Method and system for constructing digital twinborn body based on space-time coding and computing equipment

Abstract

The invention discloses a method and system for constructing a digital twinborn body based on space-time coding and a computing device, and relates to the technical field of digital twinborn, and the method comprises the steps: obtaining the original real-time data of each physical entity of each target region collected by each data collection device in real time; performing data cleaning and formatting processing on the original real-time data of the physical entity to obtain target real-time data; acquiring geographical location information and time information of the physical entity, encoding the geographical location information and the time information to generate a space-time code, and associating the target real-time data with the space-time code to obtain space-time coded real-time data of the physical entity; and constructing a data twinborn body corresponding to the physical entity based on the time-space coding real-time data so as to monitor the state of the physical entity in real time based on the data twinborn body corresponding to the physical entity. According to the invention, high-precision mapping and real-time monitoring can be carried out on the physical entity, high-precision space-time synchronization of data from different sources can be realized, and the expandability is improved.

Description

Technical Field

[0001] The present invention relates to the field of digital twin technology, and in particular to a method for constructing a digital twin based on space-time coding, a system for constructing a digital twin based on space-time coding, and a computing device. Background Art

[0002] Digital twin technology has been widely used in a variety of fields, including smart manufacturing, urban infrastructure management, and building energy management. By creating digital copies of physical entities, real-time monitoring, analysis, and prediction of the entity's status can be achieved.

[0003] In existing technologies, digital twin systems primarily rely on sensor data, Internet of Things (IoT) technologies, and cloud computing platforms. While these systems can collect and process data from the physical world, they suffer from limitations in data synchronization, real-time performance, and accurate mapping. Specifically, existing digital twin systems suffer from the following deficiencies: High-precision time synchronization is difficult for data from different sources and types; high-precision mapping of physical entities is difficult due to a lack of precise spatial and temporal encoding; Inadequate real-time performance means that existing systems experience delays when processing and analyzing data streams, making it difficult to meet the demands of real-time monitoring and rapid response. Furthermore, as the scale of applications expands and the number of monitored objects increases, existing systems face bottlenecks in scalability for physical entities or digital models.

[0004] Therefore, a method for constructing digital twins based on spatiotemporal coding is needed to solve the problems existing in the above technical solutions. Summary of the Invention

[0005] To this end, the present invention provides a method for constructing a digital twin based on space-time coding and a system for constructing a digital twin based on space-time coding to solve or at least alleviate the above problems.

[0006] According to one aspect of the present invention, a method for constructing a digital twin based on spatiotemporal coding is provided, which is executed in a server, and the server is communicatively connected to a plurality of data acquisition devices arranged in a plurality of target areas. The method comprises: acquiring in real time the original real-time data of each physical entity in each target area collected by each data acquisition device, the physical entity comprising one or more of industrial equipment, intelligent buildings, vehicles, urban infrastructure, agricultural facilities, and energy systems; for each of the physical entities, performing data cleaning and formatting on the original real-time data of the physical entity to obtain target real-time data of the physical entity, the target real-time data comprising one or more status data; obtaining the geographic location information and time information of the physical entity, and encoding the geographic location information and time information to generate a spatiotemporal coding, associating the target real-time data of the physical entity with the spatiotemporal coding to obtain the spatiotemporal coded real-time data of the physical entity; constructing a data twin corresponding to the physical entity based on the spatiotemporal coded real-time data of the physical entity, so as to monitor the status of the physical entity in real time based on the data twin corresponding to the physical entity.

[0007] Optionally, in the method for constructing a digital twin based on spatiotemporal coding according to the present invention, the geographic location information and time information of the physical entity are obtained, and the geographic location information and time information are encoded to generate spatiotemporal coding, including: obtaining the geographic location information of the physical entity from the GPS module or Beidou positioning system in the corresponding data acquisition device, encoding the geographic location information based on the spatiotemporal grid framework of the Beidou grid code to generate spatial coding information, wherein the geographic location information includes longitude information and latitude information; obtaining first timestamp information from the target real-time data of the physical entity, correcting the first timestamp information using a standard time server to obtain second timestamp information, and time-discrete coding the second timestamp information based on the spatiotemporal grid framework of the Beidou grid code to obtain discrete time information; combining the spatial coding information and the discrete time information to generate a unique spatiotemporal coding.

[0008] Optionally, in the method for constructing a digital twin based on spatiotemporal coding according to the present invention, a data twin corresponding to the physical entity is constructed based on the spatiotemporal coded real-time data of the physical entity, including: constructing a basic digital model of the physical entity; parsing the spatiotemporal coded real-time data of the physical entity to obtain the target real-time data of the physical entity and the corresponding geographic location information and time information; based on the geographic location information and time information, mapping the target real-time data of the physical entity to the corresponding position of the basic digital model to form mapping data; based on the basic digital model and the mapping data, obtaining the data twin corresponding to the physical entity, wherein the mapping data is used to represent the state of the digital twin and reflect the state of the physical entity.

[0009] Optionally, in the method for constructing a digital twin based on spatiotemporal coding according to the present invention, the server is communicatively connected to a data storage device, and the method further includes: storing the spatiotemporal coding real-time data of the physical entity in the data storage device; obtaining the latest spatiotemporal coding real-time data of the physical entity from the data storage device in real time; parsing the latest spatiotemporal coding real-time data of the physical entity to obtain the latest target real-time data of the physical entity and the corresponding geographic location information and time information; based on the geographic location information and time information, mapping the latest target real-time data of the physical entity to the corresponding position of the digital twin to form the latest mapping data, so as to update the state of the digital twin based on the latest mapping data, so that the state of the updated digital twin is consistent with the state of the physical entity.

[0010] Optionally, in the method for constructing a digital twin based on spatiotemporal coding according to the present invention, constructing a basic digital model of the physical entity includes: constructing a three-dimensional geometric model of the physical entity based on the shape and size information of the physical entity; assigning initial attribute information to the three-dimensional geometric model to obtain the basic digital model of the physical entity, the initial attribute information including material information, color information and structure information.

