CN113870619A - Ship navigation risk identification and early warning method and system - Google Patents
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Abstract
The invention provides a ship navigation risk identification and early warning method and system, which are characterized in that ship AIS data, global shipping real-time risk data and operation subject data are collected and uploaded to a cloud database, the AIS data and the global shipping real-time risk data in the cloud database are identified and analyzed to obtain ship navigation risk data, the ship navigation risk data are matched with a corresponding ship operation subject in combination with the ship database data and send early warning information, and finally the operation subject visually monitors the AIS data and the ship navigation risk data of managed ships in real time, so that the ship navigation risk can be identified in real time, the accuracy of ship navigation risk identification is improved, and the risk processing capacity of the operation subject is improved.
Description
Technical Field
The invention relates to the technical field of ship navigation risk identification, in particular to a ship navigation risk identification and early warning method and system.
Background
With the continuous deepening of trade globalization, the shipping business is increasingly busy, and ships around the world are shuttled in rivers and sea areas. In the sailing process of the ships, sailing risks such as signal loss, severe weather, pirates and the like can happen around each ship at any time, and if the risk identification is wrong or the risk processing is not timely, the loss caused by the risk is often immeasurable.
In the prior art, a method for identifying ship navigation risks generally adopts a manual judgment mode, and an early warning mechanism for the ship navigation risks is that an operation subject gives an alarm or commands to a ship in a risk place after the risks occur. The ship navigation risk identification method and the early warning mechanism have the defects of inaccuracy, lag, low efficiency and the like, and can cause the problems of misjudgment, slow response, untimely processing and the like in an actual shipping service scene, thereby causing inestimable loss.
Disclosure of Invention
The invention provides a ship navigation risk identification and early warning method, aiming at solving the problems of inaccuracy, lag, low efficiency and the like in the existing ship navigation risk identification process. The invention also relates to a ship navigation risk identification and early warning system.
The technical scheme of the invention is as follows:
a ship navigation risk identification and early warning method is characterized by comprising the following steps:
a data acquisition step: collecting ship AIS data, global shipping real-time risk data and ship database data, and uploading the ship AIS data, the global shipping real-time risk data and the ship database data to a cloud database;
risk identification step: the AIS data and the global shipping real-time risk data collected into the cloud database are identified and analyzed, and the ship navigation state risk, the ship navigation time-space risk and the ship navigation meteorological risk are identified to obtain ship navigation risk data;
risk early warning step: summarizing ship navigation risk data, matching corresponding ship operation bodies and sending early warning information to the ship operation bodies in combination with ship library data;
and (3) risk visualization step: and visually monitoring AIS data of the ship managed by the ship operation main body and ship navigation risk data in real time.
Preferably, in the data collecting step, the AIS data includes static data and dynamic data, the static data includes a ship mobile service identification code and a ship name, and the dynamic data includes ship longitude and latitude position information, a navigation state, a timestamp, a ground speed, a draught, a departure port, a destination port and a pre-arrival time.
Preferably, in the data acquisition step, the global shipping real-time risk data includes global battle area location data, global pirate area location data, global typhoon data and global oceanographic data, and the ship database data includes operation subject data.
Preferably, in the risk identifying step, the ship navigation risk data includes ship navigation state risk data, ship navigation time-space risk data and ship navigation weather risk data.
Preferably, the ship navigation state risk data is obtained by analyzing ship navigation state, navigation speed and draft data; the ship navigation time-space risk data is obtained by analyzing the longitude and latitude, the departure port, the destination port, the departure time and the pre-offset time of a ship and combining the position data of the global special war zone and the position data of the global pirate zone; the ship navigation meteorological risk data are obtained by analyzing the longitude and latitude of the ship and combining the global typhoon data and the global oceanographic data.
