论文标题
通过渔船的跟踪数据中的异常来识别可疑行为
Identification of suspicious behaviour through anomalies in the tracking data of fishing vessels
论文作者
论文摘要
自动定位设备可以生成大型数据集,其中包含有关人类,动物和物体运动的信息,从而揭示运动模式,热点和重叠。此信息是在清除不同本质错误的数据后获得的。但是,在附属于船舶的自动信息系统(AIS)的情况下,这些错误可能来自对电子设备的故意操纵。因此,对异常的分析可以提供有关可疑行为的宝贵信息。在这里,我们分析了使用自动识别系统获得的渔船轨迹的异常。沉默异常的地图,那些在缺乏定位数据的24小时以上发生的情况表明,它们发生的可能更接近土地,观察到94.9%的异常,距离海岸不到100公里。这种行为暗示了将沉默异常识别为非法活动的代理的潜力。随着船舶高分辨率定位的可用性增加以及强大的统计分析工具的开发,我们提供了自动检测非法活动的提示,这些活动可能有助于优化监视,控制和监视措施。
Automated positioning devices can generate large datasets with information on the movement of humans, animals and objects, revealing patterns of movement, hot spots and overlaps among others. This information is obtained after cleaning the data from errors of different natures. However, in the case of Automated Information Systems (AIS), attached to vessels, these errors can come from intentional manipulation of the electronic device. Thus, the analysis of anomalies can provide valuable information on suspicious behaviour. Here, we analyse anomalies of fishing vessel trajectories obtained with the Automatic Identification System. The map of silence anomalies, those occurring when positioning data is absent for more than 24 h, shows that they occur more likely closer to land, observing 94.9% of the anomalies at less than 100 km from the shore. This behaviour suggests the potential of identifying silence anomalies as a proxy for illegal activities. With the increasing availability of high-resolution positioning of vessels and the development of powerful statistical analytical tools, we provide hints on the automatic detection of illegal activities that may help optimise monitoring, control and surveillance measures.