The Design and Development of a Ship Trajectory Data Management and Analysis System Based on AIS

To address the data storage, management, analysis, and mining of ship targets, the object-oriented method was employed to design the overall structure and functional modules of a ship trajectory data management and analysis system (STDMAS). This paper elaborates the detailed design and technical inf...
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Autor*in:	Chengxu Feng [verfasserIn] Bing Fu [verfasserIn] Yasong Luo [verfasserIn] Houpu Li [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2021

Schlagwörter:	AIS ship trajectory data analysis system design trajectory classification

Übergeordnetes Werk:	In: Sensors - MDPI AG, 2003, 22(2021), 1, p 310
Übergeordnetes Werk:	volume:22 ; year:2021 ; number:1, p 310

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/s22010310

Katalog-ID:	DOAJ08705048X

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520			\|a To address the data storage, management, analysis, and mining of ship targets, the object-oriented method was employed to design the overall structure and functional modules of a ship trajectory data management and analysis system (STDMAS). This paper elaborates the detailed design and technical information of the system’s logical structure, module composition, physical deployment, and main functional modules such as database management, trajectory analysis, trajectory mining, and situation analysis. A ship identification method based on the motion features was put forward. With the method, ship trajectory was first partitioned into sub-trajectories in various behavioral patterns, and effective motion features were then extracted. Machine learning algorithms were utilized for training and testing to identify many types of ships. STDMAS implements such functions as database management, trajectory analysis, historical situation review, and ship identification and outlier detection based on trajectory classification. STDMAS can satisfy the practical needs for the data management, analysis, and mining of maritime targets because it is easy to apply, maintain, and expand.
650		4	\|a AIS
650		4	\|a ship trajectory
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650		4	\|a trajectory classification
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allfields	10.3390/s22010310 doi (DE-627)DOAJ08705048X (DE-599)DOAJddd995876667471fbb6cb48cd1230608 DE-627 ger DE-627 rakwb eng TP1-1185 Chengxu Feng verfasserin aut The Design and Development of a Ship Trajectory Data Management and Analysis System Based on AIS 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To address the data storage, management, analysis, and mining of ship targets, the object-oriented method was employed to design the overall structure and functional modules of a ship trajectory data management and analysis system (STDMAS). This paper elaborates the detailed design and technical information of the system’s logical structure, module composition, physical deployment, and main functional modules such as database management, trajectory analysis, trajectory mining, and situation analysis. A ship identification method based on the motion features was put forward. With the method, ship trajectory was first partitioned into sub-trajectories in various behavioral patterns, and effective motion features were then extracted. Machine learning algorithms were utilized for training and testing to identify many types of ships. STDMAS implements such functions as database management, trajectory analysis, historical situation review, and ship identification and outlier detection based on trajectory classification. STDMAS can satisfy the practical needs for the data management, analysis, and mining of maritime targets because it is easy to apply, maintain, and expand. AIS ship trajectory data analysis system design trajectory classification Chemical technology Bing Fu verfasserin aut Yasong Luo verfasserin aut Houpu Li verfasserin aut In Sensors MDPI AG, 2003 22(2021), 1, p 310 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:22 year:2021 number:1, p 310 https://doi.org/10.3390/s22010310 kostenfrei https://doaj.org/article/ddd995876667471fbb6cb48cd1230608 kostenfrei https://www.mdpi.com/1424-8220/22/1/310 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2021 1, p 310
spelling	10.3390/s22010310 doi (DE-627)DOAJ08705048X (DE-599)DOAJddd995876667471fbb6cb48cd1230608 DE-627 ger DE-627 rakwb eng TP1-1185 Chengxu Feng verfasserin aut The Design and Development of a Ship Trajectory Data Management and Analysis System Based on AIS 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To address the data storage, management, analysis, and mining of ship targets, the object-oriented method was employed to design the overall structure and functional modules of a ship trajectory data management and analysis system (STDMAS). This paper elaborates the detailed design and technical information of the system’s logical structure, module composition, physical deployment, and main functional modules such as database management, trajectory analysis, trajectory mining, and situation analysis. A ship identification method based on the motion features was put forward. With the method, ship trajectory was first partitioned into sub-trajectories in various behavioral patterns, and effective motion features were then extracted. Machine learning algorithms were utilized for training and testing to identify many types of ships. STDMAS implements such functions as database management, trajectory analysis, historical situation review, and ship identification and outlier detection based on trajectory classification. STDMAS can satisfy the practical needs for the data management, analysis, and mining of maritime targets because it is easy to apply, maintain, and expand. AIS ship trajectory data analysis system design trajectory classification Chemical technology Bing Fu verfasserin aut Yasong Luo verfasserin aut Houpu Li verfasserin aut In Sensors MDPI AG, 2003 22(2021), 1, p 310 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:22 year:2021 number:1, p 310 https://doi.org/10.3390/s22010310 kostenfrei https://doaj.org/article/ddd995876667471fbb6cb48cd1230608 kostenfrei https://www.mdpi.com/1424-8220/22/1/310 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2021 1, p 310
