CN115563680A

CN115563680A - Digital twin object processing method and system

Info

Publication number: CN115563680A
Application number: CN202211229157.2A
Authority: CN
Inventors: 黄晓婧; 马三立; 韩翼
Original assignee: Alibaba Cloud Computing Ltd
Current assignee: Alibaba Cloud Computing Ltd
Priority date: 2022-10-09
Filing date: 2022-10-09
Publication date: 2023-01-03

Abstract

The embodiment of the specification provides a digital twin object processing method and a system, wherein the digital twin object processing method comprises the following steps: determining object configuration data of a target physical object and a digital twin object template corresponding to the target physical object; determining an initial digital twin object corresponding to the target physical object based on the object configuration data and the digital twin object template; and determining a target digital twin object corresponding to the target physical object based on the current state data of the target physical object and the initial digital twin object. The generation efficiency of the target digital twin object is improved, so that the problem of low efficiency of constructing the digital twin object caused by spending a large amount of time on data processing is solved, and the digital twin object is quickly constructed for the target physical object.

Description

Digital twin object processing method and system

Technical Field

The embodiment of the specification relates to the technical field of computers, in particular to a digital twin object processing method and system.

Background

With the continuous development of computer technology, operations for constructing digital twin objects for physical entity objects are involved in many fields, for example, in a smart city scene, data twin technology is widely applied to constructing city digital twin objects due to the characteristic that the data twin technology can realize the construction of digital twin objects for physical entities in cities.

However, in practical applications, in the process of constructing a digital twin object for a physical entity object, since data of the physical entity is large and complex, and it takes a lot of time to perform data processing, the efficiency of constructing the digital twin object is low, and how to quickly construct the digital twin object for the physical entity object becomes an urgent problem to be solved.

Disclosure of Invention

In view of this, the embodiments of the present specification provide a digital twin object processing method. One or more embodiments of the present specification also relate to a digital twin object processing apparatus, a digital twin object processing system, a computing device, a computer-readable storage medium, and a computer program to solve technical drawbacks of the related art.

According to a first aspect of embodiments herein, there is provided a digital twin object processing method, including:

determining object configuration data of a target physical object and a digital twin object template corresponding to the target physical object;

determining an initial digital twin object corresponding to the target physical object based on the object configuration data and the digital twin object template;

and determining a target digital twin object corresponding to the target physical object based on the current state data of the target physical object and the initial digital twin object.

According to a second aspect of embodiments herein, there is provided a digital twin object processing apparatus including:

a determination module configured to determine object configuration data of a target physical object and a digital twin object template corresponding to the target physical object;

an initial object determination module configured to determine an initial digital twin object corresponding to the target physical object based on the object configuration data and the digital twin object template;

a target object determination module configured to determine a target digital twin object corresponding to the target physical object based on the current state data of the target physical object and the initial digital twin object.

According to a third aspect of embodiments herein, there is provided a digital twin object processing system comprising an object determination node, a data acquisition node, a data fusion node, and an object presentation node, wherein,

the object determination node is configured to determine object configuration data of a target physical object, determine a digital twin object template corresponding to the target physical object, and determine an initial digital twin object corresponding to the target physical object based on the object configuration data and the digital twin object template;

the data acquisition node is configured to acquire current state data of the target physical object;

the data fusion node is configured to determine a target digital twin object corresponding to the target physical object based on the current state data of the target physical object and the initial digital twin object;

the object display node is configured to render the target digital twin object to an object display page of a user terminal, and display the target digital twin object to a user through the object display page of the user terminal.

According to a fourth aspect of embodiments herein, there is provided a computing device comprising:

a memory and a processor;

the memory is configured to store computer-executable instructions and the processor is configured to execute the computer-executable instructions, which when executed by the processor, implement the steps of the above-described digital twin object processing method.

According to a fifth aspect of embodiments herein, there is provided a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the steps of the above-described digital twin object processing method.

According to a sixth aspect of embodiments herein, there is provided a computer program, wherein the computer program, when executed in a computer, causes the computer to perform the steps of the above-described digital twin object processing method.

An embodiment of the present specification provides a digital twin object processing method, including: determining object configuration data of a target physical object and a digital twin object template corresponding to the target physical object; determining an initial digital twin object corresponding to the target physical object based on the object configuration data and the digital twin object template; and determining a target digital twin object corresponding to the target physical object based on the current state data of the target physical object and the initial digital twin object.

Specifically, the method realizes that an initial digital twin object is generated quickly based on object configuration data of the target physical object through a digital twin object template corresponding to the target physical object, and then the generation efficiency of the target digital twin object is further improved through current state data of the target physical object and the initial digital twin object, so that the problem of low efficiency of constructing the digital twin object due to the fact that a large amount of time is spent on data processing is solved, and the digital twin object is quickly constructed for the target physical object.

Drawings

Fig. 1 is a schematic view of an application scenario of a digital twin object processing method provided in an embodiment of the present specification;

FIG. 2 is a flowchart illustrating a processing procedure of a digital twin object processing method according to an embodiment of the present disclosure;

fig. 3 is a schematic flow chart of a full link city digital twin scene in a digital twin object processing method provided in an embodiment of the present specification;

fig. 4 is a schematic flowchart of a global digital construction in a digital twin object processing method according to an embodiment of the present disclosure;

FIG. 5 is a schematic flow chart of multi-source data fusion in a digital twin object processing method according to an embodiment of the present disclosure;

fig. 6 is a schematic diagram of an application of a digital twinning system in a digital twinning object processing method according to an embodiment of the present disclosure;

fig. 7 is a schematic diagram of a digital twin system architecture in a digital twin object processing method according to an embodiment of the present disclosure;

fig. 8 is a schematic diagram of a data structure of a digital twin system architecture in a digital twin object processing method according to an embodiment of the present specification;

fig. 9 is a schematic diagram of a data flow of a digital twin system architecture in a digital twin object processing method according to an embodiment of the present disclosure;

FIG. 10 is a flowchart illustrating a processing procedure of a digital twin object processing method according to an embodiment of the present disclosure;

FIG. 11 is a block diagram illustrating a digital twin object processing system according to an embodiment of the present disclosure;

fig. 12 is a block diagram of a computing device according to an embodiment of the present disclosure.

Detailed Description

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present description. This description may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, as those skilled in the art will be able to make and use the present disclosure without departing from the spirit and scope of the present disclosure.

The terminology used in the description of the one or more embodiments is for the purpose of describing the particular embodiments only and is not intended to be limiting of the description of the one or more embodiments. As used in one or more embodiments of the present specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used in one or more embodiments of the present specification refers to and encompasses any and all possible combinations of one or more of the associated listed items.

It will be understood that, although the terms first, second, etc. may be used herein in one or more embodiments to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, a first can also be referred to as a second and, similarly, a second can also be referred to as a first without departing from the scope of one or more embodiments of the present description. The word "if," as used herein, may be interpreted as "at … …" or "at … …" or "in response to a determination," depending on the context.

First, the noun terms to which one or more embodiments of the present specification relate are explained.

Digital Twin (Digital Twin): also known as digital twins, is a digital map of the physical world.

Urban digital twinning: digital mapping for city universe, full life cycle.

Digital twin objects: a digitized mapping of each physical entity of a city.

Digital twin object modeling: the digital description information model of each physical entity of the city.

Digital twin object coding: the unique number of the digital twin object identifies the ID.

Constructing a digital twin space: and carrying out digital reduction on the objects in each cubic meter of space in the city.

Internet of Things (English: internet of Things, abbreviated IoT): the network is an information carrier such as the Internet, a traditional telecommunication network and the like, and all common objects capable of performing independent functions are interconnected and intercommunicated.

PaaS: is an abbreviation for Platform as a Service, which refers to Platform as a Service. A business model in which a server platform is provided as a Service, and a Service in which a program is provided via a network is referred to as SaaS (Software-as-a Service).

SaaS: the abbreviated name of Software-as-a-Service means Software as a Service, i.e., a Software Service provided through a network.

BIM: the Building Information model (Building Information Modeling, abbreviated as BIM) is a new tool in architecture, engineering and civil engineering.

And OSS: object Storage Service (OSS) is a cloud Storage Service with high volume, safety, low cost and high reliability.

A DAG: short for Database Availability Group, namely Database Availability Group.

OneID: the method is also called ID-Mapping, and maps various IDs to a uniform ID by combining information such as equipment ID, mobile phone number, identity card number, mailbox address, user name and the like with technologies and algorithms such as a label system, a knowledge graph, machine learning and the like.

RTK: the method is a difference method for processing carrier phase observed quantities of two measuring stations in Real time, and sends carrier phases acquired by a reference station to a user receiver for calculating difference and coordinates.

POS: high precision Position and Orientation Systems (POS).

DOM: refers to a Document Object Model (DOM).

DEM: the method refers to a Digital Elevation Model (Digital Elevation Model, abbreviated as DEM).

DLG: namely, a Digital Line Graphic (digitl Line Graphic), is a vector data set stored hierarchically on an existing topographic map of the underlying geographic elements.

LOD: i.e., levels of Detail, means multiple Levels of Detail. The LOD technology is used for determining resource allocation of object rendering according to the positions and the importance of the nodes of the object model in the display environment, reducing the number of faces and the detail of non-important objects and further obtaining high-efficiency rendering operation.

OGC: open Geospatial Consortium (Open Geospatial Consortium) network.

UE: the abbreviation of usereexperience, i.e., user experience, refers to the overall experience of a user when accessing a website or using a product.

Web: the World Wide Web, the global Wide area network, is also known as the World Wide Web.

CAD: refers to software that helps designers to perform design work by using a computer and its graphic devices.

A CIM platform: the method is a basic platform for building three-dimensional digital models of buildings, infrastructure and the like and expressing and managing urban three-dimensional space on the basis of urban basic geographic information.

RTK: real-time kinematic generally refers to a Real-time kinematic carrier-phase differential technique.

AOI: automated Optical Inspection, abbreviated AOI, generally refers to Automated Optical Inspection.

And GIS: the Geographic Information System, referred to as GIS for short, generally refers to a Geographic Information System.

The digital twin thought was originally named "information mirror model" and was evolved into the term "digital twin". The field of using Digital Twin technology was first proposed for the health maintenance and guarantee of aerospace vehicles. Firstly, a model of a real airplane is established in a digital space, and the model is completely synchronous with the real state of the airplane through a sensor, so that after each flight, whether maintenance is needed or not and whether the next task load can be borne or not is analyzed and evaluated in time according to the existing condition of the structure and past loads.

