Water transportation oriented cross-platform data cascade sharing method and system

Abstract

The present application relates to the technical field of data sharing, in particular to a cross-platform data cascade sharing method and system for water transportation and Internet of Things, comprising: acquiring data of each water transportation and logistics platform and dividing into several nodes, and then constructing a navigation business segment; according to the platform and time interval corresponding to the node, acquiring a business coherence coefficient; combining the Internet of Things data contained in the node, acquiring a basic sharing degree; combining the response urgency state deduced according to the time corresponding to the node, acquiring a cascade sharing necessity degree; combining the feedback after data sharing, acquiring a sharing chain adjustment priority, and finally executing cross-platform data cascade sharing accordingly. The present application continuously optimizes the cross-platform cascade sharing strategy by constructing the navigation business segment and quantitatively evaluating based on the bearing relationship, the value of filling the position and the timeliness, and optimizing the sharing strategy in a closed loop combined with the feedback.

Description

Technical Field

[0001] This invention relates to the field of data sharing technology, specifically to a cross-platform data cascading and sharing method and system for water transport IoT. Background Technology

[0002] With the development of smart ports, digital waterways, and water transport IoT technologies, a large number of front-end sensing devices are gradually being applied in water transport scenarios, including navigation aids, video surveillance equipment, ship AI terminals, underwater robots, drones, environmental monitoring equipment, and port scheduling equipment. These devices are typically deployed in different scenarios such as waterways, ports, wharves, ships, and regulatory areas to collect various water transport IoT data, including waterway status, ship status, berth status, environmental status, and scheduling status. Due to differences in the types of equipment, IoT platforms, and data management systems used by different regions, projects, and owners during construction, multiple independent IoT device management platforms have gradually formed in water transport scenarios. Each platform is responsible for its own equipment's data collection, status monitoring, and business processing. However, existing water transport IoT data sharing methods mostly use fixed interface connections, protocol conversion, or periodic synchronization to achieve data exchange between platforms. Because of differences in data structures, business rules, and equipment management methods between different platforms, it is difficult to continuously adjust subsequent sharing strategies based on the actual adoption of downstream platforms. Therefore, it cannot meet the dynamic collaboration needs between multiple platforms, multiple devices, and multiple business chains in complex water transport scenarios. Summary of the Invention

[0003] This invention provides a cross-platform data cascading and sharing method and system for water transport IoT to solve existing problems: In the current water transport IoT scenario, there is a lack of dynamic data sharing mechanism based on business acceptance relationship between different platforms, which easily leads to problems such as invalid sharing, duplicate sharing and sharing lag during the cross-platform data sharing process.

[0004] The cross-platform data cascading and sharing method and system for water transport IoT of the present invention adopts the following technical solution: One embodiment of the present invention provides a cross-platform data cascading and sharing method for water transport IoT, the method comprising the following steps: Acquire various water transport IoT data from various water transport logistics platforms, divide the water transport IoT data into several nodes, and then obtain navigation business segments; Obtain the upstream sharing platform and downstream receiving platform corresponding to the general aviation business segment; based on the platform corresponding to each node in the general aviation business segment, obtain the business overlap of the general aviation business segment; combined with the time interval between the corresponding nodes in the general aviation business segment, obtain the business continuity coefficient of the general aviation business segment; based on the water transport IoT data contained in each node of the general aviation business segment, obtain the sharing and supplementary value coefficient of the general aviation business segment. Based on the sharing and complement value coefficient and business continuity coefficient of the general aviation business segment, the basic sharing degree of the general aviation business segment is obtained. Combined with the time corresponding to each node in the general aviation business segment, the cascading sharing necessity of the general aviation business segment is obtained. Based on the necessity of cascading and sharing general aviation business segments, and combined with the adoption feedback after data sharing, the priority of adjusting the sharing chain of general aviation business segments is obtained, and cross-platform data cascading and sharing is carried out through the priority of adjusting the sharing chain of general aviation business segments.

[0005] Preferably, the specific method for acquiring each waterway logistics platform's waterway IoT data, dividing the waterway IoT data into several nodes, and then acquiring navigation business segments includes: Acquire various water transport IoT data from various water transport logistics platforms, wherein the water transport logistics platforms include at least: shipborne terminal platform, waterway monitoring platform, lock scheduling platform, port berthing and unberthing platform, freight operation platform and maritime supervision platform; Water transport IoT data containing the same vessel identifier and the same voyage identifier are grouped into the same navigation object group to obtain several navigation object groups; each piece of water transport IoT data in each navigation object group is used as a node to obtain the node set corresponding to each navigation object group. For any set of nodes in a general aviation object group, the nodes in the set of nodes in the general aviation object group are sorted according to the flow order of the preset node business type; if there are multiple nodes under the same node business type, they are sorted according to the order of their node time to obtain the general aviation business segment of the general aviation object group.

[0006] Preferably, the specific method for obtaining the service overlap of a general aviation service segment based on the platform corresponding to each node in the general aviation service segment is as follows: For any general aviation business segment, the node corresponding to the upstream sharing platform of the general aviation business segment is recorded as the upstream business node, and the node corresponding to the downstream receiving platform of the general aviation business segment is recorded as the downstream business node. For any upstream service node, if the next node of the upstream service node in the general aviation service segment is not an upstream service node, the node pair consisting of the upstream service node and its next node in the general aviation service segment is recorded as a candidate successor node pair in the general aviation service segment. If the next node of the upstream business node in the general aviation business segment is a downstream business node, the node pair consisting of the upstream business node and its next node in the general aviation business segment is denoted as the receiving node pair of the general aviation business segment. The ratio of the number of receiving node pairs to the number of candidate receiving node pairs for the general aviation service segment is taken as the receiving ratio of the general aviation service segment. For any pair of receiving nodes, the combination of business types formed by the upstream business node and the downstream business node in the receiving node pair is denoted as the business receiving combination of the receiving node pair; if the preset set of business receiving combinations includes the business receiving combination of the receiving node pair, the receiving node pair is denoted as the successor node pair. The ratio of the number of connecting node pairs to the number of receiving node pairs in the general aviation service segment is taken as the connecting ratio of the general aviation service segment. The product of the acceptance ratio and the continuity ratio of the general aviation service segment is taken as the service engagement degree of the general aviation service segment.

