Port type prediction based on Machine Learning and AIS data analysis - Archive ouverte HAL
Communication Dans Un Congrès Année : 2021

Port type prediction based on Machine Learning and AIS data analysis

Thomas Charrot
  • Fonction : Auteur
Juliette Guégan
  • Fonction : Auteur
Aldo Napoli
Cyril Ray
  • Fonction : Auteur
  • PersonId : 834747

Résumé

The estimated number of main ports and stationary areas in the world account for almost 25,000 and most of themare not well known. Being able to provide the navigator with information such as the type of surrounding ports in his navigation area is therefore of interest. Automatic Identification System data transmitted by ships is a valuable source of information whose potential can be exploited to give further knowledge onthe maritime situation. It is also useful to extract knowledgeabout ports’ activities and types. This paper aims at analysing AIS data using machine learning methods, and more specifically supervised classification to establish a harbour map with the objective of identify port’s type especially for the less documented areas of the globe.
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Dates et versions

hal-03726772 , version 1 (18-07-2022)

Identifiants

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Thomas Charrot, Juliette Guégan, Aldo Napoli, Cyril Ray. Port type prediction based on Machine Learning and AIS data analysis. IEEE/MTS OCEANS 2021, Sep 2021, San Diego, United States. ⟨10.23919/OCEANS44145.2021.9705864⟩. ⟨hal-03726772⟩
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