AIS data pricing method and device, electronic equipment, readable storage medium and chip

Abstract

The embodiment of the invention provides an AIS data pricing method and device, electronic equipment, a readable storage medium and a chip, and the method comprises the steps: receiving user data; determining a first weight corresponding to the target ship area; determining a second weight corresponding to the use cycle of the user; determining a third weight corresponding to the user type; determining a fourth weight corresponding to the user payment mode; determining a first unit price according to the user data; determining a second unit price according to the first unit price, the first weight, the second weight, the third weight and the fourth weight; and determining a pricing report according to the user data and the second unit price. According to the scheme of the invention, multiple factors such as regional flow, time periods, user types and payment modes are comprehensively considered, fine and objective pricing is realized, and subjectivity and randomness in the pricing process are avoided.

Description

Technical Field

[0001] The present invention relates to the field of AIS data processing technology, and in particular to an AIS data pricing method, device, electronic device, readable storage medium, and chip. Background Art

[0002] Currently, the pricing of the Automatic Identification System (AIS) relies primarily on human experience and judgment, and cannot be accurately determined based on traffic volume in different sea areas and different user types. This results in a lack of quantitative basis for AIS pricing, and the price setting cannot meet the differentiated needs of users in different sea areas. Summary of the Invention

[0003] The purpose of the embodiments of the present invention is to provide an AIS data pricing method, device, electronic device, readable storage medium, and chip, which can solve the problem that AIS pricing lacks a quantitative basis and the price setting cannot meet the differentiated needs of users in different sea areas.

[0004] In view of this, an embodiment of a first aspect of the present invention provides an AIS data pricing method.

[0005] An embodiment of a second aspect of the present invention provides an AIS data pricing device.

[0006] An embodiment of a third aspect of the present invention provides an electronic device.

[0007] An embodiment of a fourth aspect of the present invention provides a readable storage medium.

[0008] An embodiment of the fifth aspect of the present invention provides a chip.

[0009] To achieve the above-mentioned objectives, an embodiment of a first aspect of the present invention provides an AIS data pricing method, comprising: receiving user data, the user data including latitude and longitude coordinates corresponding to a ship, a user demand time period, a user type, and a user payment mode; determining a target ship area based on the latitude and longitude coordinates, and determining a first weight corresponding to the target ship area; determining a user usage period based on the user demand time period, and determining a second weight corresponding to the user usage period; determining a third weight corresponding to the user type; determining a fourth weight corresponding to the user payment mode; determining a first unit price based on the user data; determining a second unit price based on the first unit price, the first weight, the second weight, the third weight, and the fourth weight; and determining a pricing report based on the user data and the second unit price.

[0010] The AIS data pricing method proposed in this invention determines a weighting system based on four dimensions: target vessel area, user usage cycle, user type, and user payment model. This method uses a combination of weights and discount coefficients to calculate these four parameters, achieving precisely differentiated pricing tailored to user needs. The global ocean is divided into multiple zones with varying traffic volume. The latitude and longitude coordinates of the desired zone, entered by the user, are then matched to determine the sea area used by the user's vessel and the weight assigned to that zone, known as the first weight. The first weight is positively correlated with the vessel traffic density within the zone; the higher the vessel traffic density, the larger the first weight. The user's desired usage cycle is determined based on the user's input time period, measured in days. The second weight is determined based on the user's usage cycle; the second weight is negatively correlated with the user's usage cycle; the longer the user's usage cycle, the smaller the second weight. The second weight represents a discount factor for the user's usage cycle; that is, as the user's usage cycle increases or a long-term subscription is made, the second weight decreases, and the discount factor increases. A third weight is determined based on the user type entered by the user; it is used to determine the intensity of the user's service demand and ability to pay. The third weight is positively correlated with the user's service demand intensity and ability to pay. Higher service demand intensity and ability to pay correspond to a larger third weight. The user's service demand intensity and ability to pay are determined based on user type, with corresponding reference data stored in the database for different user types. The fourth weight is determined by the user's selected payment model. The system's default payment models include first-time payment, subscription, and long-term contract. Different payment models have different discount coefficients, with long-term contract discounts being larger than subscription discounts. Users who choose the first-time payment model receive no additional discounts; that is, the fourth weight is the initial value. Users who choose the subscription model receive discounts for the first month / first year. Users who choose the long-term contract receive discounts throughout the user's lifetime. Subscription discounts and long-term contract discounts are the fourth weight, which is added to the second weight. A discount is calculated for the first unit price based on the first, second, third, and fourth weights to determine the final price for the user, the second unit price. A pricing report is generated, showing the user detailed parameters and the final price.

[0011] As can be understood, the present invention uses automated system processing to calculate initial pricing based on regional traffic, user usage time period, user type, and payment model, achieving refined and automated pricing, quickly generating pricing results, and improving AIS pricing efficiency. Based on the first weight corresponding to the ship area and the third weight corresponding to the user type, the AIS service needs of different regions are met in combination with the user type, thereby improving the accuracy and rationality of pricing. Based on the second weight corresponding to the user usage period and the fourth weight corresponding to the user payment model, further preferential treatment is added to increase user stickiness.

[0012] In the above technical solution, the target ship area is determined according to the latitude and longitude coordinates, including: obtaining global ship traffic information; dividing the global area according to the global ship traffic information to determine multiple determination areas; determining the boundary coordinate range corresponding to the determination area; and determining the target ship area according to the latitude and longitude coordinates and the boundary coordinate range.

[0013] In this solution, global vessel trajectory data, including vessel position, speed, and heading, is received in real time via AIS. This trajectory data is stored in the system database and then cleaned (denoising or completing) and aggregated (calculating the average daily number of vessels in different sea areas) to generate a vessel traffic density heat map. Global vessel traffic information is determined based on the vessel traffic density heat map. Based on vessel traffic density and geographic location information, the global sea area is divided into multiple determination areas, and the boundaries of each determination area are determined. Multiple boundary coordinates are determined for each area boundary. Based on these multiple boundary coordinates, the boundary coordinate range corresponding to the determination area is determined. The user-entered longitude and latitude coordinates are spatially matched with the boundary coordinates of each area to determine the boundary coordinate range to which the longitude and latitude coordinates belong. This determines the area to which the user-entered longitude and latitude coordinates belong, and the area to which the user-entered longitude and latitude coordinates belong is then determined. This area is then designated as the target vessel area.

[0014] Understandably, by obtaining global vessel traffic data to determine the division of regions, the system automatically matches the longitude and latitude coordinates entered by the user to quickly determine the vessel traffic situation in the sea area required by the user's vessel, as well as the region in which the longitude and latitude coordinates are located. By spatially matching the longitude and latitude coordinates with the coordinates of each region's boundaries, it provides a reference for subsequent regional weight calculations, improving the accuracy of AIS data pricing and the efficiency of the system's automatic pricing.

[0015] In any of the above technical solutions, optionally, determining the first weight corresponding to the target ship area includes: obtaining an initial first weight; determining the traffic density corresponding to the target ship area based on global ship traffic information; determining a first historical traffic density and a second historical traffic density corresponding to the target ship area based on the global ship traffic information, the first historical traffic density being greater than the second historical traffic density; determining the first weight based on the initial first weight, the traffic density, the first historical traffic density, and the second historical traffic density.

