Marine traffic intelligent supervision method and device, electronic equipment and storage medium

Abstract

The invention discloses a marine traffic intelligent supervision method and device, electronic equipment and a storage medium, and relates to the technical field of marine traffic supervision or other related fields, and the method comprises the steps: obtaining the operation state data, including static state data and dynamic state data, of all ships in a supervision region, and performing operation situation analysis on the supervision area based on the operation state data, dividing the operation state data into multiple groups of sub-operation state data, inputting the sub-operation state data into corresponding operation situation analysis sub-models to obtain multiple risk situation assessment values, and performing fusion processing on the risk situation assessment values to obtain an operation situation analysis result. And when the operation situation analysis result meets a target condition, main view angle video data of the target ship associated with the operation situation analysis result is acquired, and the main view angle video data is displayed through a maritime traffic intelligent supervision platform. According to the invention, a technical problem of low supervision efficiency caused by dependence of a maritime traffic supervision platform on a two-dimensional monitoring picture in the prior art is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of maritime traffic supervision or other related fields, and in particular to a method and device for intelligent maritime traffic supervision, an electronic device and a storage medium. Background Art

[0002] Maritime traffic supervision is a key area for maintaining marine transportation safety, promoting trade circulation and protecting the marine environment. With the continuous growth of global trade, the use density of ocean waterways is increasing, and the demand for real-time monitoring and intelligent scheduling of ships is becoming more urgent. Maritime traffic supervision mainly relies on radar monitoring, ship automatic identification system (AIS) data and satellite images. By obtaining basic information such as the dynamic position, heading and speed of the ship, it assesses the maritime traffic situation and then dispatches and manages each ship.

[0003] In the related technologies, existing maritime traffic supervision strategies have limitations. For example, existing maritime traffic supervision strategies mainly rely on two-dimensional plane monitoring methods, lacking an intuitive presentation of the ship's surrounding environment and on-site conditions. Especially in sections with dense ships, it is difficult for supervisors to accurately judge the relative positions and dynamics between ships, as well as possible visual occlusions or sudden dangers. At the same time, the existing maritime traffic supervision strategies are limited to the generation of augmented reality interfaces for the use of ship camera data, and fail to effectively integrate with the ship dynamic information in the two-dimensional nautical chart, especially when the ship camera data is missing or cannot be obtained, and cannot provide a complete on-site situation view, which limits the decision-making ability of supervisors when facing complex traffic conditions at sea.

[0004] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0005] The embodiments of the present invention provide a method and device for intelligent monitoring of maritime traffic, an electronic device and a storage medium, so as to at least solve the technical problem in the related art that the maritime traffic monitoring platform relies on a two-dimensional monitoring screen, resulting in low monitoring efficiency.

[0006] According to one aspect of an embodiment of the present invention, a method for intelligent supervision of maritime traffic is provided, comprising: obtaining operating status data of all ships in a supervision area, wherein the operating status data comprises: static status data and dynamic status data, wherein the static status data comprises physical properties of the ship, and the dynamic status data comprises operating information of the ship during navigation; performing an operation situation analysis on the supervision area based on the operation status data, dividing the operation status data into multiple groups of sub-operation status data, inputting each group of sub-operation status data into a corresponding operation situation analysis sub-model to obtain multiple risk situation assessment values, and fusing the risk situation assessment values ​​to obtain an operation situation analysis result; when the operation situation analysis result meets a target condition, obtaining main-perspective video data of a target ship associated with the operation situation analysis result, wherein the target condition comprises: a target threshold; and displaying the main-perspective video data through a maritime traffic intelligent supervision platform.

[0007] Optionally, the step of acquiring static status data of each ship in the regulatory area includes: when it is detected that the ship enters a first trigger area corresponding to the regulatory area, sending a first acquisition signal to the ship, wherein the first trigger area includes the regulatory area; receiving static status data fed back by the ship based on the first acquisition signal, wherein the static status data includes: ship identity information, ship regulation information, the ship identity information includes: ship code ID, ship owner information, and the ship regulation information includes: ship specifications and types of cargo carried.

[0008] Optionally, the step of acquiring dynamic status data of each ship in the supervision area includes: sending a second acquisition signal to the ship when the ship enters the supervision area; receiving dynamic status data fed back by the ship based on the second acquisition signal, wherein the dynamic status data includes: the latitude and longitude, heading, and ship speed of the ship.

[0009] Optionally, the step of fusing the risk situation assessment values ​​includes: normalizing all risk situation assessment values, wherein the risk situation assessment values ​​include: collision risk assessment values, congestion risk assessment values, failure risk assessment values ​​and communication risk assessment values; determining the weight of each risk situation assessment value based on the historical occurrence probability of each risk type, wherein the risk types include: collision risk, congestion risk, failure risk and communication risk; performing weighted calculation on all risk situation assessment values ​​and corresponding weights to obtain an operation situation analysis result.

[0010] Optionally, when the operation situation analysis result meets the target condition, the step of obtaining the main perspective video data of the target ship associated with the operation situation analysis result includes: when the operation situation analysis result is greater than the target threshold in the target condition, parsing the operation situation analysis result to determine the target ship, wherein the target threshold is set in advance; obtaining the main perspective video data of the target ship, wherein the main perspective video data refers to the video data captured by the camera on the target ship.

[0011] Optionally, after obtaining the main-perspective video data of the target ship associated with the operation status analysis result, the method further includes: extracting the video status data of all ships from the main-perspective video data; matching the video status data with the operation status data to determine the missing operation status data, wherein the missing operation status data refers to the ship status data that exists in the operation status data but does not exist in the video status data; constructing virtual video operation data based on the missing operation status data, and filling the virtual video operation data in the position indicated by the missing operation status data in the main-perspective video data.