The digital twin technology was regarded as one of ten major emerging technologies in three consecutive years from 2017 to 2019, and some important strategic technical trend reports also mention that the novel technologies such as behavior internet and super automation all need the support realization of a digital twin system.

In order to promote the healthy development of digital economy, exploration and construction of a digital twin city are also incorporated into some plans of social development planning, and the construction of the digital twin city becomes an important development direction of a smart city; for example, in the field of hydraulic engineering, in order to improve defense capacity and defense standards, it is necessary to accelerate the construction of digital twin watersheds and digital twin projects, implement a forecast and early warning preview function, perfect a watershed flood control dispatching command system, strengthen unified planning, unified management, unified dispatching, unified management, and firmly keep on the flood and drought disaster defense safety baseline.

However, in urban digital twin construction, due to the lack of unified standards and unified planning, the current situations of 'strip block division, chimney standing, light cultivation reconstruction, strong and weak longitudinal and weak transverse and island perception' are formed, and unified digital twin construction guidelines and management specifications are not formed. The problems are embodied as follows:

1. the data value is low: data types and scales are increased explosively, spatial data are no longer single and static data, dimension increasing to high-performance massive space-time data processing capacity is urgently needed, heterogeneous data cause difficulty in smart city data analysis and data sharing, project relevance is lacked among massive data, data utilization efficiency is low, and data value cannot be fully utilized. Especially when the cross-system information fusion modeling analysis is carried out on the digital twin city, the difference of the data format standards greatly increases the cost of data processing time and cost.

2. Replication costs between different projects are high: different equipment standards are different, equipment access development cost is high, time is long, structured data and unstructured data lack integration online management, link automation, standards can be continued, quality can be traced, and with the increase of smart city application and equipment quantity, newly-added application needs to be customized and developed for multiple times according to different standards, so that replication cost among different projects is increased.

3. The industrial chain is difficult to combine: the smart city industry chain is numerous, and the access agreement between the different producers, data model are numerous and seal respectively, and the industry chain is inside from the system of forming for cooperation difficulty between each main part of industry chain, equipment linkage and maintenance degree of difficulty are big, and the service compatibility is poor, seriously influences user experience.

4. Conceptually, there are false areas: most of the 'digital twins' in the market are mutually split according to collection, calculation and visualization, common misunderstandings can enable the 'digital twins' to be equal to large-screen and three-dimensional visualization, and only can be displayed and can not participate in calculation.

Based on the problems, the specification provides several digital twin schemes, the first scheme is to build small-scale digital twin scenes in industrial manufacturing industry, such as physical factories, buildings or industrial plants, but the scheme can only support the small-scale scenes and cannot realize urban digital twin. The second scheme is to provide an industrial twin platform, which has wide positioning, supply chain, manufacturing, building, city, etc., and has a large number of cases and solutions for building direction, and is also small-scale, only supported by the capability of the twin object modeling part, and the product is PaaS layer service under IOT, so that the whole positioning is also an industrial twin.

The third scheme is to provide a digital twin platform aiming at visual rendering, the BIM modeling and the visual rendering of the platform are stronger, the core capability of the product is only at the visual rendering level, and the capability of constructing a digital twin object is lacked. The fourth scheme is to provide a facility digitization platform based on cloud computing, and the platform can be comprehensively provided by combining the bottom platform of a virtual engine and the video card pooling capability of the cloud computing through a map, but the core advantage of the scheme is still at the rendering side, and the digital twin full link construction capability is insufficient.

Based on this, in the present specification, a digital twin object processing method is provided, and the present specification relates to a digital twin object processing apparatus, a digital twin object processing system, a computing device, and a computer-readable storage medium, which are described in detail one by one in the following embodiments.

Referring to fig. 1, fig. 1 is a schematic diagram illustrating an application scenario of a digital twin object processing method according to an embodiment of the present disclosure, where a target building may be understood as a target physical object, building configuration data may be understood as object configuration data, human access data may be understood as current state data, an initial digital twin object of the target building may be understood as an initial digital twin object of the target physical object, and a target digital twin object of the target building may be understood as a target digital twin object of the target physical object.

Based on this, in the application of the digital twin object processing method provided by the present specification to construct a digital twin object scene for a target building, firstly, a server obtains building configuration data of the target building, which is acquired by data acquisition equipment, and generates an initial digital twin object of the target building through a digital twin object template corresponding to the target building and the building configuration information; then, monitoring personnel access data of the target building through data acquisition equipment, and fusing the personnel access data with an initial digital twin object of the target building to obtain a target digital twin object corresponding to the target building; and the target digital twin object of the target building can be rendered into a user terminal for showing to a user.

The digital twin object processing method provided by the specification forms a method for quickly constructing an urban digital twin scene in the process of constructing a systematic digital twin system, and the scheme can quickly construct urban digital twins through a process of constructing the urban digital twin scene through a full link.

Referring to fig. 2, fig. 2 is a flowchart illustrating a digital twin object processing method according to an embodiment of the present disclosure, which specifically includes the following steps:

step 202: determining object configuration data of a target physical object and a digital twin object template corresponding to the target physical object.

The target physical object may be understood as a physical entity object that needs to construct a digital twin object, for example, a building in a city, a physical entity such as a water network, a road network (traffic facility) in the city, or a physical entity such as a forest land, a river, or the like.

The object configuration data may be understood as data characterizing the composition of the target physical object, for example, images of traffic facilities in a city acquired by a satellite, point cloud data of a city road network acquired by a radar, and the like.

The digital twin object template can be understood as a digital twin data structure corresponding to the target physical object, in practical application, physical entities in a city can be abstracted to form a set of standard entity model definitions, a unified space unit is used as a basic unit for city data exchange, sharing and fusion, and the entity model definitions can be the digital twin object templates.

In an embodiment provided in this specification, the determining object configuration data of the target physical object includes:

determining a type of the target physical object;

determining object configuration data of the target physical object from object configuration data of at least two types of initial physical objects acquired in advance based on the type of the target physical object, and determining a digital twin object template corresponding to the target physical object from digital twin object templates of at least two types of initial physical objects configured in advance.

The digital twin object processing method provided by the specification can be applied to digital twin of a city in a city digital twin scene, and based on the digital twin object processing method, the at least two types of initial physical objects can be understood as various physical entities constructing the whole city, such as buildings, forest lands, road networks, water networks, power grids and the like in the city. And the target physical object can be any type of physical object in the at least two types of initial physical objects, on the basis, the digital twin of the at least two types of initial physical objects is completed in a mode of constructing the digital twin object on the target physical object, so that target digital twin objects corresponding to the at least two types of initial physical objects are obtained, and then the at least two target digital twin objects are fused, so that the digital twin object of the whole city can be obtained, and the city digital twin is realized.

Based on this, the digital twin object processing method provided in this specification can determine object configuration data of at least two types of initial physical objects, determine a type of a target physical object that needs to be subjected to digital twin, and then determine a physical configuration parameter corresponding to the target physical object from object configuration parameters based on the type of the target physical object.

For example, the target physical object is a road network, and the digital twin object processing method provided in the present specification can select a physical entity that needs to be subjected to digital twin (where performing digital twin can be understood as performing an operation of constructing a digital twin object) from physical entities such as buildings, forest lands, road networks, water networks, and power grids in the entire city as a road network, and can determine data corresponding to the road network from city data (a city high definition map, city point cloud data, and the like) of the entire city based on a physical entity type (road network type) of the road network.

In an embodiment provided in this specification, before determining the object configuration data of the target physical object, the method further includes:

acquiring to-be-processed configuration data of the at least two types of initial physical objects, wherein the to-be-processed configuration data is obtained by performing data acquisition processing on the at least two types of initial physical objects by configuration data acquisition equipment;

and performing data preprocessing on the configuration data to be processed to obtain object configuration data of the at least two types of initial physical objects.

The configuration data to be processed can be understood as data which needs to be preprocessed, and the configuration data acquisition equipment can be a satellite, a vehicle-mounted radar, a sensor and the like.

The data preprocessing includes, but is not limited to, image mosaic (error correction and splicing), integrity detection, encryption, coordinate error correction, fusion and other processing on the configuration data to be processed, and the processing is not specifically limited in this specification and can be set according to an actual application scenario.

Specifically, the digital twin object processing method provided in this specification can acquire data of at least two types of initial physical objects through the configuration data acquisition device, so as to obtain to-be-processed configuration data of the at least two types of initial physical objects, and then send the to-be-processed configuration data to a server to which the digital twin object processing method is applied, where the server performs data preprocessing on the to-be-processed configuration data through a predefined data preprocessing manner, so as to obtain object configuration data of the at least two types of initial physical objects.

For example, the digital twin object processing method provided by the present specification can access full sensing data to be a server, where the full sensing data includes spatial data such as static high-precision maps, satellite images, and urban white membranes, and data such as dynamic videos, radars, coils, and heights; after data access comes in, the server side uniformly performs standardized processing, storage and warehousing and quality monitoring; the instructions for configuring the data for the object are guaranteed, and high-quality data are available subsequently.

In an embodiment provided in this specification, the determining, from digital twin object templates of at least two types of initial physical objects configured in advance, a digital twin object template corresponding to the target physical object is specifically:

firstly, determining digital twin object templates corresponding to at least two types of initial physical objects which are configured in advance, and after determining the type of the target physical object; and determining a digital twin object template corresponding to the target physical object from the pre-configured digital twin object templates of the at least two types of initial physical objects based on the type of the target physical object.

In the digital twin object processing method provided in this specification, the operation of determining the initial digital twin object corresponding to the target physical object based on the digital twin object template may be understood as a process of performing entity modeling on the target physical object, and in the process of performing entity modeling on one physical entity, the model may include multiple types.

According to the above example, the digital twin object processing method provided by the present specification can select a physical entity that needs to be subjected to digital twin as a road network from physical entities such as buildings, forest lands, road networks, water networks, and power grids in an entire city, and determine an entity model definition corresponding to the road network from entity model definitions corresponding to city data (city high definition maps, city point cloud data, and the like) of the entire city based on a physical entity type (road network type) of the road network, thereby implementing subsequent rapid construction of a digital twin object based on the digital twin object template.

Step 204: and determining an initial digital twin object corresponding to the target physical object based on the object configuration data and the digital twin object template.

