Anchor ground ship identification system based on AIS data

Abstract

The invention discloses an AIS data-based anchor ground ship identification system, which comprises an AIS and a ship identification system, and is characterized in that the AIS is used for providing real-time ship data for the ship identification system, and the ship identification system comprises a data processing module and a ship identification module; the data processing module comprises a data analysis module, a data screening module, a data extraction module and a data storage module, and the ship identification module comprises ship position identification and ship feature identification. The ship data provided by the AIS is intelligently analyzed through the Java system and the Redis cache, and the position information and the stay time of the anchored ship are automatically identified and recorded through the ship identification system, so that the staff in the water service area can master the dynamic state of the anchored ship at any time, and the ship can be timely monitored by providing the information of the anchored ship in time. The ship identification system can optimize the distribution path and time arrangement of the unmanned aerial vehicle, so that the service efficiency is improved, and the waiting time of sailors is reduced.

Description

Technical Field

[0001] The invention relates to the technical field of anchorage ship identification systems based on AIS data, and in particular to an anchorage ship identification system based on AIS data. Background Art

[0002] In the daily operation of the river water service area, timely grasping the location and stay time of anchored ships is crucial to providing efficient services. Especially in the case of busy shipping on the Yangtze River, many ships need to stay at anchorages to wait for unloading, replenishment and other operations. Most of the existing ship management systems rely on manual records and inquiries, and cannot accurately identify and manage the information of anchored ships in real time, resulting in low service efficiency and crew members needing to wait for a long time for supplies.

[0003] Although the current AIS (Automatic Identification System) can provide real-time location and status information of ships, it lacks the function of accurately identifying ships at anchor. As a result, the staff in the water service area are unable to obtain detailed information on ships at anchor in a timely manner, which in turn affects the distribution of materials and the quality of service. Summary of the invention

[0004] The purpose of the present invention is to provide an anchorage ship identification system based on AIS data, which has the advantages of helping staff to quickly grasp the dynamics of anchorage ships, so as to provide efficient services to anchorage ship personnel and optimize the low-altitude delivery service of drones. It solves the problem that although it can provide real-time position and status information of ships, it lacks the function of accurately identifying anchorage ships, causing the staff of water service areas to be unable to obtain detailed information of anchorage ships in time, thereby affecting the distribution of materials and service quality.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: an anchorage ship identification system based on AIS data, comprising an AIS and a ship identification system, wherein the AIS is used to provide real-time ship data to the ship identification system, the ship identification system comprises a data processing module and a ship identification module, the data processing module comprises a data parsing module, a data screening module, a data extraction module and a data storage module, the ship identification module comprises a ship position identification and a ship feature identification, the data parsing module is used to parse the data received by the AIS, the data screening module is used to filter out ship information from the parsed AIS data, the data extraction module is used to extract the filtered ship static information and dynamic information, the ship position identification is used to determine whether the ship is in an anchorage, and the ship feature identification is used to identify the ship.

[0006] Preferably, the AIS provides static information of the ship, dynamic information of the ship and voyage data of the ship, which are parsed, screened and extracted by the data processing module and then stored in the data storage module.

[0007] Preferably, the data storage module is Redis, and the data processing module uses a Java system background to perform data analysis.

[0008] Preferably, the ship static information includes ship name, call sign, MMSI, IMO, ship type, and ship size, the ship dynamic information includes longitude, latitude, heading, track and speed, and the ship voyage data includes ship status, draft, destination and ETA.

[0009] Preferably, the ship identification system also uses a map and latitude and longitude coordinates to frame the anchorage range with an electronic fence, and monitors the position of the ship within the electronic fence.