[0011] Optionally, in the method for constructing a digital twin based on spatiotemporal coding according to the present invention, the target real-time data of the physical entity is mapped to the corresponding position of the basic digital model based on the geographic location information and time information, including: mapping the target real-time data to the corresponding position of the basic digital model based on the geographic location information; and superimposing the target real-time data on the time axis corresponding to the digital twin based on the time information.

[0012] Optionally, in the method for constructing a digital twin based on spatiotemporal coding according to the present invention, it also includes: obtaining spatiotemporal coded real-time data of multiple time points in the normal operating state of the physical entity from the data storage device as normal operating history data; training the isolation forest algorithm based on the normal operating history data to generate an isolation forest model; using the isolation forest model to determine the anomaly score based on the latest target real-time data of the physical entity; judging whether the anomaly score exceeds a preset score threshold to determine whether the current state of the physical entity is abnormal.

[0013] Optionally, in the method for constructing a digital twin based on spatiotemporal coding according to the present invention, the server is communicatively connected to a plurality of data acquisition devices arranged in a plurality of target areas via a plurality of edge computing nodes, wherein each target area corresponds to an edge computing node, and each of the data acquisition devices is communicatively connected to the corresponding edge computing node through a wireless communication network, and is suitable for sending the collected original real-time data of the physical entities of each target area to the corresponding edge computing node; obtaining the original real-time data of each physical entity in each target area collected by each data acquisition device in real time, including: obtaining the original real-time data of each physical entity in each target area collected by each data acquisition device in real time through each edge computing node; performing data cleaning and formatting on the original real-time data of the physical entity, including: performing data cleaning and formatting on the original real-time data of the physical entity through the corresponding edge computing node.

[0014] Optionally, the method for constructing a digital twin based on spatiotemporal coding according to the present invention also includes: real-time monitoring of the operating status and data collection status of each data acquisition device in each target area; and issuing an alarm when the operating status and / or data collection status of any data acquisition device is detected to be abnormal.

[0015] According to one aspect of the present invention, a system for constructing digital twins based on spatiotemporal coding is provided, comprising: a plurality of data acquisition devices arranged in a plurality of target areas, suitable for collecting original real-time data of each physical entity in each target area; a server, communicatively connected to the plurality of data acquisition devices, wherein a construction device is deployed in the server, and the construction device comprises: an acquisition unit, suitable for acquiring in real time the original real-time data of each physical entity in each target area collected by each data acquisition device, wherein the physical entity comprises one or more of industrial equipment, intelligent buildings, vehicles, urban infrastructure, agricultural facilities, and energy systems; a preprocessing unit, suitable for, for each of the physical entities, The original real-time data of the physical entity is cleaned and formatted to obtain the target real-time data of the physical entity, and the target real-time data includes one or more status data; the encoding unit is suitable for obtaining the geographic location information and time information of the physical entity, and encoding the geographic location information and time information to generate a spatiotemporal code, and associating the target real-time data of the physical entity with the spatiotemporal code to obtain the spatiotemporal coded real-time data of the physical entity; the construction unit is suitable for constructing a data twin corresponding to the physical entity based on the spatiotemporal coded real-time data of the physical entity, so as to monitor the status of the physical entity in real time based on the data twin corresponding to the physical entity.

[0016] According to one aspect of the present invention, a computing device is provided, comprising: at least one processor; and a memory storing program instructions, wherein the program instructions are configured to be suitable for execution by the at least one processor, and the program instructions include instructions for executing the method for constructing a digital twin based on spatiotemporal coding as described above.

[0017] According to one aspect of the present invention, a computer program product is provided, comprising a computer program / instruction, wherein the computer program / instruction implements the method described above when executed by a processor.

[0018] According to one aspect of the present invention, a readable storage medium storing program instructions is provided. When the program instructions are read and executed by a computing device, the computing device executes the method for constructing a digital twin based on spatiotemporal coding as described above.

[0019] According to the technical solution of the present invention, a method for constructing a digital twin based on spatiotemporal coding is provided. The original real-time data of each physical entity in each target area collected by each data acquisition device is obtained in real time. For each physical entity, the original real-time data of the physical entity is cleaned and formatted to obtain the target real-time data. Then, the geographic location information and time information of the physical entity are encoded to generate spatiotemporal coding, and the target real-time data is associated with the spatiotemporal coding to obtain spatiotemporal coding real-time data. Based on the spatiotemporal coding real-time data, the data twin corresponding to the physical entity is constructed, and then the state of the physical entity can be monitored in real time based on the data twin corresponding to the physical entity. Based on this, the present invention can achieve high-precision spatiotemporal synchronization of real-time data of physical entities from different sources based on spatiotemporal coding, as well as high-precision mapping between physical entities and digital twins. By acquiring and processing data in real time and constructing digital twins, the needs of real-time monitoring and rapid response can be met, and corresponding digital twins can be flexibly constructed for newly added physical entities, thereby improving the scalability of physical entities and digital twins.

[0020] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] To achieve the above and related purposes, certain illustrative aspects are described herein in conjunction with the following description and accompanying drawings, which indicate various ways in which the principles disclosed herein may be practiced, and all aspects and their equivalents are intended to fall within the scope of the claimed subject matter. The above and other objects, features, and advantages of the present disclosure will become more apparent by reading the following detailed description in conjunction with the accompanying drawings. Throughout this disclosure, the same reference numerals generally refer to the same parts or elements.

[0022] Figure 1 A schematic diagram of a system 100 for constructing a digital twin based on spatiotemporal coding according to an embodiment of the present invention is shown;

[0023] Figure 2 A schematic diagram of a computing device 200 provided according to an embodiment of the present invention is shown;

[0024] Figure 3 A flow chart of a method 300 for constructing a digital twin based on spatiotemporal coding according to an embodiment of the present invention is shown;

[0025] Figure 4 A schematic diagram of a user interface provided according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0026] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art.

[0027] Existing digital twin systems find it difficult to achieve high-precision spatiotemporal synchronization and mapping between physical entities and digital twins, are unable to process data in real time, and are unable to meet the needs of real-time monitoring and rapid response. There are bottlenecks in the scalability of physical entities or digital models.

