KR102513300B1 - Production system of marine environment predictive information for supporting navigation - Google Patents

Abstract

The present invention relates to a system of producing marine environment predictive information for supporting navigation, which can produce and provide integrated marine environment information related to a marine weather information condition around a ship and sea route prediction that affect a ship operation and navigation safety; produce and provide integrated marine environment information unlike an existing numerical prediction system performing prediction and production for each item such as a marine model, a weather model, a wave model, and the like; and produce and provide universe prediction information according to navigation areas and distances. The system of producing marine environment predictive information for supporting navigation according to the present invention is configured to include a prediction material collection and selection unit, a selection material pre-processing unit, a marine environment prediction information production unit, and a marine environment reconstruction unit that includes an artificial intelligence module performing deep learning based on the marine environment prediction information produced from the marine environment prediction information production unit.

Description

Production system of marine environment predictive information for supporting navigation}

The present invention relates to a system for producing marine environment prediction information for navigation support, and more particularly, to produce comprehensive marine environment information related to the situation of maritime weather information around a ship and prediction of sea routes that affect ship operation and navigation safety. However, unlike existing numerical prediction systems that predict and produce each item such as ocean model, meteorological model, and wave model, comprehensive marine environment information can be produced and provided, while general-purpose forecast information according to voyage area and distance can be provided. It relates to a marine environment prediction information production system for navigation support that can be produced and provided.

Due to globalization of the world, multinationalization of production bases, rapid economic growth, and growth of the Chinese economy, the volume of goods transported around the world is continuously increasing.

However, in recent years, water temperature rise and sea level rise due to global warming and various changes in the marine environment are rapidly progressing accordingly.

In other words, the marine environment such as wave height, current, and wave is a very important factor for navigation safety, ship motility, and fuel efficiency of ships, and these marine environments are rapidly changing due to global warming in recent years.

Accordingly, the technology to produce, operate, and support marine environment prediction information for navigation support is more needed and the importance of this is being highlighted. However, the existing numerical prediction model that produces marine environment and forecast information is It is produced and provided by category, and the data format for each item is different, so there is a very limited usability in ships.

In addition, domestic and foreign numerical prediction models have not been verified for their suitability to coastal and maritime conditions in Korea, and information correction and data assimilation processes through actual measurements are required.

In addition, the need to develop selective navigation technology suitable for new industrial trends such as the 4th industrial revolution and carbon neutral / eco-friendly is emerging.

Korean Patent Registration No. 10-2185971 (Announced on December 3, 2020), “Apparatus and method for providing marine weather service” Korean Patent Registration No. 10-1789808 (Announced on October 25, 2017), “Apparatus and Method for Forecasting Ship Operation Index” Korean Patent Registration No. 10-2220748 (published on February 26, 2021), “Ocean prediction system through data assimilation at future time of water temperature time series prediction data using deep learning” Korean Patent Publication No. 10-2022-0071838 (published on May 31, 2022), “Real-time ocean prediction system (KOOS-OPEM) and ocean prediction method using the same”

Embodiments of the present invention produce and provide comprehensive marine environmental information related to forecasts on the sea route and the situation of marine weather information around ships that affect ship operation and navigation safety, but each item such as ocean model, weather model, wave model, etc. Unlike existing numerical prediction systems that are predicted and produced separately, a marine environment prediction information production system for navigation support that can produce and provide comprehensive marine environment information after production and at the same time produce and provide general-purpose forecast information according to the voyage area and distance. provides

In addition, an embodiment of the present invention provides a marine environment prediction information production system for navigation support that can produce and provide marine environment prediction and reproduction information divided into long-term, short-term, and ultra-short periods.

In addition, an embodiment of the present invention provides real-time maritime information prediction data around ships using artificial intelligence prediction techniques, and produces and reproduces marine environment prediction and reproduction information that implements automation of the entire process from information collection to processing, production, and utilization. It provides a marine environment prediction information production system for navigation support that enables safety and efficient navigation of shelf navigation by checking marine environment information not only for large ships but also for small and medium-sized ships.