[0016] In this solution, the initial first weight is the basic weight corresponding to multiple judgment areas preset by the system. The initial first weight is positively correlated with the ship traffic density in the area. The greater the ship traffic density in the area, the greater the corresponding initial first weight. For example, the basic weight of the port area is 2.0, the basic weight of the traffic fortress area is 1.5, the basic weight of the main lane area is 1.2, and the basic weight of the ocean area is 1.0. Based on the global ship traffic information, multiple historical traffic density data of the current judgment area are determined, wherein the first historical traffic density is greater than the second historical traffic density, the first historical traffic density is the maximum value of the historical traffic density of the judgment area, and the second historical traffic density is the minimum value of the historical traffic density of the judgment area. The first weight of the target ship area, that is, the weight coefficient corresponding to the area type, is determined based on the traffic density of the judgment area, the maximum value of the historical traffic density, the minimum value of the historical traffic density and the initial first weight.

[0017] As can be understood, the system dynamically adjusts the first weight based on real-time traffic data, reflecting changes in regional traffic flow in real time. This replaces traditional manual judgment and improves the rationality of AIS data pricing. Furthermore, dynamically adjusting the first weight based on traffic density in the target vessel area avoids the rigidity of automatic pricing caused by static weights, thereby improving the alignment between AIS data pricing and market demand.

[0018] In any of the above technical solutions, optionally, determining the third weight corresponding to the user type includes: determining an initial third weight corresponding to the user type; determining a user contribution value based on user data; determining a reference contribution value; and determining a third weight based on the reference contribution value, the user contribution value, and the initial third weight.

[0019] In this solution, the third weight is positively correlated with the user's service demand intensity and ability to pay. Higher service demand intensity and ability to pay correspond to larger third weights. User service demand intensity and ability to pay are determined based on user type. Reference data for different user types is stored in a database. This reference data includes the service demand and ability to pay of each user group, and initial weights for each user type are preset. User types include commercial users, law enforcement users, and public welfare users. Commercial users have high service demand intensity, strong commercial dependence, and high ability to pay, and therefore require an increased weight to reflect a service premium. Law enforcement users have high service demand intensity but budget constraints, making their ability to pay less than commercial users. Public welfare users have low service demand intensity and less ability to pay than commercial users. The initial third weight for commercial users is greater than that for law enforcement users, which in turn is greater than that for public welfare users. User contribution values ​​and reference contribution values ​​are determined based on historical user behavior data. The maximum user contribution value across all historical user behavior data is the reference contribution value. The third weight for each user type is determined based on the reference contribution value, the user contribution value, and the initial third weight for that user type.

[0020] It can be understood that by normalizing the contribution values ​​of users of different sizes with reference to the contribution value, the user contribution values ​​corresponding to multiple user types are unified into the range of [0,1], so as to avoid commercial users with high payment ability from monopolizing discounts due to their high absolute consumption. Users with strong payment ability and service demand can still obtain weight improvement through long-term cooperation, thereby balancing the rights and interests of users of different sizes, realizing differentiated pricing strategies for different types of users, and thus improving user satisfaction.

[0021] In any of the above technical solutions, optionally, the user contribution value is determined based on user data, including: determining the total historical consumption and subscription duration corresponding to the user; determining the frequency of service usage based on the number of historical data requests of the user; determining the user contribution value based on the total historical consumption, subscription duration and service usage frequency.

[0022] In this solution, user contribution is determined by the user's historical total consumption, subscription duration, and service usage frequency. These total consumption, subscription duration, and service usage frequency are all derived from historical server data. The total historical consumption is the cumulative amount a user has spent on AIS data services, calculated by extracting consumption records associated with the user's ID from the server's historical data and aggregating them monthly. The subscription duration is the total duration of a user's continuous subscription to AIS services, calculated by extracting the start and end times of the user's continuous subscriptions from the server's historical data. The service usage frequency is the average number of data requests a user initiates per day, calculated by counting the number of daily requests from the server's historical data.

[0023] It is understandable that the method of determining user contribution value from three aspects: total historical consumption, subscription duration and frequency of service use, while taking into account the user's consumption capacity, service demand intensity and data activity, provides comprehensive indicators for various types of users, reduces the data deviation caused by a single indicator, and further improves the robustness of the third weight.

[0024] In any of the above technical solutions, optionally, determining the reference contribution value includes: obtaining a user history database; determining a historical user contribution value based on the user history database; and determining a reference contribution value based on multiple historical user contribution values.

[0025] In this solution, multiple historical user contribution values ​​(user contribution values) are determined in the user history database. The largest user contribution value among these values ​​is used as the reference contribution value. This reference contribution value maps user contribution values ​​to the [0, 1] interval, eliminating magnitude differences and normalizing the user contribution values. This normalization prevents large enterprises from monopolizing consumer resources due to high absolute consumption. Small and medium-sized enterprises or public welfare users can still increase their weight through long-term cooperation or frequent use, thereby improving user satisfaction and stickiness.

[0026] An embodiment of the second aspect of the present invention provides an AIS data pricing device, including: a user input module for receiving user data, the user data including the latitude and longitude coordinates corresponding to the ship, the user demand time period, the user type and the user payment mode; a data processing module for determining the target ship area based on the latitude and longitude coordinates, and determining a first weight corresponding to the target ship area; determining the user usage period based on the user demand time period, and determining a second weight corresponding to the user usage period; determining a third weight corresponding to the user type; and determining a fourth weight corresponding to the user payment mode; a pricing calculation module for determining a first unit price based on the user data; determining a second unit price based on the first unit price, the first weight, the second weight, the third weight and the fourth weight; and a report generation module for determining a pricing report based on the user data and the second unit price.

[0027] The AIS data pricing method provided by the present invention implements an AIS data pricing method, determines a weight system from four dimensions: target ship area, user usage cycle, user type, and user payment mode, and comprehensively calculates the four parameters of sea area, time, user type, and payment mode through weights and discount coefficients to achieve precise differentiated pricing based on user needs. Specifically, the user input module is used to accept the user's data needs, including the longitude and latitude coordinates of the area required by the user, the required time period range, user type, and payment mode; the pricing calculation module calculates and generates the final pricing price based on the various judgment results provided by the data processing module; the report generation module generates a visual pricing report based on the pricing results for users to download and reference; the data processing module is used to process user data and determine the weights and discounts of the four aspects of the longitude and latitude coordinates of the area required by the user, the required time period range, user type, and payment mode.

[0028] An embodiment of the third aspect of the present application provides an electronic device, including a processor, a memory, and a program or instruction stored in the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of the AIS data pricing method in the first aspect are implemented.

[0029] An embodiment of the fourth aspect of the present application provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the AIS data pricing method in the first aspect are implemented.

[0030] An embodiment of the fifth aspect of the present application provides a chip, which includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the steps of the AIS data pricing method in the first aspect.