[0012] Optionally, the step of displaying the main-perspective video data through the intelligent maritime traffic supervision platform includes: after acquiring the main-perspective video data, uploading the main-perspective video data to the intelligent maritime traffic supervision platform, and the intelligent maritime traffic supervision platform displays the main-perspective video in real time; or, after acquiring the main-perspective video data, uploading the main-perspective video data to the intelligent maritime traffic supervision platform for storage, and after receiving a viewing command initiated by an external terminal, the intelligent maritime traffic supervision platform displays the main-perspective video.

[0013] According to another aspect of an embodiment of the present invention, there is also provided a maritime traffic intelligent supervision device, comprising: a first acquisition unit, for acquiring operating status data of all ships in a supervision area, wherein the operating status data comprises: static status data and dynamic status data, the static status data comprises physical properties of the ship, and the dynamic status data comprises operating information of the ship during navigation; an analysis unit, for performing an operating situation analysis on the supervision area based on the operating status data, dividing the operating status data into multiple groups of sub-operating status data, inputting each group of sub-operating status data into a corresponding operating situation analysis sub-model, obtaining multiple risk situation assessment values, and fusing the risk situation assessment values ​​to obtain an operating situation analysis result; a second acquisition unit, for acquiring the main perspective video data of a target ship associated with the operating situation analysis result when the operating situation analysis result meets a target condition, wherein the target condition comprises: a target threshold; a display unit, for displaying the main perspective video data through a maritime traffic intelligent supervision platform.

[0014] Optionally, the first acquisition unit includes: a first sending module, used to send a first acquisition signal to the ship when it is detected that the ship enters a first trigger area corresponding to the regulatory area, wherein the first trigger area includes the regulatory area; a first receiving module, used to receive static status data fed back by the ship based on the first acquisition signal, wherein the static status data includes: ship identity information, ship regulation information, the ship identity information includes: ship code ID, ship owner information, and the ship regulation information includes: ship specifications and cargo types.

[0015] Optionally, the first acquisition unit also includes: a second sending module, used to send a second acquisition signal to the ship when the ship enters the regulatory area; a second receiving module, used to receive dynamic status data fed back by the ship based on the second acquisition signal, wherein the dynamic status data includes: the latitude and longitude, heading, and ship speed of the ship.

[0016] Optionally, the analysis unit includes: a normalization module, used to normalize all risk situation assessment values, wherein the risk situation assessment values ​​include: collision risk assessment value, congestion risk assessment value, failure risk assessment value and communication risk assessment value; a determination module, based on the historical occurrence probability of each risk type, determines the weight of each risk situation assessment value, wherein the risk types include: collision risk, congestion risk, failure risk and communication risk; a calculation module, used to perform weighted calculation on all risk situation assessment values ​​and corresponding weights to obtain an operation situation analysis result.

[0017] Optionally, the second acquisition unit includes: a parsing module, used to parse the operation situation analysis result to determine the target ship when the operation situation analysis result is greater than the target threshold in the target condition, wherein the target threshold is pre-set; an acquisition module, used to acquire the main perspective video data of the target ship, wherein the main perspective video data refers to the video data captured by the camera on the target ship.

[0018] Optionally, the second acquisition unit also includes: an extraction module, which is used to extract the video status data of all ships from the main-view video data after acquiring the main-view video data of the target ship associated with the operation status analysis result; a matching module, which is used to match the video status data with the operation status data to determine the missing operation status data, wherein the missing operation status data refers to the ship status data that exists in the operation status data but does not exist in the video status data; a filling module, which constructs virtual video operation data based on the missing operation status data, and fills the virtual video operation data in the position indicated by the missing operation status data in the main-view video data.

[0019] Optionally, the display unit includes: a first display module, which is used to upload the main-perspective video data to the intelligent maritime traffic supervision platform after acquiring the main-perspective video data, and the intelligent maritime traffic supervision platform displays the main-perspective video in real time; a second display module, which is used to upload the main-perspective video data to the intelligent maritime traffic supervision platform for storage after acquiring the main-perspective video data, and the intelligent maritime traffic supervision platform displays the main-perspective video after receiving a viewing command initiated by an external terminal.

[0020] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided, wherein the computer-readable storage medium includes a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the above-mentioned methods for intelligent maritime traffic supervision.

[0021] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement any one of the above-mentioned methods for intelligent maritime traffic supervision.

[0022] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the steps of any one of the above-mentioned methods for intelligent supervision of maritime traffic are implemented.

[0023] In the present disclosure, by obtaining the operation status data of all ships in the supervision area, the operation situation analysis of the supervision area is performed based on the operation status data, the operation status data is divided into multiple groups of sub-operation status data, each group of sub-operation status data is input into the corresponding operation situation analysis sub-model, and multiple risk situation assessment values ​​are obtained. The risk situation assessment values ​​are fused to obtain the operation situation analysis results. When the operation situation analysis results meet the target conditions, the main perspective video data of the target ship associated with the operation situation analysis results is obtained, and finally the main perspective video data is displayed through the intelligent supervision platform for maritime traffic for supervision personnel to view. The supervision of maritime traffic in the present disclosure is not limited to the viewing method of the two-dimensional supervision plane, but is combined with the two-dimensional supervision plane to display the main perspective video data of the ship when the target conditions are met, thereby improving the intuitiveness and efficiency of maritime traffic supervision, and thus solving the technical problem that the maritime traffic supervision platform in the related technology relies on the two-dimensional monitoring screen, resulting in low supervision efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0025] Figure 1 is a flow chart of an optional method for intelligent supervision of maritime traffic according to an embodiment of the present invention;

[0026] Figure 2 is a schematic diagram of an optional intelligent marine traffic monitoring device according to an embodiment of the present invention;

[0027] Figure 3 The present invention is a hardware structure block diagram of an electronic device (or mobile device) for executing a method for intelligent monitoring of maritime traffic according to an embodiment of the present invention. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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 should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0030] It should be noted that the method and device for intelligent supervision of maritime traffic in the present disclosure can be used in the field of maritime traffic supervision technology to carry out intelligent supervision of maritime traffic, and can also be used in any field outside the field of maritime traffic supervision technology to carry out intelligent supervision of maritime traffic. The present disclosure does not limit the application field of the method and device for intelligent supervision of maritime traffic.