A marine environment prediction information production system for navigation support according to an embodiment of the present invention collects domestic and foreign numerical prediction information for predicting the marine environment, and selects information to be actually used for marine environment prediction from among the collected numerical prediction information. The collection and storage of numerical prediction information includes the prediction data collection/selection unit, which is automatically performed through scripts and programming, and the numerical prediction information selected in the prediction data collection/selection unit. Selected data pre-processing unit that performs the pre-processing process, and high-resolution and data assimilation are performed on the information pre-processed by the selected data pre-processing unit to produce high-resolution marine environment prediction information, predicting marine environment by long-term and short-term periods It includes a marine environment prediction information production unit that classifies and produces information, and an artificial intelligence module that performs deep learning based on the marine environment prediction information produced by the marine environment prediction information production unit. Based on the AI information generated through learning and the short-term marine environment prediction information produced by the marine environment prediction information production unit, marine environment reproduction that produces ultra-short, short-term, and long-term marine environment reproduction information centered on the current location of the ship through data assimilation An information production unit may be included.

In addition, the system for producing marine environment prediction information for navigation support according to an embodiment of the present invention is installed on a ship, and sends sensing information for ultra-short-term marine environment prediction for production of the ultra-short-term marine environment reproduction information during the navigation of the ship at a preset period. (hereinafter referred to as “operation cycle”), and big data for ship navigation safety based on the ultra-short-term marine environment prediction sensing information transmitted from the ship-mounted complex sensing device and the ship-mounted complex sensing device. A big data unit that divides and generates the big data for navigation safety for each ship type set in advance based on the weight, volume, displacement, and material of the ship, and the ship-mounted type of the ship at the same time as being mounted on the ship The operation server of the big data part in real time by including identification information indicating the type of vessel in the sensing information for ultra-short-term marine environment prediction obtained according to the operation cycle in the complex sensing device (hereinafter referred to as “big data operation server”) and transmits a big data request signal including identification information indicating the type of ship to the big data operation server, and deep learning based on the big data for ship navigation safety transmitted from the big data operation server A ship artificial intelligence module that performs real-time generation of AI ultra-short-term prediction information, and a display panel installed in the ship's control room and displaying the AI short-term prediction information generated and output from the ship's artificial intelligence module of the ship on the screen. can do.

In addition, the ship-mounted complex sensing device includes a housing in which a first entrance for drone access and a second entrance for CCTV camera access are formed on the upper surface, respectively, and a first entrance installed in the housing for automatic opening and closing of the first entrance. 1 opening and closing door, and a second opening and closing door installed in the housing for automatic opening and closing of the second entrance, and installed inside the housing, X for observing waves in all directions in the north, south, east and west based on the current position of the ship -Band radar (hereinafter referred to as “wave observation radar”), an absolute position detection sensor, and an autonomous flight control module are mounted on the drone body, and the autonomous flight control module is based on the detection signal of the absolute position detection sensor. An autonomous flight mode is set in advance to sequentially fly from the center of the ship to a predetermined observation position in the east, west, north, south, and at the same time, and stop for a predetermined time for each observation position, the operation period of the ship-mounted complex sensing device According to this, a wave observation drone for sequentially locating the drone body at the observation position so that wave data through the wave observation radar for each observation position is observed, and installed inside the housing and at the same time through the second entrance It includes a lifting and lowering driving unit for withdrawing to the outside of the housing and retracting into the housing, and is operated according to the operation cycle of the ship-mounted complex sensing device to observe waves around the ship and other visual observation images. A CCTV camera device for obtaining information, a wind direction anemometer mounted outside the housing to detect wind direction and speed around the ship, and the first and second sensors according to the operation cycle of the ship-mounted complex sensing device. Main for operating the opening/closing door in an open state for a preset time, and transmitting the observation data obtained from the wave observation drone, CCTV camera device, and wind direction anemometer to the big data operation server in real time as sensing information for predicting the ultra-short-term marine environment. A control module may be included.