[0031] Additional aspects and advantages of the technical solutions of the present invention will become apparent in the following description or will be understood through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 A schematic diagram showing a flow chart of an AIS data pricing method according to an embodiment of the present application is shown;

[0033] Figure 2 A partial flow chart of an AIS data pricing method according to an embodiment of the present application is shown;

[0034] Figure 3 A partial flow chart of an AIS data pricing method according to an embodiment of the present application is shown;

[0035] Figure 4 A partial flow chart of an AIS data pricing method according to an embodiment of the present application is shown;

[0036] Figure 5 A partial flow chart of an AIS data pricing method according to an embodiment of the present application is shown;

[0037] Figure 6 A partial flow chart of an AIS data pricing method according to an embodiment of the present application is shown;

[0038] Figure 7 A schematic diagram of the main page of the AIS pricing tool according to one embodiment of the present application is shown;

[0039] Figure 8 A schematic diagram of a page for creating a new task according to an embodiment of the present application is shown;

[0040] Figure 9 A schematic diagram of area division according to an embodiment of the present application is shown;

[0041] Figure 10 A schematic diagram of a pricing weight setting page according to an embodiment of the present application is shown;

[0042] Figure 11 A schematic diagram of a pricing report page according to an embodiment of the present application is shown;

[0043] Figure 12 A schematic block diagram of the structure of an AIS data pricing device according to an embodiment of the present application is shown;

[0044] Figure 13 A schematic structural block diagram of an electronic device according to an embodiment of the present application is shown.

[0045] in, Figure 9 、 Figure 12 and Figure 13 The corresponding relationship between the reference numerals and component names is as follows:

[0046] 100: Port area; 102: Traffic fortress area; 104: Main lane area; 106: Ocean area; 900: AIS data pricing device; 902: User input module; 904: Data processing module; 906: Pricing calculation module; 908: Report generation module; 1000: Electronic device; 1110: Processor; 1109: Memory. DETAILED DESCRIPTION

[0047] In order to more clearly understand the above-mentioned purposes, features and advantages of the embodiments of the present invention, the embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and specific implementation methods. It should be noted that the embodiments of the present application and the features therein can be combined with each other in the absence of conflict.

[0048] In the following description, many specific details are set forth to facilitate a full understanding of the present application. However, the embodiments of the present invention may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present application is not limited to the specific embodiments disclosed below.

[0049] The following is combined with Figures 1 to 13 , through specific embodiments and their application scenarios, the AIS data pricing method, device, electronic device, readable storage medium and chip provided in the embodiments of the present application are described in detail.

[0050] This embodiment provides an AIS data pricing method, such as Figure 1 As shown, AIS data pricing methods include:

[0051] Step S100: receiving user data;

[0052] Step S102: determining a target ship area according to the latitude and longitude coordinates, and determining a first weight corresponding to the target ship area;

[0053] Step S104: determining a user usage cycle according to the user demand time period, and determining a second weight corresponding to the user usage cycle;

[0054] Step S106: determining a third weight corresponding to the user type;

[0055] Step S108: determining a fourth weight corresponding to the user payment mode;

[0056] Step S110: determining a first unit price according to user data;

[0057] Step S112: determining a second unit price according to the first unit price, the first weight, the second weight, the third weight, and the fourth weight;

[0058] Step S114: Determine a pricing report based on the user data and the second unit price.

[0059] The AIS data pricing method proposed in this invention determines a weighting system based on four dimensions: target vessel area, user usage cycle, user type, and user payment model. This method uses a combination of weights and discount coefficients to calculate these four parameters, achieving precisely differentiated pricing tailored to user needs. The global ocean is divided into multiple zones with varying traffic volume. The latitude and longitude coordinates of the desired zone, entered by the user, are then matched to determine the sea area used by the user's vessel and the weight assigned to that zone, known as the first weight. The first weight is positively correlated with the vessel traffic density within the zone; the higher the vessel traffic density, the larger the first weight. The user's desired usage cycle is determined based on the user's input time period, measured in days. The second weight is determined based on the user's usage cycle; the second weight is negatively correlated with the user's usage cycle; the longer the user's usage cycle, the smaller the second weight. The second weight represents a discount factor for the user's usage cycle; that is, as the user's usage cycle increases or a long-term subscription is made, the second weight decreases, and the discount factor increases. A third weight is determined based on the user type entered by the user; it is used to determine the intensity of the user's service demand and ability to pay. The third weight is positively correlated with the user's service demand intensity and ability to pay. Higher service demand intensity and ability to pay correspond to a larger third weight. The user's service demand intensity and ability to pay are determined based on user type, with corresponding reference data stored in the database for different user types. The fourth weight is determined by the user's selected payment model. The system's default payment models include first-time payment, subscription, and long-term contract. Different payment models have different discount coefficients, with long-term contract discounts being larger than subscription discounts. Users who choose the first-time payment model receive no additional discounts; that is, the fourth weight is the initial value. Users who choose the subscription model receive discounts for the first month / first year. Users who choose the long-term contract receive discounts throughout the user's lifetime. Subscription discounts and long-term contract discounts are the fourth weight, which is added to the second weight. A discount is calculated for the first unit price based on the first, second, third, and fourth weights to determine the final price for the user, the second unit price. A pricing report is generated, showing the user detailed parameters and the final price.

[0060] As can be understood, the present invention uses automated system processing to calculate initial pricing based on regional traffic, user usage time period, user type, and payment model, achieving refined and automated pricing, quickly generating pricing results, and improving AIS pricing efficiency. Based on the first weight corresponding to the ship area and the third weight corresponding to the user type, the AIS service needs of different regions are met in combination with the user type, thereby improving the accuracy and rationality of pricing. Based on the second weight corresponding to the user usage period and the fourth weight corresponding to the user payment model, further preferential treatment is added to increase user stickiness.

[0061] Furthermore, the present invention generates a pricing report to present the pricing process and results in detail, thereby enhancing the transparency and credibility of AIS pricing.

[0062] Optionally, the pricing report is presented in other visual formats such as a bar chart, line chart, treemap, dashboard, or overlaid with a Geographic Information System (GIS) map.

[0063] Furthermore, the user's input user demand time period is divided into days as the minimum unit of measurement to determine the user's usage cycle. User usage cycles include daily, monthly, and annual cycles. If the user's usage cycle is daily, no discount is offered, meaning the second weight is the initial value. If the user's usage cycle is monthly, the second weight is the monthly discount parameter. If the user's usage cycle is annual, the second weight is the annual discount parameter. The monthly discount parameter is greater than the annual discount parameter. The monthly and annual discount parameters can be modified by enterprise operators.

[0064] For example, the monthly discount parameter is 0.95 and the annual discount parameter is 0.8.

[0065] Furthermore, the user payment model is determined, and a fourth weight is set based on the second weight to achieve a superposition of discounts. User payment models include first-time payment, subscription, and long-term contract. When the user payment model is first-time payment, no discount is available, i.e., the fourth weight is the initial value (1.0); when the user payment model is subscription, the user pays in stages during the usage cycle, and only the first month enjoys the first subscription payment discount, and the renewal enjoys the second subscription payment discount. The value corresponding to the first subscription payment discount is smaller than the value corresponding to the second subscription payment discount; when the user payment model is long-term contract, the long-term contract payment discount is enjoyed throughout the contract period. The value corresponding to the first subscription payment discount is larger than the value corresponding to the long-term contract payment discount.

[0066] For example, the first subscription payment discount is 0.9, the second subscription payment discount is 0.95, and the long-term contract payment discount is 0.8.

[0067] Optionally, the payment model also includes prepayment. Prepayment means that the user pays all fees for the entire year or long-term contract at once. When the user payment model is prepayment, the user enjoys a prepayment discount, which corresponds to a smaller amount than the long-term contract payment discount.

[0068] It is understandable that the discount coefficient is tied to the payment model and the user's usage cycle. The longer the user's usage cycle, the greater the discount. Through gradient discounts, users are encouraged to choose long-term cooperation and improve user stickiness.

