Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/140040
Title: | Exploiting AIS data for intelligent maritime navigation : a comprehensive survey from data to methodology | Authors: | Tu, Enmei Zhang, Guanghao Rachmawati, Lily Rajabally, Eshan Huang, Guang-Bin |
Keywords: | Engineering::Electrical and electronic engineering | Issue Date: | 2017 | Source: | Tu, E., Zhang, G., Rachmawati, L., Rajabally, E., & Huang, G.-B. (2018). Exploiting AIS data for intelligent maritime navigation : a comprehensive survey from data to methodology. IEEE Transactions on Intelligent Transportation Systems, 19(5), 1559-1582. doi:10.1109/TITS.2017.2724551 | Journal: | IEEE Transactions on Intelligent Transportation Systems | Abstract: | 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. | URI: | https://hdl.handle.net/10356/140040 | ISSN: | 1524-9050 | DOI: | 10.1109/TITS.2017.2724551 | Schools: | School of Electrical and Electronic Engineering | Organisations: | Rolls-Royce@NTU Corporate Lab | Rights: | © 2017 IEEE. All rights reserved. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | EEE Journal Articles |
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