Offshore electronic fence internet monitoring method and system

Abstract

The invention relates to the technical field of maritime monitoring electronic fences, in particular to a maritime electronic fence internet monitoring method and system, and the method comprises the steps: receiving a structured operation intention statement; obtaining associated historical behavior records; according to the historical behavior record, evaluating the trust level of the ship management party; inquiring whether an effective structured operation intention statement related to the current ship in time and space exists or not; if yes, according to the trust level of the current ship, judging that the judgment result of the deviation behavior belongs to an in-plan deviation or illegal behavior; if not, the property of the deviation behavior is judged according to the electronic fence basic rule set. The method has the advantages of obviously reducing the workload of manual verification and improving the monitoring accuracy and efficiency by intelligently distinguishing in-plan deviation and real violation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of offshore monitoring electronic fence, in particular, to an offshore electronic fence internet monitoring method and system. BACKGROUND

[0002] In a complex sea environment, such as a large international shipping hub, a fishing operation area and a marine protection zone, or a multi-party joint marine engineering development area, deploying an offshore electronic fence system to monitor the compliance of a large number of ships of various types is an important means to ensure navigation order and implement regional management regulations. The system is usually monitored by the regional authority to control the running geographical boundary, passage requirements, speed limit, etc. of fishing vessels.

[0003] However, fishing vessels operating near the boundary of an electronic fence prohibited fishing area based on valid permits, research vessels staying in recommended channels for a short time at low speed for sampling, or cargo ships following economic speed instructions slightly below the recommended minimum speed of the electronic fence, etc. may be marked as abnormal or in violation by the existing system, resulting in a large number of such "apparent non-compliance" alerts. The operators of the monitoring center need to invest a lot of time and effort in manual verification, checking the sailing plans and operation declaration information of the ships, and even need to communicate with the ships or their management parties to confirm which are real violations that need to be intervened and which are within-plan deviations following legitimate instructions. In an environment with a large number of ships and frequent activities, this manual verification process is inefficient and prone to delayed or incorrect handling due to information asymmetry or judgment errors.

[0004] The prior art needs to be improved in view of the above problems. SUMMARY

[0005] The purpose of the present application is to provide an offshore electronic fence internet monitoring method and system, which has the advantages of significantly reducing the workload of manual verification and improving the monitoring accuracy and efficiency by intelligently distinguishing between within-plan deviations and real violations.

[0006] In one aspect, the present application provides an offshore electronic fence internet monitoring method, the method comprising: continuously receiving structured operation intention declarations submitted by ships, the structured operation intention declarations including planned operation parameters and specific operation instruction information; obtaining historical behavior records associated with the ships, the historical behavior records including historical accuracy records of the structured operation intention declarations and historical rule compliance records; evaluating the trust level of the ship management party according to the historical behavior records, and maintaining and updating the trust level; When the real-time behavior parameter of the current ship deviates from the preset e-fence basic rule set, it is inquired whether there is an effective structured operation intention declaration related to the current ship in space-time; If there is, according to the trust level of the current ship, the deviation tolerance threshold of the corresponding planned operation parameter is determined, the real-time behavior parameter is compared with the planned operation parameter of the current ship to obtain the actual deviation degree, and according to the comparison result of the actual deviation degree and the deviation tolerance threshold, it is judged that the deviation behavior belongs to planned deviation or violation behavior; If not, the nature of the deviation behavior is determined according to the e-fence basic rule set.

[0007] Through the above scheme, by integrating the operation intention submitted by the ship and the historical trust level, the planned deviation and the real violation can be intelligently distinguished, the artificial verification workload is significantly reduced, and the monitoring accuracy and efficiency are improved.

[0008] Further, the present application also proposes, according to the above-mentioned maritime e-fence internet monitoring method, according to the trust level of the current ship, the deviation tolerance threshold of the corresponding planned operation parameter is determined, including: Obtaining parameter type information of the planned operation parameter; Obtaining a preset application weight corresponding to the parameter type; Based on the trust level of the current ship and the application weight, the deviation tolerance threshold of the planned operation parameter is calculated.

[0009] Through the above scheme, the determination process of the deviation tolerance threshold is further refined, which is associated with the specific parameter type and the application weight, and the rationality of the threshold setting is improved.

[0010] Further, the present application also proposes, according to the above-mentioned maritime e-fence internet monitoring method, the trust level contains multiple trust dimension indexes, the trust dimension indexes include rule default times, trajectory compliance rate of intention declaration and historical conflict resolution rate, and based on the trust level of the current ship and the application weight, the deviation tolerance threshold of the planned operation parameter is calculated, including: Obtaining dimension index scores of multiple trust dimension indexes of the current ship; Obtaining an influence factor set of the application weight; Generating the application weight based on the dimension index score and the influence factor set; According to the application weight and the trust level, the deviation tolerance threshold is calculated.

[0011] Through the above scheme, multi-dimensional trust indexes are introduced, and the application weight is generated based on these indexes and influence factors, so that the calculation of trust level and deviation tolerance threshold is more detailed and comprehensive.

[0012] Further, the present application also proposes that, according to the above-mentioned offshore electronic fence Internet monitoring method, the deviation tolerance threshold is calculated according to the application weight and the trust level, including: Obtaining specific operation instruction information contained in the structured operation intention declaration corresponding to the current ship; Identifying the sensitivity level or priority of the specific operation instruction information; According to the sensitivity level or priority, the joint calculation of multiple trust dimension indicators and application weights, the deviation tolerance threshold is obtained.

[0013] Through the above scheme, the sensitivity level or priority of the specific operation instruction is included in the calculation of the deviation tolerance threshold, so that the threshold setting can better reflect the importance of the instruction, and the accuracy of the judgment is improved.

[0014] Further, the present application also proposes that, according to the above-mentioned offshore electronic fence Internet monitoring method, the deviation tolerance threshold is calculated according to the sensitivity level or priority, the joint calculation of multiple trust dimension indicators and application weights, including: Judging whether the sensitivity level or priority, the trust level and / or the application weight exist the direction conflict of the judgment result; If there is a direction conflict of the judgment result, a preset conflict processing strategy is called, and the conflict processing strategy includes: Quantitative evaluation of the specific level value of the sensitivity level or priority, the trust level and / or the application weight associated with the direction conflict of the judgment result; Based on the preset priority relationship between factors, the weight reordering corresponding to the sensitivity level or priority, the trust level and / or the application weight associated with the direction conflict of the judgment result is obtained; According to the weight reordering, the sensitivity level or priority, the multiple trust dimension indicators and the application weight are weighted and calculated to obtain the deviation tolerance threshold.

[0015] Through the above scheme, the strategy for handling the potential conflict between the sensitivity level, the trust level and the application weight is provided, and through quantitative evaluation and weight reordering, the judgment robustness in complex situations is improved.

[0016] Further, the present application also proposes that, according to the above-mentioned offshore electronic fence Internet monitoring method, based on the preset priority relationship between factors, the weight reordering corresponding to the sensitivity level or priority, the trust level and / or the application weight associated with the direction conflict of the judgment result is obtained, including: Obtaining a plurality of historical conflict decision records, the historical conflict decision records including the original specific level value of the sensitivity level or priority, the trust level and the application weight, the deviation tolerance threshold adopted at the time of the historical conflict, and the nature of the subsequent confirmation of the deviation behavior of the historical conflict; determine whether the priority relationship between the factors corresponding to the historical conflict is inconsistent with the nature of the subsequent confirmation of the deviated behavior of the historical conflict; If inconsistent, identify the corresponding misjudgment mode, and adjust the priority relationship between the factors according to the misjudgment mode.

[0017] Through the above scheme, the historical conflict decision record is introduced to optimize the priority relationship between the factors, and the misjudgment mode is identified and the priority is adjusted, so that the system can learn from historical experience and improve the accuracy of future judgment.

[0018] Further, the present application also provides, according to the above-mentioned offshore electronic fence internet monitoring method, identifying the corresponding misjudgment mode, comprising: Quantify the inconsistency degree of the priority relationship between the factors corresponding to each historical conflict decision and the nature of the subsequent confirmation of the deviated behavior of the historical conflict, and generate a degree of inconsistency quantization value; The records with the same factor combination are aggregated to form a case group; Analyze the concentration degree value of the inconsistency quantization value in the case group; If the concentration degree value meets the preset concentration threshold, it is determined as a misjudgment mode.