[0031] The following embodiments of the present invention can be applied to various systems / applications / devices for intelligent supervision of maritime traffic. The present invention obtains the operating status data of all ships in the supervision area, performs an operating situation analysis on the supervision area based on the operating status data, divides the operating status data into multiple groups of sub-operating status data, inputs each group of sub-operating status data into the corresponding operating situation analysis sub-model, obtains multiple risk situation assessment values, fuses the risk situation assessment values, obtains the operating situation analysis results, and obtains the main perspective video data of the target ship associated with the operating situation analysis results when the operating situation analysis results meet the target conditions. Finally, the main perspective video data is displayed through the intelligent supervision platform for maritime traffic for supervision personnel to view. The supervision of maritime traffic by the present invention is not limited to the viewing method of the two-dimensional supervision plane, but is combined with the two-dimensional supervision plane to display the main perspective video data of the ship when the target conditions are met, thereby improving the intuitiveness and efficiency of maritime traffic supervision.

[0032] The present invention is described in detail below in conjunction with various embodiments.

[0033] Embodiment 1

[0034] According to an embodiment of the present invention, an embodiment of a method for intelligent supervision of maritime traffic is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0035] Figure 1 is a flow chart of an optional method for intelligent supervision of marine traffic according to an embodiment of the present invention, such as Figure 1 As shown, the method comprises the following steps:

[0036] Step S101, obtaining the operating status data of all ships in the supervision area, wherein the operating status data includes: static status data and dynamic status data, the static status data includes the physical properties of the ship, and the dynamic status data includes the operating information of the ship during navigation.

[0037] The embodiment of the present invention first obtains the operating status data of all ships in the supervision area, with the aim of comprehensively grasping the navigation conditions of all ships in the supervision area to achieve more accurate and efficient traffic management, wherein the supervision area refers to the area supervised by the maritime traffic management agency, and the operating status data mainly consists of two parts: static status data and dynamic status data, which respectively provide the inherent attributes of the ship and real-time navigation status information.

[0038] Step S102, performing an operation situation analysis on the supervision area based on the operation status data, dividing the operation status data into multiple groups of sub-operation status data, inputting each group of sub-operation status data into a corresponding operation situation analysis sub-model, obtaining multiple risk situation assessment values, and fusing the risk situation assessment values ​​to obtain an operation situation analysis result.

[0039] After obtaining the operation status data, the operation status analysis of the supervision area is carried out. This process not only requires processing a large amount of operation status data, but also assessing the risks of maritime traffic from multiple dimensions to ensure that the maritime traffic intelligent supervision platform can fully understand and effectively respond to complex situations in the supervision area.

[0040] The embodiment of the present invention pre-builds multiple operation status analysis sub-models, which can respectively realize the operation status analysis of collision risk, congestion risk, failure risk, communication risk, etc., and obtain the corresponding risk status assessment value. Among them, the collision risk refers to the risk of collision between ships, ships and reefs, buoys, lighthouses, etc., the congestion risk refers to the risk of ship traffic congestion in the supervision area, the failure risk refers to the risk of equipment failure, fuel leakage, cargo leakage or capsizing in the sea water, etc. of the ship itself, and the communication risk refers to the risk of instability, link breakage, link congestion, etc. of the communication link between the ship in the supervision area and the intelligent supervision platform for maritime traffic.

[0041] At the same time, the embodiment of the present invention pre-constructs an association table between each operation situation analysis sub-model and the corresponding input data type. The association table records which operation status data each operation situation analysis sub-model needs to input. The input data corresponding to a single operation situation analysis sub-model can be one or more of dynamic status data and static status data. Based on the pre-constructed association table, the embodiment of the present invention divides the operation status data into multiple groups of sub-operation status data, and inputs each group of sub-operation status data into the corresponding operation situation analysis sub-model, and outputs multiple risk situation assessment values.

[0042] For example, for the collision risk sub-model, by inputting the latitude and longitude, heading and speed of the ship, combined with the operating status data of the surrounding ships, the possibility of the ship colliding is evaluated, and then the collision risk assessment value is obtained. For the congestion risk sub-model, by inputting the ship density in the supervision area, the ship speed and heading of the ship, the possibility of the ship being in traffic congestion is evaluated, and then the congestion risk assessment value is obtained. For the fault risk sub-model, by inputting the operating status of the ship's equipment, the possibility of equipment failure is evaluated, and then the fault risk assessment value is obtained. For the communication risk sub-model, by inputting the communication link status between the ship and the intelligent maritime traffic supervision platform and other ships, the probability of communication interruption or information delay is evaluated, and then the communication risk assessment value is obtained. The operation status analysis sub-model can be a deep learning model. Each operation status sub-model is based on a pre-built algorithm to analyze the risks of maritime traffic from different angles and obtain a variety of risk situation assessment values.

[0043] After obtaining multiple risk situation assessment values, all risk situation assessment values ​​are further fused to generate a comprehensive operation situation analysis result. This fusion process can consider the mutual influence and importance between different risk types through mathematical algorithms, such as weighted average algorithm, to ensure that the final operation situation analysis result can fully reflect the traffic conditions in the supervision area.

[0044] Step S103, when the operation situation analysis result meets the target condition, obtaining the main perspective video data of the target ship associated with the operation situation analysis result, wherein the target condition includes: a target threshold.

