Data updating method and device for digital twin entities

Abstract

The invention provides a data updating method and device for digital twin entities, and relates to the technical field of digital twin geographic information.The method includes the steps that the observation capacity satisfaction degree of a sensing node is calculated, a target node is determined, mapping between the target node and the geographic entity is established, and first entity data of the geographic entity is obtained; second entity data of the digital twin entity corresponding to the geographic entity is then updated based on the first entity data. According to the digital twin entity-oriented data updating method provided by the invention, geographic entity data can be comprehensively, accurately and timely acquired, and meanwhile, aiming at data perception of a specific entity, the traversal quantity of a leading source is greatly reduced, the entity data acquisition efficiency is improved, and accurate and timely updating of the digital twin entity data is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of digital twin geographic information, in particular to a data updating method and device for a digital twin entity. BACKGROUND

[0002] The digital twin entity is the core of data organization, management and application in the digital twin scene. The multi-dimensional information (time, space, attribute, scale, multi-source heterogeneity and business field) describing the same object is organically collected and associated by entity objects, and the intelligent application is enabled. The digital twin has the characteristics of virtual-real mapping, and the modeling, maintenance and application of the digital twin entity need to reflect the changes of the geographic entity in the real physical world. Therefore, the dynamic acquisition and updating capability of geographic entity data is crucial.

[0003] Currently, the perception nodes used for dynamically acquiring geographic entity data are still allocated and planned in an artificial dispatch mode, which is easy to cause subjective perception node configuration omissions. Therefore, when facing complex and variable digital twin entities, it is easy to have the phenomena of not comprehensive, not accurate and not timely for the geographic entity perception task, resulting in not ideal data connection results for key geographic entities and key targets in various applications, and low task completion degree. SUMMARY

[0004] The present application provides a data updating method and device for a digital twin entity, which solves the technical problem of inaccurate and timely digital twin entity data updating due to not comprehensive, not accurate and not timely geographic entity data acquisition in the prior art.

[0005] The present application provides a data updating method for a digital twin entity, comprising the following steps: acquiring a geographic entity and a perception node; based on the geographic entity and the perception node, calculating the observation ability satisfaction degree of the perception node; based on the observation ability satisfaction degree of the perception node, determining a target node; based on the target node, obtaining first entity data of the geographic entity by establishing a mapping between the target node and the geographic entity; based on the first entity data, updating second entity data of a digital twin entity corresponding to the geographic entity.

[0006] According to the data updating method for a digital twin entity provided by the present application, the observation ability satisfaction degree of the perception node is calculated based on the geographic entity and the perception node, which comprises: calculating the topic matching degree of the geographic entity and the perception node; and meshing the research area according to a preset scale to obtain the number of grids covered by the perception node; based on the number of grids covered by the perception node, statistically classify the grids covered by the perception node, determine the number of grids under different sensor accuracies corresponding to different perception nodes; and based on the sensor accuracy of the perception node, calculate the topic accuracy score of the perception node; based on the topic matching degree of the perception node, the number of grids under different sensor accuracies corresponding to different perception nodes, and the topic accuracy score of the perception node, calculate the observation ability satisfaction degree of the perception node.

[0007] According to the data updating method for the digital twin entity provided by the application, the observation ability satisfaction degree of the perception node is determined, including: In the case where the observation ability satisfaction degree of the perception node reaches the preset threshold, the perception node is taken as the target node.

[0008] According to the data updating method for the digital twin entity provided by the application, the observation ability satisfaction degree of the perception node is determined, including: In the case where the observation ability satisfaction degree of the perception node does not reach the preset threshold, continue to calculate the observation ability satisfaction degree of the next perception node until the observation ability satisfaction degree of the perception node reaches the preset threshold, and take the perception node as the target node.

[0009] According to the data updating method for the digital twin entity provided by the application, the first entity data of the geographic entity includes a perception object and a spatial positioning; The perception object is a bounding box corresponding to the geographic entity in sensor data; The spatial positioning is the geographic spatial position of the perception object relative to the sensor.