[0019] Through the above scheme, the method for quantifying and analyzing the inconsistency degree of the historical conflict is provided, and the misjudgment mode can be more accurately identified through case group analysis and concentration degree judgment.

[0020] Further, the present application also provides, according to the above-mentioned offshore electronic fence internet monitoring method, analyzing the concentration degree value of the inconsistency quantization value in the case group, comprising: Statistically analyze the inconsistency quantization value in the case group to obtain the concentration degree value.

[0021] Through the above scheme, the calculation method of the concentration degree value is clear, and the operability of the misjudgment mode identification process is ensured.

[0022] Further, the present application also provides, according to the above-mentioned offshore electronic fence internet monitoring method, quantifying the inconsistency degree of the priority relationship between the factors corresponding to each historical conflict decision and the nature of the subsequent confirmation of the deviated behavior of the historical conflict, and generating a degree of inconsistency quantization value, comprising: Obtain the determination result of the deviated behavior of the historical conflict; Obtain the nature of the subsequent confirmation of the deviated behavior of the historical conflict; According to the preset comparison matrix, the difference between the determination result of the deviated behavior and the nature of the subsequent confirmation of the deviated behavior of the historical conflict is calculated to obtain the inconsistency quantization value.

[0023] Through the above scheme, a specific method for quantifying the inconsistency degree is provided, and the quantification of the inconsistency degree is more objective and standardized by comparing the judgment result with the subsequent confirmation property.

[0024] Further, the application also provides a marine electronic fence internet monitoring system, and the technical scheme is as follows: Comprise: The receiving module is configured to continuously receive a structured operation intention declaration submitted by the ship, the structured operation intention declaration comprising planned operation parameters and specific operation instruction information; The information query module is configured to obtain a historical behavior record associated with the ship, the historical behavior record comprising a historical accuracy record of the structured operation intention declaration and a historical rule compliance record; The trust level management module is configured to evaluate the trust level of the ship manager according to the historical behavior record, and to maintain and update the trust level; The information query module is further configured to query whether there is an effective structured operation intention declaration related to the current ship in space-time when it is monitored that the real-time behavior parameter of the current ship deviates from the preset electronic fence basic rule set; The determination module is configured to determine a deviation tolerance threshold of the corresponding planned operation parameter according to the trust level of the current ship if there is, compare the real-time behavior parameter with the planned operation parameter of the current ship to obtain an actual deviation degree, and determine whether the deviation behavior is a planned deviation or a violation behavior according to a comparison result of the actual deviation degree and the deviation tolerance threshold; The determination module is further configured to determine the nature of the deviation behavior according to the electronic fence basic rule set if there is not.

[0025] Through the above scheme, a system for implementing the above method is provided, which is modularized for easy construction and deployment, and can effectively execute the monitoring method.

[0026] As can be seen from the above, the marine electronic fence internet monitoring method and system provided by the application can intelligently distinguish between planned deviation and real violation by integrating the operation intention submitted by the ship and the historical trust level, solving the problem of low efficiency of manual verification and difficulty in distinguishing between different nature deviations in the prior art, and having the advantages of being able to intelligently distinguish between planned deviation and real violation by integrating the operation intention submitted by the ship and the historical trust level, significantly reducing the workload of manual verification, and improving the monitoring accuracy and efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0027] Figure 1 A flowchart of a marine electronic fence internet monitoring method provided by one embodiment of the application.

[0028] Figure 2One of flowchart of offshore electronic fence internet monitoring method provided by another embodiment of the present application.

[0029] Figure 3 Another flowchart of offshore electronic fence internet monitoring method provided by another embodiment of the present application.

[0030] Figure 4 Another flowchart of offshore electronic fence internet monitoring method provided by another embodiment of the present application.

[0031] Figure 5 Another flowchart of offshore electronic fence internet monitoring method provided by another embodiment of the present application.

[0032] Figure 6 Another flowchart of offshore electronic fence internet monitoring method provided by another embodiment of the present application.

[0033] Figure 7 Another flowchart of offshore electronic fence internet monitoring method provided by another embodiment of the present application.

[0034] Figure 8 Another flowchart of offshore electronic fence internet monitoring method provided by another embodiment of the present application.

[0035] Figure 9 Another flowchart of offshore electronic fence internet monitoring method provided by another embodiment of the present application.

[0036] Figure 10 Program block diagram of offshore electronic fence internet monitoring system provided by another embodiment of the present application. DETAILED DESCRIPTION

[0037] The technical solutions in the present application will be described clearly and completely below in conjunction with the accompanying drawings in the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. The components of the present application described and shown in the accompanying drawings can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0038] It should be noted that similar reference numerals and letters refer to like items in the accompanying drawings, and once an item is defined in one drawing, it need not be further defined and explained in subsequent drawings. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only to distinguish descriptions, and cannot be understood as indicating or implying relative importance.

[0039] With reference to Figure 1 To this end, the present application proposes an offshore electronic fence internet monitoring method, comprising: S1000: continuously receiving structured operation intention declaration submitted by the ship, the structured operation intention declaration comprising planned operation parameters and specific operation instruction information; S2000: obtaining historical behavior records associated with the ship, the historical behavior records comprising historical accuracy records of the structured operation intention declaration and historical rule compliance records; S3000: evaluating the trust level of the ship management party according to the historical behavior records, and maintaining and updating the trust level; S4000: when it is monitored that the real-time behavior parameters of the current ship deviate from the preset electronic fence basic rule set, it is inquired whether there is an effective structured operation intention declaration related to the current ship in space-time; S5000: if there is, according to the trust level of the current ship, a deviation tolerance threshold of the corresponding planned operation parameters is determined, the real-time behavior parameters are compared with the planned operation parameters of the current ship to obtain the actual deviation degree, and according to the comparison result of the actual deviation degree and the deviation tolerance threshold, it is judged that the judgment result of the deviation behavior belongs to planned deviation or violation behavior; S6000: if there is not, the nature of the deviation behavior is judged according to the electronic fence basic rule set.

[0040] In the present embodiment, the structured operation intention declaration submitted by the ship is continuously received by the monitoring system, which continuously obtains the information actively reported by the ship in a preset format. It can be realized by means of internet communication, satellite communication or shore-based radio communication.

[0041] The structured operation intention declaration refers to an information carrier containing specific fields and data formats, which comprises planned operation parameters and specific operation instruction information, which can be represented by XML, JSON or other custom data structures, and the intention information of the ship is standardized for automatic processing by the system. The planned operation parameters refer to the specific numerical value or range related to the planned operation activities of the ship, such as planned speed, planned heading, planned operation area coordinates and other expected behavior information. The specific operation instruction information refers to the specific instruction content from the management party to which the ship belongs for the execution of a certain operation; The historical behavior record refers to a collection of data reflecting the activities of a ship over a period of time, including a historical accuracy record of structured operation intent declaration and a historical rule compliance record, which are mainly used to provide traceability of ship behavior; the historical accuracy record refers to the record of the degree of conformity between the structured operation intent declaration submitted by the ship in the past and its subsequent actual behavior, which is used to assess the credibility of the ship's intent declaration; the historical rule compliance record refers to the record of the degree of conformity between the ship's past behavior and the basic rule set of the electronic fence or other related rules, which is mainly used to assess the compliance of the ship.

[0042] The trust level of the ship management party refers to the assessment of the reliability of the management institution to which the ship belongs based on the historical behavior record of the ship, which can be realized by using a rule-based scoring model, statistical analysis method or machine learning algorithm, and is mainly used to quantify the reputation level of the ship management party. The trust level refers to the quantitative representation of the reliability of the ship management party, which can be divided into multiple levels, such as high, medium and low trust levels. Maintenance update refers to the adjustment of the evaluated trust level according to the latest behavior of the ship, which can be realized by using periodic update or event-triggered update, and is mainly used to ensure that the trust level can dynamically reflect the current performance of the ship; the system real-time acquires the current position, speed, heading and other parameters of the ship, compares them with the threshold or range set in the basic rule set of the electronic fence, and finds that there is a non-compliance situation, which is mainly used to identify potential abnormal behavior.

