Abstract
The maritime Automatic Identification System (AIS) data is obtained from many different terrestrial and satellite sources. AIS data enables safety, security, environmental protection and the economic efficiency of the maritime sector. The quality of AIS receivers is not controlled in the same manner as AIS transmitters. This has led to a situation where AIS data is not as clean as it should/could be. Added to this is the lack of accuracy and standards in entering the voyage data by the mariners such as next port of call into the AIS equipment installed on vessels. By using analytics IMIS Global Limited has been able to process the AIS data stream to eliminate a large portion of the faulty data. This has allowed the resultant AIS data to be used for more accurate detailed analysis such as the long-term vessel track, port arrival events and port departure events. New data that is derived from processing AIS data has enhanced the information available to maritime authorities enabling a significant increase in safety, security, environmental protection and economic growth. The next generation of maritime data communications technology being based AIS. This is known as the VHF Data Exchange System (VDES) and this technology now enables further opportunities. The value from the large volumes of AIS data is extracted by visual, streaming, historical and prescriptive data analytics. The datAcron project is showing the way with regards to the processing and use of AIS and resultant trajectory data.
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References
datAcron project. http://www.datacron-project.eu/
ITU-R M.1371-5 specification. http://www.itu.int/rec/R-REC-M.1371-5-201402-I
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Batty, E. (2018). Data Analytics Enables Advanced AIS Applications. In: Doulkeridis, C., Vouros, G., Qu, Q., Wang, S. (eds) Mobility Analytics for Spatio-Temporal and Social Data. MATES 2017. Lecture Notes in Computer Science(), vol 10731. Springer, Cham. https://doi.org/10.1007/978-3-319-73521-4_2
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DOI: https://doi.org/10.1007/978-3-319-73521-4_2
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