[0010] According to the data updating method for the digital twin entity provided by the application, after the first entity data is updated, the second entity data of the digital twin entity corresponding to the geographic entity is updated, and the method further includes: Based on the updated second entity data, update the digital twin entity.

[0011] The application also provides a data updating device for a digital twin entity, including the following modules: The acquisition module is used to acquire a geographic entity and a perception node; The calculation module is used to calculate the observation ability satisfaction degree of the perception node based on the geographic entity and the perception node; The determination module is used to determine a target node based on the observation ability satisfaction degree of the perception node; a mapping module configured to obtain first entity data of the geographic entity by establishing a mapping between the target node and the geographic entity based on the target node; an updating module configured to update second entity data of a digital twin entity corresponding to the geographic entity based on the first entity data.

[0012] The application further provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, and the processor implements the data updating method for a digital twin entity according to any one of the above when executing the computer program.

[0013] The application further provides a non-transitory computer-readable storage medium having a computer program stored thereon, and the computer program implements the data updating method for a digital twin entity according to any one of the above when executed by a processor.

[0014] The application further provides a computer program product comprising a computer program, and the computer program implements the data updating method for a digital twin entity according to any one of the above when executed by a processor.

[0015] The data updating method for a digital twin entity provided by the application determines a target node by calculating the observation ability satisfaction degree of a perception node, filters and sorts the perception nodes with the observation ability of the geographic entity, improves the data induction efficiency of the geographic entity, and obtains first entity data of the geographic entity by establishing a mapping between the target node and the geographic entity, thereby realizing efficient and controllable object-level data perception aggregation from the physical world to the digital world, and comprehensively, accurately and timely acquiring the geographic entity data, greatly reducing the number of induction sources for specific entity data perception, and improving the entity data acquisition efficiency, and then updating second entity data of a digital twin entity corresponding to the geographic entity based on the first entity data, and realizing accurate and timely updating of the digital twin entity data. BRIEF DESCRIPTION OF DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the application or prior art, the following will briefly introduce the drawings needed to be used in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor based on these drawings.

[0017] Figure 1 is a flowchart of the data updating method for a digital twin entity provided by the application.

[0018] Figure 2Is a sensing node observation ability satisfaction degree calculation process schematic diagram in a digital twin entity-oriented data updating method provided by the application.

[0019] Figure 3 Is a structure schematic diagram of a digital twin entity-oriented data updating device provided by the application.

[0020] Figure 4 Is a structure schematic diagram of an electronic device provided by the application. DETAILED DESCRIPTION

[0021] In order to meet the demand for increasingly complex and variable geographic entity observation tasks, it is necessary to coordinate multiple platform sensor resources for comprehensive perception. However, different geographic entities have different requirements in terms of start and end time, spatial resolution, execution area, time resolution, etc., and different observation resources (or sensing nodes) also have differences in observation ability and application scenarios.

[0022] The commonly used sensor collaborative observation planning framework mainly includes two categories of centralized and distributed. The centralized collaborative planning method is a planning method for unified modeling of observation resources, suitable for single platform multi-sensor, and initially applied to multi-satellite sensor networking observation. The advantage of centralized collaborative planning method is that it can solve and optimize the problem from a global perspective, and expects to get a globally optimized result. However, it is difficult for centralized collaborative planning to build a centralized planning model containing different types of sensors, and it is difficult to adapt to dynamically changing resources and tasks, and cannot meet the requirements of collaborative observation of multiple sensor platforms.

[0023] In order to solve this problem, distributed collaborative observation planning methods including distributed problem solving (Distributed Problem Solving, DPS) and multi-agent system (Multi-Agent System, MAS) have gradually emerged. DPS focuses on the top-down decomposition, distribution, execution and merging of observation tasks, and provides some effective planning models and strategies to solve these problems.