According to an embodiment of the present invention, comprehensive marine environmental information related to the forecast of the maritime weather information situation and route around the ship, which affects ship operation and navigation safety, is produced and provided, such as a marine model, a weather model, a wave model, etc. Unlike existing numerical prediction systems that predict and produce each item, comprehensive marine environment information can be provided after production, and at the same time, general-purpose forecast information according to voyage area and distance can be produced and provided.

In addition, marine environment prediction and reproduction information can be produced and provided in the long term, short term and ultra short term.

In addition, it is possible to produce and provide marine environment prediction and reproduction information that realizes automation of the entire process from information collection to processing, production, and utilization of real-time marine information prediction data around ships using artificial intelligence prediction techniques. It is possible to improve the safety and efficient navigation of shelf navigation by checking marine environmental information not only for ships but also for small and medium-sized ships.

1 is a block diagram illustrating a marine environment prediction information production system for navigation support according to an embodiment of the present invention.
2 is a diagram illustrating an example of data collection by a prediction data collection/selection unit in a marine environment prediction information production system for navigation support according to an embodiment of the present invention.
3 is a diagram illustrating an example of performing re-gridation of a selection data pre-processing unit in a marine environment prediction information production system for navigation support according to an embodiment of the present invention.
4 is a diagram illustrating an example of high-resolution performance of a marine environment prediction information production unit in a marine environment prediction information production system for navigation support according to an embodiment of the present invention.
5 is a diagram illustrating the production of AI ultra-short-term prediction information of the marine environment reproduction information production unit in the marine environment prediction information production system for navigation support according to an embodiment of the present invention.
6 is a diagram illustrating production of final information through information fusion of a marine environment reproduction information production unit in a marine environment prediction information production system for navigation support according to an embodiment of the present invention.
7 is a diagram illustrating that marine environment prediction information is sequentially produced and utilized in the order of long term, short term and ultra short term by the marine environment prediction information production system for navigation support according to an embodiment of the present invention.
8 is a diagram comparing techniques for producing marine environment prediction information in a marine environment prediction information production system for navigation support according to an embodiment of the present invention.
9 is a diagram illustrating an example of verifying the accuracy of the produced marine environment reproduction information in the marine environment prediction information production system for navigation support according to an embodiment of the present invention.
10 is a schematic diagram showing information collection, processing, and production processes of a marine environment prediction information production system for navigation support according to an embodiment of the present invention.
11 is a block diagram illustrating an example in which some components are added to a marine environment prediction information production system for navigation support according to an embodiment of the present invention.
Fig. 12 is a side view illustrating the mechanical configuration of the further configuration according to Fig. 11;
13 is a view schematically illustrating an example of operation of a drone for wave observation in the additional configuration according to FIG. 11

The detailed description of the present invention below refers to the accompanying drawings shown as examples of embodiments in which the present invention can be practiced. These embodiments are described in detail so that those skilled in the art will be able to practice the present invention. It should be understood that the various embodiments of the present invention are different, but need not be mutually exclusive. For example, specific shapes, structures, and characteristics described herein may be implemented in one embodiment in another embodiment without departing from the spirit and scope of the invention. Additionally, it should be understood that the location or arrangement of individual components within each described embodiment may be changed without departing from the spirit and scope of the invention.

Accordingly, the detailed description set forth below is not to be taken in a limiting sense, and the scope of the present invention, if properly described, is limited only by the appended claims, along with all equivalents as claimed by those claims. Like reference numbers in the drawings indicate the same or similar function throughout the various aspects.

The terms used in the present invention have been selected from general terms that are currently widely used as much as possible while considering the functions in the present invention, but these may vary depending on the intention of a person skilled in the art or precedent, the emergence of new technologies, and the like. In addition, in a specific case, there is also a term arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description of the invention. Therefore, the term used in the present invention should be defined based on the meaning of the term and the overall content of the present invention, not simply the name of the term.