[0045] When the operation situation analysis result meets a specific target condition, the embodiment of the present invention will obtain the main perspective video data of the target ship associated with the operation situation analysis result. The target condition refers to a set of preset thresholds and trigger criteria, including a target threshold, which is used to determine when the main perspective video data of the target ship needs to be obtained. The target ship refers to the ship with the highest risk under the current operation situation, which is obtained by parsing the operation situation analysis result, and can be a ship with a malfunction, a ship that causes congestion in the supervision area, a ship that collides with other ships, etc.

[0046] Step S104, displaying the main-view video data through the maritime traffic intelligent supervision platform.

[0047] After obtaining the main-perspective video data of the target ship, the embodiment of the present invention displays the main-perspective video data through the intelligent maritime traffic supervision platform by automatic triggering or manual triggering. Supervisors can view it on the intelligent maritime traffic supervision platform to achieve real-time monitoring and intuitive evaluation of traffic conditions in the supervision area.

[0048] Optionally, the step of acquiring static status data of each ship in the regulatory area includes: when it is detected that the ship enters a first trigger area corresponding to the regulatory area, sending a first acquisition signal to the ship, wherein the first trigger area includes the regulatory area; receiving static status data fed back by the ship based on the first acquisition signal, wherein the static status data includes: ship identity information, ship regulation information, the ship identity information includes: ship code ID, ship owner information, and the ship regulation information includes: ship specifications and types of cargo carried.

[0049] When acquiring the static status data of each ship in the supervision area, automatic data collection is achieved by setting the first trigger area. The first trigger area includes the supervision area itself, and extends outward to a certain range to form a monitoring buffer zone. When a ship enters the first trigger area for the first time, the maritime traffic intelligent supervision platform will immediately detect this event, and then automatically send the first acquisition signal to the ship, which is an instruction containing data request information, requiring the ship to provide its static status data. This mechanism ensures that all ships entering the first trigger area can be brought under supervision at the first time, avoiding possible data omissions or delays. After receiving the first acquisition signal, the ship feeds back its static status data to the maritime traffic intelligent supervision platform, which contains the key information necessary to identify the ship and understand its navigation regulations. Acquiring the static status data of the ship in this way can effectively avoid the problem of unstable signals in maritime communications.

[0050] Specifically, static status data mainly includes ship identity information and ship regulation information. Ship identity information is the ship's identity certificate, including the ship ID number and ship owner information. Ship regulation information reflects the physical properties and cargo conditions of the ship, including ship specifications (such as length, width, draft and gross tonnage) and the type of cargo carried (ordinary cargo, dangerous goods, passengers, etc.).

[0051] Optionally, the step of acquiring dynamic status data of each ship in the supervision area includes: sending a second acquisition signal to the ship when the ship enters the supervision area; receiving dynamic status data fed back by the ship based on the second acquisition signal, wherein the dynamic status data includes: the latitude and longitude, heading, and ship speed of the ship.

[0052] When acquiring the dynamic status data of each ship in the supervision area, when a ship enters the supervision area, the maritime traffic intelligent supervision platform will automatically identify this event and quickly send a second acquisition signal to the ship, which is an instruction containing data request information, requiring the ship to provide its dynamic status data. After receiving the second acquisition signal, the ship will feedback its dynamic status data to the maritime traffic intelligent supervision platform. This data is key information for the ship at the current sailing moment, and is essential for evaluating the relative position between ships, predicting collision risks, and monitoring the order of the waterway. Acquiring the dynamic status data of the ship in this way can effectively avoid the problem of unstable signals in maritime communications.

[0053] Specifically, dynamic status data mainly include the latitude and longitude, heading, speed of the ship, ship density, operating status of ship equipment, communication link status between the ship and the maritime traffic intelligent supervision platform and other ships, etc.

[0054] It should be noted that the dynamic status data generally also includes the identity information of the ship, which is conducive to associating the dynamic status data with the corresponding ship, but the identity information in the dynamic status data may be different from the identity information in the static status data. For example, the dynamic status data may only include the ship's coded ID number.

[0055] Optionally, the step of fusing the risk situation assessment values ​​includes: normalizing all risk situation assessment values, wherein the risk situation assessment values ​​include: collision risk assessment values, congestion risk assessment values, failure risk assessment values ​​and communication risk assessment values; determining the weight of each risk situation assessment value based on the historical occurrence probability of each risk type, wherein the risk types include: collision risk, congestion risk, failure risk and communication risk; performing weighted calculation on all risk situation assessment values ​​and corresponding weights to obtain an operation situation analysis result.

[0056] When fusing the risk situation assessment values, the aim is to comprehensively consider multiple risk factors, including collision risk, congestion risk, failure risk and communication risk, and convert them into a unified assessment standard through mathematical algorithms, so as to obtain a comprehensive operation situation analysis result and provide a scientific basis for regulatory decisions.

[0057] Specifically, all risk situation assessment values ​​are first normalized. The risk situation assessment values ​​include collision risk assessment values, congestion risk assessment values, failure risk assessment values ​​and communication risk assessment values. By normalizing each risk situation assessment value, the comparability of different risk types in mathematical calculations is ensured, and the analysis bias that may be caused by different dimensions of the original data is eliminated.

[0058] Secondly, based on the historical probability of occurrence of each risk type, determine the weight of each risk situation assessment value. The weight calculation formula is:

[0059]

[0060] In this formula, α i is the weight of the i-th risk situation assessment value, β is the historical probability of occurrence of all risk types based on historical statistical data, and β i is the historical probability of occurrence of the ith risk type based on historical statistical data. The risk types include collision risk, congestion risk, failure risk, and communication risk. γ is the weight reference value. Among them, the weight of the ith risk situation assessment value corresponds to the historical probability of occurrence of the ith risk type. For example, α 1 is the collision risk assessment value, β 1 is the historical probability of collision risk. The weight reference value γ is obtained based on the degree of correlation between each risk type and is a preset value. For example, congestion risk is correlated with collision risk, that is, the greater the congestion, the greater the collision risk. Congestion risk is correlated with failure risk, that is, the greater the failure risk, the greater the congestion risk. The correlation between each risk type is comprehensively calculated (for example, the average value is calculated) to obtain the weight reference value.