[0024] Compared with DPS, MAS emphasizes the autonomy of agents and the coordination between agents, thus better meeting the cooperation needs of multi-sensor platforms. There are three basic types of MAS frameworks, namely hierarchical framework, federated framework and autonomous framework, each of which has its advantages and disadvantages. For example, the hierarchical framework has higher performance in global optimization, but this framework is relatively difficult to maintain and reconfigure, and has poor flexibility in dealing with dynamic changes in problems; the autonomous framework is more adaptable to dynamic changes in problems, but since the decisions of each agent are local and autonomous, the global view of the system is not considered, and this framework has deficiencies in solving the global optimization of problems, and the behavior of each agent is unpredictable.

[0025] In the prior art, the task planning for the perception node allocation of the digital twin entity is still mainly in the artificial dispatch mode, which is easy to cause subjective perception resource node configuration omissions. Therefore, when facing complex and variable digital twin entities, it is easy to appear not comprehensive, not accurate, not timely, etc. for entity perception tasks, resulting in not ideal data connection results for key entities and key targets in various applications, and low task completion degree. Specifically, there are the following three problems: 1) The data connection for the entity is not complete, the traditional single observation method has time and space discontinuity, cannot automatically select multiple perception resource nodes for cooperative observation, resulting in time and space coverage blind area of the connected environmental data; 2) The data connection for the entity is not accurate, the traditional data based on artificial experience to select data source lacks the correlation mapping between perception task demand and perception resource node observation ability, resulting in that the precision and quality of the connected environmental data cannot be effectively guaranteed, and the perception task demand cannot be accurately responded; 3) The data connection for the entity is not timely, the traditional artificial selection of data source means for entity data connection is difficult to continuously monitor the entity situation, when the entity data changes, it is difficult to grasp the change situation in time, and update the related data of the digital twin entity.

[0026] Therefore, according to the specific needs of the digital twin entity, the mapping between the perception node, the perception object and the perception data is established, the multi-source perception resource node is cooperated for dynamic planning, and the advantages of various sensors in large-scale space coverage, high-frequency time response and high-reliable information acquisition are fully played, so as to improve the pre-perception, accurate perception and controllable perception ability of the digital twin entity. Therefore, the present application proposes a data updating method for a digital twin entity to meet the above needs.

[0027] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below in combination with the drawings in the present application. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the protection scope of the present application.

[0028] The present application provides a data updating method and device for a digital twin entity. Figures 1 to 4 The present application provides a data updating method and device for a digital twin entity.

[0029] Figure 1 FIG. 1 is a flow diagram of a data updating method for a digital twin entity provided by the present application, as shown in the figure, the method comprises steps 101 to 105: Figure 1 Step 101, acquiring a geographic entity and a perception node.

[0030] Specifically, the geographic entity refers to an individual that actually exists on the earth and is self-contained. The geographic entity can include geographic elements such as geographic landscape, landform, surface feature, geographic area, topography, water system, climate, vegetation, plant and animal community, and environment. The digital twin entity is an abstract representation of the physical world in a computer environment, which has identification significance and geographic spatial characteristics.

[0031] In the embodiments of the present application, the geographic entity to be observed and the perception node to be calculated are needed, wherein the geographic entity includes the name, identification code or number of the geographic entity, and the perception node includes some perception means arranged in the physical world, such as infrared perception device, visible light perception device, and ground camera, etc. Through the sensors built-in these devices, the data of the geographic entity is perceived.

[0032] Step 102, calculating the observation ability satisfaction degree of the perception node based on the geographic entity and the perception node.

[0033] Specifically, in order to establish accurate mapping between the perception node and the geographic entity, the perception node with the observation ability of the geographic entity needs to be screened and sorted first, so as to improve the data connection efficiency of the geographic entity.

