness (MSA) activities and an important enabler for maritime security operations. This paper proposes a data-driven approach to anomaly ...
    • A distributed approach to estimating sea port operational regions from lots of AIS data 

      Millefiori, Leonardo; Zissis, Dimitrios; Cazzanti, Luca; Arcieri, Gianfranco (CMRE, 2019/06)
      Seaports play a vital role in the global economy, as they operate as the connection corridors to all other modes of transport and as engines of growth for the wider region. But ports today are faced with numerous unique ...
    • Mining maritime vessel traffic: promises, challenges, techniques 

      Cazzanti, Luca; Pallotta, Giuliana (CMRE, 2019/06)
      This paper discusses machine learning and data mining approaches to analyzing maritime vessel traffic based on the Automated Information System (AIS). We review recent efforts to apply machine learning techniques to AIS ...
    • Multiple Ornstein-Uhlenbeck processes for maritime traffic graph representation 

      Coscia, Pasquale; Braca, Paolo; Millefiori, Leonardo; Palmieri, Francesco A. N.; Willett, Peter K. (CMRE, 2019/05)
      We propose an unsupervised procedure to automatically extract a graph-based model of commercial maritime traffic routes from historical Automatic Identification System (AIS) data. In the proposed representation, the main ...
    • Scalable and distributed sea port operational areas estimation from AIS data 

      Millefiori, Leonardo; Zissis, Dimitrios; Cazzanti, Luca; Arcieri, Gianfranco (CMRE, 2019/06)
      Seaports are spatial units that do not remain static over time. They are constantly in flux, evolving according to environmental and connectivity patterns both in size and operational capacity. As such any valid decision ...
    • Vessel pattern knowledge discovery from AIS data: a framework for anomaly detection and route prediction 

      Pallotta, Giuliana; Vespe, Michele; Bryan, Karna (CMRE, 2014/01)
      Understanding maritime traffic patterns is key to Maritime Situational Awareness applications, in particular, to classify and predict activities. Facilitated by the recent build-up of terrestrial networks and satellite ...