[0007] Preferably, the specific method for obtaining the service continuity coefficient of a general aviation service segment is as follows: For any pair of receiving nodes in any general aviation service segment, the temporal distance between the upstream and downstream service nodes in the receiving node pair of the general aviation service segment at the corresponding time is taken as the receiving interval of the receiving node pair of the general aviation service segment. The average of the acceptance intervals of all acceptance node pairs of the general aviation service segment is taken as the comprehensive acceptance interval of the general aviation service segment. Based on the comprehensive acceptance interval and business overlap of the general aviation business segment, the business continuity coefficient of the general aviation business segment is obtained; The business continuity coefficient of the general aviation business segment is positively correlated with the business overlap of the general aviation business segment; the business continuity coefficient of the general aviation business segment is negatively correlated with the comprehensive acceptance interval of the general aviation business segment.

[0008] Preferably, the specific method for obtaining the shared complement value coefficient of a navigation service segment based on the waterway IoT data contained in each node of the navigation service segment includes: For any general aviation business segment, obtain the set of information dimensions in the downstream business nodes of the general aviation business segment, denoted as the necessary information dimension set; The set of information dimensions contained in the upstream business nodes of the general aviation business segment is denoted as the upstream held information dimension set. The set of information dimensions that are necessary information dimensions and are missing in the downstream business nodes, which is the upstream information dimension set, is denoted as the supplementary information dimension set. The ratio obtained by dividing the number of information dimensions in the supplementary information dimension set by the number of information dimensions in the necessary information dimension set is used as the missing supplementation ratio of the general aviation business segment. The information dimension in the intersection between the preset key dimension information set and the supplementary information dimension set is denoted as the key supplementary information dimension. The ratio of the number of key supplementary information dimensions to the number of information dimensions in the supplementary information dimension set is denoted as the key information ratio of the general aviation business segment. The shared complement value coefficient of the general aviation business segment is obtained based on the missing complement ratio of the general aviation business segment and the key information ratio of the general aviation business segment. The shared complement value coefficient of the general aviation business segment is positively correlated with the missing complement ratio of the general aviation business segment; the shared complement value coefficient of the general aviation business segment is positively correlated with the key information ratio of the general aviation business segment.

[0009] Preferably, the specific method for obtaining the basic sharing degree of general aviation business segments based on the sharing and complement value coefficient and the business continuity coefficient of general aviation business segments includes: For any general aviation service segment, the product of the shared complement value coefficient and the service continuity coefficient of the general aviation service segment is used as the basic sharing degree of the general aviation service segment.

[0010] Preferably, the specific method for obtaining the cascading sharing necessity of general aviation service segments is as follows: For any pair of receiving nodes in any general aviation service segment, the time sequence distance between the time corresponding to the upstream service node in the receiving node pair and the current time is taken as the elapsed time of the receiving node pair. The processing lag offset of the receiving node pair is obtained by subtracting the receiving interval of the receiving node pair from the elapsed time of the receiving node pair. The processing lag offset of the receiving node pair is linearly normalized to obtain the response urgency of the general aviation service segment. The difference between the service overlap of the general aviation service segment and the basic sharing degree of the general aviation service segment is multiplied by the response urgency and used as the urgency of the general aviation service segment. The sum of the basic sharing degree and the urgent supplement degree of the general aviation service segment is taken as the cascading sharing necessity degree of the general aviation service segment.

[0011] Preferably, the specific method for obtaining the sharing chain adjustment priority of general aviation business segments based on the cascading sharing necessity of the general aviation business segments and the adoption feedback after data sharing includes: For any general aviation business segment, obtain the data sharing feedback result from the downstream receiving platform to the upstream sharing platform. The data sharing feedback result includes at least: the information dimensions already used, the information dimensions contained in the supplementary request, and adjacent nodes. The ratio of the number of information dimensions already adopted to the number of information dimensions in the upstream information dimension set of the aforementioned general aviation business segment is taken as the degree of shared adoption of the general aviation business segment. The linear normalization result of the number of information dimensions contained in the supplementary request is used as the information supplementary request factor; The linearly normalized result of the adjacent nodes included in the supplementary request is used as the node supplementary request factor. Based on the preset information supplementation request weight and node supplementation request weight, the information supplementation request factor and node supplementation request factor are weighted and summed to obtain the request expansion coefficient of the general aviation service segment. The priority of the sharing chain adjustment for the general aviation service segment is obtained based on the cascading sharing necessity, request expansion coefficient, and sharing adoption degree of the general aviation service segment.

[0012] Preferably, the specific method for obtaining the sharing chain adjustment priority of the general aviation service segment based on the cascading sharing necessity, request expansion coefficient, and sharing adoption degree of the general aviation service segment includes: The priority of the shared chain adjustment of the general aviation business segment is positively correlated with the necessity of the cascading sharing of the general aviation business segment; The priority of the shared chain adjustment of the general aviation business segment is positively correlated with the degree of shared adoption of the general aviation business segment; The priority of the shared chain adjustment of the general aviation service segment is positively correlated with the request expansion coefficient of the general aviation service segment.

[0013] Another embodiment of the present invention provides a cross-platform data cascading and sharing system for water transport IoT, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of any of the above-described cross-platform data cascading and sharing methods for water transport IoT.

[0014] The beneficial effects of the technical solution of this invention are as follows: This invention acquires water transport IoT data from various water transport logistics platforms and constructs navigation business segments based on the business flow relationships during ship navigation. This transforms the originally dispersed discrete data across different platforms into a continuous business chain structure centered around the same voyage object, thus providing a unified business foundation for subsequent cross-platform cascading sharing. Furthermore, by using business overlap and business continuity coefficients, the business connection relationships and temporal continuity between upstream and downstream platforms are jointly quantified. Combined with the shared supplement value coefficient, the information supplementation capability of the current shared data for downstream platforms is analyzed, making the cross-platform sharing process no longer dependent on fixed... Instead of interface rules, sharing is dynamically triggered based on actual business relationships and key information needs. A basic sharing degree is formed through a sharing complement value coefficient and a business continuity coefficient, and the necessity of cascading sharing is obtained by combining business time relationships. This ensures that sharing decisions simultaneously consider business stability, information complement value, and time sensitivity, avoiding issues of delayed or duplicate sharing. Furthermore, by incorporating adoption feedback after data sharing, the priority of the sharing chain is dynamically updated, enabling the system to continuously optimize subsequent sharing strategies based on the actual adoption by downstream platforms. This enhances the relevance, collaboration, and dynamic adaptability of cross-platform data sharing. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating the steps of the cross-platform data cascading and sharing method for water transport IoT according to the present invention. Detailed Implementation

[0017] To further illustrate the technical means and effects adopted by the present invention to achieve its intended purpose, the following, in conjunction with the accompanying drawings and preferred embodiments, details the specific implementation, structure, features, and effects of the cross-platform data cascading and sharing method and system for water transport IoT proposed according to the present invention. In the following description, different "one embodiment" or "another embodiment" do not necessarily refer to the same embodiment. Furthermore, specific features, structures, or characteristics in one or more embodiments can be combined in any suitable form.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0019] The following description, in conjunction with the accompanying drawings, details the specific scheme of the cross-platform data cascading and sharing method and system for water transport IoT provided by this invention.