[0028] In order to solve the above technical problems, an embodiment of the present invention provides a method and system for constructing digital twins based on space-time coding. Based on space-time coding, high-precision space-time synchronization of real-time data from different sources and high-precision mapping between physical entities and digital twins can be achieved. In addition, the requirements of real-time monitoring and rapid response can be met, and the scalability of physical entities and digital twins can be improved.

[0029] The method for constructing a digital twin based on spatiotemporal coding provided in accordance with an embodiment of the present invention can be implemented in a system for constructing a digital twin based on spatiotemporal coding. The system for constructing a digital twin based on spatiotemporal coding of the present invention is described below.

[0030] Figure 1 A schematic diagram of a system 100 for constructing a digital twin based on spatiotemporal coding according to an embodiment of the present invention is shown.

[0031] like Figure 1 As shown, the system 100 for constructing digital twins based on spatiotemporal coding includes a server 120 and multiple data acquisition devices 110 deployed in multiple target areas. The server 120 is in communication with the multiple data acquisition devices 110 deployed in the multiple target areas, for example, via a wired or wireless network connection. The multiple data acquisition devices are used to collect raw, real-time data from various physical entities in each target area.

[0032] Each target area is deployed with one or more physical entities, and each target area can be equipped with one or more data acquisition devices 110. Each data acquisition device 110 is used to collect real-time data (raw, unprocessed real-time data) from the physical entities in the corresponding target area. In some embodiments, the data acquisition device 110 can be an IoT device, specifically including various smart sensors, industrial cameras, environmental monitors, drones, and automated inspection robots.

[0033] In an embodiment of the present invention, the physical entity may include one or more of industrial equipment, intelligent buildings, transportation vehicles, urban infrastructure, agricultural facilities, and energy systems.

[0034] In some embodiments, industrial equipment includes, for example, machine tools, robots, conveyor belts, 3D printers, and the like. Real-time data from industrial equipment includes, for example, operational status data, temperature data, vibration data, and fault data. Smart buildings include, for example, buildings, rooms, and the like. Real-time data from smart buildings includes, for example, temperature data, humidity data, air quality data, light intensity data, and energy consumption data. Vehicles include, for example, cars, buses, trains, and airplanes. Real-time data from vehicles includes, for example, location data, speed data, fuel consumption data, and number of passengers. Urban infrastructure includes, for example, roads, bridges, tunnels, water pipes, and power grids. Real-time data from urban infrastructure includes, for example, traffic flow data, water flow data, current data, voltage data, and structural health data. Agricultural facilities include, for example, greenhouses, farmland, and irrigation systems. Real-time data from agricultural facilities includes, for example, soil moisture data, crop growth data, light data, and rainfall data. Energy systems include, for example, power stations, substations, wind turbines, solar panels, etc., and real-time data of energy systems include, for example, power generation data, operating status data, environmental condition data, etc. of the energy systems.

[0035] In some embodiments, each target area can be divided according to geographic location, function, or management requirements. A corresponding number of data collection devices 110 (IoT devices) can be deployed in each target area to achieve high-precision and comprehensive real-time data collection of each physical entity in the target area.

[0036] In an embodiment of the present invention, the server 120 can obtain the original real-time data of each physical entity in each target area collected by each data acquisition device 110 in real time. For each physical entity, the original real-time data of the physical entity is cleaned and formatted, and the target real-time data of the physical entity can be obtained after processing. Subsequently, the server 120 obtains the geographic location information and time information of the physical entity, and encodes the geographic location information and time information to generate a spatiotemporal code (i.e., a spatiotemporal grid code). Then, the target real-time data of the physical entity is associated with the generated spatiotemporal code to obtain the spatiotemporal coded real-time data of the physical entity. It can be understood that based on the spatiotemporal code, the spatiotemporal synchronization and integration of the real-time data of the physical entities in each target area from each data acquisition device 110 can be achieved.

[0037] Furthermore, the server 120 can construct a data twin corresponding to the physical entity based on the spatiotemporal encoded real-time data of the physical entity, so that the status of the physical entity can be monitored in real time based on the data twin corresponding to the physical entity.

[0038] In an embodiment of the present invention, the target real-time data may include one or more state data, that is, the target real-time data of the physical entity includes one or more state data of the physical entity. The state data is used to describe the state of the physical entity.

[0039] In some embodiments, the system 100 for constructing a digital twin based on spatiotemporal coding also includes a data storage device 130 coupled to a server 120. The server 120 can store the spatiotemporal coding real-time data of each physical entity in the data storage device 130, and can update the spatiotemporal coding real-time data of each physical entity in the data storage device 130 in real time.

[0040] In some embodiments, the system 100 for constructing a digital twin based on spatiotemporal coding further includes a plurality of edge computing nodes 115. The server 120 is communicatively connected to the plurality of edge computing nodes 115, and can be communicatively connected to a plurality of data acquisition devices 110 arranged in a plurality of target areas via the plurality of edge computing nodes 115. Each target area may correspond to an edge computing node 115. Each data acquisition device 110 can be communicatively connected to the corresponding edge computing node 115 through a wireless communication network (such as Wi-Fi, LoRa or 5G), and each data acquisition device 110 can send the collected original real-time data of the physical entities of each target area to the corresponding edge computing node 115. In other words, the server 120 can obtain the original real-time data of each physical entity of each target area collected by each data acquisition device 110 in real time through each edge computing node 115.

[0041] After each data acquisition device 110 sends the collected original real-time data of the physical entities in each target area to the corresponding edge computing node 115, the corresponding edge computing node 115 can perform data cleaning and formatting on the original real-time data of the physical entity to obtain the target real-time data of the physical entity. Then, the edge computing node 115 can send the target real-time data of the physical entity to the server 120.

[0042] In some embodiments, the system 100 for constructing a digital twin based on spatiotemporal coding further includes one or more clients 160. The server 120 may also be in communication with the one or more clients 160, and the user may interact with the server 120 via the user interface of the client 160.

[0043] In an embodiment of the present invention, server 120 in system 100 for constructing digital twins based on spatiotemporal coding is adapted to execute method 300 for constructing digital twins based on spatiotemporal coding to construct a digital twin corresponding to a physical entity. Method 300 for constructing digital twins based on spatiotemporal coding of the present invention is described in detail below.