[0069] Specifically, the formula for determining the second unit price according to the first unit price, the first weight, the second weight, the third weight, and the fourth weight is as follows:

[0070] ;

[0071] in, is the second unit price (i.e. the final price), is the first unit price (i.e. the basic unit price), is the first weight (i.e., regional weight coefficient), is the second weight (i.e., user usage period discount parameter), is the third weight (i.e. user type weight coefficient), is the fourth weight (i.e., the discount parameter for the user-pays model).

[0072] Optionally, the first unit price is determined based on AIS data collection costs, market competitor prices, and corporate profit targets.

[0073] Optionally, the first unit price may be updated according to a preset time period (e.g., monthly, quarterly, or annually), either by manually entering changes or automatically generating the first unit price based on AIS data collection costs, market competitor prices, and corporate profit targets.

[0074] In some embodiments, optionally, as Figure 2 As shown, step S102: determining the target ship area according to the latitude and longitude coordinates, including:

[0075] Step S1020: Obtain global ship traffic information;

[0076] Step S1022: Divide the global region according to the global ship traffic information to determine multiple determination areas;

[0077] Step S1024: determining the boundary coordinate range corresponding to the determination area;

[0078] Step S1025: Determine the target ship area based on the latitude and longitude coordinates and the boundary coordinate range.

[0079] In this embodiment, global vessel trajectory data is received in real time via AIS. This trajectory data includes information such as vessel position, speed, and heading. This data is stored in a system database and then a vessel traffic density heat map is generated through cleaning (denoising or completion) and aggregation (calculating the average daily number of vessels in different sea areas). Global vessel traffic information is determined based on the vessel traffic density heat map. Based on the vessel traffic density and geographic location information, the global sea area is divided into multiple determination areas, and the boundaries of each determination area are determined. Multiple boundary coordinates are determined for each area boundary. Based on the multiple boundary coordinates, the boundary coordinate range corresponding to the determination area is determined. The longitude and latitude coordinates entered by the user are spatially matched with the boundary coordinates of each area to determine the boundary coordinate range to which the longitude and latitude coordinates entered by the user belong. This determines the area to which the longitude and latitude coordinates entered by the user belong, and the area to which the longitude and latitude coordinates entered by the user belong is determined. This area is the target vessel area.

[0080] Understandably, by obtaining global vessel traffic data to determine the division of regions, the system automatically matches the longitude and latitude coordinates entered by the user to quickly determine the vessel traffic situation in the sea area required by the user's vessel, as well as the region in which the longitude and latitude coordinates are located. By spatially matching the longitude and latitude coordinates with the coordinates of each region's boundaries, it provides a reference for subsequent regional weight calculations, improving the accuracy of AIS data pricing and the efficiency of the system's automatic pricing.

[0081] Furthermore, the assessment areas include: port areas, transportation fortress areas, main lane areas, and ocean areas. Port areas have the highest ship traffic density, high economic value, and intensive service demand; transportation fortress areas have medium ship traffic density and are strategically located (such as straits or canals), resulting in lower service demand than port areas; main lane areas have medium traffic density, but lower than that of transportation fortress areas, as they are essential routes for ships, with shorter ship stopover times, resulting in lower service demand than transportation fortress areas; and ocean areas have the lowest traffic density, with sparsely distributed ships and low service demand.

[0082] Furthermore, the ray casting method or the built-in function of the Geographic Information System (GIS) is used to determine whether the longitude and latitude coordinates input by the user are within the boundary of a certain determination area, and at least one spatial matching is performed until the target ship area to which the longitude and latitude coordinates belong is determined.

[0083] Optionally, an R-Tree index is used to perform hierarchical management of multiple region boundaries to reduce the amount of system calculations, thereby further improving the efficiency of AIS data pricing.

[0084] Optionally, frequently visited areas (such as recent popular ports) are determined based on the system history database, and the boundary coordinates of the frequently visited areas are cached to improve the system response speed.

[0085] In some embodiments, optionally, as Figure 3 As shown, step S102: determining a first weight corresponding to the target ship area includes:

[0086] Step S1026: Obtain an initial first weight;

[0087] Step S1028: determining the flow density corresponding to the target ship area based on the global ship flow information;

[0088] Step S1030: determining a first historical traffic density and a second historical traffic density corresponding to the target ship area according to the global ship traffic information;

[0089] Step S1032: Determine the first weight according to the initial first weight, traffic density, the first historical traffic density and the second historical traffic density.

[0090] In this embodiment, the initial first weight is the basic weight corresponding to multiple judgment areas preset by the system. The initial first weight is positively correlated with the ship traffic density in the area. The greater the ship traffic density in the area, the greater the corresponding initial first weight. For example, the basic weight of the port area is 2.0, the basic weight of the traffic fortress area is 1.5, the basic weight of the main lane area is 1.2, and the basic weight of the ocean area is 1.0. Based on the global ship traffic information, multiple historical traffic density data of the current judgment area are determined, wherein the first historical traffic density is greater than the second historical traffic density, the first historical traffic density is the maximum value of the historical traffic density of the judgment area, and the second historical traffic density is the minimum value of the historical traffic density of the judgment area. The first weight of the target ship area, that is, the weight coefficient corresponding to the area type, is determined based on the traffic density of the judgment area, the maximum value of the historical traffic density, the minimum value of the historical traffic density and the initial first weight.

[0091] As can be understood, the system dynamically adjusts the first weight based on real-time traffic data, reflecting changes in regional traffic flow in real time. This replaces traditional manual judgment and improves the rationality of AIS data pricing. Furthermore, dynamically adjusting the first weight based on traffic density in the target vessel area avoids the rigidity of automatic pricing caused by static weights, thereby improving the alignment between AIS data pricing and market demand.

[0092] Specifically, the formula for determining the first weight according to the initial first weight, traffic density, first historical traffic density, and second historical traffic density is as follows:

[0093]

[0094] in, is the first weight (i.e., regional weight coefficient), is the initial first weight (i.e., regional basic weight), is the traffic density (i.e. the current traffic density of the target ship area), is the first historical traffic density (i.e. the maximum historical traffic density of the target ship area), is the second historical traffic density (i.e. the minimum historical traffic density of the target ship area), is the first adjustment factor.

[0095] Furthermore, by determining the difference between the traffic density and the second historical traffic density and the difference between the first historical traffic density and the second historical traffic density, normalization processing is performed to map the current traffic to the [0,1] interval to avoid interference from extreme values ​​and improve the robustness of the first weight.

[0096] Optionally, the traffic density is the average number of ships in the target ship area within a preset period. For example, if the preset period is one week, the traffic density is the average number of ships in the target ship area within 7 days.

[0097] Optionally, the default value of the first adjustment factor is 0.2, and the sensitivity of the traffic density to the first weight is controlled by adjusting the numerical value of the first adjustment factor. The larger the numerical value corresponding to the first adjustment factor, the more sensitive the traffic density is to the weight coefficient; the smaller the numerical value corresponding to the first adjustment factor, the less sensitive the traffic density is to the weight coefficient. In situations where a rapid response to traffic density is required (such as during a promotional period), the numerical value corresponding to the first adjustment factor automatically increases; when the user's payment model is a long-term contract, the numerical value corresponding to the first adjustment factor automatically decreases, so that the regional weight changes smoothly. By automatically adjusting the sensitivity of traffic density to the weight coefficient through the first adjustment factor, it is possible to adapt to the needs of different market stages.