[0034] In the embodiments of the present application, whether the perception node meets the required observation ability is determined by calculating the observation ability satisfaction degree of the perception node. Figure 2 FIG. 2 is a flow diagram of the calculation of the observation ability satisfaction degree of the perception node in the data updating method for the digital twin entity provided by the present application, as shown in the figure, the calculation of the observation ability satisfaction degree of the perception node comprises the following steps (1) to (3): Figure 2 ​​(1) Calculate the topic matching degree of the geographic entity and the perception node. According to the perception resource topic and task relevance standard in the expert knowledge base, the topic matching degree of the geographic entity and the perception node is determined , The value range of the topic matching degree is (0, 1).

[0035] For example, in the case of a sensor as the perception resource topic, according to the sensor topic and task relevance standard in the expert knowledge base, the measurement value of the topic matching degree is determined. Table 1 is a correspondence table of the sensor topic matching degree and the correlation degree provided by the present application, as shown in Table 1.

[0036] Table 1 Correspondence table of sensor topic matching degree and correlation degree

[0037] At the same time, the research area is gridded according to a preset scale, spatial coverage grid statistics are performed, and the number of grids covered by the perception node is obtained.

[0038] (2) The grids covered by the perception node are classified and counted according to the sensor accuracy of the perception node, and the number of grids corresponding to the accuracy is denoted as ; and based on the sensor accuracy of the perception node, the topic accuracy score of the perception node is further calculated , and the calculation expression is as follows: In the formula, the sensor accuracy of the perception node is denoted.

[0039] (3) Based on the topic matching degree of the perception node, the number of grids under different sensor accuracies corresponding to different perception nodes and the topic accuracy score of the perception node , weighted calculation is performed, so as to calculate the observation ability satisfaction degree of the perception node, and the calculation expression of the observation ability satisfaction degree of the perception node is as follows: According to the data corresponding to the geographic entity and the perception node, the observation ability satisfaction degree of the perception node is calculated in the embodiment of the present application, which provides a basis for subsequent screening of the perception node to introduce the data of the geographic entity.

[0040] Step 103, determining a target node based on the observation ability satisfaction degree of the perception node.

[0041] Specifically, in the case that the observation ability satisfaction degree of the perception node does not reach the expected target or does not meet the preset threshold, the calculation of the subsequent perception node is iterated, and if a perception node meeting the expected target or the preset threshold is obtained, the perception node is taken as a target node, a plan library of mapping of the geographic entity and the target node is established, the plan library is maintained for the hotspot area and the target node, and rapid execution of intelligent planning is supported.

[0042] The embodiment of the application calculates the observation ability satisfaction degree of the perception node by analyzing the data obtained by the perception node, and automatically obtains a node capable of data connection for a specific entity, thereby improving the data connection efficiency and accuracy compared with the traditional manual selection of data source, giving full play to the advantages of various sensors in various perception nodes in terms of wide spatial coverage, high frequency time response, and high reliable information acquisition, and improving the pre-perception, accurate perception and controllable perception capabilities for digital twin entities.

[0043] Step 104, based on the target node, the first entity data of the geographic entity is obtained by establishing the mapping between the target node and the geographic entity.

[0044] Specifically, after determining the target node, the mapping between the target node and the geographic entity is established, and the perception data (i.e., the first entity data) of the geographic entity, such as the perception object and the spatial positioning information, is accurately connected, thereby providing a basis for subsequent updating of the data of the digital twin entity.

[0045] Step 105, based on the first entity data, the second entity data of the digital twin entity corresponding to the geographic entity is updated.

[0046] Specifically, in view of the rapid updating requirement of the data of the digital twin entity, after the perception data is connected through the target node, the perception data is accurately connected to the digital twin entity database by further establishing the mapping between the digital twin entity object and the target node, thereby accurately connecting the updating data of the digital twin entity through the step-by-step mapping of the perception node and the perception data, and realizing efficient and controllable object-level data perception aggregation from the physical world perception node to the digital world.

[0047] Meanwhile, when perceiving the data of a specific entity, the data belonging to the geographic entity is judged to enter the corresponding digital twin entity database for data updating, thereby realizing accurate data connection for the specific digital twin entity, greatly reducing the traversal number of the connection source, and improving the data acquisition efficiency of the geographic entity.