[0044] In an embodiment of the present invention, Figure 1 As shown, a construction device 150 is deployed in the server 120, and the construction device 150 can be configured to execute the method 300 of constructing a digital twin based on spatiotemporal coding of the present invention.

[0045] In an embodiment of the present invention, Figure 1 As shown, the construction device 150 includes an acquisition unit 151, a pre-processing unit 152, an encoding unit 153 and a construction unit 154 coupled in sequence.

[0046] Among them, the acquisition unit 151 is used to acquire the original real-time data of each physical entity in each target area collected by each data acquisition device in real time. The physical entities include one or more of industrial equipment, intelligent buildings, transportation vehicles, urban infrastructure, agricultural facilities, and energy systems.

[0047] The pre-processing unit 152 may perform data cleaning and formatting processing on the original real-time data of each physical entity to obtain target real-time data of the physical entity. The target real-time data includes one or more state data.

[0048] The coding unit 153 is used to obtain the geographic location information and time information of the physical entity, and encode the geographic location information and time information to generate a spatiotemporal code, and then associate the target real-time data of the physical entity with the spatiotemporal code to obtain the spatiotemporal coded real-time data of the physical entity.

[0049] The construction unit 154 can be adapted to construct a data twin corresponding to the physical entity based on the spatiotemporal encoded real-time data of the physical entity, so as to monitor the status of the physical entity in real time based on the data twin corresponding to the physical entity.

[0050] It should be noted that for the specific execution logic of the acquisition unit 151, the preprocessing unit 152, the encoding unit 153 and the construction unit 154 in the construction device 150, please refer to the description of steps 310 to 340 in the method 300 for constructing a digital twin based on spatiotemporal coding below.

[0051] According to the system 100 for constructing a digital twin based on spatiotemporal coding provided by an embodiment of the present invention, the server obtains the original real-time data of each physical entity in each target area collected by each data acquisition device in real time. For each physical entity, the original real-time data of the physical entity is cleaned and formatted to obtain the target real-time data. Then, the geographic location information and time information of the physical entity are encoded to generate spatiotemporal coding, and the target real-time data is associated with the spatiotemporal coding to obtain spatiotemporal coding real-time data. Based on the spatiotemporal coding real-time data, the data twin corresponding to the physical entity is constructed, and then the state of the physical entity can be monitored in real time based on the data twin corresponding to the physical entity. Based on this, the present invention can achieve high-precision spatiotemporal synchronization of real-time data of physical entities from different sources based on spatiotemporal coding, as well as high-precision mapping between physical entities and digital twins. By acquiring and processing data in real time and constructing digital twins, it can meet the needs of real-time monitoring and rapid response, and can flexibly construct corresponding digital twins for newly added physical entities, thereby improving the scalability of physical entities and digital twins.

[0052] In an embodiment of the present invention, the server 120 can be implemented as a computing device 200 described below, so that the method 300 of constructing a digital twin based on spatiotemporal coding of the present invention can be executed in the computing device 200.

[0053] Figure 2 FIG. 2 shows a schematic diagram of a computing device 200 provided according to an embodiment of the present invention. Figure 2 As shown, in a basic configuration, computing device 200 includes at least one processing unit 202 and system memory 204. According to one aspect, depending on the configuration and type of computing device, processing unit 202 can be implemented as a processor. System memory 204 includes, but is not limited to, volatile storage (e.g., random access memory), non-volatile storage (e.g., read-only memory), flash memory, or any combination of such memories. According to one aspect, system memory 204 includes an operating system 205.

[0054] According to one aspect, operating system 205 is suitable for controlling the operation of computing device 200, for example. Furthermore, examples may be practiced in conjunction with graphics libraries, other operating systems, or any other application programs, and are not limited to any particular application or system. Figure 2 The basic configuration is shown in FIG. 1 by those components within the dashed lines. According to one aspect, the computing device 200 has additional features or functionality. For example, according to one aspect, the computing device 200 includes additional data storage devices 130 (removable and / or non-removable), such as magnetic disks, optical disks, or tapes. Such additional storage Figure 2 2 is illustrated by a removable storage device 209 and a non-removable storage device 210.

[0055] As stated above, according to one aspect, a program module 203 is stored in the system memory 204. According to one aspect, the program module 203 may include one or more application programs, and the present invention is not limited to the type of application program. For example, the application program may include an email and contact application program, a word processing application program, a spreadsheet application program, a database application program, a slide show application program, a drawing or computer-aided application program, a web browser application program, etc.

[0056] In an embodiment according to the present invention, the program module 203 includes multiple program instructions for executing the method 300 of the present invention for constructing a digital twin based on spatiotemporal coding.

[0057] According to one aspect, examples may be practiced on a circuit comprising discrete electronic components, a packaged or integrated electronic chip containing logic gates, a circuit utilizing a microprocessor, or a single chip containing electronic components or a microprocessor. Figure 2 In the embodiment of the present invention, each or many components shown in the embodiment of the present invention can be integrated into a system on a chip (SOC) on a single integrated circuit to practice the example. According to one aspect, such a SOC device may include one or more processing units, a graphics unit, a communication unit, a system virtualization unit, and various application functions, all of which are integrated (or "burned") onto a chip substrate as a single integrated circuit. When operated via the SOC, the functions described in this article can be operated via a dedicated logic integrated with other components of the computing device 200 on a single integrated circuit (chip). Other technologies capable of performing logical operations (such as AND, OR, and NOT) can also be used to practice embodiments of the present invention, and the other technologies include but are not limited to mechanical, optical, fluid, and quantum technologies. In addition, embodiments of the present invention can be practiced in a general-purpose computer or in any other circuit or system.

[0058] According to one aspect, the computing device 200 may also have one or more input devices 212, such as a keyboard, a mouse, a pen, a voice input device, a touch input device, etc. Output devices 214 may also be included, such as a display, speakers, a printer, etc. The aforementioned devices are examples, and other devices may also be used. The computing device 200 may include one or more communication connections 216 that allow communication with other computing devices 218. Examples of suitable communication connections 216 include, but are not limited to: RF transmitter, receiver, and / or transceiver circuitry; Universal Serial Bus (USB), parallel, and / or serial ports.