[0098] In some embodiments, optionally, as Figure 4 As shown, step S106: determining a third weight corresponding to the user type includes:

[0099] Step S1060: Determine an initial third weight corresponding to the user type;

[0100] Step S1062: Determine the user contribution value based on the user data;

[0101] Step S1064: Determine a reference contribution value;

[0102] Step S1066: Determine the third weight according to the reference contribution value, the user contribution value and the initial third weight.

[0103] In this embodiment, the third weight is positively correlated with the user's service demand intensity and ability to pay. Higher service demand intensity and ability to pay correspond to larger third weights. A user's service demand intensity and ability to pay are determined based on user type. Reference data for different user types is stored in a database. This reference data includes the service demand and ability to pay of user groups, and initial weights for different user types are preset. User types include commercial users, law enforcement users, and public welfare users. Commercial users have high service demand intensity, strong commercial dependence, and high ability to pay, and therefore require an increased weight to reflect a service premium. Law enforcement users have high service demand intensity but budget constraints, making their ability to pay less than commercial users. Public welfare users have low service demand intensity and less ability to pay than commercial users. The initial third weight for commercial users is greater than that for law enforcement users, which in turn is greater than that for public welfare users. User contribution values ​​and reference contribution values ​​are determined based on historical user behavior data. The maximum value of the user contribution values ​​across all user historical behavior data is the reference contribution value. The third weight for each user type is determined based on the reference contribution value, the user contribution value, and the initial third weight for that user type.

[0104] Specifically, the formula for determining the third weight according to the reference contribution value, the user contribution value, and the initial third weight is as follows:

[0105] ;

[0106] in, is the third weight, is the initial third weight, Contribute value to users, is the reference contribution value (i.e. the maximum value of the user contribution value in all user historical behavior data), is the second regulating factor.

[0107] It can be understood that by normalizing the contribution values ​​of users of different sizes with reference to the contribution value, the user contribution values ​​corresponding to multiple user types are unified into the range of [0,1], so as to avoid commercial users with high payment ability from monopolizing discounts due to their high absolute consumption. Users with strong payment ability and service demand can still obtain weight improvement through long-term cooperation, thereby balancing the rights and interests of users of different sizes, realizing differentiated pricing strategies for different types of users, and thus improving user satisfaction.

[0108] Exemplarily, the initial third weight of a commercial user is 1.2, the initial third weight of a law enforcement user is 1.0, and the initial third weight of a public welfare user is 0.8.

[0109] For example, commercial users include: shipping and logistics companies, data service providers and other companies mainly engaged in commercial activities; law enforcement users include: law enforcement units such as the Maritime Safety Administration and the Coast Guard; public welfare users include: personal research, government agencies, scientific research institutions and other groups whose service value is mainly for public welfare.

[0110] Optionally, the default value of the second adjustment factor is 0.1, and the adjustment range of the user contribution value to the third weight is controlled by adjusting the numerical value of the second adjustment factor. The larger the numerical value corresponding to the second adjustment factor, the higher the adjustment range of the user contribution value to the weight coefficient; the smaller the numerical value corresponding to the second adjustment factor, the lower the adjustment range of the user contribution value to the weight coefficient. When the demand for ships is high and the shipping logistics data is greater than the historical average, the numerical value corresponding to the second adjustment factor automatically increases to increase the contribution value ratio of commercial users; when it is necessary to expand the public welfare market and conduct scientific research activities or research, the numerical value corresponding to the second adjustment factor automatically decreases to weaken the impact of consumer finance and increase the contribution value ratio of public welfare users. By automatically adjusting the adjustment range of the user contribution value to the third weight through the second adjustment factor, the profit contribution and public welfare ratio of users of different sizes are balanced, and long-term cooperation among users is promoted.

[0111] In some embodiments, optionally, as Figure 5 As shown, step S1062: determining the user contribution value based on the user data, including:

[0112] Step S10620: Determine the total historical consumption and subscription duration corresponding to the user;

[0113] Step S10622: determining the service usage frequency based on the user's historical data request times;

[0114] Step S10624: Determine the user contribution value based on the total historical consumption, subscription duration, and service usage frequency.

[0115] In this embodiment, the user's contribution value is determined based on the user's historical total consumption, subscription duration, and service usage frequency. These total consumption, subscription duration, and service usage frequency are all obtained from historical server data. The total historical consumption is the cumulative amount a user has spent on AIS data services, calculated by extracting consumption records associated with the user's ID from the server's historical data and aggregating them monthly. The subscription duration is the total duration of a user's continuous subscription to AIS services, calculated by extracting the start and end times of the user's continuous subscriptions from the server's historical data. The service usage frequency is the average number of data requests initiated by the user per day, calculated by counting the user's daily requests from the server's historical data.

[0116] It is understandable that the method of determining user contribution value from three aspects: total historical consumption, subscription duration and frequency of service use, while taking into account the user's consumption capacity, service demand intensity and data activity, provides comprehensive indicators for various types of users, reduces the data deviation caused by a single indicator, and further improves the robustness of the third weight.

[0117] Furthermore, the total historical consumption amount corresponds to the user's ability to pay. The stronger the user's ability to pay, the larger the corresponding total historical consumption amount. The subscription duration and service usage frequency correspond to the user's service demand intensity. The higher the user's service demand intensity, the larger the corresponding subscription duration and service usage frequency. By determining the third weight based on the total historical consumption amount, subscription duration, and service usage frequency, the size of the third weight is positively correlated with the user's service demand intensity and ability to pay, realizing a differentiated pricing strategy for different types of users.

[0118] Specifically, the formula for determining user contribution value based on historical total consumption, subscription duration, and service usage frequency is as follows:

[0119] ;

[0120] in, Contribute value to users, is the consumption amount coefficient, is the cooperation duration coefficient, is the frequency coefficient, + + =1.

[0121] Optionally, 、 and is the default value.

[0122] Optionally, 、 and Dynamically adjust according to corporate strategy. For example, when the company needs to strengthen the influence of user spending amount, Increase the value of The value of will be reduced accordingly; when the enterprise needs to cultivate long-term users and enhance user stickiness, Increase the value of The value of Increase the value of The value decreases accordingly.

[0123] In some embodiments, optionally, as Figure 6As shown, step S1064: determining a reference contribution value includes:

[0124] Step S10640: Obtain user history database;

[0125] Step S10642: Determine historical user contribution values ​​based on the user history database;

[0126] Step S10644: Determine a reference contribution value based on multiple historical user contribution values.

[0127] In this embodiment, multiple historical user contribution values ​​(i.e., the historical user contribution values ​​of multiple users) are determined in the user history database. The user contribution value with the largest value among these multiple historical user contribution values ​​is used as the reference contribution value. This reference contribution value maps the user contribution values ​​to the interval [0, 1], eliminating differences in magnitude and normalizing the user contribution values. This normalization prevents large enterprises from monopolizing consumer resources due to their high absolute consumption. Small and medium-sized enterprises or public welfare users can still increase their weight through long-term cooperation or high-frequency usage, thereby improving user satisfaction and user stickiness.

[0128] Furthermore, by taking the user contribution value with the largest value among the historical user contribution values ​​of multiple users as the reference contribution value, the user contribution value is normalized, and the user value is quantified based on objective historical data, replacing the subjective pricing strategy, thereby improving the fairness and reliability of the system in the AIS data pricing process.