[0010] Preferably, the ship identification module calculates the ship position by using the Euclidean distance algorithm. The Euclidean distance formula between two points (x1, y1) and (x2, y2) in two-dimensional space is:

[0011]

[0012] Among them, χ1 and y1 are the coordinates of the ship, x2 and x2 are the coordinates of the relevant points of the anchorage. In n-dimensional space, point x=(x i , ..., x n ) and y=(y i , ..., y n ) is:

[0013]

[0014] Preferably, the ship feature recognition extracts and models the feature data of the ship through a satellite remote sensing image feature recognition algorithm, and the specific method includes the following steps:

[0015] a) Image preprocessing, including denoising, image enhancement, and sharpening, is used to improve image quality and the accuracy of feature values;

[0016] b) Ship segmentation: the ship area is separated from the background through the target segmentation algorithm;

[0017] c) Feature extraction, by extracting the color, texture, shape and size feature values ​​of the ship;

[0018] d) Feature selection, screening out the feature values ​​with the best classification and recognition effects;

[0019] e) Model training: Use known ship sample data sets to train feature sets and generate classifiers;

[0020] f) Target detection: using the trained classifier to identify and classify new remote sensing images.

[0021] Compared with the prior art, the present invention has the following beneficial effects:

[0022] The present invention uses a Java system and Redis cache to perform intelligent analysis on the ship data provided by AIS, thereby realizing efficient identification and management of anchored ships. The ship identification system automatically identifies and records the location information and stay time of anchored ships, so that the staff of the water service area can grasp the dynamics of anchored ships at any time. By timely providing the information of anchored ships, the ship identification system can optimize the delivery path and time arrangement of drones, thereby improving service efficiency and reducing the waiting time of crew members. The automatic identification and information management functions of the ship identification system reduce the need for manual intervention, reduce the operating cost of the service area, and improve the service quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic diagram of the system framework of the present invention;

[0024] Figure 2 It is a schematic diagram of the system flow of the present invention. DETAILED DESCRIPTION

[0025] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0026] Example 1

[0027] like Figure 1-2 As shown, it is the first embodiment of the present invention, which provides an anchorage ship identification system based on AIS data, including AIS and a ship identification system, the AIS is used to provide real-time ship data to the ship identification system, the ship identification system includes a data processing module and a ship identification module, the data processing module includes a data parsing module, a data screening module, a data extraction module and a data storage module, the ship identification module includes ship position identification and ship feature identification, the data parsing module is used to parse the data received by the AIS, the data screening module is used to filter out ship information from the parsed AIS data, the data extraction module is used to extract the filtered ship static information and dynamic information, the ship position identification is used to determine whether the ship is in the anchorage, and the ship feature identification is used to identify the ship.

[0028] like Figure 1-2As shown in the figure, by using the real-time ship data provided by the AIS ship automatic identification system, including the ship's positioning, speed, heading, ship name and other information, through the Java system background, these data will be collected, processed and stored in the Redis cache for rapid subsequent analysis and comparison. The system also uses the map and longitude and latitude coordinates to select the electronic fence within the anchorage range, and monitors the position of the ship within the electronic fence. By analyzing the speed and position changes of the ship, it is determined whether the ship is at anchor. When the speed of the ship is close to zero within a certain period of time and the position has not changed significantly, the system determines that the ship is at anchor, and records its anchorage stay time, identifies the anchorage ship, and the system will promptly notify the staff of the water service area. The staff can contact and arrange the distribution of materials according to the anchorage position and stay time of the ship, and deliver the daily necessities to the crew in time. Through the intelligent analysis of AIS data, efficient identification and management of anchorage ships are realized.

[0029] Example 2

[0030] Reference Figure 1-2 , which is the second embodiment of the present invention, and this embodiment is based on the previous embodiment.

[0031] In this embodiment, the AIS provides static information of the ship, dynamic information of the ship and voyage data of the ship, which are parsed, screened and extracted by the data processing module and then stored in the data storage module.

[0032] The data storage module is Redis, and the data processing module uses the Java system background for data analysis.

[0033] The static information of the ship includes the ship name, call sign, MMSI, IMO, ship type, and ship size; the dynamic information of the ship includes longitude, latitude, heading, track and speed; the voyage data includes ship status, draft, destination and ETA.