[0059] As used herein, the term computer-readable medium includes computer storage media. Computer storage media can include volatile and non-volatile, removable and non-removable media implemented with any method or technology for storing information (e.g., computer-readable instructions, data structures, or program modules). System memory 204, removable storage device 209, and non-removable storage device 210 are all examples of computer storage media (i.e., memory storage). Computer storage media can include random access memory (RAM), read-only memory (ROM), electrically erasable read-only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical storage, cassette tape, magnetic tape, disk storage or other magnetic storage device, or any other product that can be used to store information and can be accessed by computing device 200. According to one aspect, any such computer storage medium can be a part of computing device 200. Computer storage media does not include carrier waves or other propagated data signals.

[0060] According to one aspect, communication media is implemented by computer-readable instructions, data structures, program modules, or other data in a modulated data signal (e.g., a carrier wave or other transport mechanism), and includes any information delivery media. According to one aspect, the term "modulated data signal" describes a signal that has one or more characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, radio frequency (RF), infrared, and other wireless media.

[0061] In an embodiment according to the present invention, a computing device 200 is configured to execute a method 300 for constructing a digital twin based on spatiotemporal coding. The computing device 200 includes one or more processors and one or more readable storage media storing program instructions. When the program instructions are configured to be executed by the one or more processors, the computing device executes the method 300 for constructing a digital twin based on spatiotemporal coding according to an embodiment of the present invention. By executing the method 300 for constructing a digital twin based on spatiotemporal coding according to the present invention, the computing device 200 can achieve high-precision mapping and real-time monitoring of physical entities.

[0062] In an embodiment of the present invention, the computing device 200 that executes the method 300 for constructing a digital twin based on spatiotemporal coding may be a server 120 .

[0063] The server 120 can be communicatively connected to multiple data acquisition devices 110 deployed in multiple target areas, where each target area is deployed with one or more physical entities, and each target area can be deployed with one or more data acquisition devices 110. Each data acquisition device 110 is used to collect real-time data (raw, unprocessed real-time data) from the physical entities in the corresponding target area. In some embodiments, the data acquisition device 110 can be an IoT device, specifically including various smart sensors, industrial cameras, environmental monitors, drones, and automated inspection robots.

[0064] The following is a detailed description of the method 300 for constructing a digital twin based on spatiotemporal coding in an embodiment of the present invention.

[0065] Figure 3 FIG2 shows a flow chart of a method 300 for constructing a digital twin based on spatiotemporal coding according to an embodiment of the present invention. Figure 3 As shown, the method 300 for constructing a digital twin based on spatiotemporal coding includes the following steps 310 to 340.

[0066] Step 310 : The server 120 acquires in real time the original real-time data of each physical entity in each target area collected by each data collection device 110 .

[0067] In an embodiment of the present invention, the physical entity may include one or more of industrial equipment, intelligent buildings, transportation vehicles, urban infrastructure, agricultural facilities, and energy systems.

[0068] In step 320 , the server 120 may perform data cleaning and formatting on the original real-time data of each physical entity, and obtain the target real-time data of the physical entity after the processing.

[0069] In an embodiment of the present invention, the target real-time data may include one or more state data, that is, the target real-time data of the physical entity includes one or more state data of the physical entity. The state data is used to describe the state of the physical entity.

[0070] It should be noted that by performing data cleansing on the raw real-time data of physical entities, noise and redundant data can be removed from the raw real-time data, ensuring data accuracy and integrity. Furthermore, by formatting the cleaned raw real-time data, the raw real-time data can be converted into a unified data format (e.g., JSON, XML, etc.). This ensures the format consistency of the target real-time data of each physical entity.

[0071] In step 330, the server 120 performs spatiotemporal coding on the target real-time data of the physical entity. Specifically, the server 120 obtains the geographic location information and time information of the physical entity, encodes the geographic location information and time information to generate a spatiotemporal code, and then associates the target real-time data of the physical entity with the generated spatiotemporal code to obtain the spatiotemporal coded real-time data of the physical entity.

[0072] It can be understood that the spatiotemporal code generated by encoding the geographic location information and time information of the physical entity can be used to identify the location and time of the real-time data of the physical entity.

[0073] Based on the spatiotemporal coding, spatiotemporal synchronization and integration of the real-time data of physical entities in each target area from each data acquisition device 110 can be achieved.

[0074] In step 340, the server 120 may construct a data twin corresponding to the physical entity based on the spatiotemporal encoded real-time data of the physical entity, so that the status of the physical entity can be monitored in real time based on the data twin corresponding to the physical entity.

[0075] In some embodiments, the time information may specifically be timestamp information. In step 330, the server 120 may obtain the geographic location information of the physical entity from the GPS module or Beidou positioning system in the corresponding data acquisition device 110 (i.e., the data acquisition device 110 for collecting the original real-time data of the physical entity), and may obtain the time information (timestamp information) from the target real-time data of the physical entity. Furthermore, the server 120 may encode the geographic location information and time information (timestamp information) based on the spatiotemporal grid framework of the Beidou grid code to generate a spatiotemporal code. It should be noted that the Beidou grid code technology (including the segmented time code) provides a spatiotemporal grid framework that can construct a digital twin grid data model of the entire earth's space. The spatiotemporal grid framework is essentially an open big data architecture based on spatiotemporal coding, which can organize multi-source heterogeneous spatiotemporal data of cities through grid association.

[0076] Furthermore, in step 330, the server 120 obtains the geographic location information and time information of the physical entity, and encodes the geographic location information and time information to generate a spatiotemporal code. The specific manner is as follows:

[0077] The server 120 can obtain the geographic location information of the physical entity from the GPS module or Beidou positioning system in the corresponding data acquisition device 110 (i.e., the data acquisition device 110 used to collect the original real-time data of the physical entity), and then can encode the geographic location information of the physical entity based on the spatiotemporal grid framework of the Beidou grid code to generate corresponding spatially coded information. It should be noted that the geographic location information may include longitude information and latitude information. When encoding the geographic location information based on the spatiotemporal grid framework of the Beidou grid code, the longitude information and latitude information can be specifically encoded based on the spatiotemporal grid framework of the Beidou grid code, and the encoded longitude information and latitude information can be positionally corrected based on the coordinate system of the Beidou grid code to ensure the accuracy of the spatially coded information finally generated.