[0129] In a specific embodiment, optionally, the AIS data pricing method is used in an AIS pricing system (i.e., an AIS data pricing device), and the AIS pricing system includes: a user input module, a data processing module, a pricing calculation module, and a report generation module, wherein the data processing module includes an area division submodule, an area determination submodule, a time determination submodule, a user type determination submodule, and a payment mode determination submodule.

[0130] The user input module is used to receive the user's data requirements, including the latitude and longitude coordinates of the required area, the required time period, the user type, and the payment model. The regional division submodule is used to divide the global region into ports with high traffic, transportation fortresses, major waterways, etc., and ocean areas with low traffic, etc. based on global ship traffic information. The region determination submodule is used to determine the region where the user is located based on the latitude and longitude coordinates entered by the user and determine the corresponding pricing weight, i.e., the first weight. The time determination submodule is used to determine the length of time required by the user based on the user's required time period, with days as the minimum unit of measurement, and consider the strategy of more purchases, more discounts. The user type determination submodule is used to determine the corresponding pricing weight, i.e., the third weight, based on the user type (personal research, shipping and logistics companies, government agencies, law enforcement units, scientific research institutions, data service providers). The payment model determination submodule is used to introduce preferential factors based on the user's payment model (first payment, subscription, long-term contract, etc.) to determine the final discount strength. The pricing calculation module is used to calculate and generate the final pricing price based on the various determination results provided by the data processing module. The report generation module is used to generate a pricing report based on the pricing results for users to download and reference.

[0131] AIS data pricing methods include:

[0132] Step 1: User data reception: Receive the user's data requirements through the user input module, including the latitude and longitude coordinates of the required area, the required time period, user type and payment mode. Open the AIS data pricing tool, such as Figure 7 As shown, the main page of the AIS Data Pricing Tool includes the serial number, task name, pricing fee, creation time, and the corresponding operation interface. Users can view or delete pricing orders through the operation page. For example, among the first five pricing orders on the first page, the one with serial number 1, task name "A certain unit regional data", pricing fee of 27,360 yuan, and creation time of 2024-09-22 at 12:23:42, users can view the details of the pricing order by clicking the View Pricing Order button in the operation bar or delete the order by clicking the Delete button. Users can switch between the pricing tool pages by clicking Previous Page, Next Page, Home Page, and Last Page.

[0133] Click Create a new task in the upper right corner to enter user data requirements. The new task page is as follows Figure 8As shown, the user enters the task name, coordinate range, time range, user type, and payment model. The time range includes the start and end time; user types include personal research, shipping and logistics companies, government agencies, law enforcement agencies, scientific research institutions, data service providers, and others. The weights of other columns can be manually adjusted, with a recommended range of (0, 3); payment models include initial payment, subscription renewal, long-term contract, and others. The weights of other columns can be manually adjusted, with a recommended range of (0, 1). Users can click the Save button below to save or the Reset button to reset existing entries. Once the requirements are entered, click Save to enter the pricing calculation logic.

[0134] Step 2: Data processing and pricing calculation:

[0135] Regional division and determination: Using the regional division submodule, the global region is divided according to the global ship traffic information. Furthermore, based on the ship traffic and geographical location information, the world is divided into the following regions, including port areas, transportation fortress areas, main channel areas and ocean areas, such as Figure 9 As shown, the global ocean is divided based on an electronic nautical chart. The outermost frame represents the user's viewing boundary, and the multiple line segments within the rectangular frame represent regional boundaries. The global ocean is divided into multiple port areas 100, transportation hub areas 102, major waterway areas 104, and ocean areas 106. The regional determination submodule uses the user-entered longitude and latitude coordinates in conjunction with a pre-set global vessel traffic geographic information database (GIS database) for real-time matching.

[0136] The specific steps are as follows:

[0137] Step 1: Data Preparation:

[0138] A global regional division layer is preset, including the boundary coordinate ranges of port areas, transportation fortress areas, major waterway areas and ocean areas (generated based on cluster analysis of historical ship AIS trajectory data).

[0139] Step 2: Coordinate matching:

[0140] The longitude and latitude coordinates entered by the user are spatially matched with the boundaries of each area (using the ray method or the spatial relationship judgment algorithm built into the GIS library) to determine the area type.

[0141] The weight coefficient reflects the traffic density and AIS service value of different areas, and is based on the following:

[0142] Port areas (weight 2.0): have the highest traffic density (average daily number of ships > 1,000), high economic value (involving cargo loading and unloading, berthing services), and intensive service demand;

[0143] Transportation hub areas (weight 1.5): have medium traffic density (500-1000 ships per day) and are strategically located (such as straits and canals), but service demand is slightly lower than that of ports.

[0144] Main waterway area (weight 1.2): medium traffic density (average number of ships per day 200-499), a must-go route for fixed routes, but ships stay for a short time;

[0145] Ocean region (weight 1.0): The traffic density is the lowest (average number of ships per day <200), ships are sparsely distributed, and service demand is low.

[0146] The weight coefficient can be dynamically adjusted based on real-time traffic data. The formula is as follows:

[0147]

[0148] in, is the first weight (i.e. the final weight coefficient of the region), The initial first weight (i.e., regional basic weight, port area 2.0, transportation fortress area 1.5, main channel area 1.2, ocean area 1.0), is the traffic density (i.e. the current traffic density of the target ship area), is the first historical traffic density (i.e. the maximum historical traffic density of the target ship area), is the second historical traffic density (i.e. the minimum historical traffic density of the target ship area), is the first adjustment factor (the default is 0.2, which can be modified through system configuration).

[0149] Time Period Determination: The time period determination submodule determines the user's desired duration based on the minimum unit of time, using days as the minimum unit. This module also considers strategies for more purchases and more discounts. Furthermore, examples of discounts are as follows: daily billing, with a base daily fee of X yuan; continuous purchases for a month (30 days) receive a 9.5% discount; and long-term contracts (e.g., one year, or longer, 365 days or longer) receive a 20% discount.

[0150] User type determination: Utilize the user type determination submodule to determine the corresponding pricing weight according to the user type. User type weight ( ) reflects the service demand intensity, payment ability and strategic value of different user groups, and the specific basis is as follows: Personal research, government agencies, and scientific research institutions (weight 0.8): seeking stability but limited budget, the service value is mainly public welfare, and it is necessary to attract users through lower weights; Law enforcement units (weight 1.0): The demand is highly urgent (such as maritime supervision, emergency response), but subject to budget constraints, it is necessary to balance the service value and cost; Shipping and logistics companies, data service providers (weight 1.2): Strong commercial dependence (such as route optimization, data secondary sales), high payment ability, and the need to reflect the service premium through weight increase.

[0151] The weight coefficient can be dynamically adjusted based on the user's historical behavior data. The formula is as follows:

[0152] ;

[0153] in, is the third weight, is the initial third weight (i.e. the basic weight of user type, initially set according to user type, such as 0.8 / 1.0 / 1.2), Contribute value to users, is the reference contribution value (i.e. the maximum value of the user contribution value in all user historical behavior data), It is the second adjustment factor (the default value is 0.1, which can be adjusted through the system configuration page).