A ship navigation risk identification and early warning system is characterized by comprising a data acquisition module, a cloud database, a risk identification module, a risk early warning module and a risk visualization module,
the data acquisition module acquires ship AIS data, global shipping real-time risk data and ship database data and uploads the ship AIS data, the global shipping real-time risk data and the ship database data to the cloud database;
the risk identification module identifies and analyzes the AIS data and the global shipping real-time risk data collected into the cloud database, and identifies the ship navigation state risk, the ship navigation time-space risk and the ship navigation weather risk to obtain ship navigation risk data;
the risk early warning module summarizes ship navigation risk data, matches a corresponding ship operation main body by combining ship library data and sends early warning information to the ship operation main body;
the risk visualization module is used for visually monitoring AIS data of ships managed by the ship operation main body in real time and ship navigation risk data.
Preferably, the risk identification module comprises a navigation state risk identification submodule, a navigation space-time risk identification submodule and a navigation weather risk identification submodule,
the navigation state risk identification submodule is used for analyzing the AIS data of the ship, including navigation state, navigation speed and draft data, so as to obtain the navigation state risk data of the ship;
the navigation time-space risk identification submodule is used for analyzing the AIS data of the ship, including longitude and latitude, departure port, destination port, departure time and pre-offset time, and combining the global special war zone position data and the global pirate zone position data in the global shipping real-time risk data to obtain the navigation time-space risk data of the ship;
the navigation meteorological risk identification submodule is used for analyzing longitude and latitude data in the ship AIS data and combining global typhoon data and global oceanic meteorological data in the global navigation real-time risk data to obtain the ship navigation meteorological risk data.
Preferably, the vessel state risk identification submodule includes a vessel AIS loss identification unit, a vessel state anomaly identification unit and an anchoring overtime identification unit, the vessel space-time risk identification submodule includes a vessel time delay risk identification unit and a special area vessel risk identification unit, and the vessel weather risk identification submodule includes a typhoon weather risk identification unit and a oceanographic weather risk identification unit.
Preferably, the risk visualization module comprises a risk data summarizing and displaying unit and a ship position data displaying unit.
Preferably, the AIS data includes static data and dynamic data, the static data includes a ship mobile service identification code and a ship name, and the dynamic data includes ship longitude and latitude position information, a navigation state, a timestamp, a ground speed, a draught, a departure port, a destination port and a pre-arrival time;
the global shipping real-time risk data comprises global special war zone position data, global pirate zone position data, global typhoon data and global oceanographic data;
the ship base data includes operation subject data.
The invention has the beneficial effects that:
the invention provides a ship navigation risk identification and early warning method, which is characterized in that a data acquisition step, a risk identification step, a risk early warning step and a risk visualization step are sequentially arranged, all the steps are mutually matched and work cooperatively, ship AIS data, global navigation real-time risk data and ship database data are firstly acquired and uploaded to a cloud database; then, AIS data and global shipping real-time risk data in the cloud database are identified and analyzed, and a ship navigation state risk, a ship navigation time-space risk and a ship navigation meteorological risk can be identified, so that ship navigation risk data are obtained; then, the ship navigation risk data are gathered and matched with a ship operation main body, and early warning information is sent; and finally, visually monitoring AIS data of the ship managed by the operation main body and ship navigation risk data in real time. According to the method, ship AIS data are obtained in real time, and various global shipping real-time risk data such as global special war zone position data, global pirate zone position data, global typhoon data and global oceanographic data are combined to obtain ship navigation risk data in batches, and the risk information and early warning information are sent to a ship operation main body in real time, and meanwhile, the operation main body can monitor the AIS data and the ship navigation risk data of managed ships in real time, so that the accuracy of ship navigation risk identification is greatly improved, the ship navigation risk is identified in real time, and the risk processing capacity of the operation main body is improved.
The invention also relates to a ship navigation risk identification and early warning system, which corresponds to the ship navigation risk identification method and can be understood as a system for realizing the ship navigation risk identification and early warning method, and the system comprises a data acquisition module, a cloud database, a risk identification module, a risk early warning module and a risk visualization module, wherein the modules work cooperatively, ship navigation risk data are acquired in batch by acquiring the AIS data of ships in real time and combining with the global navigation real-time risk data, and the risk information and the early warning information are transmitted to a ship operation main body in real time, and the operation main body can monitor the AIS data of managed ships and the ship navigation risk data in real time and check the detailed information of a certain navigation risk data, so that the accuracy of ship navigation risk identification is improved, the ship navigation risk is identified in real time, and the risk processing capacity of the operation main body on the risks is improved, the problems that an existing ship navigation risk identification method is inaccurate, a ship navigation risk early warning mechanism is lagged, low efficiency and the like are effectively solved.
