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A method and device for online compression of massive ship AIS trajectory data

A trajectory data and ship trajectory technology, which is applied in the field of online compression of massive ship AIS trajectory data, can solve the problems of poor compression effect and achieve the effect of improving the compression effect

Active Publication Date: 2021-04-16
浙江欣挪瑞海洋科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] In view of this, the present invention provides an online compression method and device for massive ship AIS trajectory data, to solve or at least partially solve the technical problem of poor compression effect existing in the prior art

Method used

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  • A method and device for online compression of massive ship AIS trajectory data
  • A method and device for online compression of massive ship AIS trajectory data
  • A method and device for online compression of massive ship AIS trajectory data

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Embodiment 1

[0050] This embodiment provides an online compression method for massive ship AIS trajectory data, please refer to figure 1 , the method includes:

[0051] Step S1: Obtain historical features of ship trajectories in preset waters according to historical AIS data.

[0052] Specifically, in view of the disadvantages of massive data storage occupying a large amount of memory space, choose to compress data and discard non-key points with less information in the data, so as to improve data storage efficiency. However, directly compressing the current data will lead to large errors in ship trajectories. Therefore, the present invention selects and collects historical AIS data of passing ships in a certain water area, and uses the Douglas algorithm to select an appropriate threshold to extract its characteristics. Then, the obtained ship navigation characteristics in the water area are used as the basis for correcting real-time ship data compression, and the compressed data is repro...

Embodiment 2

[0099] This embodiment provides an online compression device for massive ship AIS trajectory data, please refer to Figure 4 , the device consists of:

[0100] A historical feature acquisition module 201, configured to acquire historical features of ship tracks in preset waters according to historical AIS data;

[0101] The online compression module 202 is used for performing online compression on the AIS trajectory data to be compressed based on the combination of the change of the motion state and the historical feature data, wherein the change of the motion state is obtained by comparing the motion state of the current trajectory point with the motion state of the key point out.

[0102] In one embodiment, the online compression module is specifically configured to perform online compression using a threshold combination algorithm that defines two factors, and the two factors include synchronous Euclidean distance and steering angle;

[0103] The threshold combination alg...

Embodiment 3

[0112] See Figure 5 , based on the same inventive concept, the present application also provides a computer-readable storage medium 300, on which a computer program 311 is stored. When the program is executed, the method as described in the first embodiment is implemented.

[0113] Since the computer-readable storage medium introduced in the third embodiment of the present invention is the computer equipment used to implement the online compression method for massive ship AIS track data in the first embodiment of the present invention, based on the method introduced in the first embodiment of the present invention, the technical field Those who belong to it can understand the specific structure and deformation of the computer-readable storage medium, so details will not be repeated here. All computer-readable storage media used in the method in Embodiment 1 of the present invention fall within the scope of protection intended by the present invention.

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Abstract

The invention discloses an online compression method and device for massive ship AIS trajectory data. The online compression method is a threshold combination algorithm that limits two factors (synchronous Euclidean distance and steering angle), and takes waters as the research object. First, for a certain waters, according to The historical AIS data finds the historical characteristics of the ship's trajectory in the area, and then performs online compression based on the combination of the change of the motion state and the historical characteristic data, and finally builds a visual analysis method for the ship's AIS trajectory data based on kernel density estimation. The invention can efficiently compress the AIS data, and relatively complete and accurately retain the feature points of its trajectory, which helps to realize the efficient management of the AIS data, and improves the efficiency of information exchange and supervision among ships.

Description

technical field [0001] The invention relates to the technical field of data compression, in particular to an online compression method and device for massive ship AIS track data. Background technique [0002] According to Chapter 5 of the "Convention for the Safety of Life at Sea" revised by the International Maritime Organization (IMO) MSC73, ships with a gross tonnage of more than 300 tons must be equipped with an automatic identification system (Automatic Identification System, AIS) by 2002 , to enhance the safety of life on water, improve the safety and efficiency of ship navigation. [0003] The ship's automatic identification system AIS can monitor the movement status of the ship in real time. For ship operators, using AIS data can understand the navigation dynamic information of the ship and other target ships, which is conducive to ship navigation and collision avoidance and other actions; for maritime traffic control departments, using AIS data information can mana...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F30/20G06F16/29
CPCG06F30/20
Inventor 刘钊陈通孙鹏刘文梁茂晗刘敬贤
Owner 浙江欣挪瑞海洋科技有限公司
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