[0043] The real-time behavior parameter refers to the actual running state data of the ship at a certain time, such as the position, speed, heading and other information obtained through AIS, radar or other sensors, which is mainly used to reflect the current actual behavior of the ship; the basic rule set of the electronic fence refers to the basic rule set set by the regional authority to regulate the behavior of the ship, which includes geographical boundary, speed limit, channel requirement, etc., which is mainly used to provide a standard basis for compliance judgment.

[0044] Querying whether there is an effective structured operation intent declaration related to the current ship in space and time refers to searching for whether there is a declaration related to the current position and time of the ship in the structured operation intent declaration received and in the effective period when the deviation behavior of the ship is detected, which is mainly used to judge whether the deviation behavior of the ship has a pre-declared intent; the effective structured operation intent declaration related to the current ship in space and time refers to the existence of a structured operation intent declaration previously submitted by the ship and currently still effective near the time point and geographical position where the deviation behavior occurs, which is mainly used to ensure that the queried intent declaration has relevance with the actual deviation behavior.

[0045] According to the trust level of the current ship, determining the deviation tolerance threshold of the corresponding planned operation parameter refers to setting an upper limit of the range of deviation of the actual behavior of the ship from the planned operation parameter according to the trust level of the ship management party, which is mainly to give different tolerance degrees to ships of different trust levels; the deviation tolerance threshold refers to the maximum acceptable degree of deviation of the actual behavior of the ship from the planned operation parameter, which can be a specific numerical value or a range, which is mainly to define the acceptable range of deviation within the plan; comparing the real-time behavior parameter with the planned operation parameter of the current ship to obtain the actual deviation degree refers to calculating the difference between the real-time behavior parameter of the ship and the corresponding planned operation parameter in the structured operation intent declaration, which is mainly to quantify the deviation degree between the actual behavior of the ship and its planned behavior; the actual deviation degree refers to the quantitative difference between the real-time behavior parameter of the ship and the planned operation parameter, which is mainly used for comparison with the deviation tolerance threshold; according to the comparison result of the actual deviation degree and the deviation tolerance threshold, judging whether the deviation behavior belongs to deviation within the plan or violation behavior refers to comparing the calculated actual deviation degree with the deviation tolerance threshold determined according to the trust level, if the actual deviation degree is less than or equal to the tolerance threshold, it is judged as deviation within the plan, if it is greater than the tolerance threshold, it is judged as violation behavior, which is mainly to distinguish between different types of deviation behavior; deviation within the plan refers to the behavior of the ship deviating from the electronic fence basic rule set, but conforming to the pre-declared structured operation intent declaration, and the deviation degree is within the tolerance range determined according to the trust level, which mainly represents an acceptable and reasonable deviation; violation behavior refers to the behavior of the ship deviating from the electronic fence basic rule set, and not conforming to the pre-declared structured operation intent declaration, or although conforming to the intent declaration, but the deviation degree exceeds the tolerance range determined according to the trust level, which mainly represents an illegal behavior that needs to be paid attention to or intervened; determining the nature of the deviation behavior according to the electronic fence basic rule set refers to directly judging whether the deviation behavior constitutes a violation according to the provisions of the basic rule set when the behavior of the ship deviates from the basic rule set and there is no related structured operation intent declaration, which is mainly used to handle the deviation without pre-declared intent; the nature of the deviation behavior refers to the qualitative judgment of the behavior of the ship deviating from the electronic fence basic rule set, including deviation within the plan or violation behavior, which mainly represents the final conclusion of the compliance of the behavior of the ship.

[0046] By continuously receiving the structured operation intention declaration submitted by the ship, the planned operation parameters and specific operation instruction information of the ship are obtained, so that the activity intention of the ship is known in advance. At the same time, the system obtains and maintains the historical behavior record associated with the ship, including the historical accuracy of its intention declaration and the historical rule compliance situation, based on these historical data, the system assesses and dynamically updates the trust level of the ship management party. When the system monitors that the real-time behavior parameters of the current ship deviate from the preset electronic fence basic rule set, first query whether there is an effective structured operation intention declaration related to the ship in space and time. If there is, the system does not directly determine according to the basic rule set, but according to the trust level of the current ship, determines a deviation tolerance threshold corresponding to the planned operation parameters. Then, the real-time behavior parameters of the ship are compared with the planned operation parameters, and the actual deviation degree is calculated. Finally, according to the comparison result of the actual deviation degree and the deviation tolerance threshold, it is judged whether the deviation behavior belongs to the planned deviation or the violation behavior. This way allows the ship with a higher trust level to deviate from the basic rule set within a certain range to execute its reasonable intention. If there is no related structured operation intention declaration, the system directly determines the nature of the deviation behavior according to the electronic fence basic rule set, to ensure the basic monitoring effectiveness in the absence of intention information. The whole process forms a dynamic and hierarchical judgment mechanism based on intention, history and trust, which can more accurately identify the true nature of the ship's behavior.

[0047] In some examples of the present embodiment, the maritime monitoring system is deployed in a complex sea area with basic speed limit rules. A research vessel plans to conduct a low-speed hydrological sampling operation in the sea area, and its manager submits a structured operation intent declaration to the monitoring system through the Internet, which contains planned operation parameters (e.g., operating at 5 knots in a specific area) and specific operation instruction information (e.g., performing a national scientific research project hydrological sampling task). The monitoring system continuously receives and stores this declaration. The system also maintains a historical behavior record of the research vessel, for example, its past scientific research task intent declarations are usually highly consistent with actual behavior, and its regular navigation other than scientific research operations strictly follows the basic rules, so the trust level of the ship is evaluated as high. When the research vessel enters the sampling area and reduces the speed to 5 knots, the monitoring system detects that its speed (5 knots) deviates from the minimum speed (e.g., 10 knots) set by the basic rule set in the area. The system immediately queries and finds that there is an effective structured operation intent declaration related to the current location and time of the ship. Since the trust level of the ship is high, the system determines a larger deviation tolerance threshold according to its trust level, for example, allowing the speed to deviate from the planned speed (5 knots) by 3 knots up and down. The system compares the real-time speed (5 knots) with the planned speed (5 knots), and the actual deviation is 0 knots. Comparing the actual deviation (0 knots) with the deviation tolerance threshold (3 knots), 0 knots is less than 3 knots, so the deviation behavior is determined to be within the planned deviation. The system records this judgment result, which may only generate a low-priority prompt message, without triggering a high-priority violation alarm or forced intervention measures. If the ship does not submit an intent declaration, or its trust level is low, or the actual speed deviates from the planned speed beyond the tolerance threshold (e.g., the speed drops to 1 knot), it may be determined as a violation.

[0048] Referring to Figure 2 Further, sub-step S5100 of S5000: determining a deviation tolerance threshold of the corresponding planned operation parameter according to the trust level of the current ship, comprising: S5110: obtaining parameter type information of the planned operation parameter; S5120: obtaining a preset application weight corresponding to the parameter type; S5130: calculating the deviation tolerance threshold of the planned operation parameter based on the trust level of the current ship and the application weight.

[0049] The parameter type information of the planned operation parameter refers to the specific physical quantity or behavior attribute represented by the planned operation parameter, such as speed, position, heading, draft, cargo type, etc., which can be represented in the form of identifier, enumeration value or text description, and its purpose is to distinguish the importance and sensitivity of different parameters in monitoring and safety.

[0050] The application weight refers to a value or level that is set in advance and reflects the relative importance of different parameter types in determining the deviation tolerance threshold, which can be represented in the form of a numerical coefficient, a level label or a weight vector, and its purpose is to provide a basis for the importance of the parameter level for subsequent calculations. Based on the trust level of the current ship and the application weight, the calculation of the deviation tolerance threshold of the planned operation parameter refers to using a calculation model or rule to combine the trust level representing the overall reliability of the ship with the application weight representing the importance of the specific parameter, to obtain a specific value or range that limits the maximum degree of deviation of the parameter from the planned value.

