AIS Big Data Framework for Maritime Safety Supervision

摘要

Under the pattern of rapid shipping industry development, the extensive application of the AIS data in maritime safety supervision has created gradually increased space-time data of ship. However, although the shipping industry has a massive amount of data, there are obvious shortcomings in data storage and data mining, which make it difficult to effectively use data to guide maritime safety supervision. In view of this, we build an innovation ‘CIPSODAR’ framework, which covers AIS big data technical stack system on Hadoop cluster, including AIS big data processing, AIS big data storage and query, as well as AIS big data mining. Particularly, in the data mining phase, the OD segmentation algorithm, which enables to dispose the typical ship track problems of maritime safety supervision is proposed and realized. Thus, this research result shows that AIS big data is valuable in terms of maritime safety supervision, after systematically combing AIS big data via ‘CIPSODAR’ framework and using OD segmentation algorithm to deal with AIS big data ship track problems.