In the invention, when a certain part “includes” a certain component in the whole, this means that it may further include other components, rather than excluding other components, unless otherwise stated. In addition, as described in the specification, "... wealth", "… A term such as “module” refers to a unit that processes at least one function or operation, which may be implemented as hardware or software or a combination of hardware and software.

A marine environment prediction information production system for navigation support according to an embodiment of the present invention will be described with reference to FIGS. 1 to 13 .

1 is a block diagram illustrating a system for producing marine environment prediction information for navigation support according to an embodiment of the present invention.

As shown, the marine environment prediction information production system for navigation support according to an embodiment of the present invention includes a prediction data collection/selection unit 100, a selection data preprocessing unit 200, a marine environment prediction information production unit 300, and a marine environment prediction information production unit 300. It is configured to include an environment reproduction information production unit 400 .

The prediction data collection/selection unit 100 collects domestic and foreign numerical prediction information for predicting the marine environment, and selects information to be actually used for marine environment prediction from among the collected numerical prediction information. At this time, the collection and storage of numerical prediction information in the prediction data collection/selection unit 100 is automatically performed through scripts and programming.

Referring to FIG. 2, the prediction data collection/selection unit 100 collects numerical prediction information from the Korea Meteorological Administration, CMEMS, and HYCOM, etc., and predicts the marine environment by considering the forecast period, resolution, items, and accuracy among the numerical prediction information collected in this way. Select the information to be used in practice.

In other words, the prediction data collection/selection unit 100 collects domestic and foreign numerical prediction information, which is original information for prediction of the marine environment, and then analyzes the accuracy and usability of the collected numerical prediction information, and the analysis results According to this, the actual utilization information to be used for marine environment prediction is selected.

The selection data pre-processing unit 200 performs pre-processing of re-grid, format and coordinate change, and resolution unification for the numerical prediction information selected in the prediction data collection/selection unit 100.

Referring to FIG. 3 , the selected data pre-processing unit 200 performs coordinate transformation through re-griding.

The marine environment prediction information production unit 300 performs high resolution and data assimilation on the information preprocessed by the selected data preprocessing unit 200 to produce high resolution marine environment prediction information. At this time, the marine environment prediction information production unit 300 divides and produces long-term and short-term marine environment prediction information. In addition, high-resolution information in the marine environment prediction information production unit 300 uses technically proven high-resolution techniques such as ESMF and DAPPER.

4 illustrates the resolution of the marine environment prediction information production unit 300 in progress.

And in this embodiment, the marine environment prediction information production unit 300 produces long-term marine environment prediction information at 5-day prediction, 10 km grid, and 3-hour intervals, and produces short-term marine environment prediction information at 1-day prediction, 2 km grid, and 1 Production at time intervals has been exemplified, but the present invention is not limited thereto.

In addition, it is desirable to establish an uninterrupted operating system of the marine environment prediction information production unit 300, and for this purpose, an automated operating system capable of coping with non-reception and errors was established.

The marine environment reproduction information production unit 400 includes an artificial intelligence module 410 that performs deep learning based on the marine environment prediction information produced by the marine environment prediction information production unit 300 . In addition, the marine environment reproduction information production unit 400 performs data assimilation based on the AI information generated through learning of the artificial intelligence module 410 and the short-term marine environment prediction information produced by the marine environment prediction information production unit 300. It produces ultra-short, short-term, and long-term marine environment reproduction information centered on the current location.

Referring to FIGS. 5 and 6 , the marine environment reproduction information production unit 400 produces AI ultra-short term prediction information, and at this time, the AI ultra-short term prediction information is produced through the ship's own production module. In other words, it produces route unit prediction information that combines ship observation information such as blue radar, CCTV images, and complex sensing devices with artificial intelligence techniques.