[0051] By obtaining the parameter type information of the planned operation parameter, the specific category of the parameter that needs to be judged for deviation is identified; based on the parameter type, the pre-set application weight corresponding to it is obtained, which reflects the importance or sensitivity of this type of parameter in the overall monitoring system; then, based on the trust level of the current ship and the obtained application weight, the deviation tolerance threshold of the planned operation parameter is calculated. This way combines the overall trust level of the ship with the importance of the specific parameter, so that the determination of the deviation tolerance threshold is no longer dependent only on the trust level of the ship, but also takes into account the characteristics of the parameter itself. For example, for a ship with a high trust level, the deviation tolerance threshold for its non-critical parameters (low application weight) can be appropriately relaxed, but for its critical parameters (high application weight), even if the trust level is high, the deviation tolerance threshold will be relatively strict. Conversely, for a ship with a low trust level, the deviation tolerance threshold will be relatively small regardless of the parameter type, especially for critical parameters. This combination of ship trust level and parameter importance makes the calculation of the deviation tolerance threshold more refined and reasonable, and can more accurately distinguish between planned deviations and real violations, thereby improving the accuracy of monitoring and judgment.

[0052] In some examples of the present embodiment, assume that the deviation tolerance threshold of a ship on the parameter of "speed" in the intended declaration of the planned operation is to be determined. First, the system obtains the parameter type information of the planned operation parameter as "speed". According to the preset rules, the application weight corresponding to the "speed" parameter type is set to a relatively high value, for example, 0.8, which indicates that the speed is a key parameter affecting the safety and efficiency of navigation. At the same time, the system queries that the trust level of the current ship is "high". Based on the "high" trust level and the application weight of 0.8, the system calls a preset calculation model to calculate the deviation tolerance threshold. The calculation model can be a function, for example: deviation tolerance threshold = basic threshold * f(trust level) * g(application weight), where f(trust level) is a function positively related to the trust level, and g(application weight) is a function negatively related to the application weight (because the higher the weight, the lower the tolerance). Assume that the basic speed deviation threshold is 2 knots, f("high") = 1.2, and g(0.8) = 0.5. Then the calculated speed deviation tolerance threshold is 2 * 1.2 * 0.5 = 1.2 knots. This means that the maximum deviation allowed by the high-trust-level ship when executing the planned speed is 1.2 knots. If the real-time speed of the ship deviates from the planned speed by more than 1.2 knots, it may be judged as a violation. In this way, even if the ship is of high trust level, the deviation tolerance of its key parameters is reasonably limited.

[0053] With reference to Figure 3 Further, S5130 comprises: S5131: obtaining dimension indicator scores of multiple trust dimension indicators of the current ship; S5132: obtaining an influence factor set of the application weight; S5133: generating the application weight based on the dimension indicator scores and the influence factor set; S5134: calculating the deviation tolerance threshold according to the application weight and the trust level.

[0054] The trust level comprises multiple trust dimension indicators, which are quantitative indicators for evaluating the reliability of the ship from different aspects, and can specifically include the number of rule violations, the trajectory compliance rate of the intended declaration, and the historical conflict resolution rate, etc.

[0055] The dimension index score refers to a score obtained by quantitatively evaluating each trust dimension index, which can be calculated through a preset scoring rule or model; the application weight influencing factor set refers to a set of various factors influencing the application weight of the planned operation parameter, which can specifically include parameter types, current environmental conditions, operation area characteristics, etc.; based on the dimension index score and the influencing factor set, generating the application weight refers to calculating the application weight value of the planned operation parameter according to the performance of the ship in each trust dimension and the specific circumstances of the influencing factors, which can be realized through weighted average, machine learning model prediction or rule engine judgment, etc.

[0056] By refining the trust level of the ship into multiple trust dimension indexes and quantitatively scoring these dimensions, the reliability of the ship can be more comprehensively evaluated. At the same time, by introducing the application weight influencing factor set, the generation process of the application weight can take into account various actual situations such as parameter types and environmental factors, realizing the dynamic adjustment and refinement of the application weight. It is precisely due to the combination of multi-dimensional trust evaluation and dynamic application weight that the finally calculated deviation tolerance threshold can more accurately reflect the actual reliability of the ship in a specific situation and the importance of the parameter, thereby improving the accuracy of the judgment of the deviation of the behavior of the ship. When the deviation of the behavior of the ship from the basic rules is monitored, the system can more effectively distinguish whether it is a planned deviation with rationality or a real violation of rules based on a more accurate deviation tolerance threshold, avoiding misjudgment caused by single trust evaluation or fixed weight, and improving the monitoring efficiency and judgment accuracy.

[0057] In some examples of the present embodiment, the application is implemented as follows. It is assumed that the deviation tolerance threshold of the speed parameter of a specific cargo ship on a certain voyage needs to be calculated. First, the system obtains the dimension indicator scores of multiple trust dimension indicators of the cargo ship. For example, according to historical records, the cargo ship has a low number of rule violations, corresponding to a dimension indicator score of 90; the trajectory compliance rate of the intent declaration is high, with a score of 85; the historical conflict resolution rate is high, with a score of 95. Next, the system obtains a set of influence factors of the application weight. The weight of the speed parameter needs to be calculated at present, while considering environmental factors such as low navigation density and good visibility of the current voyage. Then, based on these dimension indicator scores (90, 85, 95) and the set of influence factors (parameter type: speed; environmental factors: low navigation density, good visibility), the system generates the application weight of the speed parameter. For example, through a preset rule, high trust scores and good environmental factors cause the application weight of the speed parameter to be set to a relatively high value, for example, 0.8. Finally, according to the generated application weight (0.8) and the overall trust level of the cargo ship (for example, a high trust level obtained based on the comprehensive dimension scores), the deviation tolerance threshold of the speed parameter is calculated. For example, through a formula: threshold = basic threshold * (1 - trust level coefficient) * (1 - application weight), or by consulting a two-dimensional lookup table based on trust level and application weight, a specific speed deviation tolerance threshold is obtained, for example, 0.5 knots.

[0058] Referring to Figure 4 Further, S5134 comprises: S51341: obtaining specific operation instruction information contained in the structured operation intent declaration corresponding to the current ship; S51342: identifying the sensitivity level or priority of the specific operation instruction information; S51343: obtaining the deviation tolerance threshold by joint calculation according to the sensitivity level or priority, the multiple trust dimension indicators, and the application weight.

[0059] The specific operation instruction information refers to the instructions explicitly listed in the structured operation intent declaration, issued by the management system to which the ship belongs, and guiding the specific operation of the ship, which can include route instructions, speed instructions, operation area instructions, and specific task instructions. The sensitivity level or priority refers to the assessment of the importance or urgency of the specific operation instruction information, which can be determined according to factors such as instruction content, safety risks involved, and impact on navigation order, for example, divided into three levels of high, medium, and low, or assigned different priority values The scheme more accurately calculates the deviation tolerance threshold, further introduces the consideration of the importance of the specific operation instruction information currently executed on the basis of considering the historical trust performance of the ship and the importance of the parameters. Specifically, first, the specific operation instruction information in the structured operation intention declaration submitted by the ship is obtained, which is the basis for judging the nature of the current task. Then, the sensitivity level or priority of these instructions is identified, so as to quantify the importance of the instructions. It is just because that different instructions have different influences on safety and order, the deviation tolerance during the execution of the instructions should also be different. On this basis, the identified sensitivity level or priority is jointly calculated with the multiple trust dimension indicators reflecting the historical performance of the ship and the application weight reflecting the importance of the parameters. This joint calculation mechanism makes the determination of the deviation tolerance threshold no longer rely on the general trust level of the ship or the general importance of the parameters, but comprehensively considers the information of "how is the ship" (trust dimension indicators), "are the parameters important or not" (application weight) and "is the current task urgent or dangerous" (sensitivity level or priority). It is just because of this multi-dimensional and situational joint calculation that the finally obtained deviation tolerance threshold can more accurately reflect the actual tolerance degree of the deviation of the ship in the current specific situation, so as to effectively distinguish the apparent deviation caused by following the specific instruction with rationality from the real violation behavior.