In practical applications, the object configuration data may be understood as static data of the target physical object, which is used to represent the structure, position, etc. of the target physical object, and the initial digital twin object obtained by performing digital twin through the object configuration data may be understood as a static digital twin model of the target physical object;

further, in an embodiment provided in this specification, the determining an initial digital twin object corresponding to the target physical object based on the object configuration data and the digital twin object template includes:

determining an object generation algorithm corresponding to the digital twin object template, and processing the object configuration data by using the object generation algorithm to obtain digital twin data corresponding to the object configuration data;

and filling the digital twin data into the digital twin object template to obtain an initial digital twin object corresponding to the target physical object.

Wherein the object generation algorithm may be understood as an algorithm for modeling the target physical object based on the object configuration algorithm. In practical application, the object processing method provided by the specification provides a low-code programmable platform in the twin object generation process, for different physical entities, due to the variety of source data, different types of data need to be abstracted into operators, and through the arrangement capacity of DAG, the development of an algorithm is flexible and open, and through the capacity of the platform, the algorithm and the entity model definition are bound and issued to be an entity generation algorithm.

The digital twinning data may be understood as a model obtained by solid modelling based on the object configuration data, for example the digital twinning data may be a road surface, vegetation surface, building surface, road markings, city parts, etc.

Specifically, in the digital twin object processing method provided by the present specification, in the process of determining an initial digital twin object, an object generation algorithm corresponding to the digital twin object template needs to be determined, and the object configuration data is input to the object generation algorithm for modeling processing, so as to obtain digital twin data corresponding to the object configuration data;

and then based on a data storage rule corresponding to the digital twin object template, filling the digital twin data into the digital twin object template to obtain an initial digital twin object corresponding to the target physical object.

In addition, in practical application, after the object generation is completed, the quality inspection module performs inspection on the accuracy, integrity and uniqueness of data of each object, and provides corresponding intersection coverage in space and the like for topology inspection. The object passing the quality inspection can be issued, the change of the object needs to be managed in the whole life cycle of the object, an object generating algorithm can be operated for many times under one entity, the result of each calculation is firstly put into a temporary table, and finally, the object which is finally effective can be taken into effect under the condition of meeting the requirements of service and quality, and the finally effective object provides service to the outside and can be seen to other service systems.

In an embodiment provided in this specification, the number of the object generation algorithms is at least two, and the object configuration data is of at least two types;

correspondingly, the processing the object configuration data by using the object generation algorithm to obtain the digital twin data corresponding to the object configuration data includes:

determining a data type of at least two types of object configuration data, and determining an object generation algorithm associated with the at least two types of object configuration data from at least two object generation algorithms based on the data type;

and inputting the at least two types of object configuration data into an associated object generation algorithm to obtain digital twin data corresponding to the at least two types of object configuration data.

In practical applications, the digital twin object processing method provided in this specification may use a large amount of structured and unstructured data in the twin construction process, including or not limited to: 1. grid type data: including but not limited to tif, grib2, png, etc. grid-type data. 2. Vector type data: including but not limited to shp, gdb, dwg, fly, etc. vector-type data. 3. Three-dimensional type of data: including but not limited to rvt, 3ds, osgb, etc. 4. The rest of the data also contains static csv data, such as standing book data of facility equipment, IOT real-time data and the like. And, can store the unstructured data through OSS, and through the data engine, carry on the unified expression with the unstructured data structuredly, through the unified data access, form the data of three big data types: the method has the advantages that various operators can be realized on the storage types, and the purpose of data fusion unified calculation is realized.

And the solid modeling comprises project modeling, geometric modeling, mechanism modeling and space semantic modeling, and the initial digital twin object corresponding to the target physical object is formed by the solid model constructed by the solid modeling.

1. Item modeling is the description of attributes of an entity, typically expressed using conventional data types, like strings, integers, floats, timestamps, etc.

2. Geometric modeling is two-dimensional and three-dimensional expression facing to an entity, generally, a point, a line, a plane, a body (Geometry), a grid (Raster) and a triangular surface (Mesh), one entity can have various geometric expressions, and the geometric expressions depend on the observation mode of the entity, for example, at a height of thousands of meters, a road seen by people is a line, at a height of hundreds of meters, the road seen by people is a plane, when the gradient of the road needs to be acted, the road is changed into a three-dimensional body from a two-dimensional surface, and the abstraction degree and the expression mode depend on which information needs to be extracted to participate in calculation.

3. Mechanistic modeling is a mathematical expression that expresses the physical characteristics of the entity, such as the dynamic model of the car, the coefficient of friction of the road, etc.

4. The method comprises the following steps of space semantic modeling, wherein the space semantic expresses the relation among objects, particularly the space relation, the space relation is divided into a distance relation and a topological relation, the distance relation is one of the most common space relations, generally, the Euclidean distance is adopted, and the topological relation does not change along with the change of the distance and the angle. For example, the relationship between adjacent polygons and common arcs, and the edge-to-edge connection relationship in a geometric network, the topology relationship with practical significance includes: intersect, meet, equal, separate, contain, cover, covered, overlap, etc.

It should be noted that the method for quickly constructing an urban digital twin scene provided by the digital twin object processing method mainly includes full link processes such as global digital construction, intelligent fusion perception, multi-source data fusion, twin unified service, space-time data visualization and the like, and referring to fig. 3, fig. 3 is a schematic flow diagram of the full link construction of the urban digital twin scene in the digital twin object processing method provided by an embodiment of the present specification. Referring to fig. 3, a specific flow of the urban digital twinning technology, a type of a basic platform supporting implementation of the urban digital twinning technology, a scene of the urban digital twinning technology and corresponding industry products, and a service that can be implemented based on the urban digital twinning technology are shown in fig. 3. The specific process of the urban digital twin technology comprises the steps of global digital construction, intelligent fusion perception, multi-source data fusion, twin unified service, space-time data visualization and the like; the global digital construction comprises the steps of twin object modeling, unified identification coding, twin object generation (the twin objects comprise road network, building, water network, land parcel and the like), two-three-dimensional space construction and the like, so that a static digital twin object is constructed; the intelligent fusion perception means: abstracting physical entities in cities to form a set of standard entity model definition, taking a unified space unit as a basic unit for city data exchange, sharing and fusion, simultaneously, constructing a unified code as a unique identity card of the space unit, mapping the corresponding relation between each cubic meter digital space and an entity space in the cities, fusing data with different levels, dimensions and granularities by using a unit-code-attribute, carrying out omnibearing and full-period digital description on the cities from space-time dimensions, and finally realizing editing at one place, wherein four types of scenes (perception, calculation, display and simulation) take effect synchronously, thereby ensuring the data consistency of various project domains, improving the data accuracy and realizing intelligent fusion perception by functions of point cloud basic setting monitoring, basic visual perception, millimeter wave radar perception, data processing, perception fusion technology and the like, and further acquiring the dynamic data of the physical entities in the cities (comprising road networks, buildings, water networks, land blocks and the like). The multi-source data fusion is realized in a dynamic and static fusion mode, namely, dynamic data and static twin objects are fused, so that twin data models (including water conservancy, traffic, government affairs, regulation and the like) are obtained, and in the dynamic fusion process, a specific twin intelligent algorithm is required to be based, wherein the specific twin intelligent algorithm includes but is not limited to flow prediction, track reduction, diffusion early warning, source tracing and the like. The twin unified service is a service adopted for realizing the urban digital twin, and includes, but is not limited to, a structured RESTFul (internet software architecture) service, a real-time WebSocket (protocol for full duplex communication), a spatial OGC service, a three-dimensional S3M (spatial three-dimensional model data format) service, a three-dimensional 3DTiles (three-dimensional spatial data standard) service, and the like. After the digital twin object is constructed, the digital twin object can be rendered through a space-time data visualization step, and the rendering is realized in a three-dimensional model generation mode, a three-dimensional data mounting mode, a low code building mode, a WEB/UE rendering mode and the like. The project scenes of the urban digital twin technology comprise traffic research and judgment, intelligent signal control, vehicle-road cooperation, intelligent sea navigation, one-network management, one-network communication and the like, and industrial products provided based on the urban digital twin technology comprise a traffic cloud control platform, a water conservancy and limousic platform, a transportation supervision platform, a space management CIM platform, government affair intelligent service, urban intelligent operation and the like. The basic platform types supporting the realization of the urban digital twin technology comprise an acquisition platform, a scheduling platform, a research and development platform, a monitoring platform, an alarm platform, a calculation and storage platform information release platform and the like. In addition, services which can be realized based on the urban digital twin technology include but are not limited to simulation deduction analysis and cloud-side cooperative computing, the simulation deduction analysis includes functions of traffic simulation, natural resource simulation, automatic driving simulation and the like, and the cloud-side cooperative computing includes functions of multilayer interconnection, data compilation, node scheduling and the like.

Referring to fig. 4, fig. 4 is a schematic flowchart of a global digital construction in a digital twin object processing method according to an embodiment of the present disclosure; the process comprises data acquisition, raw data processing, standard achievement data and object generation.

Firstly, configuring devices such as hyperspectral sensors and infrared sensors on carriers such as spaceborne carriers and airborne carriers; the vehicle-mounted, vehicle-mounted and man-carried vehicles and the fixed points are provided with devices such as hyperspectral, panchromatic and infrared sensors, and the like, and the devices such as monocular/monocular optical sensors, laser radars and the like are carried in the vehicle-mounted, vehicle-mounted and man-carried modes; by arranging RTK, total station and other equipment on the fixed point. Then, data such as images (satellite), images (aerial photograph), images (ground acquisition), images (oblique photography), POS data, ground control points, laser point cloud, and the like of the city are acquired through the equipment. The device can be understood as a configuration data acquisition device, and the data can be understood as object configuration data.

The data acquired by the configuration data acquisition equipment is subjected to an original data processing flow, so that the data is subjected to image mosaic (correction and splicing), space-time-space-three encryption, three-dimensional reconstruction, coordinate correction and fusion and the like. Thereby obtaining standard outcome data: DOM, DEM, live-action three-dimensional data, point cloud (image), point cloud (lidar), DLG, planning CAD (which is a physically corresponding planning CAD drawing drawn by CAD software), BIM data.