[0061] Finally, all risk situation assessment values ​​and corresponding weights are weighted to obtain the operation situation analysis results. The weighted calculation formula is:

[0062] Pv=α 1 Pv 1 +α 2 Pv 2 +…+α i Pv i ,

[0063] In this formula, Pv is the value of the operation status analysis result, α i is the weight of the i-th risk situation assessment value, Pv i is the normalized value of the ith risk situation assessment value. The embodiment of the present invention adopts a weighted formula to fuse the risk situation assessment values ​​output by each operation situation analysis sub-model, and the obtained operation situation analysis result can reflect the degree of traffic anomaly in the supervision area as a whole, thereby providing a data basis for subsequent scientific decision-making.

[0064] Optionally, when the operation situation analysis result meets the target condition, the step of obtaining the main perspective video data of the target ship associated with the operation situation analysis result includes: when the operation situation analysis result is greater than the target threshold in the target condition, parsing the operation situation analysis result to determine the target ship, wherein the target threshold is set in advance; obtaining the main perspective video data of the target ship, wherein the main perspective video data refers to the video data captured by the camera on the target ship.

[0065] When judging whether the operation situation analysis result meets the target condition, it includes judging whether the value of the operation situation analysis result is greater than the target threshold in the target condition. When the operation situation analysis result is greater than the target threshold in the target condition, it indicates that the traffic conditions in the supervision area have changed and need special attention. At this time, the operation situation analysis result will be further analyzed to determine the direct cause of the abnormality and the associated target ship.

[0066] Parsing the results of the operation situation analysis means tracing the results of the operation situation analysis. Specifically, the tracing calculation will examine which risk situation assessment values ​​in the operation situation analysis results are significantly high. These high-risk situation assessment values ​​are manifestations of abnormal collision risk assessment values, surges in the waterway congestion index, increased probability of ship failures, or increased communication risk levels. By comparing and analyzing these high-risk situation assessment values, the main driving factors that cause the operation situation analysis results to exceed the target threshold are determined. For example, if the collision risk assessment value is abnormally high, the calculation process of this assessment value is further analyzed, including factors such as the relative position, speed, and heading of the ship, to determine which ships' action patterns constitute the main factors of the collision risk. At the same time, the static state data and dynamic state data of the ship can also be combined to investigate and confirm the suspected ships. Static state data, such as the ship's specifications and the type of cargo carried, help determine whether the ship carries dangerous goods or has special navigation requirements; dynamic state data, such as the ship's latitude and longitude, heading, and speed, are directly related to the ship's immediate position and behavior pattern, and play a decisive role in identifying potential risks. Through comprehensive analysis of these data, the embodiment of the present invention can accurately determine which ships' behaviors directly affect the deterioration of the current operation situation, and these ships are the target ships.

[0067] The target ship may be a malfunctioning ship, a ship causing congestion in the regulatory area, a ship that collides with other ships, etc. There may be more than one target ship. For example, when there is a risk of malfunction, there is only one target ship, and when there is a risk of collision, there may be two or more target ships.

[0068] After the target ship is identified, the main perspective video data of the target ship is obtained to provide the supervisor with an intuitive on-site situation, helping them to quickly determine the nature and scope of the risk and formulate effective response measures. Among them, the main perspective video data refers to the video data taken by the camera deployed on the target ship, especially the video data taken by the camera located in the ship's cockpit or high on the top of the ship. This type of video data can cover the real scene of the area where the target ship is located, and the supervisor can see the situation of the target ship itself and other surrounding ships. In addition, another benefit of using the main perspective video data is that if other ships are unable to send their own operating status data to the maritime traffic intelligent supervision platform in a timely manner due to failures or network problems, the supervisor can still understand the operation of each ship on site through the main perspective video data of the target ship.

[0069] It should be noted that the target threshold is pre-set. Specifically, the target threshold is set by judging whether there is a key ship in the second trigger area. The first trigger area includes the supervision area and a monitoring buffer area extending outward to a certain range, while the second trigger area includes the first trigger area and a monitoring buffer area extending outward to a certain range, that is, the second trigger area is larger than the first trigger area.

[0070] By monitoring the activities of ships in the second trigger area, it is identified whether there are key ships in the second trigger area. In the second trigger area, which ships can be regarded as key ships are identified based on preset rules or standards. These rules may include: the determination of the type of ship (such as large oil tankers, chemical tankers, ships carrying special cargoes, etc.), the determination of the size of the ship (length, width, draft, etc.), the determination of the dynamic state of the ship (course, speed, etc.), the determination of the special state of the ship (such as reporting of equipment failure, cargo leakage, etc.), etc. For example, large oil tankers, chemical tankers, ships carrying dangerous or special cargoes, etc., due to the special nature of the cargoes they carry, may cause more serious environmental pollution or safety problems once an accident occurs, so they are regarded as high-risk ship types. The embodiments of the present invention can automatically mark these ships and focus on them as potential key ships; large ships, especially in areas with narrow channels or limited water depths, have low maneuverability and steering flexibility, and have a relatively high risk of collision with other ships or obstacles, and the passage of large ships may have a significant impact on the congestion of the channel. The embodiments of the present invention can evaluate the potential impact of the ship size on the operating status of the regulatory area and mark eligible ships as potential key ships; by real-time monitoring of ships The dynamic data of the ship is analyzed to analyze whether its course deviates from the normal route, whether its speed is too fast or too slow, and whether it changes its course frequently, etc. These may indicate potential risks or special conditions. Based on the dynamic state analysis, the embodiment of the present invention can identify those ships with abnormal behavior patterns or that may cause shipping problems, and mark them as potential key ships; the special state of the ship, such as equipment failure, cargo leakage, etc., is an important indicator for identifying key ships. These special states may not only pose a threat to the safety of the ship itself, but also may affect the surrounding ships and the marine environment. The embodiment of the present invention can timely discover the special state of the ship through the abnormal data automatically reported or monitored by the ship, mark the ship with such problems, and regard it as a potential key ship. After collecting and analyzing all the above information, the embodiment of the present invention will conduct a comprehensive assessment of the ship based on preset rules or standards. These rules or standards are formulated on the basis of historical data, risk assessment models and team experience to ensure the accuracy and reliability of the assessment results. According to the results of the comprehensive assessment, the embodiment of the present invention determines which ships may have a significant impact on the operating situation of the regulatory area, thereby identifying them as key ships.