[0060] In some examples of the embodiment, it is assumed that the current ship is executing an operation instruction of passing through a specific narrow channel. The system first obtains the structured operation intention declaration submitted by the ship, and extracts the specific operation instruction information about "passing through the narrow channel" from it. Then, the system identifies the sensitivity level or priority of the instruction. Since passing through the narrow channel requires high safety for navigation, the system identifies it as a high sensitivity level. At the same time, the system queries the historical behavior record of the ship to obtain the scores of multiple trust dimension indicators, for example, the historical rule violation times of the ship are few, and the trajectory compliance rate of the intention declaration is high. The system also obtains the application weight corresponding to the planned operation parameters (such as the trajectory and the speed) related to the operation instruction. Finally, the system jointly calculates the deviation tolerance threshold of the ship during passing through the narrow channel according to the identified high sensitivity level, the high trust dimension indicator score of the ship and the corresponding application weight. In this case, even if the historical trust degree of the ship is high, since the sensitivity level of the operation instruction is high, the calculated deviation tolerance threshold will be set very small, for example, the allowed position deviation range is limited to a very small range, to ensure the safety of navigation.

[0061] Reference Figure 5 Further, step S51343 comprises: A1: judging whether the sensitivity level or priority, the trust level and / or the application weight exist a judgment result direction conflict; A2: if there is a direction conflict of the judgment result, a preset conflict processing strategy is called, and the conflict processing strategy includes: A3: quantitative evaluation is performed on specific level values of the sensitive level or priority, trust level and / or application weight associated with the direction conflict of the judgment result; A4: based on a preset priority relationship between factors, weight reordering corresponding to the sensitive level or priority, trust level and / or application weight associated with the direction conflict of the judgment result is obtained; A5: according to the weight reordering, the sensitive level or priority and the multiple trust dimension indicators and the application weight are weighted and calculated to obtain the deviation tolerance threshold.

[0062] wherein the direction conflict of the judgment result refers to a situation that the sensitive level or priority, trust level and / or application weight are contradictory or inconsistent when indicating whether the deviation tolerance threshold should be biased to strict or lenient, which can be realized by comparing the threshold directions indicated by each factor (for example, high sensitive level indicates strict, and high trust level indicates lenient); the conflict processing strategy refers to a series of preset rules and calculation steps for solving the above-mentioned direction conflict of the judgment result, which can be realized by a rule-based expert system or a lookup table method; the quantitative evaluation of the specific level values refers to the conversion of the qualitative or semi-quantitative factors such as the sensitive level or priority, trust level and / or application weight into numerical values that can be operated mathematically, which can be realized by a preset numerical mapping table or function; the preset priority relationship between factors refers to the relative importance order of the influence of each factor (sensitive level or priority, trust level, application weight) when the direction conflict of the judgment result occurs, which can be realized by a priority list or a hierarchical structure; the weight reordering refers to adjusting the proportion or influence of the sensitive level or priority, multiple trust dimension indicators and application weight in the joint calculation of the deviation tolerance threshold according to the preset priority relationship between factors, which can be realized by adjusting the coefficients in the weighted calculation formula or introducing a correction factor.

[0063] The conflict processing mechanism is started by judging whether there is a conflict in the direction of the judgment result of the sensitivity level or priority, trust level and / or application weight. The reason for judging whether there is a conflict is that only when there is a conflict, simple weighted calculation may lead to unreasonable threshold, and when there is no conflict, regular weighted calculation is enough. It is because of the identification of the conflict that the preset conflict processing strategy needs to be called. The strategy first quantitatively evaluates the specific level value of the conflict associated factors, which is to unify different nature factors into a calculable numerical form, laying the foundation for subsequent weight adjustment. On this basis, based on the preset priority relationship between factors, the weight of these conflict associated factors is reordered. This step is the core of solving the conflict. Through the preset priority relationship, for example, the sensitivity level is higher than the trust level, it is ensured that when the sensitivity level requires strictness and the trust level tends to be lenient, the requirement of the sensitivity level can be given priority to be reflected, so as to avoid excessive relaxation of the monitoring of sensitive areas or instructions due to high trust level. Finally, the sensitivity level or priority and multiple trust dimension indicators and application weights are weighted calculated according to the weight reordering to obtain the final deviation tolerance threshold. This weighted calculation after weight adjustment can effectively coordinate the influence of conflict factors, so that the calculated deviation tolerance threshold is more reasonable and accurate. Compared with the basic scheme (claim 4), the basic scheme only performs joint calculation and does not consider the potential conflict between factors and its processing, which may lead to deviation of the threshold setting in the conflict scenario. The present scheme introduces conflict judgment and weight adjustment mechanism based on priority relationship, further improves the robustness and accuracy of threshold determination in the calculation framework of the basic scheme, so that the final deviation tolerance threshold can more accurately reflect the actual risk and management demand, thereby better supporting the accurate determination of the deviation behavior of the ship.

[0064] In some examples of the present embodiment, specifically, when the system monitors that the real-time behavior parameters of a vessel deviate from the electronic fence base rule set, and there is an effective structured operation intent declaration associated with the vessel, the system determines the deviation tolerance threshold according to the trust level of the vessel. In the process of determining the threshold, the system obtains the sensitive level or priority of the specific operation instruction in the intent declaration, and the trust dimension index scores and the application weight related to the planned operation parameter type of the vessel. The system determines whether there is a conflict in the judgment direction of the sensitive level or priority, the trust level and the application weight. For example, if the sensitive level is high (indicating that a very strict threshold is required), but the trust level of the vessel is also high and the application weight is large (both indicating that the threshold can be appropriately relaxed), the system will identify such a conflict. If there is a conflict, the system will call a preset conflict handling strategy. First, the specific values of high sensitive level, high trust level and large application weight are quantitatively evaluated, for example, the sensitive level is mapped to a value of 3, the trust level score is 95, and the application weight is 0.8. Then, based on the preset priority relationship between factors, for example, set the sensitive level priority higher than the trust level, and the trust level priority higher than the application weight, the system will reorder or adjust the weights used to calculate the threshold according to this priority relationship. For example, even if the trust level and the application weight are high, since the sensitive level has the highest priority and its value is high, the system will adjust the weight in the calculation formula so that the high sensitive level has a much greater impact on the final threshold than the high trust level and the large application weight. Finally, the system calculates the final deviation tolerance threshold according to the re-ordered weights, and combines the sensitive level, the trust dimension index score and the application weight. This threshold will be more stringent than the threshold obtained by simple weighting calculation without conflict handling, thus more in line with the monitoring requirements in the high sensitive level scenario.

[0065] Referring to Figure 6 Further, step A4 comprises: A41: obtaining a plurality of historical conflict decision records, the historical conflict decision records comprising original specific level values of the sensitive level or priority, the trust level and the application weight at the time of the historical conflict, the deviation tolerance threshold adopted at the time of the historical conflict, and the nature of the subsequent confirmation of the deviation behavior of the historical conflict; A42: determining whether the priority relationship between the factors corresponding to the historical conflict is inconsistent with the nature of the subsequent confirmation of the deviation behavior of the historical conflict; A43: if inconsistent, identifying a corresponding misjudgment mode, and adjusting and updating the priority relationship between factors according to the misjudgment mode.

[0066] The historical conflict decision record refers to the complete record of the decision-making process and results generated by the system when handling historical deviation behavior conflict events. It specifically includes the specific values or levels of each factor (sensitivity level or priority, trust level, application weight) that caused the conflict, the deviation tolerance threshold calculated by the system based on the rules and priority relationships at that time, and the true nature of the deviation behavior confirmed by artificial review or external information afterwards (for example, whether it is a real violation or a reasonable planned deviation). These records can be stored in a database for subsequent analysis and learning. The priority relationship between factors refers to the relative importance or influence order between the sensitivity level or priority, the trust level, and the application weight when handling the direction conflict of the judgment result. It determines which factor's tendency dominates in the final deviation tolerance threshold calculation when the judgment directions of these factors are inconsistent. The misjudgment mode refers to a recognizable and regular error judgment mode formed due to improper setting of the priority relationship between factors, resulting in repeated judgments by the system that are inconsistent with the true nature of the subsequent confirmed deviation behavior for specific combinations of factor values or specific types of deviation behavior.