In the process of selecting digital twinning of different physical entities according to different application scenes, the physical entities in a city need to be abstracted to form a set of standard entity model definitions (schema); for example, physical entities such as urban traffic, natural resources, watershed water networks and the like are selected to construct twins (i.e., digital twins). Further, for example, in the process of constructing a city traffic twin, an entity contained in the city traffic needs to be determined, and the entity needs to be abstracted to obtain entity model definitions (digital twin object templates) corresponding to the entity, where each entity model definition corresponds to a plurality of model data, for example, the city traffic entity corresponds to model data of a road network type, including roads, information points, lanes, stations, intersections, and traffic areas, because each digital twin object needs to be supported by a plurality of data models; model data of facility types including traffic markings, traffic signs, drive test facilities; model data of the type of equipment, including signal lights, monitoring systems, lighting systems, etc.

Based on the method, in the process of generating the object, an object generating algorithm corresponding to each entity is determined, and standard result data are processed through the algorithm to obtain data required by generating the digital twin object; specifically, the scheme can perform target recognition and extraction and terrain classification on the remote sensing image, and finally perform object extraction on the extracted target and the extracted terrain classification so as to obtain data required by generating a digital twin object on vegetation surfaces, building surfaces and the like, or perform target recognition and extraction, real-scene three-dimensional singleization and the like on point cloud data, and perform urban road marking extraction and vectorization on a processing result so as to obtain data required by generating the digital twin object on road surfaces, building surfaces, road markings, urban parts and the like.

Finally, in order to facilitate the query of the constructed digital twin objects, corresponding codes are generated for each digital twin object, multiple industry standards are fused for entity code management, a system covering macroscopic microcosmic, indoor and outdoor and overground and underground is formed, industry classification expressions which are easy to change and differ are weakened, the industry classification expressions are included into attributes, and the encoding and classification are not carried out. The mapping relation established by the industry standard realizes the accurate identification and the quick construction of the city elements through the digital identification of the universe object, thereby providing the standardized management of the codes.

The unified coding locks the space unit change rule and the start and end of the full life cycle through the mode of management codes, space codes and time codes; the coding hierarchy needs to follow principles of uniqueness, hierarchy, scalability, applicability, and ease of use. Wherein, the management code: and uniformly classifying and recording the space entities or the concept entities according to the characteristics of the space entities or the concept entities by referring to the classification standard specified by the national standard. Space code: and performing two-dimensional grid coding and three-dimensional elevation coding based on the spatial characteristics of the spatial entity. Time code: and carrying out time coding based on the life cycle characteristics of the space entity or the concept entity. Specifically, in an embodiment provided in this specification, after determining, based on the object configuration data and the digital twin object template, an initial digital twin object corresponding to the target physical object, the method further includes:

determining a corresponding digital twin object code for the initial digital twin object based on a code generation rule;

correspondingly, after determining the target digital twin object corresponding to the target physical object based on the current state data of the target physical object and the initial digital twin object, the method further includes:

receiving an object acquisition request sent by an object acquisition end, wherein the object acquisition request carries a digital twin object code of a digital twin object to be acquired, and the digital twin object code of the initial digital twin object is the same as that of the corresponding target digital twin object;

and determining a digital twin object to be acquired from the target digital twin object based on the digital twin object coding, and returning the digital twin object to be acquired to the object acquisition end.

The digital twin object coding may be understood as a uniform coding determined for the initial digital twin object.

The object obtaining end may be a user terminal corresponding to the user, and based on this, the object obtaining request may be understood as a request sent by the user to obtain the specific target digital twin object. Or, the object obtaining end may be another server end, and based on this, the object obtaining request may be understood as a request for the other server end to invoke the specific target digital twin object.

Further, the determining a corresponding digital twin object code for the initial digital twin object based on a preset coding rule includes:

determining the space parameters of the initial digital twin object, and coding the space parameters to obtain the space coding of the initial digital twin object;

determining a time parameter of the initial digital twin object, and coding the time parameter to obtain a time code of the initial digital twin object;

determining an object type parameter of the initial digital twin object, and coding the object type parameter to obtain an object management code of the initial digital twin object;

determining the spatial encoding, temporal encoding, and/or object management encoding as a digital twin object encoding of the initial digital twin object.

The spatial parameter may be understood as spatial information of the target physical object corresponding to the initial digital twin object, for example, the above-mentioned spatial semantic model; the time parameter may be understood as a creation time of a target physical object corresponding to the initial digital twin object, and the like. The object type parameter may be understood as a parameter characterizing the type of the target physical object to which the initial digital twin object corresponds.

Specifically, the digital twin object processing method provided by the present specification obtains a spatial code of an initial digital twin object by determining a spatial parameter of the initial digital twin object and performing a coding process on the spatial parameter; determining a time parameter of the initial digital twin object, and coding the time parameter to obtain a time code of the initial digital twin object; determining an object type parameter of the initial digital twin object, and coding the object type parameter to obtain an object management code of the initial digital twin object; and then, determining the space code, the time code and/or the object management code as the digital twin object code of the initial digital twin object, and uniformly storing the digital twin object, so that the target digital twin object can be conveniently inquired based on the digital twin object code.

Step 206: and determining a target digital twin object corresponding to the target physical object based on the current state data of the target physical object and the initial digital twin object.

Specifically, after the initial digital twin object is determined, the server can determine current state data of the target physical object, and generate a target digital twin object corresponding to the target physical object based on the current state data and the initial digital twin object.

Specifically, the determining a target digital twin object corresponding to the target physical object based on the current state data of the target physical object and the initial digital twin object provided by the present specification includes:

monitoring the current state of the target physical object based on state data acquisition equipment to acquire the current state data of the target physical object;

and updating and/or newly adding digital twin data corresponding to the initial digital twin object based on the current state data to obtain a target digital twin object corresponding to the target physical object.

And acquiring the current state of the target physical object by state data acquisition equipment. The process can be understood as intelligent combined perception in the process of constructing the urban digital twin scene by the full link, wherein the intelligent combined perception refers to all-weather, full-coverage, full-factor and low-delay multi-mode fusion perception restoration, and high-performance perception equipment and a high-performance algorithm are needed; by a model compression cutting technology and a smart fusion strategy, the algorithm time delay is less than 100ms, the decimeter-level sensing error is realized, and the target fusion reduction rate is about 97%. And the implementation of the intelligent joint perception requires four conditions of higher resolution, longer distance, higher computational power and more complex algorithm. Among these, higher resolution: the camera, the millimeter wave radar and the laser radar can improve the respective resolution through hardware, software or software and hardware, and even derive a new form like a 4D millimeter wave radar. The farther distance: for the camera, a multi-view camera can be adopted, wherein a low-pixel camera looks at a near position, and a high-pixel camera looks at a far position; for the millimeter wave radar, because the resolution depends on the number of channels, a cascaded antenna design can be adopted, wherein the number of channels at the near part is relatively small, and the number of channels at the far part is relatively large; similarly, for the laser radar, the near channel number (line number) is relatively less, and the far channel number is relatively more, so that the approximate consistency of the resolution of the whole road section is realized. Greater computational effort: the longer distance inevitably brings new problems such as recognition problem of small target objects, occlusion problem, stability problem caused by equipment shake, which needs more intensive calculation power and algorithm to solve. The single-task equipment (such as speed measuring equipment) is difficult to meet the required all-weather, full-coverage and full-factor perception, so that detection devices are often installed at some intersections and road sections to realize (but not limited to) traffic object violation snapshot, traffic parameter monitoring, traffic event discovery, traffic environment and road factor perception, and digital twin and vehicle-road cooperative attention to traffic object position/track restoration, traffic environment and road factor perception. More complex algorithms: on the one hand, the perception tasks as described above are more diverse, and on the other hand, even for the same perception task, the algorithm used is more complex to achieve more stable and accurate perception. For example, the algorithm needs to be able to accommodate straight roads, curves, flat roads, undulating roads, large objects, small objects, good weather, inclement weather, low or stationary objects, high speed moving objects, and the like.

Based on the above, in the digital twin object processing method provided in this specification, when there is a problem that identification of a small target object is unclear, a problem of occlusion, a problem of stability caused by device jitter, and the like in an image, a greater computational effort and a more complex algorithm are required to process image data, so as to ensure data quality, specifically, the obtaining device based on state data monitors a current state of the target physical object to obtain current state data of the target physical object, and the method includes:

monitoring the current state of the target physical object based on state data acquisition equipment to obtain initial current state data of the target physical object;

judging whether the initial current state data meets a preset data condition or not,

if yes, the initial current state data is used as the current state data of the target physical object,

if not, adjusting the initial current state data through a data processing algorithm, and taking the adjusted initial current state data as the current state data of the target physical object.

Along with the above example, the status data acquisition device may be a camera, a radar, or the like; based on the above, in the process of collecting the current driving vehicle data of the urban traffic through the camera and the radar, the collected data has an unclear problem due to the problems of weather, equipment inclination and the like, so that the current driving vehicle data collected by the equipment needs to be analyzed, and when the current driving vehicle data is determined to have no problem, the current driving vehicle data is directly put into a warehouse for processing; when the data of the current running vehicle is determined to have the problems, the collected data needs to be subjected to processing such as error correction, adjustment, accurate identification and the like by adopting an algorithm, so that the data of the current running vehicle with high quality is obtained.

In the digital twin object processing method provided in this specification, after determining current state data of a target physical object, object simulation data corresponding to the initial digital twin object is also updated and/or newly added based on the current state data, so as to obtain a target digital twin object corresponding to the target physical object. In the digital twin object processing method provided by the present specification, after determining the current state data of the target physical object, the digital twin data corresponding to the initial digital twin object is updated and/or newly added based on the current state data, so as to obtain the target digital twin object corresponding to the target physical object. And this operation can be understood as multi-source data fusion in the process of constructing the urban digital twin scene in full link, referring to fig. 5, fig. 5 is a schematic flow diagram of multi-source data fusion in the digital twin object processing method provided by an embodiment of this specification. The multi-source data refers to digital twin objects corresponding to city entities in the process of urban digital twin, for example, see objects such as high buildings, houses, road networks, vegetation, water sources, terrains, and the like in fig. 5. The multi-source data fusion is to solve the problems of consistency and reusability of dynamic and static data in the process of urban digital twinning, change the traditional mode of organizing Spatio-temporal data by layers, establish digital body mapping of twin entity objects, draw through the full life cycle and full element data of the twin entity objects, enable the dynamic and static data to freely flow and perform fusion calculation in an index calculation domain, a simulation deduction domain (simulation domain), a display domain (three-dimensional rendering domain for example) and a perception domain (automatic driving domain for example), realize visual calculation integration of twin data, perform four-domain fusion, and establish a Spatio-temporal data structure (Spatio temporal data fabric) of a city, namely the urban digital twinning.