[0071] When there is a key ship in the second trigger area, the target threshold is set to the first threshold; when there is no key ship in the second trigger area, the target threshold is set to the second threshold, wherein the first threshold is smaller than the second threshold, and both the first threshold and the second threshold are pre-set based on historical data and experience. That is to say, when there is a key ship in the second trigger area, the target threshold is smaller, and the operation status analysis result is more likely to exceed the target threshold, and then the main perspective video data of the target ship will be obtained earlier, and the supervisor has more opportunities to control the operation status of the ship in the supervision area, thereby improving the probability of smooth passage of the ship; on the contrary, when there is no key ship in the second trigger area, the target threshold is larger, and the operation status analysis result is not easy to exceed the target threshold, which can reduce the supervisor's frequent attention and scheduling of the ship operation status in the supervision area, and improve the supervision efficiency. The embodiment of the present invention determines whether there is a key ship in the second trigger area, sets the target threshold to a smaller value when there is a key ship in the second trigger area, and sets the target threshold to a larger value when there is no key ship in the second trigger area. Through the size relationship of the target threshold, the sensitivity of paying attention to abnormal situations in the supervision area is improved.

[0072] Optionally, after obtaining the main-perspective video data of the target ship associated with the operation status analysis result, the method further includes: extracting the video status data of all ships from the main-perspective video data; matching the video status data with the operation status data to determine the missing operation status data, wherein the missing operation status data refers to the ship status data that exists in the operation status data but does not exist in the video status data; constructing virtual video operation data based on the missing operation status data, and filling the virtual video operation data in the position indicated by the missing operation status data in the main-perspective video data.

[0073] In the embodiment of the present invention, although the real situation of the scene can be observed through the real scene by retrieving the main perspective video data, the ships in the real scene image may become invisible due to meteorological conditions, ship occlusion, etc. In this regard, the embodiment of the present invention extracts the video status data of all ships from the main perspective video data, and then matches the video status data with the operating status data obtained in step S101 one by one, so as to obtain the missing operating status data that only exists in the operating status data. These missing operating status data correspond to the ships that have become invisible due to meteorological conditions, ship occlusion, etc. Next, the invisible ships are virtually modeled according to the missing operating status data, and the corresponding operating parameters are configured for them based on the dynamic status data, that is, virtual video operating data is constructed, and finally the virtual video operating data of the corresponding ship is filled into the corresponding position in the main perspective video data, so that the main perspective video data is more complete and more accurate.

[0074] It should be noted that if the ship is invisible due to meteorological conditions, the virtual video operation data of the corresponding ship will be directly filled into the corresponding position in the main perspective video data; if the ship is invisible due to ship occlusion, the virtual video operation data will be blurred and then filled into the corresponding position in the main perspective video data to reflect that the invisible ship is behind the ship in front.

[0075] In this way, even in bad weather or when the line of sight is obstructed by other ships, regulators can still fully understand the distribution and dynamics of ships in the regulatory area from the main perspective video data, providing comprehensive information support for decision-making.

[0076] Optionally, the step of displaying the main-perspective video data through the intelligent maritime traffic supervision platform includes: after acquiring the main-perspective video data, uploading the main-perspective video data to the intelligent maritime traffic supervision platform, and the intelligent maritime traffic supervision platform displays the main-perspective video in real time; or, after acquiring the main-perspective video data, uploading the main-perspective video data to the intelligent maritime traffic supervision platform for storage, and after receiving a viewing command initiated by an external terminal, the intelligent maritime traffic supervision platform displays the main-perspective video.

[0077] In an embodiment of the present invention, when the main-perspective video data is displayed through the maritime traffic intelligent supervision platform, it can be done by automatic triggering and manual triggering. Automatic triggering means that after the main-perspective video data is acquired, the main-perspective video data is automatically uploaded to the maritime traffic intelligent supervision platform, and the maritime traffic intelligent supervision platform automatically pops up the main-perspective video data for the supervisor to view. Manual triggering means that after the main-perspective video data is acquired, the main-perspective video data is uploaded to the maritime traffic intelligent supervision platform for storage, but it does not pop up actively. Instead, after the supervisor has a viewing demand and initiates a viewing command, the maritime traffic intelligent supervision platform responds to the viewing command and pops up the main-perspective video data corresponding to the viewing command for the supervisor to view.

[0078] The steps provided by the above-mentioned intelligent maritime traffic supervision method are to obtain the operating status data of all ships in the supervision area, perform an operating situation analysis on the supervision area based on the operating status data, divide the operating status data into multiple groups of sub-operating status data, input each group of sub-operating status data into the corresponding operating situation analysis sub-model, obtain multiple risk situation assessment values, fuse the risk situation assessment values, obtain the operating situation analysis result, and when the operating situation analysis result meets the target conditions, obtain the main perspective video data of the target ship associated with the operating situation analysis result, and finally display the main perspective video data through the intelligent maritime traffic supervision platform for supervision personnel to view. The supervision of maritime traffic in the embodiment of the present invention is not limited to the viewing method of the two-dimensional supervision plane, but is combined with the two-dimensional supervision plane to display the main perspective video data of the ship when the target conditions are met, thereby improving the intuitiveness and efficiency of maritime traffic supervision, and thus solving the technical problem that the maritime traffic supervision platform in the related technology relies on the two-dimensional monitoring screen, resulting in low supervision efficiency.