[0067] By obtaining and analyzing historical conflict decision records, the system compares the historical judgment results made based on the preset priority relationship between factors with the subsequent true nature of the deviation behavior. When the historical judgment results are found to be inconsistent with the true nature, it indicates that the current priority relationship between factors is biased when handling such specific situations, leading to misjudgment. The system further identifies the specific mode that leads to misjudgment, such as whether it is due to overemphasis on the sensitivity level ignoring the reasonableness of the high trust level, or vice versa. Based on the identified misjudgment mode, the system can adjust and update the preset priority relationship between factors. For example, if it is found that the system tends to misjudge reasonable planned deviations as violations in a certain mode, the relative priority of the factor that leads to misjudgment (such as sensitivity level) can be appropriately reduced, or the relative priority of another factor (such as trust level) can be appropriately increased. Through this feedback and adjustment mechanism based on historical experience, the priority relationship between factors can be continuously optimized to better fit actual situations, thereby improving the accuracy of the system's judgment when handling future conflicts and reducing the occurrence of misjudgments. This mechanism of self-adaptive optimization of judgment rules based on historical data enables the system to more intelligently distinguish between different types of deviation behavior, improving the reliability of overall monitoring.

[0068] In some embodiments of the present disclosure, the system can maintain a database of historical conflict decision records. When a deviation conflict occurs and the true nature of the conflict is confirmed later, the system stores the key information of the event, including the sensitive level or priority at that time, the trust level, the specific values of the application weight, the deviation tolerance threshold calculated by the system, the preliminary decision made by the system based on the threshold (planned deviation or violation), and the final confirmed nature of the event, as a historical conflict decision record in the database. The system can periodically or after accumulating a certain number of records, start an optimization process. For example, the system traverses the historical conflict decision records, and for each record, compares the system's decision at that time with the later confirmed nature. If the two are inconsistent, it is marked as a misjudgment. The system can further analyze these misjudgment records, for example, statistics on which factor combinations (such as high sensitive level, medium trust level, low application weight) have a higher frequency of misjudgment or a larger degree of inconsistency. The system can quantify the degree of inconsistency, for example, if the system judges as "planned deviation" but later confirms as "serious violation", the degree of inconsistency is higher; if the system judges as "violation" but later confirms as "reasonable planned deviation", the degree of inconsistency is also higher. The system can group records with similar factor combinations and degrees of inconsistency to form case groups. By analyzing the concentration of the degree of inconsistency in the case group, for example, calculating the average degree of inconsistency or statistics of the proportion of high inconsistency records, if the concentration exceeds a pre-set threshold, it is determined that there is a misjudgment pattern. For example, it is found that when the sensitive level is high and the trust level is low, the system tends to misjudge the reasonable deviation as a violation. In response to this misjudgment pattern, the system can adjust the priority relationship between factors, for example, when dealing with high sensitive level and low trust level conflicts, appropriately reduce the influence weight of the sensitive level, or increase the influence weight of the trust level, so that in future conflict processing, the system can more accurately weigh the two factors and reduce the occurrence of such misjudgments.

[0069] Referring to Figure 7 Further, the step of identifying the corresponding misjudgment pattern comprises: B1: quantifying the degree of inconsistency between the priority relationship between factors corresponding to each historical conflict decision and the nature of the subsequent confirmation of the deviation behavior of the historical conflict, generating an inconsistency quantization value; B2: aggregating records with the same factor combination of a plurality of inconsistency quantization values to form a case group; B3: analyzing the concentration value of the inconsistency quantization values in the case group; B4: if the concentration value meets a pre-set concentration threshold, it is determined that there is a misjudgment pattern.

[0070] wherein, the degree-of-inconsistency quantification value refers to a numerical representation of the difference between the judgment result of the deviating behavior based on the priority relationship between the factors at that time and the actual nature of the deviating behavior subsequently confirmed in the historical conflict decision, which can be calculated according to the combination of the judgment result (deviating behavior within plan or violation) and the subsequent confirmed nature (actually allowed or actually violated) using a preset comparison matrix, for example, complete inconsistency (judgment violation but actually allowed) is assigned a higher numerical value, partial inconsistency (judgment within plan but actually violated) is assigned a medium numerical value, and complete consistency is assigned a zero value; the factor combination refers to the combination of the specific values or value ranges of the sensitive level or priority, the trust level, and the application weight that lead to the historical conflict decision; the case group refers to a collection formed by gathering multiple historical conflict decision records with the same factor combination together; the concentration degree value refers to a statistical quantity of the dispersion or concentration degree of multiple degree-of-inconsistency quantification values in the case group, which can be measured using statistical indicators such as standard deviation, variance, mean absolute deviation, interquartile range, etc.; the concentration threshold refers to a preset numerical value used to determine whether the degree-of-inconsistency quantification values in the case group are sufficiently concentrated, thereby determining whether there is a misjudgment mode.

[0071] In the joint calculation of the deviation tolerance threshold based on the sensitivity level or priority, trust level and application weight, if there is a directional conflict in the judgment result, a conflict handling strategy will be called, which reorders the weights based on the pre-set priority relationship between factors. In order to optimize this priority relationship, the system will obtain historical conflict decision records. These records contain the factor level values at the time of conflict, the judgment result based on the priority relationship at the time, and the subsequent confirmation nature of the deviation behavior. In order to accurately identify the misjudgment patterns in historical conflict decisions, the system analyzes each historical conflict decision. First, quantify the degree of inconsistency between the priority relationship between factors corresponding to the historical conflict decision (implicit in the judgment result at the time) and the subsequent confirmation nature, generating a quantified inconsistency value. This quantified value reflects the degree of "error" in the decision at the time. Then, historical records with the same factor combination (i.e. conflicts occurring under similar sensitivity levels, trust levels, and application weight conditions) are aggregated to form a case group. This is done to analyze whether misjudgment under certain conditions is universal. Next, analyze the concentration of these quantified inconsistency values in the case group. If these quantified values are relatively concentrated (e.g. under a certain factor combination, many historical records show that the judgment result is highly inconsistent with the subsequent confirmation nature), it indicates that the current priority relationship under this factor combination is likely to cause systematic misjudgment. Finally, if the concentration value meets the pre-set concentration threshold, it is determined that there is a misjudgment pattern. After identifying the misjudgment patterns, the system can adjust the priority relationship between factors more accurately based on these patterns, rather than simply adjusting based on a single historical record. This pattern-based adjustment can more effectively reduce the likelihood of future misjudgment under similar factor combinations, thereby improving the accuracy of the deviation tolerance threshold calculation, making the system's judgment of ship deviation behavior more accurate, and reducing false positives and false negatives.

[0072] In some examples of the embodiment, the system records multiple historical conflict decisions. For example, in a certain case group, all records correspond to the factor combination of "medium sensitivity level, low trust level, high application weight". For each historical record in this case group, the system calculates a degree of inconsistency quantification value. For example, if in a certain record, the system judged as "planned deviation" at that time, but later confirmed that it was actually "violation of rules", according to the preset comparison matrix, a higher degree of inconsistency quantification value can be calculated, for example, the value is 3. If in another record, the system judged as "violation of rules" at that time, and later confirmed that it was actually "planned deviation", a higher degree of inconsistency quantification value can be calculated, for example, the value is 5. If the judgment and the confirmation are consistent, the quantification value is 0. The system collects the degree of inconsistency quantification values of all records in this case group, for example, obtains a set of values {3, 5, 4, 4, 5, 3, 4, 5}. The system calculates the central tendency value of this set of values. For example, calculate its standard deviation. If the standard deviation is low, it means that these degree of inconsistency quantification values are relatively concentrated, for example, all between 3 and 5. The system compares the calculated standard deviation with the preset centralization threshold. For example, the preset threshold is 1.0. If the calculated standard deviation is 0.8, which is less than the threshold 1.0, it is determined that there is a misjudgment mode under the factor combination of "medium sensitivity level, low trust level, high application weight". After identifying the misjudgment mode, the system can adjust the priority relationship between factors accordingly, for example, under this factor combination, reduce the influence of trust level or application weight on the final judgment, or increase the influence of sensitivity level, to reduce the possibility of misjudging actual violation of rules as planned deviation in the future under this condition.