[0020] Please see Figure 1 The diagram illustrates a flowchart of a cross-platform data cascading and sharing method for water transport IoT provided by an embodiment of the present invention. The method includes the following steps: Step S001: Obtain the water transport IoT data from each water transport logistics platform, divide the water transport IoT data into several nodes, and then obtain the navigation business segments.

[0021] It should be noted that in the context of water transport IoT, the same vessel will sequentially go through multiple business stages during the same voyage, such as entering the port, waiting to berth, berthing, waiting to pass through the lock, loading and unloading, and departing. Different platforms typically only record local states within their own business scope. Therefore, the original data in each platform is naturally in a discrete distribution state. If cross-platform sharing is directly based on the platform's original records, problems such as data mixing between different voyages, overlap between historical and current states, and disordered business acceptance order are likely to occur. Therefore, this embodiment first groups the water transport IoT data of multiple platforms according to the vessel identifier and voyage identifier, and then constructs navigation business segments by combining the business type flow order and node time order. This transforms the originally discrete records scattered across different platforms into a continuous business chain structure formed around the same navigation object. This ensures that subsequent business acceptance analysis, sharing supplement analysis, and sharing priority adjustment are all based on the actual navigation process, thereby avoiding problems such as invalid splicing, duplicate sharing, and incorrect acceptance during cross-platform sharing.

[0022] Specifically, it acquires various water transport IoT data from various water transport logistics platforms, which at least include: shipborne terminal platforms, waterway monitoring platforms, lock scheduling platforms, port berthing and unberthing platforms, freight operation platforms, and maritime supervision platforms. Water transport IoT data containing the same vessel identifier and the same voyage identifier are grouped into the same navigation object group to obtain several navigation object groups; each piece of water transport IoT data in each navigation object group is used as a node to obtain the node set corresponding to each navigation object group. For any set of nodes in a navigation object group, the nodes in the set of nodes are sorted according to the preset flow order of node business types (the preset flow order of node business types is: entering port, waiting to berth, berthing, waiting to pass through the lock, loading and unloading, and leaving port). If there are multiple nodes under the same node business type, they are sorted according to the order of their node times to obtain the navigation business segments of the navigation object group. In this embodiment, the water transport IoT data refers to the structured state dataset collected by sensing devices in the water transport scenario. Its data structure includes at least: device identifier, timestamp, spatial coordinates (such as latitude and longitude), and state quantities of the corresponding business type (such as water level, speed, gate opening and closing status, etc.).

[0023] It should be noted that each node in a navigation service segment includes at least the source platform identifier, vessel identifier, voyage identifier, service type, node time, node location, and a set of key fields corresponding to that node. The content of the key field set is determined by the source platform of the navigation service node. For example: when the source platform is a waterway monitoring platform, the key field set includes at least water level information and navigation restriction status; when the source platform is a lock scheduling platform, the key field set includes at least the lock waiting number and lock status; when the source platform is a port berthing / departure platform, the key field set includes at least the berth status and estimated arrival time; when the source platform is a cargo handling platform, the key field set includes at least cargo type information and loading / unloading progress; when the source platform is a maritime supervision platform, the key field set includes at least dangerous goods identifier and abnormal alarm tag. The service type includes port entry, waiting to berth, berthing, waiting to lock, passing through lock, loading / unloading, and departure. The navigation service segment is a real-time service segment that dynamically expands with the progress of vessel navigation.

[0024] It should be further explained that the shipborne terminal platform is used to collect AIS / BeiDou location, speed, heading, ship identification, voyage number, and draft information; the waterway monitoring platform is used to collect waterway passage status, water level, current speed, wind speed, visibility, and navigation restriction information; the lock scheduling platform is used to collect lock waiting sequence number, lock session arrangement, estimated lock passage time, and lock chamber allocation status; the port berthing and departure platform is used to collect estimated arrival time, berth preparation status, berthing status, departure status, and berth occupancy status; the cargo handling platform is used to collect cargo type, dangerous goods identification, loading and unloading progress, and loading and unloading completion status; and the maritime supervision platform is used to collect overload, oversize, abnormal trajectory, key supervision, and law enforcement concern tags.

[0025] Step S002: Obtain the upstream sharing platform and downstream receiving platform corresponding to the general aviation business segment; obtain the business overlap of the general aviation business segment based on the platform corresponding to each node in the general aviation business segment; obtain the business continuity coefficient of the general aviation business segment based on the time interval between each node in the general aviation business segment; obtain the sharing and supplementary value coefficient of the general aviation business segment based on the water transport IoT data contained in each node in the general aviation business segment.

[0026] It should be noted that in the context of waterway IoT, the existence of the same vessel record on any two platforms does not necessarily indicate the formation of a genuine business connection. For example, although a vessel may appear on both a waterway monitoring platform and a maritime supervision platform, if the vessel has not yet entered the waiting, lock-keeping, or berthing stage, an effective business connection has not yet been formed between the relevant platforms. Furthermore, even if a business connection has been formed, the information held by the current platform may not necessarily have an actual business impact on the downstream platform. Therefore, this embodiment first quantifies the degree of matching between navigation business segments in terms of business structure continuity and time continuity stability through business overlap and business continuity coefficients to determine whether the current sharing chain has formed an effective connection basis. Subsequently, it further analyzes which information held by the current platform can supplement the missing information dimensions of the downstream platform and have an actual impact on the subsequent processing flow of the downstream platform, thereby obtaining the sharing supplement value coefficient. Through the above method, cross-platform sharing behavior no longer relies on fixed interfaces or full synchronization rules, but rather makes dynamic judgments based on the real business connection relationship and key information supplementation needs, thereby improving the pertinence and effectiveness of cross-platform cascading sharing.

[0027] Specifically, it involves acquiring upstream sharing platforms and downstream receiving platforms corresponding to general aviation business segments.