In addition, the marine environment reproduction information production unit 400 produces vessel transmission, standardization, and final information of long-term and short-term prediction information, and utilizes a general-purpose waterway data model (S-100) for transmission speed improvement and standardization, and AI-based Convergence of ultra-short-term forecast information and long-term and short-term forecast information is performed.

And, in the present embodiment, reproduction of the marine environment in a 4 km area around the ship is taken as an example, but the present invention is not limited thereto.

7 illustrates that marine environment prediction information is sequentially produced and utilized in the order of long-term, short-term, and ultra-short term by the system for producing marine environment prediction information for navigation support according to an embodiment of the present invention.

8 is a diagram comparing techniques for producing marine environment prediction information, and FIG. 9 is a diagram illustrating an example of verifying the accuracy of the produced marine environment reproduction information.

10 is a schematic diagram showing information collection, processing, and production processes of the marine environment prediction information production system for navigation support according to an embodiment of the present invention.

With the configuration described above, it is possible to produce and provide comprehensive marine environment information related to forecasts on the sea route and conditions of maritime weather information (sea level, waves, sea wind, etc.) around the ship that affect ship operation and navigation safety. .

In addition, unlike existing numerical prediction systems that predict and produce each item, such as ocean models, meteorological models, and wave models, comprehensive marine environment information can be produced and provided.

In addition, it is possible to produce and provide general-purpose forecast information according to the voyage area and distance.

In addition, marine environment reproduction information is produced and provided, and this marine environment reproduction information includes long-term prediction information for navigation of more than one day, long-term prediction information of 5-day prediction, 3-hour interval, and 9km interval prediction, and Short-term forecast information for navigation, short-term forecast information for 1-day forecast, 1-hour interval, and 2km interval forecast, and ultra-short-term forecast information for real-time route setting and navigation safety, 5-minute forecast, and ultra-short-term forecast information for 3km radius forecast It can be separately produced and provided.

In addition, it is possible to produce and correct prediction information using numerical prediction models, observation information, in-ship sensors and image information.

In addition, it will be possible to provide real-time maritime information prediction data around ships using artificial intelligence prediction techniques.

In addition, it will be possible to produce and provide marine environment prediction and reproduction information that can be automated in the entire process from information collection to processing, production, and utilization.

In addition, it is possible to improve safety and efficient navigation of shelf navigation by checking marine environmental information not only for large ships but also for small and medium-sized ships.

Next, with reference to FIGS. 11 to 13, an example in which some components are added to the marine environment prediction information production system for navigation support according to an embodiment of the present invention will be described.

11 is a block configuration diagram illustrating an example in which some components are added to a marine environment prediction information production system for navigation support according to an embodiment of the present invention, and FIG. 12 is a side view illustrating a mechanical configuration of the additional configuration according to FIG. 11 13 is a diagram schematically illustrating an example of operation of a drone for wave observation in the additional configuration according to FIG. 11.

As shown, the marine environment prediction information production system for navigation support according to an embodiment of the present invention includes a ship-mounted complex sensing device 500, a big data unit 600, a ship artificial intelligence module 700, and a display panel ( 800) may be further included.

The ship-mounted complex sensing device 500 is installed on a ship, and the ship-mounted complex sensing device 500 produces the ultra-short-term marine environment reproduction information described above in the description with reference to FIGS. 1 to 10 while the ship is sailing. It automatically generates sensing information for ultra-short-term marine environment prediction according to a preset cycle (hereinafter referred to as “operation cycle”). And the detailed configuration of the ship-mounted complex sensing device 500 will be described in more detail later.

The big data unit 600 generates big data for ship navigation safety based on the ultra-short-term marine environment prediction sensing information transmitted from the ship-mounted complex sensing device 500, and measures the weight, volume, displacement, and material of the ship. As a reference, the big data for ship navigation safety is divided and generated for each type of ship set in advance.