[0034] The vessel identification system also uses maps and longitude and latitude coordinates to frame the anchorage area within the electronic fence and monitor the position of ships within the electronic fence.

[0035] like Figure 1-2As shown, the ship identification system uses the map and longitude and latitude coordinates to select the electronic fence within the anchorage range, and monitors the position of the ship within the electronic fence. By using the static information, dynamic information and voyage data of the ship provided by AIS, the ship feature information and the ship data information provided by AIS are parsed, screened and extracted through the data processing module to determine whether the ship is in an anchorage state. When the speed of the ship is close to zero and the position has not changed within a certain period of time, the ship is determined to be in an anchorage state, and its anchorage stay time is recorded. After identifying that the ship is in an anchorage state, the service area staff is notified by remote transmission. The staff can contact and arrange the distribution of materials according to the anchorage position and stay time of the ship, and deliver the daily necessities to the crew in time, which not only improves the service efficiency, but also reduces the waiting time of the crew and improves the service quality.

[0036] Example 3

[0037] Reference Figure 1-2 , which is the third embodiment of the present invention, and this embodiment is based on the previous two embodiments.

[0038] In this embodiment, the ship identification module calculates the ship position by using the Euclidean distance algorithm. The Euclidean distance formula between two points (x1, y1) and (x2, y2) in two-dimensional space is:

[0039]

[0040] Among them, χ1 and y1 are the coordinates of the ship, x2 and x2 are the coordinates of the relevant points of the anchorage. In n-dimensional space, point x=(x i , ..., x n ) and y=(y i , ..., y n ) is:

[0041]

[0042] Ship feature recognition extracts and models the ship's feature data through satellite remote sensing image feature recognition algorithms, and the specific method includes the following steps:

[0043] a) Image preprocessing, including denoising, image enhancement, and sharpening, is used to improve image quality and the accuracy of feature values;

[0044] b) Ship segmentation: the ship area is separated from the background through the target segmentation algorithm;

[0045] c) Feature extraction, by extracting the color, texture, shape and size feature values ​​of the ship;

[0046] d) Feature selection, screening out the feature values ​​with the best classification and recognition effects;

[0047] e) Model training: Use known ship sample data sets to train feature sets and generate classifiers;

[0048] f) Target detection: using the trained classifier to identify and classify new remote sensing images.

[0049] like Figure 1-2 As shown in the figure, the ship identification system uses the map and longitude and latitude coordinates to select the electronic fence within the anchorage range, and the electronic fence is used to grid the activity range of the ship. The ship identification module calculates the ship position through the Euclidean distance algorithm. After the ship enters the electronic fence and stops, a certain initial reference point of the ship is taken as the origin, the bow direction is the positive direction of the x-axis, and the left direction perpendicular to the bow is the positive direction of the y-axis. When there are multiple measurement points on the ship, the bow is P1 = (x1, y1), and the stern is P2 = (x2, y2). Then the Euclidean distance between the two points is The ship identification module calculates the location of the ship, and then identifies and judges the ship's features. The satellite remote sensing image is preprocessed, mainly including denoising, image enhancement, and sharpening operations, which helps to improve the image quality and the accuracy of the feature value. Then, the target segmentation algorithm is used in the satellite remote sensing image to separate the ship area from the background to obtain the ship's image data. The color characteristics of the ship are obtained through color distribution analysis. For ships of different colors, the corresponding color space model can be used to perform fine feature extraction and analysis to achieve more accurate ship identification and classification. The texture characteristics of the ship are obtained through the analysis of the ship's surface texture characteristics, and the shape characteristics are analyzed. Through analysis, the shape characteristics of the ship can be obtained. The contour features can be accurately extracted and analyzed through the number, distance and direction of contour points. The size characteristics of the ship can be obtained through size feature analysis. These feature values ​​are integrated and modeled to form a target feature set. Then, the identified characteristics are selected and screened, and feature values ​​with better classification and recognition effects are selected to improve the discrimination and accuracy of the feature set. The known ship sample data set is used to train the model of the established target feature set to generate a ship recognition classifier. Finally, the generated ship classifier is used to automatically identify and classify unknown satellite remote sensing images to obtain the target detection results of the ship.