[0073] Referring to Figure 8 Further, B3 comprises: B31: statistically analyze the degree of inconsistency quantification values in the case group to obtain a central tendency value.

[0074] Among them, statistical analysis refers to the use of statistical methods to process and interpret data, which can use descriptive statistics, such as mean, median, mode, variance, standard deviation, quartile, skewness, kurtosis, etc., or inferential statistical analysis, such as hypothesis testing, regression analysis, etc. to achieve.

[0075] By statistically analyzing the quantified values of the degree of inconsistency in the case group, a concentration degree value that reflects the tightness of the distribution of these quantified values can be obtained. In the process of identifying the misjudgment pattern, first, the quantified values of the degree of inconsistency are generated according to the historical conflict decision records, and records with the same factor combination are classified into the same case group. In order to determine whether the case group represents a typical misjudgment pattern, it is necessary to evaluate the concentration degree of the quantified values of the degree of inconsistency in the case group. Through statistical analysis, the mean, median, variance, standard deviation and other indicators can be calculated. These indicators can quantify the distribution characteristics of the quantified values of the degree of inconsistency. For example, a smaller variance or standard deviation indicates that the quantified values are more concentrated, meaning that the historical conflict decisions in the case group show a high consistency in the degree of inconsistency, and thus are more likely to represent a misjudgment pattern with universality. Conversely, a larger variance or standard deviation indicates that the quantified values are more dispersed, which may mean that the case group contains multiple different situations, or that the misjudgment pattern is not typical. Through such statistical analysis, the overall characteristics of the case group can be converted into one or a set of numerical values, providing an objective basis for subsequent judgment of whether the concentration threshold is met. This concentration degree evaluation based on statistical analysis can more comprehensively and accurately reflect the distribution characteristics of the quantified values compared to simple aggregation, thereby improving the accuracy of misjudgment pattern identification. This method, combined with the steps of aggregating records with the same factor combination into a case group and determining a misjudgment pattern if the concentration degree value meets the pre-set concentration threshold, forms a complete misjudgment pattern identification process based on data analysis, which helps the system to more effectively learn and improve the priority relationship between factors from historical data.

[0076] In some examples of the present embodiment, statistical analysis can be performed on the quantified values of the degree of inconsistency of a case group. For example, a case group contains 10 historical conflict records, and their quantified values of the degree of inconsistency are 0.8, 0.9, 0.7, 0.85, 0.92, 0.78, 0.88, 0.75, 0.81, and 0.89. The mean (about 0.826), median (0.84), variance (about 0.004), and standard deviation (about 0.063) can be calculated. These statistical quantities constitute the concentration degree value. If the pre-set concentration threshold is that the standard deviation is less than 0.1, then the standard deviation of 0.063 of this case group meets the threshold, and it can be determined as a misjudgment pattern.

[0077] Reference Figure 9 Further, B1 comprises: B11: obtaining a determination result of the deviating behavior of the historical conflict; B12: obtaining the nature of the subsequent confirmation of the deviating behavior of the historical conflict; B13: calculating the inconsistency quantification value according to the preset comparison matrix, by synthesizing the difference between the judgment result of the deviating behavior and the nature of the subsequent confirmation of the deviating behavior of the historical conflict.

[0078] The inconsistency quantification value is generated by quantifying the inconsistency between the priority relationship between factors corresponding to each historical conflict decision and the nature of the subsequent confirmation of the deviating behavior of the historical conflict, which means that the difference between the preliminary judgment result made by the system based on the priority relationship between factors when the historical conflict occurs and the true nature of the deviating behavior finally confirmed is objectively represented by a numerical index. The judgment result of the deviating behavior of the historical conflict is obtained by making a preliminary judgment on the deviating behavior of the ship according to the rules and the priority relationship between factors at that time when the historical conflict occurs, and the judgment result can be a planned deviating or a violation behavior. The nature of the subsequent confirmation of the deviating behavior of the historical conflict is obtained by obtaining the final evaluation result of the deviating behavior in the historical conflict, which can come from manual review, cross verification of other system data or supplementary information provided by the ship management party, and its nature can include confirming planned deviating, confirming minor violation, confirming serious violation, etc. The preset comparison matrix is a set of predefined mapping relationships, which defines the inconsistency quantification value corresponding to different combinations of the judgment result of the deviating behavior and the nature of the subsequent confirmation of the deviating behavior, which can be realized in the form of table, rule set or function, etc. The inconsistency quantification value is calculated by synthesizing the difference between the judgment result of the deviating behavior and the nature of the subsequent confirmation of the deviating behavior of the historical conflict, which means that according to the obtained judgment result of the deviating behavior and the nature of the subsequent confirmation of the deviating behavior, the mapping relationship defined in the preset comparison matrix is consulted or applied to obtain the corresponding inconsistency quantification value.

[0079] By obtaining the initial determination result of the system on the deviation behavior when the historical conflict occurs, and obtaining the final confirmation nature of the deviation behavior, then using the preset comparison matrix, the difference between the two results is converted into a quantitative value, that is, the inconsistency degree quantitative value. This quantitative value objectively reflects the degree of inconsistency between the decision made by the system based on the priority relationship between the factors at that time and the actual situation. In this way, the originally ambiguous or qualitative "inconsistency" judgment is converted into an accurate numerical representation. These quantitative values can be used for aggregation and statistical analysis of historical conflict records with the same factor combination, so as to identify the case group with high concentration of inconsistency degree quantitative value, and then determine the misjudgment mode. This quantitative method provides a reliable data basis for subsequent statistical analysis and pattern recognition, making the identification of misjudgment mode more accurate and objective. This quantitative basis combined with the subsequent case group aggregation, concentration degree analysis forms a complete misjudgment mode identification mechanism based on quantitative data, thereby improving the effectiveness of the entire misjudgment mode identification process, and further adjusting the priority relationship between factors more accurately, improving the accuracy of monitoring.

[0080] In some examples of the present embodiment, a comparison matrix can be preset, for example, the matrix can define: if the determination result is "planned deviation", and the subsequent confirmation nature is "confirm planned deviation", the inconsistency degree quantitative value is 0; if the determination result is "planned deviation", and the subsequent confirmation nature is "confirm slight violation", the inconsistency degree quantitative value is 1; if the determination result is "planned deviation", and the subsequent confirmation nature is "confirm serious violation", the inconsistency degree quantitative value is 3; if the determination result is "violation behavior", and the subsequent confirmation nature is "confirm planned deviation", the inconsistency degree quantitative value is 2; if the determination result is "violation behavior", and the subsequent confirmation nature is "confirm slight violation", the inconsistency degree quantitative value is 0.5; if the determination result is "violation behavior", and the subsequent confirmation nature is "confirm serious violation", the inconsistency degree quantitative value is 0. When processing a historical conflict decision record, first obtain the determination result of the deviation behavior recorded in the record, for example "violation behavior", and then obtain the nature of the subsequent confirmation of the deviation behavior, for example "confirm planned deviation". According to the preset comparison matrix, find the quantitative value corresponding to the determination result "violation behavior" and the subsequent confirmation nature "confirm planned deviation", and get the inconsistency degree quantitative value as 2. This quantitative value represents the inconsistency degree of the historical conflict decision.

[0081] Reference Figure 10 Further, the present application also provides a marine electronic fence internet monitoring system, comprising: A receiving module is configured to continuously receive a structured operation intent declaration submitted by a ship, wherein the structured operation intent declaration comprises planned operation parameters and specific operation instruction information. an information query module, configured to obtain a historical behavior record associated with the ship, the historical behavior record comprising a historical accuracy record of structured operation intent declaration and a historical rule compliance record; a trust level management module, configured to evaluate a trust level of a ship manager according to the historical behavior record, and to maintain and update the trust level; the information query module is further configured to query whether there exists an effective structured operation intent declaration related to the current ship in space-time when it is monitored that the real-time behavior parameter of the current ship deviates from the preset e-fence basic rule set; a determination module, configured to, if there exists, determine a deviation tolerance threshold of a corresponding planned operation parameter according to the trust level of the current ship, compare the real-time behavior parameter with the planned operation parameter of the current ship to obtain an actual deviation degree, and determine whether the deviation behavior is an in-plan deviation or a rule violation behavior according to a comparison result of the actual deviation degree and the deviation tolerance threshold; the determination module is further configured to, if there does not exist, determine the nature of the deviation behavior according to the e-fence basic rule set.