Drawings
FIG. 1 is a flow chart of a ship navigation risk identification and early warning method of the present invention.
Fig. 2 is a block diagram of a preferred structure of the ship navigation risk identification and early warning system of the invention.
Detailed Description
The present invention will be described with reference to the accompanying drawings.
The invention relates to a ship navigation risk identification and early warning method, the flow chart of which is shown in figure 1, and the method sequentially comprises the following steps:
a data acquisition step: the method comprises the steps of collecting ship Automatic Identification System (AIS) data, global shipping real-time risk data and ship database data, uploading the data to a cloud database, specifically, continuously collecting ship AIS data through a third-party service provider, regularly collecting ship database data (namely ship basic data) at all global ship information websites through a web crawler technology, obtaining the global shipping real-time risk data through a public data service platform, and storing the data into the cloud database in real time. Preferably, the AIS data includes static data and dynamic data, the static data includes a ship mobile service identification code MMSI and a ship name, and the dynamic data includes ship longitude and latitude position information, a navigation state, a time stamp, a speed to ground, a draught, a departure port, a destination port and a pre-arrival time. Preferably, the global shipping real-time risk data includes global battle district location data, global pirate district location data, global typhoon data and global oceanographic data, and the ship base data includes operational subject data.
The global special War zone position data is generated according to War zones listed by Joint War risk Committee (JWC for short), and comprises boundary longitude and latitude data of each special War zone; the global pirate Area position data is generated according to a High Risk Area (HRA for short) established by the shipping industry and other interest relatives, and comprises boundary longitude and latitude data of each pirate Area; the global typhoon data is generated by acquiring the global typhoon data in real time through a meteorological data platform; the global oceanographic data is generated by acquiring wind speed and wave height data corresponding to global longitude and latitude through a meteorological data platform, and in addition, the storm flow data near the longitude and latitude of the ship is acquired in a sparse mode due to huge amount of global oceanographic data.
It should be noted that the acquisition of the ship AIS data is to continuously acquire the same or different AIS data of the ship mobile service identification code MMSI by a third-party service provider, and the above acquisition scheme is continuously executed by a timing task program, and the obtained data has two situations, one is dynamic data of the same MMSI ship at different time points, and the other is dynamic data of different MMSI ships at the same time points, and the obtained data is stored in a cloud database to form massive ship analysis data.
Risk identification step: and continuously reading the AIS data and the global shipping real-time risk data from the cloud database to perform identification analysis, identifying the ship navigation state risk, the ship navigation time-space risk and the ship navigation meteorological risk, processing in real time to obtain ship navigation risk data, and storing the ship navigation risk data into the cloud database.
Preferably, the ship navigation risk data comprise ship navigation state risk data, ship navigation time-space risk data and ship navigation meteorological risk data, wherein the ship navigation state risk data are sorted in a reverse order according to state occurrence time and state duration, the ship navigation time-space risk data are sorted in a reverse order according to delay time proportion and time length when the ship navigation time-space risk data enter a special war zone or a pirate zone, and the ship navigation meteorological risk data are sorted in a reverse order according to meteorological grade and longitude and latitude similarity. Further preferably, the ship navigation state risk data is obtained by analyzing ship navigation state, speed and draft data, the ship navigation time-space risk data is obtained by analyzing ship longitude and latitude, departure port, destination port, departure time and advance time, and combining global special war zone position data and global pirate zone position data, and the ship navigation weather risk data is obtained by analyzing ship longitude and latitude, and combining global typhoon data and global oceanographic weather data.
And analyzing the data of the ship AIS data such as navigation state, navigation speed, draft and the like, and judging to obtain ship navigation state risk data. For example: traverse boats and ships AIS data, screen out and lose time length data with the AIS that the current time phase difference is more than 6 hours, the sign is lost for boats and ships AIS, boats and ships AIS loses still can discern according to the following formula:
tdiff＝t0-max(t1,t2,...,tn) (1)
in the above formula, t0Time stamp, t, representing the current system timeiTime stamp, t, representing all AIS data of a certain vesseldiffIndicating the AIS loss duration.