[0028] It should be noted that the upstream sharing platform corresponding to the general aviation business segment refers to the initiating platform that holds the business node record to be shared within the system at the current moment and initiates cross-platform cascading induction as a data source; the downstream receiving platform corresponding to the general aviation business segment refers to the target receiving platform that is located after the upstream platform business in the actual general aviation flow sequence and is expected to take business continuity action.

[0029] Furthermore, for any general aviation business segment, the node corresponding to the upstream sharing platform of the general aviation business segment is recorded as the upstream business node, and the node corresponding to the downstream receiving platform of the general aviation business segment is recorded as the downstream business node. For any upstream service node, if the next node of the upstream service node in the general aviation service segment is not an upstream service node, the node pair consisting of the upstream service node and its next node in the general aviation service segment is recorded as a candidate successor node pair in the general aviation service segment. If the next node of the upstream business node in the general aviation business segment is a downstream business node, the node pair consisting of the upstream business node and its next node in the general aviation business segment is denoted as the receiving node pair of the general aviation business segment. The ratio of the number of receiving node pairs to the number of candidate receiving node pairs for the general aviation service segment is taken as the receiving ratio of the general aviation service segment. For any pair of receiving nodes, the combination of business types formed by the corresponding business types of the upstream business nodes and the downstream business nodes in the pair of receiving nodes is denoted as the business receiving combination of the receiving node pair; if the preset set of business receiving combinations includes the business receiving combination of the receiving node pair (the preset set of business receiving combinations is: port entry-waiting for berthing, waiting for berthing-berthing, berthing-waiting for gate, waiting for gate-passing through gate, passing through gate-loading and unloading, loading and unloading-departure), the receiving node pair is denoted as the successor node pair; The ratio of the number of connecting node pairs to the number of receiving node pairs in the general aviation service segment is taken as the connecting ratio of the general aviation service segment. The product of the acceptance ratio and the continuity ratio of the general aviation service segment is taken as the service engagement degree of the general aviation service segment.

[0030] It should be noted that during the navigation of the same vessel, there are usually clear sequential relationships between various business nodes. Therefore, the flow between nodes can be used to analyze whether a real business connection has been formed between different platforms. Since the same platform may participate in multiple business phases consecutively, this embodiment first screens candidate node pairs where the business begins to detach from the current platform, and then further screens node pairs that have actually flowed to downstream platforms. The ratio of the number of node pairs to the number of candidate node pairs is used to form a connection ratio, which quantifies the degree of real business flow between upstream and downstream platforms in the current navigation business segment. Simultaneously, although some nodes have sequential relationships, they may not conform to a true sequential relationship. Therefore, this invention further filters the business type combinations corresponding to the receiving node pairs by pre-setting a business receiving combination set, and forms a continuity ratio by the ratio of the number of successor node pairs to the number of receiving node pairs. This ratio is used to quantify the rationality of the current business flow relationship at the business semantic level. Among them, the receiving ratio mainly reflects whether a real business receiving relationship has been formed between platforms, and the continuity ratio mainly reflects whether the receiving relationship conforms to the actual general aviation process. Furthermore, the receiving ratio and the continuity ratio are jointly quantified to form the business overlap, so that the business overlap can simultaneously characterize the business connection strength and business flow effectiveness between platforms, thereby providing a reliable business receiving foundation for subsequent cross-platform cascading and sharing analysis.

[0031] Specifically, for any pair of receiving nodes in any general aviation service segment, the temporal distance between the upstream and downstream service nodes in the receiving node pair of the general aviation service segment at the corresponding time is used as the receiving interval of the receiving node pair of the general aviation service segment. The average of the acceptance intervals of all acceptance node pairs of the general aviation service segment is taken as the comprehensive acceptance interval of the general aviation service segment. Based on the comprehensive acceptance interval and business overlap of the general aviation business segment, the business continuity coefficient of the general aviation business segment is obtained; The business continuity coefficient of the general aviation business segment is positively correlated with the business overlap of the general aviation business segment; the business continuity coefficient of the general aviation business segment is negatively correlated with the comprehensive acceptance interval of the general aviation business segment.

[0032] As an example, the specific formula for calculating the business continuity coefficient of the general aviation business segment is as follows: ; In the formula, This represents the business continuity coefficient of the general aviation business segment; This indicates the degree of service overlap of the general aviation service segment; This indicates the overall connection interval of the general aviation service segment; This refers to the preset benchmark acceptance interval for the upstream and downstream business nodes corresponding to the business types of the receiving nodes in the navigation business segment. In this embodiment, the preset benchmark acceptance intervals for arrival-waiting for berthing, waiting for berthing-berthing, berthing-waiting for gate, waiting for gate-passing through gate, passing through gate-loading and unloading, and loading and unloading-departure are respectively 4 hours, 1 hour, 6 hours, 0.5 hours, 3 hours, and 2 hours. This embodiment uses an exponential function with the natural constant as the base. The model is used to represent the inverse proportional relationship and for normalization processing. As input to the model, implementers can set inverse proportional functions and normalization functions according to the actual situation.

[0033] It should be noted that in actual navigation operations, even if upstream and downstream platforms have established business continuity relationships, there are still significant differences in the stability of continuity between different business chains. For example, some vessels can quickly enter the berthing stage after completing their waiting period, while others may experience long waiting times between different business nodes due to berth congestion, scheduling delays, or gate queues. Therefore, relying solely on the degree of business overlap cannot accurately reflect the continuity and stability of the current business chain. Therefore, in this embodiment, the temporal distance between upstream and downstream business nodes in the receiving node pair is defined as the receiving interval, which is used to characterize the actual receiving time experienced by the business from the upstream platform to the downstream platform. The smaller the comprehensive receiving interval, the tighter the connection between the business stages in the current business chain, and the more stable the business continuity between platforms. Furthermore, since the business interlocking degree mainly reflects whether a real and reasonable business receiving relationship has been formed between platforms, and the comprehensive receiving interval mainly reflects the continuity of the receiving relationship in the time dimension, the higher the business interlocking degree and the smaller the receiving interval, the more stable the business receiving relationship is, the fewer waiting or interruptions there are in the business flow process, and the higher its business continuity coefficient, that is, the stability of the business chain in terms of structural continuity and temporal continuity.