[0048] The application provides a data updating method for a digital twin entity, which comprises the following steps: determining a target node by calculating the observation ability satisfaction degree of a perception node, screening and sorting the perception nodes with the observation ability of the geographic entity, improving the data introduction efficiency of the geographic entity, and obtaining the first entity data of the geographic entity by establishing a mapping between the target node and the geographic entity, realizing efficient and controllable object-level data perception aggregation of the physical world perception node to the digital world, thereby comprehensively, accurately and timely acquiring the geographic entity data, greatly reducing the traversal number of the introduction source for the data perception of a specific entity, improving the entity data acquisition efficiency, then updating the second entity data of the digital twin entity corresponding to the geographic entity based on the first entity data, and realizing accurate and timely updating of the digital twin entity data.

[0049] Optionally, the calculation of the observation ability satisfaction degree of the perception node based on the geographic entity and the perception node comprises the following steps: calculating the theme matching degree of the geographic entity and the perception node; and griding the research area according to a preset scale to obtain the number of grids covered by the perception node; based on the number of grids covered by the perception node, classifying and counting the grids covered by the perception node to determine the number of grids under different sensor accuracies corresponding to different perception nodes; and based on the sensor accuracy of the perception node, calculating the theme accuracy score of the perception node;

[0050] Specifically, the calculation of the observation ability satisfaction degree of the perception node comprises the following steps (1) to (3): (1) calculating the theme matching degree of the geographic entity and the perception node. According to the perception resource theme and task correlation standard in the expert knowledge base, the theme matching degree of the geographic entity and the perception node is determined , , and the value range of the theme matching degree is (0, 1); At the same time, the research area is gridded according to a preset scale to obtain the number of grids covered by the perception node.

[0051] (2) classifying and counting the grids covered by the perception node according to the sensor accuracy of the perception node, and the number of grids corresponding to the accuracy is denoted as ; and based on the sensor accuracy of the perception node, further calculating the theme accuracy score of the perception node , and the calculation expression is as follows: In the formula, represents the sensor accuracy of the perception node.

[0052] (3) Subject matching degree of the perception node , the number of grids under different sensor accuracies corresponding to different perception nodes and the subject accuracy score of the perception node , a weighted calculation is performed to calculate the observation ability satisfaction degree of the perception node, and the calculation expression of the observation ability satisfaction degree of the perception node is as follows: According to the data corresponding to the geographic entity and the perception node, the observation ability satisfaction degree of the perception node is calculated in the embodiment of the application, so that the perception node with the observation ability of the geographic entity is screened and sorted, and the data connection efficiency of the geographic entity is improved.

[0053] Optionally, the target node is determined based on the observation ability satisfaction degree of the perception node, and the method comprises the following steps: In the case that the observation ability satisfaction degree of the perception node reaches a preset threshold, the perception node is taken as the target node.

[0054] Specifically, in the case that the observation ability satisfaction degree of the perception node reaches an expected target or meets a preset threshold, the perception node is taken as the target node, so that the number of traversed connection sources is greatly reduced, and the entity data acquisition efficiency is improved.

[0055] Optionally, the target node is determined based on the observation ability satisfaction degree of the perception node, and the method comprises the following steps: In the case that the observation ability satisfaction degree of the perception node does not reach a preset threshold, the observation ability satisfaction degree of the next perception node is continuously calculated until the observation ability satisfaction degree of the perception node reaches a preset threshold, and the perception node is taken as the target node.

[0056] Specifically, in the case that the observation ability satisfaction degree of the perception node does not reach an expected target or does not meet a preset threshold, the calculation of the subsequent perception node is iteratively performed until the perception node meeting the expected target or the preset threshold is obtained, and the perception node is taken as the target node.