By reading real-time ship AIS data, respectively marking the data with the navigation states of 3, 4 and 6 as the states of mobility limitation, draft limitation and grounding; by reading the AIS data of the ship, if the current sailing state of the same ship is '6' and the duration time of the state exceeds 2 hours, the anchoring overtime is marked, and the anchoring overtime can be identified according to the following formula:
tsum＝max({tn})-min({tn}) (2)
in the above formula, tnSet of timestamps, t, representing a flight status of "6" in the continuous AIS data for a certain shipsumIndicating the length of the mooring time.
Calculating the estimated delay time proportion according to the departure port, the destination port, the departure time and the pre-arrival time in the AIS data of the ship and the current longitude and latitude of the ship, and marking the delay time as the delay time for more than 10% of the ships; according to the longitude and latitude in the ship AIS data, the global special war zone position data and the global pirate zone position data are combined, the ship in the global special war zone and the global pirate zone is marked as a special area navigation risk, and the special area navigation risk can be identified according to the following formula:
where y + b denotes two consecutive points (x) of the boundary of the special region0,y0),(x1,y1) The straight line formed, y ═ cx + d, represents the longitude and latitude point (x) of two consecutive AIS data of a certain ship2,y2),(x3,y3) And if the point exists and is simultaneously positioned in the line segment formed by the two groups of points, the current navigation passes through the special area and the navigation risk of the special area exists.
Calculating the latitude and longitude of a range boundary influenced by typhoon according to the global typhoon data, and identifying the current or future ships in the range as typhoon weather risks; according to global oceanographic data, meteorological longitude and latitude data with the wind speed of more than 17.1m/s and the wave height of more than 2.5m are screened out, and according to the longitude and latitude in the ship AIS data, the ships meeting the weather data are matched and marked as oceanographic risks. Analyzing the longitude and latitude of the ship, and obtaining the ship navigation weather risk by combining the typhoon weather risk and the oceanographic weather risk, wherein the ship navigation weather risk is identified according to the following formula:
sdiff＝distance(p1,p2) (4)
wherein p is1Representing the longitude and latitude coordinate point, p, of the current AIS data of the ship2Representing longitude and latitude coordinate points of the place where the meteorological data occurs, distance representing a function for calculating the distance between two longitude and latitude points, sdiffRepresenting the distance between the vessel and the place of meteorological data.
And storing the identified data into the cloud database to form ship navigation risk data, wherein the failed ship navigation risk data needs to be deleted every time the latest ship navigation risk data is stored into the cloud database.
Risk early warning step: the method comprises the steps of summarizing ship navigation risk data, sending the collected ship library data to a ship operation main body, sending early warning information, specifically traversing the summarized ship navigation risk data, obtaining operation main bodies corresponding to the ship navigation risk data by matching MMSI in ship AIS data, summarizing according to the operation main bodies to obtain the ship navigation risk data of the operation main bodies, sending the navigation risk data of corresponding ships to the operation main bodies through communication modes such as WeChat public number information, network mails and mobile phone short messages, and sending the early warning information.
And a risk visualization step, namely visually monitoring AIS data of the ship managed by the operation main body in real time, ship navigation risk data and further viewing detailed information of certain navigation risk data. Specifically, data visualization is performed on ship AIS data and ship navigation risk data in the cloud database by using a data visualization technology, and the ship AIS data and the ship navigation risk data are summarized and displayed in a WEB webpage.