[0034] Specifically, for any general aviation business segment, the set of information dimensions in the downstream business nodes of the general aviation business segment is obtained and denoted as the necessary information dimension set; The set of information dimensions contained in the upstream business nodes of the general aviation business segment is denoted as the upstream held information dimension set. The set of information dimensions that are necessary information dimensions and are missing in the downstream business nodes, which is the upstream information dimension set, is denoted as the supplementary information dimension set. The ratio obtained by dividing the number of information dimensions in the supplementary information dimension set by the number of information dimensions in the necessary information dimension set is used as the missing information supplementation ratio of the general aviation business segment. The missing information supplementation ratio of the general aviation business segment ranges from 0 to 1. The information dimensions in the intersection of the preset key dimension information set and the supplementary information dimension set are denoted as key supplementary information dimensions. The preset key dimension information set is determined according to the business node type of the downstream business node to the receiving node of the navigation business segment. In this embodiment, the key dimension information set corresponding to the waiting berthing node includes {draft, dangerous goods identification, ship dimensions, abnormal alarm tag}, the key dimension information set corresponding to the waiting lock node includes {draft, ship width, dangerous goods identification, water level limit}, the key dimension information set corresponding to the berthing node includes {dangerous goods identification, actual ship draft, abnormal trajectory tag}, the key dimension information set corresponding to the loading and unloading node includes {cargo type, dangerous goods identification, ship draft}, and the key dimension information set corresponding to the regulatory warning node includes {operation status, historical receiving node, abnormal alarm tag}. The ratio of the number of key supplementary information dimensions to the number of information dimensions in the supplementary information dimension set is denoted as the key information ratio of the general aviation business segment. The key information ratio of the general aviation business segment ranges from 0 to 1. Based on the missing information ratio and key information ratio of the general aviation service segment, the shared supplement value coefficient of the general aviation service segment is obtained. The shared complement value coefficient of the general aviation business segment is positively correlated with the missing complement ratio of the general aviation business segment; the shared complement value coefficient of the general aviation business segment is positively correlated with the key information ratio of the general aviation business segment.

[0035] As an example, the specific formula for calculating the shared complement value coefficient of the general aviation service segment is as follows: ; In the formula, This represents the shared complement value coefficient of the general aviation service segment; This indicates the missing component replacement ratio of the general aviation service segment; This indicates the ratio of key information in the general aviation business segment.

[0036] It should be noted that whether the data held by the upstream platform is worth sharing with the downstream platform depends not only on how many missing fields the upstream platform can supplement, but also on whether these supplementary fields can truly affect the business processing path of the downstream platform. Therefore, this embodiment constructs a necessary information dimension set based on the information dimensions of the downstream business nodes to characterize the key fields that the downstream platform truly needs at the current business node; it also constructs an upstream-held information dimension set based on the information dimensions of the upstream business nodes to characterize the range of data that the upstream platform can currently provide; the supplementary information dimension set accurately identifies the effective fields that the upstream platform can supplement for the downstream by taking the intersection of the upstream-held data and the necessary and missing data of the downstream; the missing data supplementation ratio is used to measure the impact of the supplementary fields on the downstream platform. The coverage of necessary fields and the higher the missing data completion rate, the more comprehensive the upstream data fills in the downstream. The key information ratio measures the proportion of the filler fields that belong to the preset key dimension information set. The higher the key information ratio, the more key fields in the filler fields that can trigger changes in the downstream business processing path. When the key information ratio is low, even if the missing data completion rate is high, it means that although there are many filler fields, they are mostly regular or marginal fields, and their impact on downstream business decisions is limited. At this time, the shared filler value coefficient will be suppressed. Only when both the missing data completion rate and the key information ratio are high will the shared filler value coefficient reach a high level, thereby ensuring that the shared decision is driven by filler fields that have real business influence and reducing redundant transmission in cross-platform sharing.

[0037] It needs to be further explained that when This indicates that the number of dimensions in the supplementary information dimension set is 0; and when the number of dimensions in the supplementary information dimension set is 0, the information dimension in the intersection between the preset key dimension information set and the supplementary information dimension set is 0. Therefore, when hour Therefore, it does not exist. and There is no case where the denominator is 0.

[0038] Thus, the shared complement value coefficient of general aviation business segments is obtained.

[0039] Step S003: Based on the sharing and complement value coefficient and business continuity coefficient of the general aviation business segment, obtain the basic sharing degree of the general aviation business segment, and combine the corresponding time of each node in the general aviation business segment to obtain the cascading sharing necessity of the general aviation business segment.

[0040] It should be noted that the business continuity coefficient mainly reflects the continuity of the current general aviation business segment in terms of business acceptance structure and time continuity stability, while the shared supplement value coefficient mainly reflects the supplementary significance and business impact of the current shared information on downstream platforms. If sharing is based solely on business continuity, it is easy to cause duplicate sharing when downstream platforms already have relevant information; if sharing is based solely on supplement value, it may trigger sharing prematurely before the business has entered the actual acceptance stage. Therefore, this embodiment forms a basic sharing degree based on the shared supplement value coefficient and the business continuity coefficient to characterize the basic sharing needs that the current general aviation business segment already has. Subsequently, by combining the relationship between node time and the current time, the urgency of the current business chain in the time dimension is further analyzed to form the cascading sharing necessity degree. This ensures that the sharing decision takes into account business acceptance continuity, information supplement value, and time sensitivity, avoiding the problems of delayed or premature sharing.

[0041] Specifically, for any general aviation service segment, the product of the shared complement value coefficient and the service continuity coefficient of the general aviation service segment is used as the basic sharing degree of the general aviation service segment.

[0042] It should be noted that the shared supplement value coefficient reflects the ability of the upstream platform to supplement the missing fields of the downstream platform and its business influence; the business continuity coefficient reflects the degree of continuity and stability of the business connection between the upstream and downstream platforms in the time dimension. Therefore, the larger the shared supplement value coefficient and the business continuity coefficient, the more effectively the data currently held by the upstream platform can supplement the key missing fields of the downstream platform in terms of content, and the more compact and stable the business connection between the upstream and downstream platforms is in terms of time. At this time, the basic sharing degree is higher, indicating that the current general aviation business segment has high basic sharing value in both content and time dimensions, and is worth prioritizing in the scope of cascade sharing decision-making.

[0043] This embodiment uses the product of content and time as the basic sharing degree because the contributions of content and time to the sharing value have a joint constraint relationship: the basic sharing degree can only reach a high level when the supplementary value is high and the business transition time is tight; if the supplementary value is insufficient, or the business interval is too long leading to a decrease in continuity, the basic sharing degree will decrease accordingly. In this way, the basic sharing degree can jointly constrain the evaluation of basic sharing value from both the content and time dimensions, avoiding the sharing decision bias caused by relying on only a single dimension.