[0079] The following is a detailed description in conjunction with another embodiment.

[0080] Embodiment 2

[0081] The intelligent maritime traffic monitoring device provided in this embodiment includes multiple implementation units, each of which corresponds to each implementation step in the above-mentioned embodiment 1.

[0082] Figure 2 is a schematic diagram of an optional intelligent marine traffic monitoring device according to an embodiment of the present invention, such as Figure 2 As shown, the intelligent maritime traffic supervision device may include: a first acquisition unit 21, an analysis unit 22, a second acquisition unit 23, and a display unit 24.

[0083] Among them, the first acquisition unit 21 is used to obtain the operating status data of all ships in the supervision area, wherein the operating status data includes: static status data and dynamic status data, the static status data includes the physical properties of the ship, and the dynamic status data includes the operating information of the ship during navigation.

[0084] The analysis unit 22 performs an operation situation analysis on the supervision area based on the operation status data, divides the operation status data into multiple groups of sub-operation status data, inputs each group of sub-operation status data into a corresponding operation situation analysis sub-model, obtains multiple risk situation assessment values, and fuses the risk situation assessment values ​​to obtain an operation situation analysis result.

[0085] The second acquisition unit 23 is used to acquire the main perspective video data of the target ship associated with the operation situation analysis result when the operation situation analysis result meets the target condition, wherein the target condition includes: a target threshold.

[0086] The display unit 24 is used to display the main perspective video data through the maritime traffic intelligent supervision platform.

[0087] The above-mentioned intelligent marine traffic supervision device can obtain the operating status data of all ships in the supervision area, perform operating situation analysis on the supervision area based on the operating status data, divide the operating status data into multiple groups of sub-operating status data, input each group of sub-operating status data into the corresponding operating situation analysis sub-model, obtain multiple risk situation assessment values, fuse the risk situation assessment values, obtain the operating situation analysis result, and obtain the main perspective video data of the target ship associated with the operating situation analysis result when the operating situation analysis result meets the target condition. Finally, the main perspective video data is displayed through the intelligent marine traffic supervision platform for supervision personnel to view. The supervision of marine traffic in the embodiment of the present invention is not limited to the viewing method of the two-dimensional supervision plane, but is combined with the two-dimensional supervision plane to display the main perspective video data of the ship when the target condition is met, thereby improving the intuitiveness and efficiency of marine traffic supervision, and thus solving the technical problem that the marine traffic supervision platform in the related technology relies on the two-dimensional monitoring screen, resulting in low supervision efficiency.

[0088] Optionally, the first acquisition unit 21 includes: a first sending module, used to send a first acquisition signal to the ship when it is detected that the ship enters a first trigger area corresponding to the regulatory area, wherein the first trigger area includes the regulatory area; a first receiving module, used to receive static status data fed back by the ship based on the first acquisition signal, wherein the static status data includes: ship identity information, ship regulation information, the ship identity information includes: ship code ID, ship owner information, and the ship regulation information includes: ship specifications and cargo types.

[0089] Optionally, the first acquisition unit 21 also includes: a second sending module, used to send a second acquisition signal to the ship when the ship enters the regulatory area; a second receiving module, used to receive dynamic status data fed back by the ship based on the second acquisition signal, wherein the dynamic status data includes: the latitude and longitude, heading, and ship speed of the ship.

[0090] Optionally, the analysis unit 22 includes: a normalization module, used to normalize all risk situation assessment values, wherein the risk situation assessment values ​​include: collision risk assessment value, congestion risk assessment value, failure risk assessment value and communication risk assessment value; a determination module, based on the historical occurrence probability of each risk type, determines the weight of each risk situation assessment value, wherein the risk types include: collision risk, congestion risk, failure risk and communication risk; a calculation module, used to perform weighted calculation on all risk situation assessment values ​​and corresponding weights to obtain an operation situation analysis result.

[0091] Optionally, the second acquisition unit 23 includes: a parsing module, used to parse the operation status analysis result when the operation status analysis result is greater than a target threshold in the target condition, and determine the target ship, wherein the target threshold is pre-set; an acquisition module, used to acquire the main perspective video data of the target ship, wherein the main perspective video data refers to the video data captured by a camera on the target ship.

[0092] Optionally, the second acquisition unit 23 also includes: an extraction module, which is used to extract the video status data of all ships from the main-view video data after acquiring the main-view video data of the target ship associated with the operation status analysis result; a matching module, which is used to match the video status data with the operation status data to determine the missing operation status data, wherein the missing operation status data refers to the ship status data that exists in the operation status data but not in the video status data; a filling module, which constructs virtual video operation data based on the missing operation status data, and fills the virtual video operation data in the position indicated by the missing operation status data in the main-view video data.

[0093] Optionally, the display unit 24 includes: a first display module, which is used to upload the main-perspective video data to the intelligent maritime traffic supervision platform after acquiring the main-perspective video data, and the intelligent maritime traffic supervision platform displays the main-perspective video in real time; a second display module, which is used to upload the main-perspective video data to the intelligent maritime traffic supervision platform for storage after acquiring the main-perspective video data, and the intelligent maritime traffic supervision platform displays the main-perspective video after receiving a viewing command initiated by an external terminal.

[0094] The above-mentioned intelligent maritime traffic supervision device may also include a processor and a memory. The above-mentioned first acquisition unit 21, analysis unit 22, second acquisition unit 23, display unit 24, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize corresponding functions.

[0095] The processor includes a kernel, which retrieves the corresponding program unit from the memory. One or more kernels can be set, and the marine traffic can be intelligently supervised by adjusting the kernel parameters.

[0096] The above-mentioned memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one storage chip.