The invention also relates to a ship navigation risk identification and early warning system, which corresponds to the ship navigation risk identification and early warning method and can be understood as a system for realizing the method, such as a preferred structure shown in fig. 2, and the system comprises a data acquisition module 201, a cloud database 202, a risk identification module 203, a risk early warning module 204 and a risk visualization module 205, and particularly,
and the data acquisition module 201 is used for acquiring ship AIS data, global shipping real-time risk data and ship database data and uploading the data to the cloud database 202. Preferably, the AIS data includes static data and dynamic data, the static data includes a ship mobile service identification code and a ship name, and the dynamic data includes ship longitude and latitude position information, a navigation state, a time stamp, a speed to ground, draught, a departure port, a destination port and a pre-arrival time. Preferably, the global shipping real-time risk data includes global battle district location data, global pirate district location data, global typhoon data, and global oceanographic data. Preferably, the ship library data comprises operational subject data.
And the risk identification module 203 is used for identifying and analyzing the AIS data and the global shipping real-time risk data in the cloud database 202, identifying the ship navigation state risk, the ship navigation time-space risk and the ship navigation weather risk, obtaining the ship navigation risk data and storing the ship navigation risk data into the cloud database 202.
Preferably, the risk identification module 203 includes a navigation state risk identification submodule 2031, a navigation time-space risk identification submodule 2032 and a navigation weather risk identification submodule 2033, and the ship navigation state risk data, the ship navigation time-space risk data and the ship navigation weather risk data are respectively obtained through the three submodules; specifically, the navigation state risk identification submodule 2031 is configured to analyze the data of the ship AIS, including the navigation state, the navigation speed, the draft, and the like, and determine to obtain the ship navigation state risk data; preferably, the sailing state risk identification sub-module 2031 comprises a ship AIS loss identification unit 2031-1, a ship sailing state abnormality identification unit 2031-2 and an anchoring overtime identification unit 2031-3, wherein the ship AIS loss identification unit 2031-1 screens out data which is different from the current time by more than 6 hours by traversing ship AIS data in a cloud database and is used for identifying that the ship AIS is lost; the ship navigation state abnormality recognition unit 2031-2 reads the ship AIS data in real time, and respectively identifies the data of the navigation states "3", "4" and "6" as "mobility limited", "draft limited" and "stranded" states, and summarizes the data as ship navigation state abnormality; the mooring timeout identifying unit 2031-3 reads the AIS data of the ship, and identifies that the current sailing state is "6" for the same ship and the duration of the state exceeds 2 hours as a mooring timeout.
The navigation time-space risk identification submodule 2032 is configured to analyze the ship AIS data including longitude and latitude, departure port, destination port, departure time, pre-offset time and other data, and obtain ship navigation time-space risk data by combining with the global shipping real-time risk data; preferably, the navigation space-time risk identification sub-module 2032 comprises a time delay risk identification unit 2032-1 and a special area navigation risk identification unit 2032-2, wherein the time delay risk identification unit 2032-1 calculates an estimated delay time proportion according to a departure port, a destination port, departure time and pre-arrival time in the ship AIS data in combination with the current longitude and latitude of the ship, and identifies the time delay for more than 10% of the ships; the special area navigation risk recognition unit 2032-2 marks ships in the global special war zone and the global pirate zone as special area navigation according to the longitude and latitude in the ship AIS data and by combining the global special war zone position data and the global pirate zone position data.
The sailing weather risk identification submodule 2033 is configured to analyze longitude and latitude data in the ship AIS data, and obtain ship sailing weather risk data by combining the global typhoon data and the global oceanographic weather data; preferably, the sailing weather risk identification submodule 2033 comprises a typhoon weather risk identification unit 2033-1 and a marine weather risk identification unit 2033-2, wherein the typhoon weather risk identification unit 2033-1 calculates the longitude and latitude of a range boundary affected by typhoon according to global typhoon data, and identifies the current or future ships in the range as typhoon weather risks; the meteorology risk identification unit 2033-2 screens meteorological longitude and latitude data with wind speed greater than 17.1m/s and wave height greater than 2.5m according to the global meteorology data, matches the satisfied ships according to the longitude and latitude in the ship AIS data, and identifies the meteorology risk.
And the cloud database 202 is used for storing the ship AIS data and the global shipping real-time risk data acquired by the data acquisition module 201 and storing the ship shipping risk data of the risk identification module 203.