[0154] User contribution value is calculated based on the following dimensions: total historical consumption: cumulative consumption amount in the past 12 months; duration of cooperation: number of consecutive subscription months; frequency of service use: average number of data requests per day.

[0155] The calculation formula is as follows:

[0156] ;

[0157] in, is the consumption amount coefficient, is the cooperation duration coefficient, is the frequency coefficient, Contribute value to users, + + =1.

[0158] Payment Model Determination: The payment model determination submodule uses this to introduce preferential factors based on the user's payment model and determine the final discount level. Further, examples of preferential factors are as follows: First-time payment: no additional discount; Subscription (first month / first year discount): 10% discount for the first month; Long-term contract: higher preferential factors. The specific value depends on the contract term and negotiation results. In this example, it is assumed to be 20% discount (combined with the time period discount).

[0159] Furthermore, the above weights are not fixed and unchanging. We can set the pricing weights in the system (entry is Figure 7 ), such as Figure 10 As shown, pricing weighting settings include regional weighting, time weighting, user weighting, and payment weighting. Regional weighting includes: port areas, transportation hub areas, major roadway areas, and ocean areas; time weighting includes: base fee (unit: RMB / day), monthly discounts (greater than 30 days and less than 365 days), and annual discounts (greater than or equal to 365 days); user weighting includes: individual research, government agencies, scientific research institutions, law enforcement units, shipping and logistics companies, and data service providers; payment weighting includes: first payment, subscription (first month / first year discount), and long-term contract. Users can click the Save button below to save or reset the entered information using the Reset button.

[0160] Pricing calculation: Use the pricing calculation module to calculate and generate the final pricing price based on the above judgment results.

[0161] The final pricing price is calculated using the following formula:

[0162] ;

[0163] in, is the second unit price (i.e. the final price), is the first unit price (i.e. the basic unit price), is the first weight (i.e., regional weight coefficient), is the second weight (i.e., user usage period discount parameter), is the third weight (i.e. user type weight coefficient), is the fourth weight (i.e., the discount parameter for the user-pays model).

[0164] For example, : Basic unit price (e.g. 100 yuan / day); : Regional weight coefficient (port 2.0, transportation fortress 1.5, waterway 1.2, ocean 1.0); : User type weight coefficient (0.8 for public welfare users, 1.0 for law enforcement units, and 1.2 for commercial users); : Time period discount (set by purchase duration, e.g. 0.95 corresponds to 9.5% off); : Preferential discounts for payment models (such as 0.9 for the first month of subscription and 0.8 for long-term contracts).

[0165] The basis for setting the basic unit price is: based on the comprehensive determination of AIS data collection costs, market competitor prices and corporate profit targets.

[0166] In addition, the basic unit price can be updated regularly (such as quarterly), and can be manually entered or automatically generated based on the cost formula.

[0167] Time period discounts The setting rules are as follows:

[0168] Daily rate: =1.0 (no discount);

[0169] Monthly subscription: Purchase 30 days, =0.95 (9.5% off);

[0170] Long-term contract: Purchase ≥365 days, =0.85 (even lower after adding the discount of the paid model).

[0171] Paid model discounts The setting rules are as follows:

[0172] First payment: =1.0 (no discount);

[0173] Subscription: First Month =0.9, renewal =0.95;

[0174] Long-term contracts: =0.8~0.9 (dynamically set according to negotiation results).

[0175] Pricing reports such as Figure 11 As shown in the figure, the pricing sheet for a company's demand area data includes: demand area, demand time period, user type, payment model, daily base fee, area weight, time period discount, user type weight, payment model discount, and pricing fee. The demand area is a polygonal area with vertex coordinates of: 28°19.867′, 121°38.695′; 28°19.867′, 121°43.598′; 28°14.78′, 121°43.289′; and 28°15.017′, 121°36.635′. The demand time period is 2024 / 09 / 01-2024 / 09 / 30 (January 0 day); the user type is a shipping and logistics enterprise; the payment mode is first payment; the basic daily fee is 500 yuan; the regional weight is 2.0 (port area); the time period discount is 9.5%; the user type weight is 1.2; the payment mode discount is 20%; the pricing fee is 27,360 yuan.

[0176] The pricing calculation process includes: Input parameters: user input region, time period, user type and payment mode;

[0177] Weight and discount matching: the system calls the database to obtain the corresponding 、 、 、 ; Calculation formula: According to Generate price; Result output: Generate pricing report, showing the details of each parameter and the final price.

[0178] Step 3: Report generation and output: Use the report generation module to generate a pricing report based on the pricing results for pricers to download and refer to.

[0179] The present invention implements quantitative pricing through the system, improving the accuracy and rationality of pricing. The quantitative pricing method achieves refined and personalized pricing by comprehensively considering multiple factors such as regional traffic, time period, user type and payment model.

[0180] like Figure 12 As shown, an embodiment of the present application also provides an AIS data pricing device 900, including: a user input module 902, used to receive user data, the user data including the latitude and longitude coordinates corresponding to the ship, the user demand time period, the user type and the user payment mode; a data processing module 904, used to determine the target ship area according to the latitude and longitude coordinates, and determine a first weight corresponding to the target ship area; determine the user usage period according to the user demand time period, and determine a second weight corresponding to the user usage period; determine a third weight corresponding to the user type; determine a fourth weight corresponding to the user payment mode; a pricing calculation module 906, used to determine a first unit price according to the user data; determine a second unit price according to the first unit price, the first weight, the second weight, the third weight and the fourth weight; a report generation module 908, used to determine a pricing report according to the user data and the second unit price.

[0181] The AIS data pricing method provided by the present invention is implemented by the AIS data pricing device 900. The weight system is determined from four dimensions: the target ship area, the user's usage cycle, the user type, and the user's payment mode. The four parameters of sea area, time, user type, and payment mode are comprehensively calculated through weights and discount coefficients to achieve precise differentiated pricing based on user needs. Specifically, the user input module 902 is used to accept the user's data needs, including the longitude and latitude coordinates of the area required by the user, the required time period range, the user type, and the payment mode; the pricing calculation module 906 calculates and generates the final pricing price based on the various judgment results provided by the data processing module; the report generation module 908 generates a visual pricing report based on the pricing results for the user to download and refer to; the data processing module 904 is used to process user data and determine the weights and discounts of the four aspects: the longitude and latitude coordinates of the area required by the user, the required time period range, the user type, and the payment mode.

[0182] Optionally, the data processing module 904 includes: a region division submodule, a region determination submodule, a time period determination submodule, a user type determination submodule, and a payment mode determination submodule. The region division submodule is configured to divide global regions into high-traffic ports, transportation hubs, major shipping routes, and low-traffic ocean regions based on global ship traffic information; the region determination submodule is configured to determine the region where the user is located based on the latitude and longitude coordinates input by the user and determine the corresponding pricing weight; the time period determination submodule is configured to determine the length of time required by the user based on the minimum unit of measurement, using days, and to determine the discount or weight corresponding to the time period, taking into account the strategy of "more purchases, more discounts"; the user type determination submodule is configured to determine the corresponding pricing weight based on the user type (individual research, shipping and logistics companies, government agencies, law enforcement agencies, scientific research institutions, data service providers); and the payment mode determination submodule is configured to introduce preferential factors based on the user's payment mode (first-time payment, subscription, long-term contract, etc.) to determine the final preferential strength, i.e., the final discount.