The data source types of the urban digital twin can be divided into project data, space two-dimensional data and space three-dimensional data, and the detail layer and the special data layer are respectively subjected to model design by adopting ideas such as normal modeling, dimension modeling, KV (Key-value, stored data) modeling and the like.

Based on a project-driven data model architecture design concept, on the basis of a unified platform, a loosely-coupled and elastically-opened industry data model system is constructed by taking a project as a guide, so that the system is built for multiple times, capacity precipitation and reuse in different service scenes are realized, and standardized, componentized and specialized data services are provided for upper-layer application. The industrial data modeling mainly covers information of a subject domain, a hierarchy, an application field, an affiliated environment, a release range, a storage type and the like of the physical table. Taking a traffic industry data model as an example: the detail layer is divided into entity basic information, object relation, traffic control, traffic incident, positioning information, traffic operation, financial information, maintenance, space information and the like; the summary layer theme comprises a situation center, a trip center, a control center, a vehicle center, a user center, an equipment center, a network center, an event center, a charging center, city experience, an ecological environment, a space portrait, an enterprise portrait and the like; and processing the application layer data according to the application corresponding to the product line, and classifying according to the application theme.

A set of standard, telescopic and widely applicable data model perception system and automated data processing flow of multi-source data fusion are constructed in an urban digital twin system, and by taking a traffic scene as an example, data fusion analysis is carried out on basic road network topology channelized information, equipment facility data (portal/bayonet/video, coil, microwave and other data), toll record data, vehicle satellite positioning data, alarm receiving data, meteorological data and other data and internet data, so that on one hand, data layer fusion is realized to repair single data source data loss, incompleteness and the like, and the purpose of expanding data resources to the maximum extent is realized; and on the other hand, the data characteristics are processed to obtain a corrected traffic characteristic expression with more robustness. And finally, the integrated, uniformly expressed and high-quality traffic parameter service is provided for the application. All indexes of the platform can provide services to the outside in a data interface mode, and digital ecology can be built quickly.

Index fusion needs to be carried out on the basis of unified twin object construction data standards, an index system required by service development research and judgment is constructed, and then space-time data index fusion is carried out. The road network basic traffic parameters can be completed according to various data, including speed, flow, track and some index parameters. The basic index algorithm has certain requirements on input data, when the input data do not meet the requirements, the algorithm can automatically degrade, and index output can be stopped under the limit condition.

The data quality management system has the advantages that the quality such as data timeliness and data correctness can be subjected to standardized definition in the aspects of prevention and control of problems in advance, problem solving in the process, depth optimization in the process of data acquisition (production), processing and use, the monitoring, verifiability and verifiability of the data quality are guaranteed to be managed, a long-acting, stable and safe data quality management system is built, the data quality is controlled, and the data operation value is improved.

In an embodiment provided by this specification, after obtaining the target digital twin object, the target digital twin object may be presented to the user in a manner of spatiotemporal data visualization, and specifically, after determining the target digital twin object corresponding to the target physical object based on the current state data of the target physical object and the initial digital twin object, the method further includes:

and in response to an object rendering request sent by a user, rendering the target digital twin object to an object display page of a user terminal, and displaying the target digital twin object to the user through the object display page of the user terminal.

For example, the target digital twin object is a digital twin object of urban traffic; based on this, after the digital twin object of the urban traffic is generated, after the object rendering request sent by the user is received, the digital twin object of the urban traffic can be determined, the digital twin object of the urban traffic is rendered to the object display page of the user terminal, and the digital twin object of the urban traffic is displayed to the user through the digital twin object of the urban traffic of the user terminal.

It should be noted that, a user may send an object rendering request to the server through an object display page of the user terminal; and the server side renders the digital twin object of the urban traffic to an object display page of the user terminal. In some scenarios, the terminal device of the object rendering request is different from the user terminal. For example, in an urban traffic monitoring scene, the user may send an object rendering request to the server through the terminal device; in order to enable people in a city to feel the traffic condition in real time, the server renders the digital twin object of the city traffic to devices such as a subway display screen and a mall display screen, and under the condition, the device sending the object rendering request is inconsistent with the device of the digital twin object of the rendered city traffic.

The process of rendering the target digital reduction object (namely the target digital twin object) can be understood as the visualization of space-time data in the process of constructing the urban digital twin scene by a full link; the space-time data visualization adopts a real-time rendering engine to perform dynamic and static combined real-time three-dimensional rendering on a digital twin model, and combines various three-dimensional model data (including but not limited to GLTF, OBJ, FBX, BIM, oblique photography, satellite images and DEM) to perform environment and natural environment restoration. The three-dimensional scene supports the LOD display capability, three-dimensional model simulation is carried out on three-dimensional rivers, mountain bodies, buildings, streets, automobiles, ground basic equipment, underground pipe networks and the like, the real environment scene of a city is really restored, the application of 3D scenes and multiple visual angles is realized, the application of the 3D scenes of different angles of customers is solved, and management is carried out by creating different scenes. For example, a twin full-factor of a city of 8000 kilometers squared is generated in one minute, and the overall stability and CPU (central processing unit)/GPU (graphics processing unit) utilization are reduced by 10X times. In the process of realizing visualization, a twin visualization engine of a super-large city is adopted: the GIS and game engine characteristics are integrated, and the real environment simulation and space analysis capabilities are achieved; the method comprises the steps of fast loading, and supporting real-time rendering from a scene of a super-large city to a component; multi-end multi-engine seamless switching can be realized only by once construction; in addition, the specification provides a graphical application building mode, a user can realize application development in a graphical dragging mode, the twin application development threshold of the user is reduced, and the application maintenance efficiency is improved; the space simulation algorithm carries out real-time dynamic accurate mapping and restores the details of the algorithm.

In addition, twin unified service is also included in the flow of constructing the urban digital twin scene through the full link, which means that the urban digital twin unified service supports conventional structured offline and real-time data services, and also provides two-dimensional and three-dimensional spatial data service and a map engine core module, so that source data or processed spatial data are transmitted to users in a low-delay and accurate manner as required according to a sharing principle of 'comprehensive, efficient and overall', more application consumption data are facilitated, and the value of the data is realized. Various organizations are cooperatively controlled, support is provided for intelligent operation, cross-level, cross-department, cross-industry and cross-region information instant sharing is realized, high reliability and low delay are achieved, and closed loop from production to use to evaluation of data is completed. Among other things, spatial data services provide the following data service capabilities. 1. Supporting the registration and management of file type vector data. 2. And registration and management of the Raster file data are supported. 3. And the registration and management of three-dimensional data are supported. 4. And release of the OGC standard map service is supported. 5. Unified proxy supporting the GIS service of the mainstream business software.

The spatial data service provides a data servitization capacity in the process of building a platform in the spatial data for a user, and provides convenient data query transfer service, service management and service operation and maintenance capacity which covers the unified experience of each processing stage for a data developer; the data asset manager is oriented to provide statistical analysis, service usage statistical analysis and hot data statistical analysis capabilities of services, effective landing of data application in the second half of data center platform construction is achieved, and efficient development of data intelligent application is supported.

The digital twin object processing method provided by the present specification is explained by the above embodiments, and in practical applications, the complete digital twin system is composed of a general infrastructure, a twin data base, an intelligent application support, and best practices. Fig. 6 is a schematic diagram of an application of a digital twin system in a digital twin object processing method according to an embodiment of the present disclosure, and refer to fig. 6, where the digital twin system is a twin construction step in fig. 6, and specifically includes steps of data access, entity modeling, object generation, space construction, index fusion, quality monitoring, and the like.

The basic capability dependency in fig. 6 is a basic capability that a twin of city data depends on, and specifically, the basic capability dependency mainly includes PaaS (universal platform as) and IaaS infrastructure, where the infrastructure is an environmental protection and provides capability supports such as intelligent perception, space-time storage, and mass computation for the construction of a twin system; the intelligent sensing system comprises facilities such as a public transportation cloud, a special transportation cloud and a transportation all-in-one machine, and road side sensing equipment, communication infrastructure equipment, an intelligent edge terminal, control infrastructure, a mobile terminal intelligent sensing terminal and the like. The PaaS (universal platform) comprises facilities for supporting digital twins, such as a flying base, an agile base, a light-weight base and the like. The PaaS core capability layer: by means of a digital twin base and based on the general capability of a data center platform, dynamic and static factors of a city are subjected to two-three-dimensional integrated coding, multi-source heterogeneous data are accurately and efficiently fused, a knowledge map among various factors is generated, quick retrieval of various city information, events, subjects and associations is realized, a computable digital city is constructed, and a stable spatial basis is provided for traffic index calculation, simulation analysis, twin rendering and the like; the system provides the capabilities of space-time data source aggregation, entity modeling, space construction, object generation, index fusion, service release, quality monitoring and the like, and realizes integrated traffic basic data access, management, fusion and analysis calculation. The PaaS layer organically combines a machine learning algorithm and an urban system model; the data resources are fully utilized to restore the full-time and full-place information of the city, an industry knowledge engineering and map technology base is constructed, and the industrial digital process is assisted by the industrial data model standardization to the precipitation of industry knowledge.

In addition, it should be noted that the intelligent sensing layer including the facilities such as the roadside sensing device, the communication infrastructure device, the intelligent edge terminal, the control infrastructure device, the mobile end intelligent sensing terminal and the like reduces the operation and maintenance and upgrading costs of the digital city system in a large scale and practically reduces the threshold of digital transformation by a method of integrating the terminal intelligent device, the edge acquisition computing unit and software and hardware. Geographic entity data (including basic geographic space data, two-dimensional basic road network data, high-precision data and environmental element related data) are gathered based on unified data standard specifications, and internet of things perception data (including IOT (Internet of things) equipment data, video AI (artificial intelligence) analysis data, road disease inspection data and vehicle and road cooperative related data) and internal and external related system data (including enterprise internal data, external related department traffic data, meteorological environment data, internet trip related data and the like) are collected in real time.

In addition, the infrastructure platform adopts a cloud native architecture, is based on self-developed distributed technology and products, and a set of system supports all cloud products and services, provides complete cloud platform openness capability, has perfect enterprise-level service characteristics, perfect disaster tolerance and backup capability, has complete autonomous controllable capability, provides full-stack safety support, and ensures the reliability and continuity of the cloud platform.