The risk early warning module 204 summarizes the ship navigation risk data, combines the ship database data, sends the ship navigation risk data to the ship operation subject, and sends early warning information, specifically, reads the ship navigation risk data and the ship database data from the cloud database 202, matches the operation subject corresponding to the ship according to the corresponding ship MMSI, and then sends the early warning data to the operation subject in the modes of wechat public number information, internet mail, mobile phone short message and the like.
And the risk visualization module is used for visually monitoring AIS data of the ship managed by the operation main body in real time, ship navigation risk data and further used for viewing detailed information of certain navigation risk data. Specifically, data visualization is performed on ship AIS data and ship navigation risk data in the cloud database 202 by using a data visualization technology, and the data are summarized and displayed in a WEB page.
Preferably, the risk visualization module 205 comprises a risk data summarizing and displaying unit 205-1, a ship position data displaying unit 205-2 and a risk data detail displaying unit 205-3, wherein the risk data summarizing and displaying unit 205-1 displays the total number of ships classified under the operation subject according to the ship navigation risk data summarized according to the operation subject in a pie graph mode, wherein the ship AIS loss, the ship navigation state abnormity, the navigation time delay, the navigation in a special area, the typhoon weather risk and the oceanographic weather risk are respectively displayed; the ship position data presentation unit 205-2 uses a third-party mapping function to map the ship position, and simulates the global geographical position of the ship in the form of a dot to distinguish the ship navigation states by colors, for example: the method comprises the following steps that a green dot simulates a ship with a navigation state of 0, a yellow dot simulates a ship with a navigation state of 5, a purple dot simulates a ship with a navigation state of 1, a red dot simulates other ships with navigation states, and when a mouse moves into the dot, ship AIS data and ship navigation risk data corresponding to the dot are displayed; the risk data detail display unit 205-3 displays the ship risk data of the ship AIS loss, the ship navigation state abnormality, the time delay, the special area navigation, the typhoon weather risk and the oceanographic weather risk in a list form, and can directly see the detailed information of the ship navigation risk data, for example: ship name, MMSI, risk type, risk occurrence time and the like.
The invention provides an objective and scientific ship navigation risk identification and early warning method and system, which can identify ship navigation risks in real time, improve the accuracy of ship navigation risk identification and improve the risk processing capacity of an operating main body by acquiring ship AIS data in real time, combining various data such as global special war zone position data, global pirate zone position data, global typhoon data, global oceanographic meteorological data and the like, acquiring ship navigation risk data in batches, transmitting the risk information to the operating main body in real time, and simultaneously summarizing according to the operating main body to form a ship navigation risk identification and early warning system.
It should be noted that the above-mentioned embodiments enable a person skilled in the art to more fully understand the invention, without restricting it in any way. Therefore, although the present invention has been described in detail with reference to the drawings and examples, it will be understood by those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention.
Claims (10)
1. A ship navigation risk identification and early warning method is characterized by comprising the following steps:
a data acquisition step: collecting ship AIS data, global shipping real-time risk data and ship database data, and uploading the ship AIS data, the global shipping real-time risk data and the ship database data to a cloud database;
risk identification step: the AIS data and the global shipping real-time risk data collected into the cloud database are identified and analyzed, and the ship navigation state risk, the ship navigation time-space risk and the ship navigation meteorological risk are identified to obtain ship navigation risk data;
risk early warning step: summarizing ship navigation risk data, matching corresponding ship operation bodies and sending early warning information to the ship operation bodies in combination with ship library data;
and (3) risk visualization step: and visually monitoring AIS data of the ship managed by the ship operation main body and ship navigation risk data in real time.
2. The vessel navigation risk identification and early warning method according to claim 1, wherein in the data collection step, the AIS data includes static data and dynamic data, the static data includes a vessel mobile service identification code and a vessel name, and the dynamic data includes vessel longitude and latitude position information, a navigation state, a timestamp, a speed to ground, draught, a departure port, a destination port and a pre-arrival time.
3. The method for identifying and warning ship navigation risks as claimed in claim 1, wherein in the data acquisition step, the global navigation real-time risk data comprises global battle area position data, global pirate area position data, global typhoon data and global marine meteorological data, and the ship base data comprises operation subject data.