[0057] The embodiment of the present application calculates the observation ability satisfaction degree of the perception node by analyzing the data obtained by the perception node, automatically screens the node capable of data connection for the specific entity, improves the data connection efficiency and accuracy compared with the traditional manual selection of data source method, fully plays the advantages of various sensors in various perception nodes in terms of wide range of space coverage, high frequency of time response, high reliable information acquisition, and improves the pre-perception, accurate perception and controllable perception ability for digital twin entity.

[0058] Optionally, the first entity data of the geographic entity includes a perception object and a spatial positioning; The perception object is a bounding box corresponding to the geographic entity in the sensor data; The spatial positioning is a geographic spatial position of the perception object relative to the sensor.

[0059] Specifically, in terms of accurate mapping of perception data (i.e. first entity data) and digital twin entity, the perception data is mapped to the digital twin entity, mainly including detection of the perception object, spatial positioning of the perception object and mapping of the perception content.

[0060] The detection of the perception object refers to extracting key objects from the data obtained by the sensor of the perception node, for example, when the geographic entity to be observed is a building, the perception object can be all building bounding boxes detected and extracted in the range of view from the video data obtained by the ground camera; for another example, when the geographic entity to be observed is a moving car, the perception object can be all car infrared images detected and extracted in the range of view from the data obtained by the infrared perception device (such as infrared thermal imager).

[0061] The spatial positioning of the perception object refers to the geographic spatial position of the perception object, which is determined by the positioning system of the sensor of the perception node and the obtained data, for example, when the geographic entity to be observed is a building, the depth information of the target building is recovered from the multi-view images obtained by the ground camera, and the target building is accurately positioned in the space-time grid in combination with the pose of the ground camera.

[0062] The mapping of the perception content refers to mapping the perception data into the digital twin entity database, that is, mapping the data perceived by the sensor to the digital twin entity data, and updating the data of the digital twin entity.

[0063] The embodiment of the present application can accurately and timely update the positioning of the digital twin entity by establishing the mapping of the perception data and the geographic entity, and the perception object, positioning information and pose information obtained by the sensor of the perception node.

[0064] Optionally, after the second entity data of the digital twin entity corresponding to the geographic entity is updated based on the first entity data, the method further comprises: updating the digital twin entity based on the updated second entity data.

[0065] Specifically, after the second entity data of the digital twin entity corresponding to the geographic entity is updated based on the first entity data, the digital twin entity can also be updated synchronously, realizing dynamic updating of the multi-dimensional spatial correlation of the topology, orientation, distance of the geographic entity in the spatial domain, reflecting the changes of the real physical world. At the same time, by updating the digital twin entity, the multi-dimensional information (time, space, attribute, scale, multi-source heterogeneity, business field) describing the same geographic entity can be organically collected and correlated, enabling intelligent applications, and providing a reliable basis for important applications such as geographic entity data conflict management, correlated entity data intelligent pushing, and entity knowledge graph construction.

[0066] A digital twin entity-oriented data updating device provided by the present application is described below. The digital twin entity-oriented data updating device described below can be referred to in conjunction with the digital twin entity-oriented data updating method described above.

[0067] Based on any of the above embodiments, Figure 3 is a structural schematic diagram of a digital twin entity-oriented data updating device provided by the present application, as Figure 3 shown. The embodiment of the present application provides a digital twin entity-oriented data updating device, which comprises an acquisition module 301, a calculation module 302, a determination module 303, a mapping module 304 and an updating module 305, wherein: The acquisition module 301 is configured to acquire a geographic entity and a perception node. The calculation module 302 is configured to calculate an observation ability satisfaction degree of the perception node based on the geographic entity and the perception node. The determination module 303 is configured to determine a target node based on the observation ability satisfaction degree of the perception node. The mapping module 304 is configured to obtain first entity data of the geographic entity by establishing a mapping between the target node and the geographic entity based on the target node. The updating module 305 is configured to update second entity data of a digital twin entity corresponding to the geographic entity based on the first entity data.