allfields_unstemmed	10.3390/s22010310 doi (DE-627)DOAJ08705048X (DE-599)DOAJddd995876667471fbb6cb48cd1230608 DE-627 ger DE-627 rakwb eng TP1-1185 Chengxu Feng verfasserin aut The Design and Development of a Ship Trajectory Data Management and Analysis System Based on AIS 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To address the data storage, management, analysis, and mining of ship targets, the object-oriented method was employed to design the overall structure and functional modules of a ship trajectory data management and analysis system (STDMAS). This paper elaborates the detailed design and technical information of the system’s logical structure, module composition, physical deployment, and main functional modules such as database management, trajectory analysis, trajectory mining, and situation analysis. A ship identification method based on the motion features was put forward. With the method, ship trajectory was first partitioned into sub-trajectories in various behavioral patterns, and effective motion features were then extracted. Machine learning algorithms were utilized for training and testing to identify many types of ships. STDMAS implements such functions as database management, trajectory analysis, historical situation review, and ship identification and outlier detection based on trajectory classification. STDMAS can satisfy the practical needs for the data management, analysis, and mining of maritime targets because it is easy to apply, maintain, and expand. AIS ship trajectory data analysis system design trajectory classification Chemical technology Bing Fu verfasserin aut Yasong Luo verfasserin aut Houpu Li verfasserin aut In Sensors MDPI AG, 2003 22(2021), 1, p 310 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:22 year:2021 number:1, p 310 https://doi.org/10.3390/s22010310 kostenfrei https://doaj.org/article/ddd995876667471fbb6cb48cd1230608 kostenfrei https://www.mdpi.com/1424-8220/22/1/310 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2021 1, p 310
allfieldsGer	10.3390/s22010310 doi (DE-627)DOAJ08705048X (DE-599)DOAJddd995876667471fbb6cb48cd1230608 DE-627 ger DE-627 rakwb eng TP1-1185 Chengxu Feng verfasserin aut The Design and Development of a Ship Trajectory Data Management and Analysis System Based on AIS 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To address the data storage, management, analysis, and mining of ship targets, the object-oriented method was employed to design the overall structure and functional modules of a ship trajectory data management and analysis system (STDMAS). This paper elaborates the detailed design and technical information of the system’s logical structure, module composition, physical deployment, and main functional modules such as database management, trajectory analysis, trajectory mining, and situation analysis. A ship identification method based on the motion features was put forward. With the method, ship trajectory was first partitioned into sub-trajectories in various behavioral patterns, and effective motion features were then extracted. Machine learning algorithms were utilized for training and testing to identify many types of ships. STDMAS implements such functions as database management, trajectory analysis, historical situation review, and ship identification and outlier detection based on trajectory classification. STDMAS can satisfy the practical needs for the data management, analysis, and mining of maritime targets because it is easy to apply, maintain, and expand. AIS ship trajectory data analysis system design trajectory classification Chemical technology Bing Fu verfasserin aut Yasong Luo verfasserin aut Houpu Li verfasserin aut In Sensors MDPI AG, 2003 22(2021), 1, p 310 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:22 year:2021 number:1, p 310 https://doi.org/10.3390/s22010310 kostenfrei https://doaj.org/article/ddd995876667471fbb6cb48cd1230608 kostenfrei https://www.mdpi.com/1424-8220/22/1/310 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2021 1, p 310
allfieldsSound	10.3390/s22010310 doi (DE-627)DOAJ08705048X (DE-599)DOAJddd995876667471fbb6cb48cd1230608 DE-627 ger DE-627 rakwb eng TP1-1185 Chengxu Feng verfasserin aut The Design and Development of a Ship Trajectory Data Management and Analysis System Based on AIS 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier To address the data storage, management, analysis, and mining of ship targets, the object-oriented method was employed to design the overall structure and functional modules of a ship trajectory data management and analysis system (STDMAS). This paper elaborates the detailed design and technical information of the system’s logical structure, module composition, physical deployment, and main functional modules such as database management, trajectory analysis, trajectory mining, and situation analysis. A ship identification method based on the motion features was put forward. With the method, ship trajectory was first partitioned into sub-trajectories in various behavioral patterns, and effective motion features were then extracted. Machine learning algorithms were utilized for training and testing to identify many types of ships. STDMAS implements such functions as database management, trajectory analysis, historical situation review, and ship identification and outlier detection based on trajectory classification. STDMAS can satisfy the practical needs for the data management, analysis, and mining of maritime targets because it is easy to apply, maintain, and expand. AIS ship trajectory data analysis system design trajectory classification Chemical technology Bing Fu verfasserin aut Yasong Luo verfasserin aut Houpu Li verfasserin aut In Sensors MDPI AG, 2003 22(2021), 1, p 310 (DE-627)331640910 (DE-600)2052857-7 14248220 nnns volume:22 year:2021 number:1, p 310 https://doi.org/10.3390/s22010310 kostenfrei https://doaj.org/article/ddd995876667471fbb6cb48cd1230608 kostenfrei https://www.mdpi.com/1424-8220/22/1/310 kostenfrei https://doaj.org/toc/1424-8220 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2057 GBV_ILN_2111 GBV_ILN_2507 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 22 2021 1, p 310