4. The method for identifying and warning ship navigation risks according to claim 3, wherein in the risk identifying step, the ship navigation risk data comprise ship navigation state risk data, ship navigation time-space risk data and ship navigation weather risk data.
5. The ship navigation risk identification and early warning method according to claim 4, wherein the ship navigation state risk data is obtained by analyzing ship navigation state, speed and draft data; the ship navigation time-space risk data is obtained by analyzing the longitude and latitude, the departure port, the destination port, the departure time and the pre-offset time of a ship and combining the position data of the global special war zone and the position data of the global pirate zone; the ship navigation meteorological risk data are obtained by analyzing the longitude and latitude of the ship and combining the global typhoon data and the global oceanographic data.
6. A ship navigation risk identification and early warning system is characterized by comprising a data acquisition module, a cloud database, a risk identification module, a risk early warning module and a risk visualization module,
the data acquisition module acquires ship AIS data, global shipping real-time risk data and ship database data and uploads the ship AIS data, the global shipping real-time risk data and the ship database data to the cloud database;
the risk identification module identifies and analyzes the AIS data and the global shipping real-time risk data collected into the cloud database, and identifies the ship navigation state risk, the ship navigation time-space risk and the ship navigation weather risk to obtain ship navigation risk data;
the risk early warning module summarizes ship navigation risk data, matches a corresponding ship operation main body by combining ship library data and sends early warning information to the ship operation main body;
the risk visualization module is used for visually monitoring AIS data of ships managed by the ship operation main body in real time and ship navigation risk data.
7. The vessel sailing risk identification and early warning system of claim 6, wherein the risk identification module includes a sailing status risk identification submodule, a sailing spatiotemporal risk identification submodule, and a sailing weather risk identification submodule,
the navigation state risk identification submodule is used for analyzing the AIS data of the ship, including navigation state, navigation speed and draft data, so as to obtain the navigation state risk data of the ship;
the navigation time-space risk identification submodule is used for analyzing the AIS data of the ship, including longitude and latitude, departure port, destination port, departure time and pre-offset time, and combining the global special war zone position data and the global pirate zone position data in the global shipping real-time risk data to obtain the navigation time-space risk data of the ship;
the navigation meteorological risk identification submodule is used for analyzing longitude and latitude data in the ship AIS data and combining global typhoon data and global oceanic meteorological data in the global navigation real-time risk data to obtain the ship navigation meteorological risk data.
8. The system of claim 7, wherein the vessel sailing risk identification submodule comprises a vessel AIS loss identification unit, a vessel sailing state anomaly identification unit and an anchoring overtime identification unit, the sailing space-time risk identification submodule comprises a sailing delay risk identification unit and a special area sailing risk identification unit, and the sailing weather risk identification submodule comprises a typhoon weather risk identification unit and a oceanographic weather risk identification unit.
9. The system of claim 6, wherein the risk visualization module comprises a risk data summary display unit and a ship position data display unit.
10. The vessel navigation risk identification and early warning system of claim 6, wherein the AIS data comprises static data and dynamic data, the static data comprises a vessel mobile service identification code and a vessel name, and the dynamic data comprises vessel longitude and latitude position information, a navigation state, a time stamp, a speed to ground, a draught, a departure port, a destination port and a pre-arrival time;
the global shipping real-time risk data comprises global special war zone position data, global pirate zone position data, global typhoon data and global oceanographic data;
the ship base data includes operation subject data.
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| CN114444315A (en) * | 2022-01-30 | 2022-05-06 | 中远海运科技股份有限公司 | Ship station avoidance route simulation method and system |
| CN115511174A (en) * | 2022-09-22 | 2022-12-23 | 中远海运科技股份有限公司 | Ship risk prediction method and system |
| CN115983627A (en) * | 2022-12-05 | 2023-04-18 | 中远海运散货运输有限公司 | Ship navigation environment risk prediction method and device, electronic equipment and medium |
| CN117037089A (en) * | 2023-10-09 | 2023-11-10 | 亿海蓝（北京）数据技术股份公司 | Method and device for detecting ship unauthorized exit behavior and readable storage medium |
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