The core capability sediment comprises an intelligent engine SssS, a universal service function of the sediment can be extracted from a scene, a standardized intelligent engine is provided for services by means of a digital reduction base and an intelligent algorithm capability, and the digital intelligent engine comprises a simulation analysis engine, an intelligent optimization engine, a green travel engine, a safety service engine, a twin rendering engine, an intelligent scheduling engine, a planning decision engine, a temperature-sensitive video analysis engine and the like. The intelligent algorithm is applied to communicate the industry requirements with twin data, application is realized, and the project is quickly hatched; the final result is the value embodiment of the construction of the digitalization-informatization-intellectualization-twinning ability, and rich services are provided for the fields of urban management, economic development, civil service and the like. It should be noted that, the SaaS industry engine layer: and by utilizing technologies such as cloud computing, big data, artificial intelligence and the like, a safe, smooth, commanding and service platform cloud base is uniformly constructed. Ecological aggregation, namely, the cloud base is utilized to realize safety control, efficient command, fine treatment and convenience for people to service and manage the core actual combat value; the method has the advantages that the method realizes accurate perception, accurate analysis, fine management and control and elaborate service of highway management and control, and obviously improves the management and control efficiency and travel safety of the highway; accurate perception, accurate analysis, fine management and control and elaborate service of urban comprehensive traffic supervision are achieved, and the supervision efficiency and the service quality of urban comprehensive traffic are remarkably improved. Combining ecological upstream and downstream partners, constructing a rich and prosperous solution system around three-layer digital requirements of city capital construction, treatment and service, and supporting government and enterprise user parties to realize comprehensive digital management and upgrading of cities.

In addition, the core capability sediment further comprises a data base DaaS, namely a digital twin base in fig. 6, the data base provides project-scene twin data base construction capability, and helps ISVs (Independent Software developers) to quickly implement data access, management, scene construction, data fusion and service release, specifically, the digital twin base is core production data, and cross-domain data fusion is implemented by establishing a large data processing closed loop of unified expression, twin construction, project modeling and unified service; including asset centers with twin asset valuation, unified service management, twin asset management, and the above-described function of building urban digital twins, twin build in fig. 6. The city digital twin platform is a complex comprehensive technology platform for supporting the construction of a novel smart city, is a key support for continuous innovation of city intelligent operation, is evolution and upgrade of the novel smart city, and is a city future foundation base for symbiotic coexistence and virtuality and reality convergence of the virtuality and reality cities. The urban digital twin platform is based on a cloud native spatio-temporal data technology stack, a structured and unstructured data online integrated management system is constructed, and the full stack capability of a new generation twin data base of a set of data + tools + models + algorithms is formed.

Best practice construction: the method is characterized in that on the basis of industrial standard product capability, ISV capability is integrated/relied, an end-to-end complete product solution is provided, and the solution includes but is not limited to applications in aspects of intelligent transportation, natural resources and the like, wherein products provided in intelligent transportation scenes include but are not limited to transportation management and control, high-speed operation management and control, public travel transportation supervision and the like. The traffic control product comprises traffic analysis and judgment, control optimization, situation perception, unified signal control, congestion analysis, timing optimization, organization optimization, integrated command, situation directing, attendance, intelligent induction, special duty guarantee and the like. The high-speed operation management and control product comprises intelligent high speed, traffic situation, cooperative control, analysis and study, facility maintenance, vehicle and road cooperation, a digital parallel world, travel service, emergency safety, operation management and control and the like, and the public travel product comprises an intelligent hub, traffic operation, hub passenger flow monitoring, comprehensive passenger flow analysis, hub evacuation scheduling, public transport network study and study, green travel, bus track connection study and study, integrated travel, green travel supervision and the like. The Transportation supervision products comprise hazardous chemical Transportation supervision, TOCC (traffic operation monitoring and dispatching Center), highway maintenance, commercial vehicle supervision, regional traffic comprehensive management and the like; other products include digital terminals, digital plateaus, urban parking, high-speed auditing, intelligent channels, intelligent ports, etc.

Based on the foregoing fig. 6, it can be seen that the digital twin object processing method provided in this specification is applied in an actual scene and an infrastructure situation supporting implementation thereof, and reference may be made to fig. 7 for a structure of a digital twin object processing system, where fig. 7 is a schematic diagram of a digital twin system architecture in the digital twin object processing method provided in an embodiment of this specification; as can be seen from fig. 7, the digital twin object processing system provided in the present description is implemented by means of cloud primitive, and the system includes basic modules such as a computing engine, a unified data chassis, source data, and a data space engine, and processes the device collected at the device side through the basic modules and provides the other modules to construct the urban digital twin object.

In the process of constructing the urban digital twin, the system can acquire data provided by a basic module based on a data access module, complete construction of the urban digital twin through modules such as data processing, data modeling, a data execution engine, system operation and maintenance, twin object construction, a space construction platform and the like, and simulate based on the urban digital twin through the urban simulation platform. In addition, the system also comprises a metadata center, data asset management, unified service, packaging/instantiation and other modules for managing the urban digital twin. Finally, the system provides services to users through clients based on various types of industry applications and city simulation platform applications in the use stage. For example, the industry applications include, but are not limited to, applications in transportation, residential, water pollution tracing, rain and sewage network health analysis, waterlogging traffic impact analysis, and the like. The urban simulation platform application comprises but is not limited to applications in traffic, water systems, multi-mode simulation scenes and the like. It should be noted that the system also manages the edge end and the device end through the cloud control end.

Based on the architecture diagram of the digital twin object processing system, fig. 8 shows a data architecture diagram corresponding to the digital twin object processing system, and referring to fig. 8, fig. 8 is a schematic diagram of a data structure of a digital twin system architecture in a digital twin object processing method according to an embodiment of the present disclosure. Specifically, the data architecture of the digital twin object processing system comprises a global digital construction part and a project application part.

The global digital construction comprises three parts, namely data access, an industry model and global digital assets; the data access means that data required for constructing city data twins are acquired from a device side, and the data comprises project data, two-dimensional data and three-dimensional data, wherein the project data comprises but is not limited to traffic facility data, engineering construction data, environment monitoring data, traffic flow data, meteorological data, economic data, population data, enterprise data, land data and the like. The two-dimensional data includes, but is not limited to, road networks, river channels, public transportation networks, enterprise industry, sewage treatment plants, two-dimensional pipelines, remote sensing images, resource investigation, planning management, and the like. Three-dimensional data includes, but is not limited to, digital elevation, BIM models, pipeline corridors, laser point clouds, fine mode data, white mode data, oblique photography, CAD data, and the like.

Then, the data is processed by a normalization process and a model is constructed. The standardization processing comprises data standardization conversion, space calibration, twin object management, data unified coding and the like. Wherein, the data standardization conversion includes but is not limited to format conversion, coordinate system conversion, quality detection, repair processing, etc.; the spatial calibration comprises but is not limited to image pixel geographic coordinate calibration, inclined space geometric adjustment, three-dimensional model spatial position calibration, BIM spatial coordinatization and the like; twin object management includes, but is not limited to, spatial object definition, object relationship construction, logical model design, data standard definition, etc.; the unified data coding includes, but is not limited to, road network coding, water network coding, land block coding, pipeline coding, building coding, bus route coding, etc.

The industry model part is an application of a city data twin model constructed according to different scenes, wherein the scenes comprise traffic scenes and natural resource scenes, and the data structure comprises a detail layer, a thematic layer and an application layer in the application of the traffic scenes by taking the traffic scenes as an example; the detail layer comprises basic information, object relation, traffic control, traffic events, positioning information, traffic operation and other data of the city data twin model; the basic information includes but is not limited to unified road network, vehicles, traffic participants, transportation facilities, etc.; the object relationship includes but is not limited to intersection relationship, road section relationship, equipment intersection relationship, vehicle-road relationship, etc.; the traffic control includes but is not limited to signal control, disable control, current limit control, etc.; the traffic events include, but are not limited to, alarm receiving events, construction events, internet events, weather events, and the like. The positioning information includes, but is not limited to, personnel positioning, vehicle positioning, ship positioning, equipment positioning, and the like, and the traffic operation includes, but is not limited to, road condition information, equipment speed, vehicle passing data, trajectory data, and the like.

The data of the detail layer can be processed by a reduction algorithm to obtain a thematic data set included in the thematic layer, and the reduction algorithm comprises a diffusion algorithm (aiming at traffic flow and pollutants), a track path reduction algorithm (aiming at vehicles, people and pollutants), a traceability algorithm (aiming at traffic flow and pollutants), a high-precision flow reduction and prediction algorithm, a high-precision road condition reduction and prediction algorithm and the like. The thematic layer comprises a situation center, a trip center, a control center, a vehicle center, an event center, an equipment center and other thematic data sets; the situation center comprises data such as traffic efficiency, delay indexes, queuing length, congestion duration and the like; the travel center comprises but is not limited to data such as traffic statistics, traffic prediction, OD (traffic volume) travel, passenger flow analysis and the like; the control center comprises but is not limited to signal optimization, green wave recommendation, tide lane, variable lane and other data; the vehicle center includes but is not limited to data such as vehicle representation travel purpose, vehicle track and the like; the event center comprises but is not limited to data such as congestion mining, congestion events, security events, illegal events and the like; the equipment center includes but is not limited to equipment statistics, equipment status, equipment blindness, equipment monitoring, etc. The application layer refers to application services provided in the application process of the urban data twin model, and the application services include but are not limited to traffic guidance, signal optimization, situation perception, public transportation optimization, event perception, transportation supervision, digital apron, safety prevention and control, inspection fee evasion, key vehicles and the like.

Taking a natural resource scene as an example, in the application of the natural resource scene, the data structure comprises a detail layer, a topic layer and an application layer; the detail layer comprises basic information of a natural resource digital twin model, project information, spatial information, object relationship, events and other data, wherein the basic information comprises but is not limited to participants, natural resources, buildings (structures) and management units; project information includes, but is not limited to, development, construction, protection, management, transactions; object relationships include, but are not limited to, river reach relationships, spatial relationships, component relationships, plot relationships; events include, but are not limited to, disaster events, regulatory events, violation events; spatial information includes, but is not limited to, vectors, coordinate systems, grid grids.