[0078] Furthermore, the server 120 can obtain the first timestamp information from the target real-time data of the physical entity and correct the first timestamp information using a standard time server to obtain the second timestamp information. Subsequently, the second timestamp information can be time-discrete encoded (time-sliced) based on the space-time grid framework of the Beidou grid code to obtain discretized time information.

[0079] Furthermore, the server 120 may combine the above-mentioned spatial coding information and the discretized time information to generate a unique spatiotemporal code (ie, a spatiotemporal code that uniquely corresponds to the target real-time data of the physical entity).

[0080] In some embodiments, in step 340, the server 120 constructs a data twin corresponding to the physical entity based on the spatiotemporal encoding real-time data of the physical entity. The specific process includes the following steps D1 to D4.

[0081] D1. Construct a basic digital model of the physical entity. Specifically, a 3D geometric model of the physical entity can be constructed based on its shape and size information. This shape information can be obtained from design drawings or CAD models of the physical entity. Furthermore, initial attribute information can be assigned to the 3D geometric model to obtain a basic digital model of the physical entity. This initial attribute information includes material information, color information, and structural information.

[0082] D2. Parse the spatiotemporal coded real-time data of the physical entity to obtain the target real-time data of the physical entity and the corresponding geographic location information and time information.

[0083] It should be noted that the present invention does not limit the execution order of D1 and D2. D1 can be executed first and then D2, or D2 can be executed first and then D1.

[0084] D3. Based on the parsed geographic location information and time information, the target real-time data of the physical entity (including one or more state data, such as temperature data, humidity data, and vibration data) is mapped to the corresponding location of the base digital model to form mapping data on the base digital model. Specifically, the target real-time data can be mapped to the corresponding location of the base digital model based on the geographic location information, and the target real-time data can be superimposed on the corresponding time axis of the digital twin based on the time information, thereby forming mapping data.

[0085] D4. Based on the basic digital model and mapping data, a data twin corresponding to the physical entity can be obtained.

[0086] It should be noted that the mapping data is used to represent the state of the digital twin and can reflect the state (actual state) of the physical entity corresponding to the digital twin.

[0087] For example, the temperature data of the industrial equipment is mapped to the corresponding position of the basic digital model of the industrial equipment, and the resulting mapping data can reflect the thermal distribution state of the industrial equipment.

[0088] In some embodiments, the server 120 can also classify and label the target real-time data of the physical entity based on the type of the physical entity and the type of the corresponding data acquisition device 110, so as to determine the corresponding physical entity and data acquisition device based on the labeled target real-time data.

[0089] In some embodiments, server 120 is in communication with data storage device 130. After generating the spatiotemporally coded real-time data of the physical entity in step 330, server 120 may store the spatiotemporally coded real-time data of the physical entity in data storage device 130 for subsequent use. Furthermore, for each physical entity, server 120 may store the spatiotemporally coded real-time data of the physical entity at each time point, generated based on the original real-time data of the physical entity at each time point, in data storage device 130, respectively, to enable real-time updating of the spatiotemporally coded real-time data of each physical entity in data storage device 130.

[0090] The server 120 can also update the state of the data twin in real time by: obtaining the latest spatiotemporal coded real-time data of the physical entity from the data storage device 130 in real time, and parsing the latest spatiotemporal coded real-time data of the physical entity to obtain the latest target real-time data of the physical entity and the corresponding geographic location information and time information. Furthermore, based on the geographic location information and time information, the latest target real-time data of the physical entity can be mapped to the corresponding position of the digital twin to form the latest mapping data on the digital twin. In this way, the state of the digital twin can be updated based on the latest mapping data so that the state of the updated digital twin is consistent with the state (actual state) of the physical entity. It should be noted that updating the state of the digital twin can specifically include updating one or more state attributes of the digital twin, and the state attributes can include temperature, humidity, speed, acceleration, etc.

[0091] In some embodiments, according to the method 300 for constructing a digital twin based on spatiotemporal coding of the present invention, the server 120 can also perform intelligent analysis on the state of the physical entity.

[0092] In some embodiments, the server 120 can use the isolation forest algorithm (a decision tree-based anomaly detection algorithm) to perform intelligent analysis on the state of the physical entity. The specific method is as follows: the spatiotemporal coded real-time data of multiple time points when the physical entity is in normal operation is obtained from the data storage device 130 as normal operation history data (training data). Specifically, the spatiotemporal coded real-time data of multiple time points when the physical entity is in normal operation can be cleaned and normalized and used as normal operation history data. Thereafter, the isolation forest algorithm can be trained based on the normal operation history data to generate an isolation forest model. Furthermore, the isolation forest model can be used to determine an anomaly score based on the latest target real-time data of the physical entity. By determining whether the anomaly score exceeds a preset score threshold, it can be determined whether the current state of the physical entity is abnormal.

[0093] In some embodiments, server 120 can also perform intelligent analysis of the state of a physical entity by obtaining spatiotemporally encoded real-time data of the physical entity at various time points from data storage device 130, normalizing it, and extracting features to generate time series features of the physical entity. Subsequently, an LSTM (Long Short Term Memory) neural network can be trained based on the time series features to generate an LSTM model. Furthermore, the LSTM model can be used to predict the future state of the physical entity based on the physical entity's latest target real-time data, and can also predict future state data trends of the physical entity.

[0094] In some embodiments, the state types of physical entities include, for example: normal operating state (including uniform motion state, accelerated motion state, decelerated motion state, vibration state, etc.), alarm state, abnormal state, fault state, maintenance state, and shutdown state.

