A Formal and Visual Data-Mining Model for Complex Ship Behaviors and Patterns
The successful emergence of real-time positioning systems in the maritime domain has favored the development of data infrastructures that provide valuable monitoring and decision-aided systems. However, there is still a need for the development of data mining approaches oriented to the detection of...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/14/5281 |
| _version_ | 1797443846044385280 |
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| author | Yongfeng Suo Yuxiang Ji Zhenye Zhang Jinhai Chen Christophe Claramunt |
| author_facet | Yongfeng Suo Yuxiang Ji Zhenye Zhang Jinhai Chen Christophe Claramunt |
| author_sort | Yongfeng Suo |
| collection | DOAJ |
| description | The successful emergence of real-time positioning systems in the maritime domain has favored the development of data infrastructures that provide valuable monitoring and decision-aided systems. However, there is still a need for the development of data mining approaches oriented to the detection of specific patterns such as unusual ship behaviors and collision risks. This research introduces a CSBP (complex ship behavioral pattern) mining model aiming at the detection of ship patterns. The modeling approach first integrates ship trajectories from automatic identification system (AIS) historical data, then categorizes different vessels’ navigation behaviors, and introduces a visual-oriented framework to characterize and highlight such patterns. The potential of the model is illustrated by a case study applied to the Jiangsu and Zhejiang waters in China. The results show that the CSBP mining model can highlight complex ships’ behavioral patterns over long periods, thus providing a valuable environment for supporting ship traffic management and preventing maritime accidents. |
| first_indexed | 2024-03-09T13:02:58Z |
| format | Article |
| id | doaj.art-937e1402a7ac4ee0b03e17887c272fce |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T13:02:58Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-937e1402a7ac4ee0b03e17887c272fce2023-11-30T21:51:46ZengMDPI AGSensors1424-82202022-07-012214528110.3390/s22145281A Formal and Visual Data-Mining Model for Complex Ship Behaviors and PatternsYongfeng Suo0Yuxiang Ji1Zhenye Zhang2Jinhai Chen3Christophe Claramunt4Navigation College, Jimei University, Xiamen 361021, ChinaNavigation College, Jimei University, Xiamen 361021, ChinaNavigation College, Jimei University, Xiamen 361021, ChinaNavigation College, Jimei University, Xiamen 361021, ChinaNaval Academy Research Institute, 29240 Brest, FranceThe successful emergence of real-time positioning systems in the maritime domain has favored the development of data infrastructures that provide valuable monitoring and decision-aided systems. However, there is still a need for the development of data mining approaches oriented to the detection of specific patterns such as unusual ship behaviors and collision risks. This research introduces a CSBP (complex ship behavioral pattern) mining model aiming at the detection of ship patterns. The modeling approach first integrates ship trajectories from automatic identification system (AIS) historical data, then categorizes different vessels’ navigation behaviors, and introduces a visual-oriented framework to characterize and highlight such patterns. The potential of the model is illustrated by a case study applied to the Jiangsu and Zhejiang waters in China. The results show that the CSBP mining model can highlight complex ships’ behavioral patterns over long periods, thus providing a valuable environment for supporting ship traffic management and preventing maritime accidents.https://www.mdpi.com/1424-8220/22/14/5281complex behavioral patternCSBP miningAIS dataspatiotemporal analysis |
| spellingShingle | Yongfeng Suo Yuxiang Ji Zhenye Zhang Jinhai Chen Christophe Claramunt A Formal and Visual Data-Mining Model for Complex Ship Behaviors and Patterns Sensors complex behavioral pattern CSBP mining AIS data spatiotemporal analysis |
| title | A Formal and Visual Data-Mining Model for Complex Ship Behaviors and Patterns |
| title_full | A Formal and Visual Data-Mining Model for Complex Ship Behaviors and Patterns |
| title_fullStr | A Formal and Visual Data-Mining Model for Complex Ship Behaviors and Patterns |
| title_full_unstemmed | A Formal and Visual Data-Mining Model for Complex Ship Behaviors and Patterns |
| title_short | A Formal and Visual Data-Mining Model for Complex Ship Behaviors and Patterns |
| title_sort | formal and visual data mining model for complex ship behaviors and patterns |
| topic | complex behavioral pattern CSBP mining AIS data spatiotemporal analysis |
| url | https://www.mdpi.com/1424-8220/22/14/5281 |
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