The thematic layer comprises thematic data sets such as management examination and approval, ecological environment, urban physical examination, enterprise portrait, natural resources, space portrait and the like, wherein the management examination and approval comprises data such as state, quantity, tense, evaluation and the like; the ecological environment includes but is not limited to climate, AOI, weather, quality, etc. data; urban physical examination comprises but is not limited to data such as ecological livable life, convenient traffic, physiognomic characteristics, safety and toughness; enterprise representations include, but are not limited to, emissions, land, credit, financial, etc. data; natural resources include, but are not limited to, tense, density, quantity, weight; spatial representations include, but are not limited to, development intensity, density, contact intensity, terrain. The application layer comprises application services of city physical examination, job and residence analysis, one yard of management areas, intelligent site selection, space management, benefit evaluation, land identification, asset evaluation, space planning, BIM examination and the like.

The universal digital assets comprise three aspects of data assets, unified services and twin object construction, wherein the data assets comprise but are not limited to asset cataloging, asset retrieval, asset authority, asset access, security policy and full link consanguinity; unified services include, but are not limited to, data reporting services, spatial service distribution, data service distribution, service flow control, service monitoring, and service authentication; twin object construction includes, but is not limited to, twin object construction, spatial semantic retrieval, spatial object management, spatial association analysis, object relationship management, object attribute management.

In addition, in the global digital construction China, two three-dimensional rendering engines and a data governance tool are further provided, wherein the two three-dimensional rendering engines comprise two-dimensional map rendering, three-dimensional scene rendering, physical entity rendering and index rendering; the data governance tool is provided with a solution tool comprising product version packaging, version management and solution instantiation; the quality tool comprises quality rule design, quality plan management, quality report and quality monitoring alarm; the data modeling tool comprises data standard management, physical table design and model relation management; the data exploration tool comprises a physical table exploration tool and a spatial data exploration tool; the data synchronization tool comprises unstructured data access, vectors, structured data access, a database and raster message middleware.

The project application part can be understood as application provided for users based on constructed urban digital twin, the application mainly comprises traffic, main construction, water pollution source tracing, rain pollution pipe network health analysis, waterlogging traffic influence analysis and the like, wherein the residential construction application comprises aspects of idle low-efficiency land comprehensive treatment, urban physical examination, cim digital construction evaluation, house full life cycle and the like, and the traffic application comprises aspects of signal optimization control, traffic situation analysis, traffic simulation pre-research, holographic intersection reduction and the like; the water pollution tracing comprises aspects of pollutant propagation space-time distribution analysis, propagation path calculation, water quality parameter inversion and the like, the rain and sewage pipe network health analysis application comprises aspects of universe liquid level, flow and water quality analysis, waterlogging point position identification, waterlogging space-time analysis and the like, and the waterlogging traffic influence analysis application comprises aspects of meteorological influence analysis, waterlogging traffic simulation, pipe network water flow simulation and the like.

Based on the above fig. 8, it can be known that the digital twin object processing method provided in the present specification is applied to an actual scene and a data structure of a digital twin object processing system; for the data flow of the digital twin object processing system, reference may be made to fig. 9, where fig. 9 is a schematic diagram of a data flow of a digital twin system architecture in a digital twin object processing method provided in an embodiment of the present specification; as can be seen from FIG. 9, the data stream includes three parts of file storage, database, and front-end rendering. The data stream corresponding to the file storage comprises spatial data and project data, wherein the spatial data comprises raster data, vector data, two-dimensional data, three-dimensional data and the like. The project data includes offline data as well as real-time data. After the data received by file storage is stored in the database, a twin object construction process is carried out based on the data in the database, the construction of urban digital twin objects is realized through the steps of data access, object management and the like included in twin object construction, and index fusion is carried out on the digital twin objects and project data; meanwhile, the constructed digital twin object can be sent to a front end (client) for rendering through a rendering service.

According to the twin object processing method provided by the specification, the target configuration data based on the target physical object is quickly generated into the initial digital twin object through the digital twin object template corresponding to the target physical object, and then the generation efficiency of the target digital twin object is further improved through the current state data of the target physical object and the initial digital twin object, so that the problem that the efficiency of constructing the digital twin object is low due to the fact that a large amount of time is spent on data processing is solved, and the digital twin object is quickly constructed for the target physical object.

The following description further explains the digital twin object processing method provided in this specification with reference to fig. 10 by taking an application of the digital twin object processing method in constructing an urban traffic twin scene as an example. Fig. 10 shows a processing flow chart of a digital twin object processing method provided in an embodiment of the present specification, and specifically includes the following steps.

Step 1002: based on the conditions of physical entities such as roads, traffic lights, ground and the like of cities of various regions, a set of standard entity data templates (namely entity model definition) are defined by a server; and generating an algorithm for one or more objects corresponding to each entity data template.

Wherein each physical entity corresponds to a digital twin object.

Step 1004: and receiving a digital twin construction request aiming at the urban traffic of the city A, and selecting an entity data template corresponding to the urban traffic of the city A from the pre-defined entity data templates based on the digital twin construction request.

The urban traffic has a plurality of corresponding entity data templates, and each entity data template corresponds to one type of traffic facilities (such as roads, traffic lights, bus stops and the like). The digital twin construction request is a request sent by a user through a terminal device.

Step 1006: and acquiring data of traffic entity facilities such as roads, traffic lights, bus stops and the like of the city A.

Specifically, according to the scheme, equipment such as a sensor, a radar or a camera is configured on a vehicle such as a satellite vehicle and an airborne vehicle, data acquisition is carried out on traffic entity facilities such as roads, traffic lights and bus stops of the city A, and facility data of the urban traffic facilities are obtained, wherein the facility data comprise space data such as static high-precision maps, satellite images and urban white films, and data such as dynamic videos, radars, coils and heights; after data are accessed, standardized processing, storage and quality monitoring are uniformly carried out; subsequent data is guaranteed to be available.

Step 1008: and carrying out data preprocessing such as format unification, integrity detection and the like on the traffic facility data to obtain standardized traffic facility data.

Step 1010: based on the facility type of the transportation facility data, a corresponding entity data template is determined for the transportation facility data.

Step 1012: and inputting the traffic facility data into an object generation algorithm corresponding to each entity, and performing entity modeling to obtain a digital twin object corresponding to the entity.

The entity modeling comprises project modeling, geometric modeling, mechanism modeling and space semantic modeling; a plurality of data models corresponding to the transportation facilities can be obtained through solid modeling.

For example, the image data of the road entity is input into the algorithm model for modeling, so as to obtain the road surface data module corresponding to the road entity. One physical entity has multiple types of entity data (such as images and point cloud data), so that after the entity is modeled, the physical entity corresponds to multiple data models; digital twinning of a physical entity is achieved through multiple data models.

Based on the operation, the whole road network model can be constructed, and the spatial attributes of the road network are enriched; the method comprises the steps of editing a high-precision road network, mounting intersection equipment, three-dimensional modeling and the like.

Step 1014: and uniformly coding each object through a predefined uniform coding rule to obtain a management code, a space code and a time code of each digital twin object, wherein the management code, the space code and the time code are used for inquiring the digital twin objects.

Step 1016: and constructing urban traffic twins of the city A based on the digital twins corresponding to the entities.

Step 1018: dynamic traffic data of urban traffic of the city A is collected in real time through equipment such as a camera and a sensor.

The dynamic traffic data may be traffic flow, pedestrian number, etc.

Step 1020: and determining the dynamic traffic data and the corresponding digital twin object, and performing fusion calculation on the dynamic traffic data and the digital twin object through an intelligent algorithm to obtain the digital twin object of the urban traffic.

Specifically, fusion analysis of multi-source indexes is performed based on a road network model with spatial attributes, and various dynamic data are fused on the basis of a road segment entity ONEID to realize analysis of various traffic indexes, such as congestion rate.

In addition, analysis and simulation of a road network can be performed based on the collected data, wherein the analysis and simulation comprises vehicle track reduction, vehicle-road coordination, variable lane analysis and optimization and the like. And the user can realize real signal optimization and vehicle-road cooperation by issuing the service and the command and controlling the access side and the terminal, thereby forming a closed loop from data perception to fusion calculation to analysis simulation to control optimization.

Step 1022: and carrying out visualization processing on the urban traffic twin and the simulation result, and displaying the result to a user through a terminal.

The urban traffic twin can be understood as a digital twin object of urban traffic.

Step 1024: dynamic traffic data of the traffic entity facility is monitored in real time and urban traffic twins are updated based on the data.

Compared with a scheme focusing on visual rendering and a scheme focusing on construction of a digital twin object knowledge map in the industrial manufacturing field, the method for constructing the urban digital twin scene through the full link provided by the description can be used for quickly establishing digital body mapping of twin entity objects, achieving pull-through of full-life-cycle and full-element data of the twin entity objects, enabling dynamic and static data to freely flow and be fused and calculated in an index calculation domain, a simulation deduction domain, a three-dimensional rendering domain and an automatic driving domain, and achieving vision calculation integration and four-domain fusion of the twin data.

The method for constructing the urban digital twin scene through the full link is a set of data intelligent generation assembly line integrating data acquisition, urban digital twin object generation, twin scene construction, multi-source data fusion calculation, twin unified service and three-dimensional space-time data rendering, can quickly construct the urban digital twin scene, and supports the construction of the digital twin scene of a super-large-scale city; the method comprises the steps of urban digital twin data acquisition, twin object generation, spatial scene construction, multi-source fusion index calculation, two-three-dimensional rendering integration and full link construction.

Based on the core capability, a set of intelligent production line for quickly constructing city space-time digital twins is formed, and unified entity definition, unified space-time coding, unified twins construction and unified service support are realized. The urban twin object digital generation-space editing-three-dimensional-visual secondary development closed-loop output is realized, and a full-flow one-stop platform for data access, editing, index calling, three-dimensional model generation and visual development is provided for partners; the ecological cooperative partners construct urban digital twin application based on the platform, so that the richness and expression precision of twin elements are greatly improved, and the efficiency of application research and development is improved by 50%.

Corresponding to the above method embodiment, the present specification further provides a digital twin object processing system embodiment, and fig. 11 shows a schematic structural diagram of a digital twin object processing system provided in an embodiment of the present specification. As shown in fig. 11, the system includes an object determination node 1102, a data acquisition node 1104, a data fusion node 1106, and an object exposure node 1108, wherein,

the object determining node 1102 is configured to determine object configuration data of a target physical object, determine a digital twin object template corresponding to the target physical object, and determine an initial digital twin object corresponding to the target physical object based on the object configuration data and the digital twin object template;

the data acquisition node 1104 is configured to acquire current state data of the target physical object;

the data fusion node 1106 is configured to determine a target digital twin object corresponding to the target physical object based on the current state data of the target physical object and the initial digital twin object;

the object presentation node 1108 is configured to render the target digital twin object to an object presentation page of a user terminal, and present the target digital twin object to a user through the object presentation page of the user terminal.