[0095] It should be noted that the normal operating state indicates that the physical entity is operating normally, with no anomalies, and all status data of the physical entity are within the corresponding preset normal threshold range. The alarm state indicates that at least one status data exceeds the warning threshold but has not yet reached the failure standard. The abnormal state indicates that at least one status data significantly exceeds the preset normal threshold, which may affect the normal operation of the physical entity. The fault state indicates that at least one status data exceeds the danger threshold, the physical entity has failed, and emergency treatment is required. The maintenance state indicates that the physical entity is in maintenance or repair. The shutdown state indicates that the physical entity is in shutdown or off state. In the shutdown state, various status data remain unchanged or are displayed as shutdown status codes.

[0096] In some embodiments, the server 120 can also monitor the operating status and data collection status of each data collection device 110 in each target area in real time. If the operating status and / or data collection status of any data collection device 110 is abnormal, an alarm will be issued, and backup equipment can be activated or the collection plan can be reconfigured. This ensures the reliability and stability of the digital twin system 100 built based on spatiotemporal coding.

[0097] In some embodiments, the server 120 is communicatively connected to a plurality of edge computing nodes 115, and can be communicatively connected to a plurality of data acquisition devices 110 arranged in a plurality of target areas via the plurality of edge computing nodes 115. Each target area can correspond to an edge computing node 115. Each data acquisition device 110 can be communicatively connected to a corresponding edge computing node 115 via a wireless communication network (e.g., Wi-Fi, LoRa, or 5G), and each data acquisition device 110 can send the collected raw real-time data of the physical entities in each target area to the corresponding edge computing node 115.

[0098] In step 310 , the server 120 may obtain, through each edge computing node 115 , the original real-time data of each physical entity in each target area collected by each data collection device 110 in real time.

[0099] In step 320, the server 120 may perform data cleaning and formatting on the raw real-time data of the physical entity through the corresponding edge computing node 115. Specifically, after each data acquisition device 110 sends the collected raw real-time data of the physical entity in each target area to the corresponding edge computing node 115, the corresponding edge computing node 115 may then perform data cleaning and formatting on the raw real-time data of the physical entity to obtain the target real-time data of the physical entity. Then, the edge computing node 115 may send the target real-time data of the physical entity to the server 120.

[0100] In some embodiments, the server 120 may also be in communication with one or more clients 160, and a user may interact with the server 120 via a user interface of the client 160. Specifically, the user may perform interactive operations in the user interface of the client 160, such as manually adjusting a threshold, initiating a device check, and querying data. In response to the user's interactive operations, the client 160 may send a corresponding request to the server 120, and the server 120 may then perform the corresponding operation.

[0101] The server 120 may send the constructed digital twin to the client 160 for display on the user interface of the client 160 . Figure 4 FIG. 1 shows a schematic diagram of a user interface provided according to an embodiment of the present invention. Figure 4 As shown, the user interface can display the digital twins of each physical entity and their status in real time. Based on the user interface, the digital twins of each physical entity and their status can be displayed intuitively, making it easy for users to operate.

[0102] According to the method 300 for constructing a digital twin based on spatiotemporal coding of the present invention, by acquiring the original real-time data of each physical entity in each target area collected by each data acquisition device in real time, for each physical entity, the original real-time data of the physical entity is cleaned and formatted to obtain the target real-time data, and then, the geographic location information and time information of the physical entity are encoded to generate spatiotemporal coding, and the target real-time data is associated with the spatiotemporal coding to obtain spatiotemporal coding real-time data, and the data twin corresponding to the physical entity is constructed based on the spatiotemporal coding real-time data, and then the state of the physical entity can be monitored in real time based on the data twin corresponding to the physical entity. Based on this, the present invention can achieve high-precision spatiotemporal synchronization of real-time data of physical entities from different sources based on spatiotemporal coding, as well as high-precision mapping between physical entities and digital twins. By acquiring and processing data in real time and constructing digital twins, it can meet the needs of real-time monitoring and rapid response, and can flexibly construct corresponding digital twins for newly added physical entities, thereby improving the scalability of physical entities and digital twins.

[0103] In addition, an embodiment of the present invention further discloses: A8, a method as described in any one of A1-A7, wherein the server is communicatively connected to a plurality of data acquisition devices arranged in a plurality of target areas via a plurality of edge computing nodes, wherein each target area corresponds to an edge computing node, and each of the data acquisition devices is communicatively connected to the corresponding edge computing node via a wireless communication network, and is suitable for sending the collected original real-time data of the physical entities in each target area to the corresponding edge computing node; obtaining the original real-time data of each physical entity in each target area collected by each data acquisition device in real time, including: obtaining the original real-time data of each physical entity in each target area collected by each data acquisition device in real time through each edge computing node; performing data cleaning and formatting on the original real-time data of the physical entity, including: performing data cleaning and formatting on the original real-time data of the physical entity through the corresponding edge computing node. A9, a method as described in any one of A1-A8, wherein the server further includes: monitoring the operating status and data collection status of each data acquisition device in each target area in real time; and issuing an alarm when the operating status and / or data collection status of any data acquisition device is abnormal. B13. A readable storage medium storing program instructions, which, when read and processed by a computing device, enables the computing device to process the method described in any one of A1 to A9.

[0104] The various techniques described herein may be implemented in conjunction with hardware or software, or a combination thereof. Thus, the methods and apparatus of the present invention, or certain aspects or portions of the methods and apparatus of the present invention, may be implemented in the form of program codes (i.e., instructions) embedded in a tangible medium, such as a removable hard disk, a USB flash drive, a floppy disk, a CD-ROM, or any other machine-readable storage medium, wherein when the program is loaded into a machine such as a computer and executed by the machine, the machine becomes an apparatus for practicing the present invention.

[0105] When the program code is executed on a programmable computer, the mobile terminal generally includes a processor, a storage medium readable by the processor (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device. The memory is configured to store the program code; the processor is configured to execute the method of constructing a digital twin based on spatiotemporal coding according to the instructions in the program code stored in the memory.

[0106] By way of example and not limitation, readable media include readable storage media and communication media. Readable storage media store information such as computer-readable instructions, data structures, program modules, or other data. Communication media typically embody computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and include any information delivery medium. Combinations of any of the above are also included within the scope of readable media.