[0082] Among them, the receiving module refers to a unit for receiving external input information, which can be realized by a network communication interface, a data acquisition interface or a message queue interface. Among them, the information query module refers to a unit for obtaining data from a storage medium or an external source, which can be realized by a database access interface, a file system interface or a remote data service interface. Among them, the trust level management module refers to a unit for processing and updating the logic related to the trust level of the ship, which can be realized by a calculation processing unit, an algorithm execution unit or a state machine management unit. Among them, the determination module refers to a unit for logical judgment and decision-making according to input information, which can be realized by a logical judgment unit, a rule engine or a decision tree execution unit.

[0083] The above only describes the embodiments of the present application and does not limit the protection scope of the present application. For those skilled in the art, the present application can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A method for monitoring an offshore electronic fence via the Internet, characterized in that: The method comprises: Continuously receiving structured operation intention statements submitted by vessels, wherein the structured operation intention statements include planned operation parameters and specific operation instruction information; Obtaining a historical behavior record associated with the vessel, the historical behavior record including a historical accuracy record and a historical rule compliance record of the structured operational intent statement; Assess the trust level of the vessel manager based on the historical behavior records, and maintain and update the trust level; When it is detected that the real-time behavior parameters of the current vessel deviate from the preset electronic fence basic rule set, query whether there is an effective structured operation intention statement related to the current vessel in time and space; If so, determining a deviation tolerance threshold for the corresponding planned operation parameter based on the trust level of the current vessel, comparing the real-time behavior parameter with the planned operation parameter of the current vessel to obtain an actual degree of deviation, and determining whether the deviation behavior is a planned deviation or a violation based on a comparison result of the actual degree of deviation with the deviation tolerance threshold; If not, the nature of the deviation behavior is determined according to the electronic fence basic rule set.

2. The method for monitoring maritime electronic fences via the Internet according to claim 1, wherein: The step of determining a deviation tolerance threshold of the corresponding planned operation parameter according to the trust level of the current vessel includes: Obtain parameter type information of the planned operation parameter; Obtaining a preset application weight corresponding to the parameter type; A deviation tolerance threshold of the planned operation parameter is calculated based on the trust level of the current vessel and the application weight.

3. The method for monitoring maritime electronic fences via the Internet according to claim 2, characterized in that: The trust level includes multiple trust dimension indicators, including the number of rule violations, the trajectory compliance rate of the statement of intent, and the historical conflict resolution rate. The calculation of the deviation tolerance threshold of the planned operation parameter based on the trust level of the current vessel and the application weight includes: Obtaining dimension indicator scores of the plurality of trust dimension indicators of the current vessel; Obtaining a set of influencing factors of the application weight; Generating the application weight based on the dimension indicator score and the impact factor set; The deviation tolerance threshold is calculated according to the application weight and the trust level.

4. The method for monitoring maritime electronic fences via the Internet according to claim 3, wherein: The calculating the deviation tolerance threshold according to the application weight and the trust level includes: Obtaining specific operation instruction information contained in the structured operation intention statement corresponding to the current vessel; Identify the sensitivity level or priority of the specific work instruction information; The deviation tolerance threshold is obtained by jointly calculating the sensitivity level or priority, the multiple trust dimension indicators and the application weight.

5. The method for monitoring maritime electronic fences via the Internet according to claim 4, characterized in that: The step of obtaining the deviation tolerance threshold by jointly calculating the sensitivity level or priority, the plurality of trust dimension indicators, and the application weight includes: Determining whether there is a directional conflict in the sensitivity level or priority, the trust level, and / or the application weight; If there is a directional conflict in the judgment result, a preset conflict handling strategy is called, and the conflict handling strategy includes: Performing a quantitative evaluation on specific level values ​​of the sensitivity level or priority, the trust level, and / or the application weight associated with the directional conflict of the judgment result; Based on the preset priority relationship between the factors, reorder the weights corresponding to the sensitivity level or priority, the trust level and / or the application weight associated with the directionality conflict of the judgment result; The sensitivity level or priority level is reordered according to the weights and weighted calculation is performed on the plurality of trust dimension indicators and the application weights to obtain the deviation tolerance threshold.

6. The method for monitoring maritime electronic fences via the Internet according to claim 5, characterized in that: The reordering of the sensitivity level or priority, the trust level, and / or the application weight corresponding to the directionality conflict associated with the judgment result based on the preset priority relationship between the factors includes: Acquiring a plurality of historical conflict decision records, the historical conflict decision records including original specific level values ​​of the sensitivity level or priority, the trust level, and the application weight when the historical conflict occurred, the deviation tolerance threshold adopted when the historical conflict occurred, and the nature of subsequent confirmation of the deviation behavior of the historical conflict; determining whether the priority relationship between the factors corresponding to the historical conflict is inconsistent with the nature of the subsequent confirmation of the deviation behavior of the historical conflict; If they do not match, the corresponding misjudgment pattern is identified, and the priority relationship between the factors is adjusted and updated according to the misjudgment pattern.

7. The method for monitoring maritime electronic fences via the Internet according to claim 6, characterized in that: The misjudgment pattern corresponding to the identification includes: quantifying the degree of inconsistency between the priority relationship between the factors corresponding to each of the historical conflict decisions and the nature of the subsequent confirmation of the deviation behavior of the historical conflict, and generating a quantitative value of the degree of inconsistency; aggregating a plurality of records having the same factor combination in the quantitative values ​​of the non-compliance degree to form a case group; Analyzing the concentration values ​​of the quantitative values ​​of the degree of non-compliance in the case group; If the concentration value meets the preset concentration threshold, it is determined to be the misjudgment mode.

8. The method for monitoring maritime electronic fences via the Internet according to claim 7, characterized in that: The analyzing the concentration value of the quantitative value of the non-compliance degree in the case group includes: The quantitative values ​​of the degree of non-compliance in the case group are statistically analyzed to obtain a concentration value.

9. The method for monitoring maritime electronic fences via the Internet according to claim 7, characterized in that: The step of quantifying the degree of inconsistency between the priority relationship between the factors corresponding to each of the historical conflict decisions and the nature of the subsequent confirmation of the deviation behavior of the historical conflict to generate a quantitative value of the degree of inconsistency includes: Obtaining a determination result of the deviation behavior of the historical conflict; obtaining the nature of subsequent confirmation of said deviation from said historical conflict; The quantitative value of the degree of non-compliance is calculated based on a preset comparison matrix and the difference between the determination result of the deviation behavior and the subsequent confirmed properties of the deviation behavior of the historical conflict.

10. An Internet monitoring system for marine electronic fences, characterized in that: include: a receiving module, configured to continuously receive a structured operation intention statement submitted by a vessel, wherein the structured operation intention statement includes planned operation parameters and specific operation instruction information; an information query module, configured to obtain historical behavior records associated with the vessel, the historical behavior records including historical accuracy records and historical rule compliance records of the structured operational intent statement; A trust level management module, configured to evaluate the trust level of the vessel manager based on the historical behavior records and to maintain and update the trust level; The information query module is further configured to query whether there is an effective structured operation intention statement related to the current vessel in time and space when it is detected that the real-time behavior parameters of the current vessel deviate from the preset electronic fence basic rule set; a determination module configured to, if present, determine a deviation tolerance threshold for the corresponding planned operation parameter based on the trust level of the current vessel, compare the real-time behavior parameter with the planned operation parameter of the current vessel to obtain an actual degree of deviation, and determine, based on a comparison result of the actual degree of deviation with the deviation tolerance threshold, whether the determination result of the deviation behavior is a planned deviation or a violation; The determination module is further configured to determine the nature of the deviation behavior based on the electronic fence basic rule set if the deviation behavior does not exist.

Images