Wherein, the plurality of nodes included in the digital twin object processing system can be understood as a plurality of servers, which can be cloud servers or physical servers,

the object determination node 1102 can implement the step of constructing the global domain number, the data acquisition node 1104 can implement the step of intelligently fusing and sensing, the data fusion node 1106 can implement the step of fusing the multi-source data, and the object display node 1108 can implement the step of visualizing the spatio-temporal data.

It should be noted that, for the explanation of the digital twin object processing system, reference may be made to corresponding or corresponding contents in the above digital twin object processing method, which is not described in detail herein.

The digital twin object processing system provided by the present specification implements, through a digital twin object template corresponding to a target physical object, rapid generation of an initial digital twin object based on object configuration data of the target physical object, and then further improves generation efficiency of the target digital twin object through current state data of the target physical object and the initial digital twin object, thereby avoiding a problem of low efficiency of constructing the digital twin object due to data processing that takes a lot of time, and rapidly constructing the digital twin object for the target physical object.

The above is a schematic scheme of a digital twin object processing system of the present embodiment. It should be noted that the technical solution of the digital twin object processing system and the technical solution of the digital twin object processing method belong to the same concept, and details of the technical solution of the digital twin object processing system that are not described in detail can be referred to the description of the technical solution of the digital twin object processing method.

Corresponding to the above method embodiments, the present specification also provides digital twin object processing apparatus embodiments, the apparatus comprising:

Optionally, the determining module is further configured to:

determining the type of the target physical object;

and determining object configuration data of the target physical object from object configuration data of at least two types of initial physical objects acquired in advance based on the type of the target physical object, and determining a digital twin object template corresponding to the target physical object from digital twin object templates of at least two types of initial physical objects configured in advance.

Optionally, the digital twin object processing apparatus further includes a data acquisition module configured to:

Optionally, the initial object determination module is further configured to:

Optionally, the number of the object generation algorithms is at least two, and the object configuration data is of at least two types;

accordingly, the initial object determination module is further configured to:

Optionally, the digital twin object processing apparatus further comprises an encoding module configured to:

Optionally, the encoding module is further configured to:

determining a time parameter of the initial digital twin object, and performing coding processing on the time parameter to obtain a time code of the initial digital twin object;

Optionally, the target object determination module is further configured to:

and updating and/or newly adding the digital twin data corresponding to the initial digital twin object based on the current state data to obtain a target digital twin object corresponding to the target physical object.

Optionally, the target object determination module is further configured to:

monitoring the current state of the target physical object based on state data acquisition equipment to acquire initial current state data of the target physical object;

if so, taking the initial current state data as the current state data of the target physical object,

Optionally, the digital twin object processing apparatus further comprises a rendering module configured to:

According to the digital twin object processing device provided by the specification, the target configuration data based on the target physical object is quickly generated into the initial digital twin object through the digital twin object template corresponding to the target physical object, and then the generation efficiency of the target digital twin object is further improved through the current state data of the target physical object and the initial digital twin object, so that the problem that the efficiency of constructing the digital twin object is low due to the fact that a large amount of time is spent on data processing is solved, and the digital twin object is quickly constructed for the target physical object.

The above is a schematic scheme of a digital twin object processing apparatus of the present embodiment. It should be noted that the technical solution of the digital twin object processing apparatus and the technical solution of the digital twin object processing method belong to the same concept, and details of the technical solution of the digital twin object processing apparatus, which are not described in detail, can be referred to the description of the technical solution of the digital twin object processing method.

FIG. 12 illustrates a block diagram of a computing device 1200, according to one embodiment of the present description. The components of the computing device 1200 include, but are not limited to, memory 1210 and processor 1220. Processor 1220 is coupled to memory 1210 via bus 1230, and database 1250 is used to store data.

The computing device 1200 also includes an access device 1240, the access device 1240 enabling the computing device 1200 to communicate via one or more networks 1260. Examples of such networks include the Public Switched Telephone Network (PSTN), a Local Area Network (LAN), a Wide Area Network (WAN), a Personal Area Network (PAN), or a combination of communication networks such as the internet. The access device 1240 may include one or more of any type of network interface, e.g., a Network Interface Card (NIC), wired or wireless, such as an IEEE802.11 Wireless Local Area Network (WLAN) wireless interface, a worldwide interoperability for microwave access (Wi-MAX) interface, an ethernet interface, a Universal Serial Bus (USB) interface, a cellular network interface, a bluetooth interface, a Near Field Communication (NFC) interface, and so forth.

In one embodiment of the present description, the above-described components of computing device 1200 and other components not shown in FIG. 12 may also be connected to each other, such as by a bus. It should be understood that the block diagram of the computing device architecture shown in FIG. 12 is for purposes of example only and is not limiting as to the scope of the description. Those skilled in the art may add or replace other components as desired.

Computing device 1200 may be any type of stationary or mobile computing device, including a mobile computer or mobile computing device (e.g., tablet, personal digital assistant, laptop, notebook, netbook, etc.), mobile phone (e.g., smartphone), wearable computing device (e.g., smartwatch, smartglasses, etc.), or other type of mobile device, or a stationary computing device such as a desktop computer or PC. Computing device 1200 may also be a mobile or stationary server.

Wherein the processor 1220 is configured to execute computer-executable instructions that, when executed by the processor, implement the steps of the digital twin object processing method described above.

The above is an illustrative scheme of a computing device of the present embodiment. It should be noted that the technical solution of the computing device and the technical solution of the above digital twin object processing method belong to the same concept, and details that are not described in detail in the technical solution of the computing device can be referred to the description of the technical solution of the above digital twin object processing method.

An embodiment of the present specification also provides a computer-readable storage medium storing computer-executable instructions which, when executed by a processor, implement the steps of the above-mentioned digital twin object processing method.

The above is an illustrative scheme of a computer-readable storage medium of the present embodiment. It should be noted that the technical solution of the storage medium and the technical solution of the above digital twin object processing method belong to the same concept, and details that are not described in detail in the technical solution of the storage medium can be referred to the description of the technical solution of the above digital twin object processing method.

An embodiment of the present specification further provides a computer program, wherein when the computer program is executed in a computer, the computer program is used for executing the steps of the digital twin object processing method.

The above is an illustrative scheme of a computer program of the present embodiment. It should be noted that the technical solution of the computer program is the same as the technical solution of the above digital twin object processing method, and details that are not described in detail in the technical solution of the computer program can be referred to the description of the technical solution of the above digital twin object processing method.

The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims can be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

The computer instructions comprise computer program code which may be in the form of source code, object code, an executable file or some intermediate form, or the like. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, usb disk, removable hard disk, magnetic disk, optical disk, computer Memory, read-Only Memory (ROM), random Access Memory (RAM), electrical carrier wave signals, telecommunications signals, software distribution medium, and the like. It should be noted that the computer readable medium may contain content that is subject to appropriate increase or decrease as required by legislation and patent practice in jurisdictions, for example, in some jurisdictions, computer readable media does not include electrical carrier signals and telecommunications signals as is required by legislation and patent practice.

It should be noted that, for the sake of simplicity, the foregoing method embodiments are described as a series of acts, but those skilled in the art should understand that the present embodiment is not limited by the described acts, because some steps may be performed in other sequences or simultaneously according to the present embodiment. Further, those skilled in the art should also appreciate that the embodiments described in this specification are preferred embodiments and that acts and modules referred to are not necessarily required for an embodiment of the specification.

In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.

The preferred embodiments of the present specification disclosed above are intended only to aid in the description of the specification. Alternative embodiments are not exhaustive and do not limit the invention to the precise embodiments described. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the embodiments and the practical application, to thereby enable others skilled in the art to best understand and utilize the embodiments. The specification is limited only by the claims and their full scope and equivalents.

Claims

1. A digital twin object processing method, comprising:

2. The digital twin object processing method of claim 1, the determining object configuration data of a target physical object and a digital twin object template corresponding to the target physical object, comprising:

determining the type of the target physical object;

3. The digital twin object processing method according to claim 2, before determining the object configuration data of the target physical object and the digital twin object template corresponding to the target physical object, further comprising:

4. The digital twin object processing method of claim 1, the determining an initial digital twin object to which the target physical object corresponds based on the object configuration data and the digital twin object template, comprising:

5. A digital twin object processing method according to claim 4, the object generating algorithms being at least two, the object configuration data being of at least two types;

6. The digital twin object processing method according to any one of claims 1 to 5, after determining an initial digital twin object corresponding to the target physical object based on the object configuration data and the digital twin object template, further comprising:

7. The digital twin object processing method of claim 6, the determining a corresponding digital twin object code for the initial digital twin object based on a code generation rule, comprising:

determining an object type parameter of the initial digital twin object, and performing coding processing on the object type parameter to obtain an object management code of the initial digital twin object;

8. The digital twin object processing method according to any one of claims 1 to 5, wherein determining a target digital twin object corresponding to the target physical object based on the current state data of the target physical object and the initial digital twin object comprises:

9. The digital twin object processing method according to claim 8, wherein the monitoring the current state of the target physical object based on the state data obtaining device to obtain the current state data of the target physical object includes:

judging whether the initial current state data meets a preset data condition or not;

if so, taking the initial current state data as the current state data of the target physical object;

10. The digital twin object processing method according to claim 8, after determining a target digital twin object corresponding to the target physical object based on the current state data of the target physical object and the initial digital twin object, further comprising:

and in response to an object rendering request of a user, rendering the target digital twin object to an object display page of a user terminal, and displaying the target digital twin object to the user through the object display page of the user terminal.

11. A digital twin object processing system includes an object determination node, a data acquisition node, a data fusion node, and an object presentation node, wherein,

12. A computing device, comprising:

a memory and a processor;

the memory is configured to store computer-executable instructions for execution by the processor, which when executed by the processor implement the steps of the digital twin object processing method of any one of claims 1 to 10.

13. A computer readable storage medium storing computer executable instructions which, when executed by a processor, carry out the steps of the digital twin object processing method of any one of claims 1 to 10.