为充分探索船舶自动识别系统大数据在统计决策和安全监管方面的应用价值，系统性地提出了船舶AIS大数据资源管理与分析应用架构。首先，根据船舶AIS大数据特点，设计了船舶AIS大数据处理流程和存储策略，为后续高效计算提供支撑；然后，提出并实现了基于船舶AIS大数据的船舶轨迹重建算法、断面船舶流量统计算法、船舶进出港区识别算法、船舶航行状态分析算法四种基础算法；最后，基于上述计算方法，将船舶AIS大数据应用于断面流量统计、船舶规范使用船载AIS设备行为监控以及船舶规范执行进出港报告情况监控等场景，结果表明船舶AIS数据在统计决策和安全监管方面具有一定的应用价值。
Abstract
In order to fully explore the value of ship Automatic Identification System (AIS) big data in terms of statistical analysis and maritime supervision, the ship AIS big data management, analysis and application architecture was systematically proposed. Firstly, according to the characteristics of ship AIS big data, the processing flow and storage strategy of ship AIS big data were designed in order to support the following high efficient computation. Secondly, four basic algorithms based on ship AIS big data were proposed and realized, including ship trajectory reconstruction, section ship flow statistics, identification of ship entering and leaving the port, and ship navigation status judgement. Finally, on the basis of the four basic algorithms, ship AIS big data was applied to several scenes, including the section ship flow statistics, behavior supervision of ship normally using ship AIS equipment, behavior supervision of ship reporting its entering and leaving the port and so on. The application results show that ship AIS big data is valuable in terms of statistical analysis and maritime supervision to some extent.
关键词
船舶自动识别系统 /
大数据 /
架构设计 /
船舶流量统计 /
海事监管
Key words
ship Automatic Identification System (AIS) /
big data /
architecture design /
ship flow statistics /
statistical analysis
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