language	English
source	In Sensors 22(2021), 1, p 310 volume:22 year:2021 number:1, p 310
sourceStr	In Sensors 22(2021), 1, p 310 volume:22 year:2021 number:1, p 310
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institution	findex.gbv.de
topic_facet	AIS ship trajectory data analysis system design trajectory classification Chemical technology
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container_title	Sensors
authorswithroles_txt_mv	Chengxu Feng @@aut@@ Bing Fu @@aut@@ Yasong Luo @@aut@@ Houpu Li @@aut@@
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callnumber-first	T - Technology
author	Chengxu Feng
spellingShingle	Chengxu Feng misc TP1-1185 misc AIS misc ship trajectory misc data analysis misc system design misc trajectory classification misc Chemical technology The Design and Development of a Ship Trajectory Data Management and Analysis System Based on AIS
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topic_title	TP1-1185 The Design and Development of a Ship Trajectory Data Management and Analysis System Based on AIS AIS ship trajectory data analysis system design trajectory classification
topic	misc TP1-1185 misc AIS misc ship trajectory misc data analysis misc system design misc trajectory classification misc Chemical technology
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title_auth	The Design and Development of a Ship Trajectory Data Management and Analysis System Based on AIS
abstract	To address the data storage, management, analysis, and mining of ship targets, the object-oriented method was employed to design the overall structure and functional modules of a ship trajectory data management and analysis system (STDMAS). This paper elaborates the detailed design and technical information of the system’s logical structure, module composition, physical deployment, and main functional modules such as database management, trajectory analysis, trajectory mining, and situation analysis. A ship identification method based on the motion features was put forward. With the method, ship trajectory was first partitioned into sub-trajectories in various behavioral patterns, and effective motion features were then extracted. Machine learning algorithms were utilized for training and testing to identify many types of ships. STDMAS implements such functions as database management, trajectory analysis, historical situation review, and ship identification and outlier detection based on trajectory classification. STDMAS can satisfy the practical needs for the data management, analysis, and mining of maritime targets because it is easy to apply, maintain, and expand.
abstractGer	To address the data storage, management, analysis, and mining of ship targets, the object-oriented method was employed to design the overall structure and functional modules of a ship trajectory data management and analysis system (STDMAS). This paper elaborates the detailed design and technical information of the system’s logical structure, module composition, physical deployment, and main functional modules such as database management, trajectory analysis, trajectory mining, and situation analysis. A ship identification method based on the motion features was put forward. With the method, ship trajectory was first partitioned into sub-trajectories in various behavioral patterns, and effective motion features were then extracted. Machine learning algorithms were utilized for training and testing to identify many types of ships. STDMAS implements such functions as database management, trajectory analysis, historical situation review, and ship identification and outlier detection based on trajectory classification. STDMAS can satisfy the practical needs for the data management, analysis, and mining of maritime targets because it is easy to apply, maintain, and expand.
abstract_unstemmed	To address the data storage, management, analysis, and mining of ship targets, the object-oriented method was employed to design the overall structure and functional modules of a ship trajectory data management and analysis system (STDMAS). This paper elaborates the detailed design and technical information of the system’s logical structure, module composition, physical deployment, and main functional modules such as database management, trajectory analysis, trajectory mining, and situation analysis. A ship identification method based on the motion features was put forward. With the method, ship trajectory was first partitioned into sub-trajectories in various behavioral patterns, and effective motion features were then extracted. Machine learning algorithms were utilized for training and testing to identify many types of ships. STDMAS implements such functions as database management, trajectory analysis, historical situation review, and ship identification and outlier detection based on trajectory classification. STDMAS can satisfy the practical needs for the data management, analysis, and mining of maritime targets because it is easy to apply, maintain, and expand.
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title_short	The Design and Development of a Ship Trajectory Data Management and Analysis System Based on AIS
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