[0050] When in use, the ship identification system uses maps and longitude and latitude coordinates to select an electronic fence within the anchorage range and monitor the position of ships within the electronic fence. By utilizing the static information, dynamic information and voyage data of the ship provided by AIS, the data processing module parses, filters and extracts the ship feature information and the ship data information provided by AIS to determine whether the ship is in an anchorage state. When the ship's speed is close to zero and its position has not changed within a certain period of time, it is determined that the ship is in an anchorage state and its anchorage stay time is recorded. After identifying that the ship is in an anchorage state, the service area staff is notified remotely. The staff can contact and arrange the distribution of materials according to the ship's anchorage position and stay time, and deliver daily necessities to the crew in a timely manner, which not only improves service efficiency, but also reduces the waiting time of the crew and improves service quality.

[0051] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0052] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An anchorage ship identification system based on AIS data, comprising AIS and a ship identification system, characterized in that: The AIS is used to provide real-time ship data to the ship identification system. The ship identification system includes a data processing module and a ship identification module. The data processing module includes a data parsing module, a data screening module, a data extraction module and a data storage module. The ship identification module includes ship position identification and ship feature identification. The data parsing module is used to parse the data received by the AIS. The data screening module is used to filter out ship information from the parsed AIS data. The data extraction module is used to extract the filtered static information and dynamic information of the ship. The ship position identification is used to determine whether the ship is at an anchorage, and the ship feature identification is used to identify the ship.

2. The anchorage ship identification system based on AIS data according to claim 1, characterized in that: The AIS provides static information, dynamic information and voyage data of the ship, which are analyzed, screened and extracted by the data processing module and then stored in the data storage module.

3. The anchorage ship identification system based on AIS data according to claim 1 is characterized by: The data storage module is Redis, and the data processing module uses a Java system background to perform data analysis.

4. The anchorage ship identification system based on AIS data according to claim 1, characterized in that: The ship static information includes ship name, call sign, MMSI, IMO, ship type, and ship size; the ship dynamic information includes longitude, latitude, heading, track and speed; the ship voyage data includes ship status, draft, destination and ETA.

5. The anchorage ship identification system based on AIS data according to claim 1, characterized in that: The ship identification system also uses the map and longitude and latitude coordinates to frame the anchorage area out of the electronic fence and monitor the position of the ship within the electronic fence.

6. The anchorage ship identification system based on AIS data according to claim 1, characterized in that: The ship identification module calculates the ship position by the Euclidean distance algorithm. The Euclidean distance formula between two points (χ1, y1) and (χ2, y2) in two-dimensional space is: Among them, χ1 and y1 are the coordinates of the ship, χ2 and y2 are the coordinates of the anchorage related points. In n-dimensional space, point χ=(x i , ..., x n ) and y=(y i , ..., y n ) is:

7. The anchorage ship identification system based on AIS data according to claim 1, characterized in that: The ship feature recognition method extracts and models the feature data of the ship through a satellite remote sensing image feature recognition algorithm, and the specific method includes the following steps: a) Image preprocessing, including denoising, image enhancement, and sharpening, is used to improve image quality and the accuracy of feature values; b) Ship segmentation: the ship area is separated from the background through the target segmentation algorithm; c) Feature extraction, by extracting the color, texture, shape and size feature values ​​of the ship; d) Feature selection, screening out the feature values ​​with the best classification and recognition effects; e) Model training: Use known ship sample data sets to train feature sets and generate classifiers; f) Target detection: using the trained classifier to identify and classify new remote sensing images.

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