[0044] Specifically, for any pair of receiving nodes in any general aviation service segment, the time sequence distance between the time corresponding to the upstream service node in the receiving node pair and the current time is taken as the elapsed time of the receiving node pair. The processing lag offset of the receiving node pair is obtained by subtracting the receiving interval of the receiving node pair from the elapsed time of the receiving node pair. The processing lag offset of the receiving node pair is linearly normalized (the maximum and minimum values ​​can be normalized using a maximum and minimum value normalization function, the maximum and minimum values ​​of which can be obtained based on historical data or prior experience, and the maximum and minimum values ​​can be adjusted, calibrated or optimized, which does not constitute a limitation of the present invention, and the normalized value range is ultimately [0, 1]), to obtain the response urgency of the general aviation business segment; The difference between the service overlap of the general aviation service segment and the basic sharing degree of the general aviation service segment is multiplied by the response urgency and used as the urgency of the general aviation service segment. The sum of the basic sharing degree and the urgent supplement degree of the general aviation service segment is used as the cascading sharing necessity degree of the general aviation service segment, and the value range of the cascading sharing necessity degree of the general aviation service segment is from 0 to 1.

[0045] It should be noted that the elapsed time represents the length of time that has passed from the upstream business node to the current moment. The larger the value, the further back the data generated by the upstream business node is from the current moment. The processing lag offset is obtained by subtracting the acceptance interval from the elapsed time, and represents the degree of deviation of the current moment from the expected time of the downstream business node. When the processing lag offset is positive, it means that the current moment has exceeded the node time of the downstream business node, and the business processing has lagged behind. The larger the processing lag offset, the more serious the degree to which the current moment has exceeded the time of the downstream business node, and the more obvious the business processing lag. The closer the response urgency is to 1, the higher the time pressure of business processing. The difference between the business overlap and the basic sharing degree represents the business in the current general aviation business segment. The remaining sharing needs that have been established but not yet covered by the basic sharing level are identified. The urgency of supplementary sharing is obtained by multiplying the remaining sharing needs by the urgency of response. This ensures that when processing is severely delayed and the urgency of response is high, even if the basic sharing level is low, the remaining sharing needs can be activated by time pressure and transformed into actual sharing driving force. This ensures that time-sensitive business nodes are not ignored due to low supplementary value assessment. Thus, cascading sharing includes both the static sharing foundation determined by supplementary value and time continuity, and the urgent sharing needs dynamically driven by the degree of business processing delay. It can comprehensively reflect the sharing necessity of current general aviation business segments in terms of content value and time sensitivity, providing a quantitative basis for cross-platform cascading sharing decisions that takes into account both static value and dynamic timeliness.

[0046] This provides an urgent need to fill gaps in the general aviation business segment.

[0047] Step S004: Based on the necessity of cascading and sharing general aviation business segments and the adoption feedback after data sharing, obtain the priority of adjusting the sharing chain of general aviation business segments, and carry out cross-platform data cascading and sharing through the priority of adjusting the sharing chain of general aviation business segments.

[0048] It should be noted that in traditional cross-platform data sharing, once data is sent, the system typically only records whether the transmission was successful, lacking continuous feedback on the actual adoption by downstream platforms. Therefore, it is difficult to determine whether the current sharing granularity, scope, and priority are reasonable. In this invention, after receiving shared data, the downstream receiving platform further provides feedback on the adopted information dimensions, supplementary request information, and requests from adjacent nodes. This allows the system to analyze whether the currently shared content has truly participated in the downstream platform's business processing flow. If the shared data is widely adopted, it indicates that the current sharing chain structure and sharing granularity are reasonable; if the downstream platform further requests supplementary fields or adjacent nodes, it indicates that the current shared content still has insufficient supplementation issues. Therefore, this invention further establishes a sharing chain adjustment priority based on the necessity of cascading sharing and the adoption feedback results, and uses this priority to dynamically adjust the sharing strategy under subsequent similar receiving relationships. This enables cross-platform data sharing to have continuous optimization capabilities, avoiding the sharing redundancy or insufficient sharing problems caused by long-term use of fixed sharing strategies.

[0049] Specifically, for any general aviation business segment, the data sharing feedback results from the downstream receiving platform to the upstream sharing platform are obtained. The data sharing feedback results include at least: the information dimensions already used, the information dimensions contained in the supplementary request, and adjacent nodes. The ratio of the number of information dimensions already adopted to the number of information dimensions in the upstream information dimension set of the general aviation business segment is used as the degree of shared adoption of the general aviation business segment. The value of the degree of shared adoption of the general aviation business segment ranges from 0 to 1. The linearly normalized result of the number of information dimensions contained in the supplementary request (which can be normalized using a maximum and minimum value normalization function) is used as the information supplementary request factor. The linearly normalized results of the adjacent nodes included in the supplementary request (which can be normalized using the maximum and minimum value normalization function) are used as the node supplementary request factor. Based on the preset information supplementation request weight and node supplementation request weight, the information supplementation request factor and node supplementation request factor are weighted and summed to obtain the request expansion coefficient of the general aviation business segment. The value range of the request expansion coefficient of the general aviation business segment is 0 to 1. The specific values ​​of the information supplementation request weight and node supplementation request weight are not strictly required in this embodiment. In this embodiment, the information supplementation request weight is equal to 0.6 and the node supplementation request weight is equal to 0.4 as an example. Based on the cascading sharing necessity, request expansion coefficient, and sharing adoption degree of the general aviation service segment, the priority of the sharing chain adjustment of the general aviation service segment is obtained; The priority of the shared chain adjustment of the general aviation business segment is positively correlated with the necessity of the cascading sharing of the general aviation business segment; The priority of the shared chain adjustment of the general aviation business segment is positively correlated with the degree of shared adoption of the general aviation business segment; The priority of the shared chain adjustment of the general aviation service segment is positively correlated with the request expansion coefficient of the general aviation service segment.

[0050] As an example, the specific calculation formula for obtaining the shared chain adjustment priority of the general aviation service segment is as follows: ; In the formula, This indicates the priority of the shared chain adjustment for the aforementioned general aviation service segment; This indicates the degree of necessity for cascading and sharing of the aforementioned general aviation service segments; This indicates the degree of sharing and adoption of the aforementioned general aviation service segments; This represents the request expansion coefficient of the general aviation service segment.