The ship artificial intelligence module 700 is mounted on the ship and at the same time, identification information for displaying the type of ship in the ultra-short-term marine environment prediction sensing information obtained according to the operating cycle from the ship-mounted complex sensing device 500 of the ship. is included and transmitted to the operation server of the big data unit (hereinafter referred to as “big data operation server 650”) in real time. In addition, the vessel artificial intelligence module 700 transmits a big data request signal including identification information indicating the type of vessel to the big data operation server 650, and the ship navigation safety transmitted from the big data operation server 650 Deep learning is performed based on big data for AI to generate ultra-short-term prediction information in real time.

The display panel 800 is installed in the control room of the ship, and displays the AI short-term prediction information generated and output from the ship artificial intelligence module 700 of the ship.

In addition, the ship-mounted complex sensing device 500 includes a housing 510, a first opening and closing door 520 and a second opening and closing door 530, a drone for wave observation 540, a CCTV camera device 550, and an anemometer ( 560) and a main control module 570.

The housing 510 has a first entrance 511 for drone access and a second entrance 512 for CCTV camera access, respectively.

The first opening and closing door 520 is installed in the housing 510 for automatic opening and closing of the first entrance 511, and the second opening and closing door 530 is installed in the housing 510 for automatic opening and closing of the second entrance 512. installed on In addition, the configuration in which the first opening and closing door 520 and the second opening and closing door 530 are installed in the housing 510 so as to be automatically opened and closed can be implemented in various forms through known technologies, and in this embodiment, Detailed description and illustration are omitted.

The wave observation drone 540 is installed inside the housing 510, and the wave observation drone 540 is an X-band radar (hereinafter referred to as “X-band radar”) for observing waves in all directions based on the current position of the ship. The wave observation radar 542”), the absolute position sensor 543, and the autonomous flight control module 544 are mounted on the drone body 541.

In addition, the autonomous flight control module 544 of the drone 540 for wave observation moves the drone body 541 sequentially from the center of the ship to a predetermined observation position in the north, south, east and west based on the detection signal of the absolute position sensor 543. An autonomous flight mode is set in advance to stop for a preset time for each observation position at the same time as it flies. Accordingly, the autonomous flight control module 544 sequentially positions the drone body 541 at the observation position according to the operation cycle of the ship-mounted complex sensing device 500 and uses the wave observation radar 542 for each observation position. so that the wave data through the

The CCTV camera device 550 is installed inside the housing 510, and at the same time, the lifting driving unit 551 for withdrawing to the outside of the housing 510 through the second entrance 512 and retracting into the housing 510 It is composed of. In addition, since the lift driver 551 of the CCTV camera device 550 can be implemented in various forms through known technologies, a detailed description thereof is omitted in the present embodiment, and is briefly shown in a telescopic form in the drawings. And this CCTV camera device 550 is operated according to the operation cycle of the ship-mounted complex sensing device 500 to acquire image information for wave observation and other visual observations around the ship.

The wind direction anemometer 560 is mounted on the outside of the housing 510 to detect the wind direction and speed around the ship.

The main control module 570 operates the first and second opening and closing doors 520 and 530 in an open state for a preset time according to the operation cycle of the ship-mounted complex sensing device 500, and the drone 540 for wave observation And the observation data obtained from the CCTV camera device 550 and the wind direction anemometer 560 are transmitted in real time to the big data operation server 650 as sensing information for predicting the marine environment in the short term.

With the above-described configuration, sensing information for ultra-short-term marine environment prediction for navigational safety of ships is commonly acquired from the same ship type for each ship type, and based on this, big data generated for each ship type and deep learning for each ship type. Through the artificial intelligence module, ultra-short-term prediction information for navigation safety is provided for each ship in real time between each voyage by ship type, and accordingly, various types of ships navigate while receiving AI ultra-short-term prediction information suitable for them in real time, Significant increases in navigational safety are possible.

As described above, in the present description, specific details such as specific components and limited embodiments and drawings have been described, but this is only provided to help a more general understanding of the present invention, and the present invention is not limited to the above embodiments. No, and those skilled in the art can make various modifications and variations from these descriptions.

