Visualising maritime vessel open data for better situational awareness in ice conditions

被引:2
作者
Jussila, Jari [1 ]
Lehtonen, Timo [2 ]
Laitinen, Jari [2 ]
Makkonen, Markus [3 ]
Frank, Lauri [3 ]
机构
[1] Hame Univ Appl Sci, Hameenlinna, Finland
[2] Solita Plc, Tampere, Finland
[3] Univ Jyvaskyla, Jyvaskyla, Finland
来源
MINDTREK'18: PROCEEDINGS OF THE 22ND INTERNATIONAL ACADEMIC MINDTREK CONFERENCE | 2018年
关键词
Data science; open data; open source; AIS data; maritime vessel; ice conditions; situational awareness; THICKNESS DISTRIBUTION; SYSTEM; AIS;
D O I
10.1145/3275116.3275124
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Situational awareness of maritime vessels in ice conditions is important for the operation of supply chains. In the artic sea areas, the ice conditions pose a major challenge for maritime vessels getting stuck in the ice and being significantly delayed in arrival to harbor. Data science and open data provide new opportunities to overcome these challenges. This paper introduces available open data sources and data visualizations that can be used to develop applications, for example, for detecting maritime vessel collision, predicting estimated time of arrival to harbor, as well as maritime vessel route optimization in ice conditions. The paper begins by introducing available open data sources and existing computational studies on maritime vessels in ice conditions, then presents the developed data science solution and visualizations of the open data along with the open source software code, and finally concludes with a discussion on the potential application areas and opportunities for further research.
引用
收藏
页码:92 / 99
页数:8
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