[0051] It should be noted that the sharing adoption rate represents the proportion of currently shared content actually utilized by downstream platforms. The higher the value, the more effective the current shared content is in supporting downstream business processing. The information supplementation request factor represents the degree to which downstream platforms believe the current sharing is insufficient in terms of field coverage. The node supplementation request factor represents the degree to which downstream platforms believe the current sharing is insufficient in terms of business node coverage. The two are weighted and summed to form the request expansion coefficient, which comprehensively characterizes the completeness of the current sharing in covering downstream business needs. The higher the request expansion coefficient, the more difficult it is for the current sharing to meet the business needs of downstream platforms. A higher adoption rate indicates a more effective sharing relationship. When the adoption rate is low but the request expansion coefficient is high, it means that although the current sharing is not fully adopted, downstream platforms still have clear expansion needs. In this case, the request expansion coefficient can offset the decline effect caused by insufficient adoption, ensuring that the adjustment priority is not too low and reserving space for expanding the sharing granularity or supplementing the sharing content in the future. When both the adoption rate and the request expansion coefficient are low, it means that the current sharing is neither effectively adopted nor has it triggered further demand. The adjustment priority will be reduced accordingly, and the sharing granularity can be compressed or only summary sharing can be retained. This allows the sharing chain adjustment priority to be dynamically adjusted according to the actual feedback from downstream platforms, enabling the cross-platform sharing scope and sharing intensity to adaptively optimize with changes in business needs.

[0052] It should be further explained that a request expansion coefficient threshold is preset. The specific value of the request expansion coefficient threshold can be set according to the actual situation. This embodiment does not make a hard requirement. In this embodiment, the request expansion coefficient threshold is equal to 0.7 as an example. When the request expansion coefficient is less than the request expansion coefficient threshold, it means that the request expansion coefficient is low. When the request expansion coefficient is greater than or equal to the request expansion coefficient threshold, it means that the request expansion coefficient is high.

[0053] Furthermore, a high sharing threshold and a low sharing threshold are preset. The specific values ​​of the high sharing threshold and the low sharing threshold can be set according to the actual situation. This embodiment does not make a hard requirement. In this embodiment, the high sharing threshold is equal to 0.6 and the low sharing threshold is equal to 0.3 as an example. When the priority of the sharing chain adjustment of the general aviation business segment is greater than the high sharing threshold, all information of the upstream business node in the general aviation business segment is shared to the downstream receiving platform. When the priority of the shared chain adjustment of the general aviation business segment is less than or equal to the high sharing threshold and greater than the low sharing threshold, only the information in the supplementary information dimension set of the general aviation business segment is shared to the downstream receiving platform, and the supplementary field interface is reserved for subsequent requests from the downstream platform. When the priority of the shared chain adjustment of the general aviation service segment is less than or equal to the low sharing threshold, sharing is not triggered, and the information in the current general aviation service segment is retained until the next synchronization cycle for batch synchronization and sharing. The system adaptively adjusts the sharing strategy of subsequent general aviation service segments with the same upstream sharing platform and downstream receiving platform according to the value of the shared chain adjustment priority: if the shared chain adjustment priority is high, the subsequent sharing priority under the same receiving relationship is increased and the sharing granularity is expanded; if the shared chain adjustment priority is low, the sharing granularity of subsequent objects of the same type is compressed or only summary sharing is retained, thereby realizing the continuous optimization of the cross-platform cascading sharing strategy.

[0054] Another embodiment of the present invention provides a cross-platform data cascading and sharing system for water transport IoT, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the cross-platform data cascading and sharing method for water transport IoT in steps S001 to S004.

[0055] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications or equivalent substitutions made within the principles of the present invention are permitted.

Claims

1. A cross-platform data cascading and sharing method for water transport IoT, characterized in that, The method includes the following steps: Acquire various water transport IoT data from various water transport logistics platforms, divide the water transport IoT data into several nodes, and then obtain navigation business segments; Obtain the upstream sharing platform and downstream receiving platform corresponding to the general aviation business segment; based on the platform corresponding to each node in the general aviation business segment, obtain the business overlap of the general aviation business segment; combined with the time interval between the corresponding nodes in the general aviation business segment, obtain the business continuity coefficient of the general aviation business segment; based on the water transport IoT data contained in each node of the general aviation business segment, obtain the sharing and supplementary value coefficient of the general aviation business segment. Based on the sharing and complement value coefficient and business continuity coefficient of the general aviation business segment, the basic sharing degree of the general aviation business segment is obtained. Combined with the time corresponding to each node in the general aviation business segment, the cascading sharing necessity of the general aviation business segment is obtained. Based on the necessity of cascading and sharing general aviation business segments, and combined with the adoption feedback after data sharing, the priority of adjusting the sharing chain of general aviation business segments is obtained, and cross-platform data cascading and sharing is carried out through the priority of adjusting the sharing chain of general aviation business segments.

2. The cross-platform data cascading and sharing method for water transport IoT according to claim 1, characterized in that, The specific method for acquiring various water transport IoT data from each water transport logistics platform, dividing the water transport IoT data into several nodes, and then acquiring general navigation business segments includes: Acquire various water transport IoT data from various water transport logistics platforms, wherein the water transport logistics platforms include at least: shipborne terminal platform, waterway monitoring platform, lock scheduling platform, port berthing and departure platform, freight operation platform and maritime supervision platform; Water transport IoT data containing the same vessel identifier and the same voyage identifier are grouped into the same navigation object group to obtain several navigation object groups; each piece of water transport IoT data in each navigation object group is used as a node to obtain the node set corresponding to each navigation object group. For any set of nodes in a general aviation object group, the nodes in the set of nodes in the general aviation object group are sorted according to the flow order of the preset node business type; if there are multiple nodes under the same node business type, they are sorted according to the order of their node time to obtain the general aviation business segment of the general aviation object group.

3. The cross-platform data cascading and sharing method for water transport IoT according to claim 1, characterized in that, The specific method for obtaining the service overlap of a general aviation service segment based on the platform corresponding to each node in the segment is as follows: For any general aviation business segment, the node corresponding to the upstream sharing platform of the general aviation business segment is recorded as the upstream business node, and the node corresponding to the downstream receiving platform of the general aviation business segment is recorded as the downstream business node. For any upstream service node, if the next node of the upstream service node in the general aviation service segment is not an upstream service node, the node pair consisting of the upstream service node and its next node in the general aviation service segment is recorded as a candidate successor node pair in the general aviation service segment. If the next node of the upstream business node in the general aviation business segment is a downstream business node, the node pair consisting of the upstream business node and its next node in the general aviation business segment is denoted as the receiving node pair of the general aviation business segment. The ratio of the number of receiving node pairs to the number of candidate receiving node pairs for the general aviation service segment is taken as the receiving ratio of the general aviation service segment. For any pair of receiving nodes, the combination of business types formed by the upstream business node and the downstream business node in the receiving node pair is denoted as the business receiving combination of the receiving node pair; if the preset set of business receiving combinations includes the business receiving combination of the receiving node pair, the receiving node pair is denoted as the successor node pair. The ratio of the number of connecting node pairs to the number of receiving node pairs in the general aviation service segment is taken as the connecting ratio of the general aviation service segment. The product of the acceptance ratio and the continuity ratio of the general aviation service segment is taken as the service engagement degree of the general aviation service segment.