Therefore, the spirit of the present invention should not be limited to the described embodiments and should not be defined, and all things that have modifications equivalent or equivalent to these claims as well as the claims described below will fall within the scope of the spirit of the present invention.

100: prediction data collection/selection department 200: selection data pre-processing unit
300: marine environment prediction information production unit 400: marine environment reproduction information production unit
410: artificial intelligence module 500: ship-mounted complex sensing device
510: housing 511: first entrance
512: second entrance 520: first opening and closing door
530: second opening and closing door 540: drone for blue observation
541: drone body 542: blue observation radar
543: absolute position sensor 544: autonomous flight control module
550: CCTV camera device 560: wind direction anemometer
570: main control module 600: big data unit
650: Big data operation server 700: Artificial intelligence module for ships
800: display panel

Claims (2)

delete A ship-mounted complex sensing device 500 installed on a ship and automatically generating sensing information for predicting the marine environment during the ship's voyage according to a preset cycle (hereinafter referred to as "operation cycle");
Based on the sensing information for predicting the marine environment transmitted from the ship-mounted complex sensing device 500, big data for ship navigation safety is generated, and each ship type is preset based on the weight, volume, displacement, and material of the ship. a big data unit 600 that divides and generates the big data for ship navigation safety;
At the same time, the ship-mounted complex sensing device 500 of the ship includes the identification information indicating the type of ship in the sensing information for predicting the marine environment, which is obtained according to the operation cycle, and stores the big data in real time. It is transmitted to the operation server (hereinafter referred to as “big data operation server 650”), and a big data request signal including identification information indicating the type of ship is transmitted to the big data operation server 650, and the big data operation server 650 A ship artificial intelligence module 700 that generates AI ultra-short-term prediction information in real time by performing deep learning based on the big data for ship navigation safety transmitted from the data operation server 650: and
It is installed in the control room of the ship and includes a display panel 800 for displaying the AI ultra-short-term prediction information generated and output from the ship artificial intelligence module 700 of the ship,
The ship-mounted complex sensing device 500,
A housing 510 in which a first entrance 511 for drone access and a second entrance 512 for CCTV camera access are formed on the upper surface, respectively;
A first opening/closing door 520 installed in the housing 510 to automatically open and close the first entrance 511;
a second opening/closing door 530 installed in the housing 510 to automatically open and close the second entrance 512;
Installed inside the housing 510, X-band radar (hereinafter referred to as “wave observation radar 542”) and absolute position sensor (hereinafter referred to as “wave observation radar 542”) for observing waves in all directions based on the current position of the ship 543) and autonomous flight control module 544 are mounted on the drone body 541, and the autonomous flight control module 544 controls the drone body 541 based on the detection signal of the absolute position sensor 543. An autonomous flight mode is set in advance to sequentially fly from the center of the ship to a predetermined observation position in the east, west, north, south, and at the same time stop for a predetermined time for each observation position, so that the ship-mounted complex sensing device 500 A wave observation drone 540 for observing wave data through the wave observation radar 542 for each observation position while sequentially positioning the drone body 541 at the observation positions according to an operating cycle;
It is installed inside the housing 510 and at the same time includes a lift drive unit 551 for withdrawing to the outside of the housing 510 through the second entrance 512 and retracting into the inside of the housing 510, , CCTV camera device 550 that is operated according to the operation cycle of the ship-mounted complex sensing device 500 to obtain image information for wave observation and other visual observations around the ship;
An anemometer 560 mounted outside the housing 510 to sense wind direction and speed around the vessel; and
According to the operating cycle of the ship-mounted complex sensing device 500, the first and second opening and closing doors 520 and 530 are operated in an open state for a preset time, and the wave observation drone 540 and CCTV camera device (550) and a main control module (570) for real-time transmission of the observation data obtained from the anemometer (560) to the big data operation server (650) as sensing information for predicting the marine environment. Environmental predictive information production system.

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