Exploiting AIS Data for Intelligent Maritime Navigation: A Comprehensive Survey From Data to Methodology
By Enmei Tu, Guanghao Zhang, Lily Rachmawati, Eshan Rajabally, G. Huang. IEEE transactions on intelligent transportation systems (Print), 2016
418 citations recorded by the source corpus.
The automatic identification system (AIS) tracks vessel movement by means of electronic exchange of navigation data between vessels, with onboard transceiver, terrestrial, and/or satellite base stations. The gathered data contain a wealth of information useful for maritime safety, security, and efficiency. Because of the close relationship between data and methodology in marine data mining and the importance of both of them in marine intelligence research, this paper surveys AIS data sources and relevant aspects of navigation in which such data are or could be exploited for safety of seafaring, namely traffic anomaly detection, route estimation, collision prediction, and path planning.
Subfields: Ocean Engineering, Transportation
View Paper: https://www.semanticscholar.org/paper/7f585a7f6bf51606f9cfa80f19ec4720532c4f19
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In Transportation
Citations in the corpus
- How big data enriches maritime research – a critical review of Automatic Identification System (AIS) data applications (2019, methodology): “For instance, Vespe et al. (2016) proposed a method for mapping the fishing footprint at the European level by extracting fishing”