[0068] The application provides a data updating device for a digital twin entity. The observation ability satisfaction degree of a perception node is calculated to determine a target node, the perception nodes with the observation ability of the geographic entity are screened and sorted, the data introduction efficiency for the geographic entity is improved, the mapping between the target node and the geographic entity is established to obtain first entity data of the geographic entity, efficient and controllable object-level data perception aggregation from the physical world perception node to the digital world is realized, the geographic entity data is comprehensively, accurately and timely acquired, the data perception for a specific entity greatly reduces the traversal number of the introduction source, the entity data acquisition efficiency is improved, the second entity data of the digital twin entity corresponding to the geographic entity is updated based on the first entity data, and the accurate and timely updating of the digital twin entity data is realized.

[0069] Figure 4 An entity structure diagram of an electronic device is shown as an example. Figure 4 As shown in the figure, the electronic device can include a processor 410, a communications interface 420, a memory 430 and a communications bus 440, wherein the processor 410, the communications interface 420 and the memory 430 complete mutual communication through the communications bus 440. The processor 410 can call the logical instructions in the memory 430 to execute the data updating method for a digital twin entity, and the method includes: Obtaining a geographic entity and a perception node; Based on the geographic entity and the perception node, the observation ability satisfaction degree of the perception node is calculated; Based on the observation ability satisfaction degree of the perception node, a target node is determined; Based on the target node, the mapping between the target node and the geographic entity is established to obtain the first entity data of the geographic entity; Based on the first entity data, the second entity data of the digital twin entity corresponding to the geographic entity is updated.

[0070] Further, the logic instructions in the memory 430 described above can be implemented in the form of software functional units and sold or used as independent products, and can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the parts that make contributions to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0071] In another aspect, the present application also provides a computer program product, which comprises a computer program, the computer program can be stored on a non-transitory computer readable storage medium, and the computer program can be executed by a processor to enable a computer to execute the data updating method for a digital twin entity provided by the above-mentioned methods, the method comprising: obtaining a geographic entity and a perception node; based on the geographic entity and the perception node, calculating an observation ability satisfaction degree of the perception node; based on the observation ability satisfaction degree of the perception node, determining a target node; based on the target node, obtaining first entity data of the geographic entity by establishing a mapping between the target node and the geographic entity; based on the first entity data, updating second entity data of a digital twin entity corresponding to the geographic entity.

[0072] In another aspect, the present application also provides a non-transitory computer readable storage medium, which stores a computer program, the computer program is executed by a processor to implement the data updating method for a digital twin entity provided by the above-mentioned methods, the method comprising: obtaining a geographic entity and a perception node; based on the geographic entity and the perception node, calculating an observation ability satisfaction degree of the perception node; based on the observation ability satisfaction degree of the perception node, determining a target node; based on the target node, obtaining first entity data of the geographic entity by establishing a mapping between the target node and the geographic entity; based on the first entity data, updating second entity data of a digital twin entity corresponding to the geographic entity.

[0073] The device embodiments described above are only illustrative, wherein the units described as separate components can or can not be physically separated, and the components displayed as units can or can not be physical units, i.e., can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0074] Through the description of the above embodiments, those skilled in the art can clearly understand that the embodiments can be realized by means of software and necessary universal hardware platforms, and of course can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of a software product, which can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in the embodiments or some parts of the embodiments.

[0075] It should be noted that in this document, the terms "comprising", "including", or any other variant thereof are intended to cover non-exclusive inclusions, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such a process, method, article or device. Without more limitations, the element defined by the statement "including a" does not exclude the presence of another identical element in the process, method, article or device including the element. In addition, it should be pointed out that the scope of the methods and devices in the embodiments of the present application is not limited to the order of performing the functions as shown or discussed, but can also include performing the functions in a substantially simultaneous manner or in reverse order according to the functions involved, for example, the described method can be performed in an order different from the described order, and various steps can also be added, omitted or combined. In addition, the features described with reference to some examples can be combined in other examples.

[0076] In addition, it should be noted that the terms "target", "first", "second", etc. in the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than those illustrated or described herein, and the objects distinguished by "first", "second" are usually a class, and do not limit the number of objects, for example, the first object can be one or more.