4. The cross-platform data cascading and sharing method for water transport IoT according to claim 3, characterized in that, The specific methods for obtaining the service coherence coefficient of general aviation service segments are as follows: For any pair of receiving nodes in any general aviation service segment, the temporal distance between the upstream and downstream service nodes in the receiving node pair of the general aviation service segment at the corresponding time is taken as the receiving interval of the receiving node pair of the general aviation service segment. The average of the acceptance intervals of all acceptance node pairs of the general aviation service segment is taken as the comprehensive acceptance interval of the general aviation service segment. Based on the comprehensive acceptance interval and business overlap of the general aviation business segment, the business continuity coefficient of the general aviation business segment is obtained; The business continuity coefficient of the general aviation business segment is positively correlated with the business overlap of the general aviation business segment; the business continuity coefficient of the general aviation business segment is negatively correlated with the comprehensive acceptance interval of the general aviation business segment.

5. The cross-platform data cascading and sharing method for water transport IoT according to claim 3, characterized in that, The specific method for obtaining the shared complement value coefficient of a navigation service segment based on the water transport IoT data contained in each node of the navigation service segment includes: For any general aviation business segment, obtain the set of information dimensions in the downstream business nodes of the general aviation business segment, denoted as the necessary information dimension set; The set of information dimensions contained in the upstream business nodes of the general aviation business segment is denoted as the upstream held information dimension set. The set of information dimensions that are necessary information dimensions and are missing in the downstream business nodes, which is the upstream information dimension set, is denoted as the supplementary information dimension set. The ratio obtained by dividing the number of information dimensions in the supplementary information dimension set by the number of information dimensions in the necessary information dimension set is used as the missing supplementation ratio of the general aviation business segment. The information dimension in the intersection between the preset key dimension information set and the supplementary information dimension set is denoted as the key supplementary information dimension. The ratio of the number of key supplementary information dimensions to the number of information dimensions in the supplementary information dimension set is denoted as the key information ratio of the general aviation business segment. The shared complement value coefficient of the general aviation business segment is obtained based on the missing complement ratio of the general aviation business segment and the key information ratio of the general aviation business segment. The shared complement value coefficient of the general aviation business segment is positively correlated with the missing complement ratio of the general aviation business segment; the shared complement value coefficient of the general aviation business segment is positively correlated with the key information ratio of the general aviation business segment.

6. The cross-platform data cascading and sharing method for water transport IoT according to claim 1, characterized in that, The specific method for obtaining the basic sharing degree of general aviation business segments based on the sharing and complement value coefficient and the business continuity coefficient of general aviation business segments includes: For any general aviation service segment, the product of the shared complement value coefficient and the service continuity coefficient of the general aviation service segment is used as the basic sharing degree of the general aviation service segment.

7. The cross-platform data cascading and sharing method for water transport IoT according to claim 3, characterized in that, The specific methods for obtaining the cascading sharing necessity of general aviation service segments are as follows: For any pair of receiving nodes in any general aviation service segment, the time sequence distance between the time corresponding to the upstream service node in the receiving node pair and the current time is taken as the elapsed time of the receiving node pair. The processing lag offset of the receiving node pair is obtained by subtracting the receiving interval of the receiving node pair from the elapsed time of the receiving node pair. The processing lag offset of the receiving node pair is linearly normalized to obtain the response urgency of the general aviation service segment. The difference between the service overlap of the general aviation service segment and the basic sharing degree of the general aviation service segment is multiplied by the response urgency and used as the urgency of the general aviation service segment. The sum of the basic sharing degree and the urgent supplement degree of the general aviation service segment is taken as the cascading sharing necessity degree of the general aviation service segment.

8. The cross-platform data cascading and sharing method for water transport IoT according to claim 5, characterized in that, The method for obtaining the priority of the sharing chain adjustment of general aviation business segments based on the necessity of cascading sharing of general aviation business segments and the adoption feedback after data sharing includes the following specific methods: For any general aviation business segment, obtain the data sharing feedback result from the downstream receiving platform to the upstream sharing platform. The data sharing feedback result includes at least: the information dimensions already used, the information dimensions contained in the supplementary request, and adjacent nodes. The ratio of the number of information dimensions already adopted to the number of information dimensions in the upstream information dimension set of the aforementioned general aviation business segment is taken as the degree of shared adoption of the general aviation business segment. The linear normalization result of the number of information dimensions contained in the supplementary request is used as the information supplementary request factor; The linearly normalized result of the adjacent nodes included in the supplementary request is used as the node supplementary request factor. Based on the preset information supplementation request weight and node supplementation request weight, the information supplementation request factor and node supplementation request factor are weighted and summed to obtain the request expansion coefficient of the general aviation service segment. The priority of the sharing chain adjustment for the general aviation service segment is obtained based on the cascading sharing necessity, request expansion coefficient, and sharing adoption degree of the general aviation service segment.

9. The cross-platform data cascading and sharing method for water transport IoT according to claim 8, characterized in that, The specific method for obtaining the sharing chain adjustment priority of the general aviation service segment based on the cascading sharing necessity, request expansion coefficient, and sharing adoption degree of the general aviation service segment includes: The priority of the shared chain adjustment of the general aviation business segment is positively correlated with the necessity of the cascading sharing of the general aviation business segment; The priority of the shared chain adjustment of the general aviation business segment is positively correlated with the degree of shared adoption of the general aviation business segment; The priority of the shared chain adjustment of the general aviation service segment is positively correlated with the request expansion coefficient of the general aviation service segment.

10. A cross-platform data cascading and sharing system for water transport IoT, comprising a memory, a processor, and a computer program stored on the memory and capable of running on the processor, characterized in that, When the computer program is executed by the processor, it implements the steps of the cross-platform data cascading and sharing method for water transport IoT as described in any one of claims 1-9.

Images