[0097] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored computer program, wherein when the computer program is running, the device where the computer-readable storage medium is located is controlled to execute any one of the methods for intelligent supervision of maritime traffic in the above-mentioned embodiment 1.

[0098] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors implement the method for intelligent supervision of maritime traffic of any one of the above-mentioned embodiments one.

[0099] The present application also provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the method for intelligent supervision of maritime traffic described in each embodiment of the present application.

[0100] The present application also provides a computer program product, including a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for intelligent supervision of maritime traffic described in each embodiment of the present application are implemented.

[0101] Figure 3 1 is a hardware structure block diagram of an electronic device (or mobile device) for executing a method for intelligent monitoring of maritime traffic according to an embodiment of the present invention. Figure 3 As shown, the electronic device may include one or more ( Figure 3 302a, 302b, ..., 302n are used to illustrate) processor 302 (processor 302 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), memory 304 for storing data. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, a keyboard, a power supply and / or a camera. It can be understood by those skilled in the art that Figure 3The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 3 More or fewer components as shown, or with Figure 3 Different configurations are shown.

[0102] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0103] In the above embodiments of the present invention, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0104] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units can be a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0105] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0106] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0107] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and other media that can store program codes.

[0108] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for intelligent supervision of maritime traffic, characterized in that: include: Acquire the operation status data of all ships in the supervision area, wherein the operation status data includes: static status data and dynamic status data, wherein the static status data includes the physical properties of the ship, and the dynamic status data includes the operation information of the ship during navigation; Based on the operation status data, the operation status data is divided into multiple groups of sub-operation status data, each group of sub-operation status data is input into a corresponding operation status analysis sub-model to obtain multiple risk situation assessment values, and the risk situation assessment values ​​are fused to obtain an operation situation analysis result; When the operation situation analysis result meets the target condition, obtaining the main perspective video data of the target ship associated with the operation situation analysis result, wherein the target condition includes: a target threshold; The main perspective video data is displayed through the maritime traffic intelligent supervision platform.

2. The supervision method according to claim 1, characterized in that: The step of obtaining static status data of each ship in the supervision area comprises: In the case of detecting that a ship enters a first triggering area corresponding to the supervision area, sending a first acquisition signal to the ship, wherein the first triggering area includes the supervision area; Receive the static status data fed back by the ship based on the first acquisition signal, wherein the static status data includes: ship identity information, ship regulation information, the ship identity information includes: ship code ID, ship owner information, the ship regulation information includes: ship specifications, and cargo types.

3. The supervision method according to claim 1, characterized in that: The step of obtaining dynamic status data of each ship in the supervision area includes: When a ship enters the supervision area, sending a second acquisition signal to the ship; Receive the dynamic state data fed back by the ship based on the second acquisition signal, wherein the dynamic state data includes: the longitude and latitude, heading, and ship speed of the ship.

4. The supervision method according to claim 1, characterized in that: The step of fusing the risk situation assessment value comprises: Normalizing all the risk situation assessment values, wherein the risk situation assessment values ​​include: a collision risk assessment value, a congestion risk assessment value, a failure risk assessment value, and a communication risk assessment value; Determine the weight of each risk situation assessment value based on the historical occurrence probability of each risk type, wherein the risk types include: collision risk, congestion risk, failure risk and communication risk; All the risk situation assessment values ​​and their corresponding weights are weightedly calculated to obtain the operation situation analysis result.

5. The supervision method according to claim 1, characterized in that: When the operation situation analysis result meets the target condition, the step of acquiring the main perspective video data of the target ship associated with the operation situation analysis result comprises: When the operation situation analysis result is greater than the target threshold in the target condition, analyzing the operation situation analysis result to determine the target ship, wherein the target threshold is preset; Obtain main-view video data of the target ship, wherein the main-view video data refers to video data captured by a camera on the target ship.

6. The supervision method according to claim 1, characterized in that: After obtaining the main-view video data of the target ship associated with the operation status analysis result, the method further includes: Extracting video status data of all ships from the main-view video data; Matching the video status data with the running status data to determine missing running status data, wherein the missing running status data refers to ship status data that exists in the running status data but does not exist in the video status data; Virtual video running data is constructed based on the missing running status data, and the virtual video running data is filled in the position indicated by the missing running status data in the main-view video data.

7. The supervision method according to claim 1, characterized in that: The step of displaying the main-view video data through the marine traffic intelligent supervision platform includes: After acquiring the main-view video data, uploading the main-view video data to the maritime traffic intelligent supervision platform, and the maritime traffic intelligent supervision platform displays the main-view video in real time; or, After acquiring the main-view video data, the main-view video data is uploaded to the maritime traffic intelligent supervision platform for storage, and after receiving a viewing command initiated by an external terminal, the maritime traffic intelligent supervision platform displays the main-view video.

8. An intelligent marine traffic monitoring device, characterized in that: include: A first acquisition unit is used to acquire the operation status data of all ships in the supervision area, wherein the operation status data includes: static status data and dynamic status data, wherein the static status data includes the physical properties of the ship, and the dynamic status data includes the operation information of the ship during navigation; an analysis unit, performing an operation situation analysis on the supervision area based on the operation status data, dividing the operation status data into multiple groups of sub-operation status data, inputting each group of the sub-operation status data into a corresponding operation situation analysis sub-model, obtaining multiple risk situation assessment values, and fusing the risk situation assessment values ​​to obtain an operation situation analysis result; A second acquisition unit is configured to acquire the main perspective video data of the target ship associated with the operation situation analysis result when the operation situation analysis result meets the target condition, wherein the target condition includes: a target threshold; A display unit is used to display the main perspective video data through the maritime traffic intelligent supervision platform.

9. An electronic device, characterized in that: It includes one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the intelligent maritime traffic supervision method as described in any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method for intelligent supervision of maritime traffic described in any one of claims 1 to 7 are implemented.

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