[0077] The "determining B based on A" in the embodiments of the present application means that A is considered as a factor when determining B. It is not limited to "B can be determined based on A only", but also includes "B is determined based on A and C", "B is determined based on A, C and E", "C is determined based on A, and B is further determined based on C", and the like. In addition, it can also include A as a condition for determining B, for example, "when A meets a first condition, B is determined using a first method"; for example, "when A meets a second condition, B is determined"; for example, "when A meets a third condition, B is determined based on a first parameter"; and the like. Of course, A can also be a condition for determining B as a factor, for example, "when A meets a first condition, C is determined using a first method, and B is further determined based on C"; and the like.

[0078] In the present application, the term "a plurality of" refers to two or more, and other quantifiers are similar.

[0079] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: it can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacement for part of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A data update method for digital twin entities, characterized in that: include: Get geographic entities and perception nodes; Calculating the observation capability satisfaction of the sensing node based on the geographic entity and the sensing node; Determining a target node based on the observation capability satisfaction of the sensing node; Based on the target node, obtaining first entity data of the geographic entity by establishing a mapping between the target node and the geographic entity; Based on the first entity data, the second entity data of the digital twin entity corresponding to the geographic entity is updated.

2. The data updating method for digital twin entities according to claim 1, characterized in that: The calculating, based on the geographical entity and the sensing node, the observation capability satisfaction of the sensing node includes: Calculating the subject matching degree between the geographic entity and the sensing node; and gridding the research area according to a preset scale to obtain the number of grids covered by the sensing node; Based on the number of grids covered by the sensing nodes, the grids covered by the sensing nodes are classified and counted to determine the number of grids at different sensor accuracies corresponding to different sensing nodes; and based on the sensor accuracies of the sensing nodes, a subject accuracy score of the sensing nodes is calculated; The observation capability satisfaction of the perception node is calculated based on the subject matching degree of the perception node, the number of grids under different sensor accuracies corresponding to different perception nodes, and the subject accuracy score of the perception node.

3. The data updating method for digital twin entities according to claim 1, characterized in that: The determining of the target node based on the observation capability satisfaction of the sensing node includes: When the observation capability satisfaction of the sensing node reaches a preset threshold, the sensing node is used as a target node.

4. The data updating method for digital twin entities according to claim 1, characterized in that: The determining of the target node based on the observation capability satisfaction of the sensing node includes: When the observation capability satisfaction of the sensing node does not reach the preset threshold, the observation capability satisfaction of the next sensing node is continuously calculated until the observation capability satisfaction of the sensing node reaches the preset threshold, and the sensing node is used as the target node.

5. The data updating method for digital twin entities according to claim 1, characterized in that: The first entity data of the geographic entity includes a perception object and a spatial location; The perception object is a bounding box corresponding to the geographic entity in the sensor data; The spatial positioning is the geographic spatial position of the sensing object relative to the sensor.

6. The data updating method for digital twin entities according to claim 1, characterized in that: After updating the second entity data of the digital twin entity corresponding to the geographic entity based on the first entity data, the method further includes: Based on the updated second entity data, the digital twin entity is updated.

7. A data updating device for digital twin entities, characterized in that: include: Acquisition module, used to acquire geographic entities and perception nodes; A calculation module, configured to calculate the observation capability satisfaction of the sensing node based on the geographic entity and the sensing node; A determination module, configured to determine a target node based on the observation capability satisfaction of the sensing node; A mapping module, configured to obtain first entity data of the geographic entity by establishing a mapping between the target node and the geographic entity based on the target node; An updating module is used to update the second entity data of the digital twin entity corresponding to the geographic entity based on the first entity data.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, it implements the data updating method for digital twin entities as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the data updating method for a digital twin entity as described in any one of claims 1 to 6 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the data updating method for a digital twin entity as described in any one of claims 1 to 6 is implemented.

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