[0183] like Figure 13 As shown, an embodiment of the present application further provides an electronic device 1000, including a processor 1110, a memory 1109, and a program or instruction stored in the memory 1109 and executable on the processor 1110. When the program or instruction is executed by the processor 1110, the various processes of the embodiment of the above-mentioned AIS data pricing method are implemented, and the same technical effect can be achieved. To avoid repetition, they will not be described here.

[0184] Optionally, the processor 1110 is configured to receive user data;

[0185] Optionally, the processor 1110 is further configured to determine a target ship area according to the latitude and longitude coordinates, and determine a first weight corresponding to the target ship area;

[0186] Optionally, the processor 1110 is further configured to determine a user usage cycle according to the user demand time period, and determine a second weight corresponding to the user usage cycle;

[0187] Optionally, the processor 1110 is further configured to determine a third weight corresponding to the user type; determine a fourth weight corresponding to the user payment mode;

[0188] Optionally, the processor 1110 is further configured to determine a first unit price according to the user data; and determine a second unit price according to the first unit price, the first weight, the second weight, the third weight, and the fourth weight;

[0189] Optionally, the processor 1110 is further configured to determine a pricing report based on the user data and the second unit price.

[0190] Memory 1109 can be used to store software programs and various data. Memory 1109 may primarily include a first storage area for storing programs or instructions and a second storage area for storing data. The first storage area may store an operating system, applications or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). Furthermore, memory 1109 may include volatile memory or non-volatile memory, or both. Non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory may be random access memory (RAM), static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (SDRAM), double data rate synchronous dynamic random access memory (DDRSDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link dynamic random access memory (SLDRAM), and direct RAM bus random access memory (DRRAM). The memory 1109 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0191] The present application also provides a readable storage medium having a program or instruction stored thereon. When executed by a processor, the program or instruction implements the various processes of the aforementioned AIS data pricing method embodiment, achieving the same technical effects. To avoid repetition, these are not described here. Furthermore, the readable storage medium improves the data storage capacity and data processing speed corresponding to the AIS data pricing method of the present application.

[0192] A computer-readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. A computer-readable storage medium can be, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer-readable storage media includes: portable computer floppy disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital versatile disk (DVD), memory cards, floppy disks, encoding mechanical devices (such as punched cards or grooves with raised structures containing recorded instructions), and any suitable combination of the foregoing. As used herein, computer-readable storage medium should not be understood to refer to transmission signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media, or electrical signals transmitted via wires.

[0193] The processor is the processor in the electronic device in the above embodiment. The readable storage medium includes a computer-readable storage medium, such as a computer read-only memory (ROM), random access memory (RAM), a magnetic disk, or an optical disk.

[0194] The present application also provides a chip comprising a processor and a communication interface coupled to the processor. The processor is configured to execute programs or instructions to implement the various processes of the aforementioned AIS data pricing method embodiment, achieving the same technical effects. To avoid repetition, these steps are omitted here. Furthermore, the chip improves the data processing speed corresponding to the AIS data pricing method of the present application.

[0195] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0196] In the present invention, the terms "first," "second," and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance. The term "plurality" refers to two or more, unless expressly limited otherwise. Terms such as "installed," "connected," "connected," and "fixed" should be interpreted broadly. For example, "connected" can mean a fixed connection, a detachable connection, or an integral connection; "connected" can mean a direct connection or an indirect connection through an intermediary. Those skilled in the art will understand the specific meanings of these terms in the present invention based on specific circumstances.

[0197] In the description of the present invention, it should be understood that the directions or positional relationships indicated by terms such as "up", "down", "left", "right", "front" and "back" are based on the directions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or unit referred to must have a specific direction, be constructed and operated in a specific direction. Therefore, they should not be understood as limiting the present invention.

[0198] Throughout this specification, terms such as "one embodiment," "some embodiments," and "specific embodiments" mean that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of the present invention. In this specification, schematic representations of these terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0199] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. An AIS data pricing method, characterized in that: include: receiving user data, the user data including the latitude and longitude coordinates corresponding to the vessel, the user's desired time period, the user type, and the user's payment mode; determining a target ship area according to the latitude and longitude coordinates, and determining a first weight corresponding to the target ship area; determining a user usage cycle according to the user demand time period, and determining a second weight corresponding to the user usage cycle; determining a third weight corresponding to the user type; determining a fourth weight corresponding to the user payment mode; determining a first unit price according to the user data; determining a second unit price according to the first unit price, the first weight, the second weight, the third weight, and the fourth weight; A pricing report is determined based on the user data and the second unit price.

2. The AIS data pricing method according to claim 1, characterized in that: Determining the target ship area according to the latitude and longitude coordinates includes: Obtain global ship traffic information; Dividing the global region according to the global ship traffic information to determine a plurality of determination regions; Determining a boundary coordinate range corresponding to the determination area; A target ship area is determined according to the latitude and longitude coordinates and the boundary coordinate range.

3. The AIS data pricing method according to claim 2, characterized in that: The determining a first weight corresponding to the target vessel area includes: Get the initial first weight; determining a flow density corresponding to the target ship area according to the global ship flow information; determining a first historical traffic density and a second historical traffic density corresponding to the target ship area according to the global ship traffic information, wherein the first historical traffic density is greater than the second historical traffic density; A first weight is determined according to the initial first weight, the traffic density, the first historical traffic density, and the second historical traffic density.

4. The AIS data pricing method according to claim 1, wherein: The determining a third weight corresponding to the user type includes: determining an initial third weight corresponding to the user type; Determine a user contribution value based on the user data; Determine the reference contribution value; A third weight is determined according to the reference contribution value, the user contribution value, and the initial third weight.

5. The AIS data pricing method according to claim 4, characterized in that: Determining the user contribution value according to the user data includes: Determine the total historical consumption and subscription duration corresponding to the user; Determining the frequency of service usage based on the number of historical data requests by the user; The user contribution value is determined based on the total historical consumption, the subscription duration, and the service usage frequency.

6. The AIS data pricing method according to claim 4, characterized in that: Determining the reference contribution value includes: Get the user history database; Determining a historical user contribution value based on the user history database; A reference contribution value is determined according to the plurality of historical user contribution values.

7. An AIS data pricing device, characterized in that: include: A user input module is used to receive user data, wherein the user data includes the latitude and longitude coordinates corresponding to the ship, the user's required time period, the user type and the user's payment mode; a data processing module, configured to determine a target ship area according to the latitude and longitude coordinates, and determine a first weight corresponding to the target ship area; determining a user usage cycle according to the user demand time period, and determining a second weight corresponding to the user usage cycle; determining a third weight corresponding to the user type; determining a fourth weight corresponding to the user payment mode; a pricing calculation module, configured to determine a first unit price based on the user data; determining a second unit price according to the first unit price, the first weight, the second weight, the third weight, and the fourth weight; A report generating module is configured to determine a pricing report based on the user data and the second unit price.

8. An electronic device, characterized in that: The method comprises a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the AIS data pricing method according to any one of claims 1 to 6.

9. A readable storage medium, characterized in that The readable storage medium stores a program or instruction, and when the program or instruction is executed by a processor, the steps of the AIS data pricing method according to any one of claims 1 to 6 are implemented.

10. A chip, characterized in that: The chip includes a processor and a communication interface, the communication interface is coupled to the processor, and the processor is used to run a program or instruction to implement the steps of the AIS data pricing method according to any one of claims 1 to 6.

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