[0107] In the description provided herein, the algorithms and displays are not inherently related to any particular computer, virtual system, or other device. Various general-purpose systems may also be used in conjunction with the examples of the present invention. Based on the above description, it is apparent that the structure required for constructing such systems is well understood. In addition, the present invention is not directed to any specific programming language. It should be understood that various programming languages ​​may be utilized to implement the present invention described herein, and the description of specific languages ​​above is provided for the purpose of disclosing the preferred embodiment of the present invention.

[0108] In the description provided herein, a large number of specific details are described. However, it is understood that embodiments of the present invention can be practiced without these specific details. In some instances, well-known methods, structures, and techniques are not shown in detail so as not to obscure the understanding of this description.

[0109] Similarly, it should be understood that in order to streamline the disclosure and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together into a single embodiment, figure, or description thereof.

[0110] Those skilled in the art will appreciate that the modules, units, or components of the devices in the examples disclosed herein may be arranged in the device described in the embodiment, or alternatively may be located in one or more devices different from the devices in the examples. The modules in the foregoing examples may be combined into one module or further divided into multiple submodules.

[0111] Unless otherwise specified, the use of ordinal numbers "first," "second," "third," etc. to describe common objects merely indicates that different instances of similar objects are involved and is not intended to imply that the objects so described must have a given order in time, space, ranking, or in any other manner.

Claims

1. A method for constructing a digital twin based on spatiotemporal coding, executed in a server, wherein the server is communicatively connected to a plurality of data acquisition devices arranged in a plurality of target areas, the method comprising: Acquire in real time the original real-time data of each physical entity in each target area collected by each data collection device, wherein the physical entity includes one or more of industrial equipment, intelligent buildings, transportation vehicles, urban infrastructure, agricultural facilities, and energy systems; For each of the physical entities, data cleaning and formatting are performed on the original real-time data of the physical entity to obtain target real-time data of the physical entity, wherein the target real-time data includes one or more state data; Acquire the geographic location information and time information of the physical entity, encode the geographic location information and time information to generate a spatiotemporal code, associate the target real-time data of the physical entity with the spatiotemporal code, and obtain the spatiotemporal coded real-time data of the physical entity; Based on the spatiotemporal encoded real-time data of the physical entity, a data twin corresponding to the physical entity is constructed so as to monitor the state of the physical entity in real time based on the data twin corresponding to the physical entity.

2. The method of claim 1, wherein: Acquiring geographic location information and time information of the physical entity, and encoding the geographic location information and time information to generate a spatiotemporal code, including: Acquire the geographic location information of the physical entity from the GPS module or Beidou positioning system in the corresponding data acquisition device, encode the geographic location information based on the spatiotemporal grid framework of the Beidou grid code, and generate spatially encoded information, wherein the geographic location information includes longitude information and latitude information; Acquire first timestamp information from the target real-time data of the physical entity, correct the first timestamp information using a standard time server to obtain second timestamp information, and perform time discrete encoding on the second timestamp information based on the space-time grid framework of the Beidou grid code to obtain discretized time information; The spatial coding information and the discretized time information are combined to generate a unique spatiotemporal code.

3. The method according to claim 1 or 2, wherein: Based on the spatiotemporal encoded real-time data of the physical entity, a data twin corresponding to the physical entity is constructed, including: constructing a basic digital model of the physical entity; Parsing the spatiotemporal coded real-time data of the physical entity to obtain target real-time data of the physical entity and corresponding geographic location information and time information; Based on the geographic location information and time information, mapping the target real-time data of the physical entity to a corresponding position of the basic digital model to form mapping data; Based on the basic digital model and the mapping data, a data twin corresponding to the physical entity is obtained, wherein the mapping data is used to represent the state of the digital twin and reflect the state of the physical entity.

4. The method of claim 3, wherein: The server is in communication with the data storage device, and the method further comprises: storing the spatiotemporally encoded real-time data of the physical entity in the data storage device; Acquire the latest spatiotemporal encoded real-time data of the physical entity from the data storage device in real time; Parsing the latest spatiotemporal coded real-time data of the physical entity to obtain the latest target real-time data of the physical entity and corresponding geographic location information and time information; Based on the geographic location information and time information, the latest target real-time data of the physical entity is mapped to the corresponding position of the digital twin to form the latest mapping data, so as to update the state of the digital twin based on the latest mapping data so that the state of the updated digital twin is consistent with the state of the physical entity.

5. The method according to claim 3 or 4, wherein: Constructing a basic digital model of the physical entity, including: Constructing a three-dimensional geometric model of the physical entity based on the shape and size information of the physical entity; Initial attribute information is assigned to the three-dimensional geometric model to obtain a basic digital model of the physical entity, wherein the initial attribute information includes material information, color information and structure information.

6. The method according to any one of claims 3 to 5, wherein: Based on the geographic location information and the time information, mapping the target real-time data of the physical entity to the corresponding position of the basic digital model includes: Based on the geographic location information, mapping the target real-time data to a corresponding position of the basic digital model; Based on the time information, the target real-time data is superimposed on the time axis corresponding to the digital twin.

7. The method of claim 4, wherein: Also includes: Acquire the spatiotemporally encoded real-time data of multiple time points in the normal operating state of the physical entity from the data storage device as normal operating history data; Training the isolation forest algorithm based on the normal operation historical data to generate an isolation forest model; Determining an anomaly score based on the latest target real-time data of the physical entity using the isolation forest model; It is determined whether the abnormality score exceeds a preset score threshold to determine whether the current state of the physical entity is abnormal.

8. A system for constructing a digital twin based on spatiotemporal coding, comprising: A plurality of data acquisition devices arranged in a plurality of target areas, adapted to acquire original real-time data of each physical entity in each target area; A server is connected to the plurality of data acquisition devices in communication, wherein a construction device is deployed in the server, and the construction device includes: An acquisition unit, adapted to acquire in real time the original real-time data of each physical entity in each target area collected by each data acquisition device, wherein the physical entity includes one or more of industrial equipment, intelligent buildings, transportation vehicles, urban infrastructure, agricultural facilities, and energy systems; A preprocessing unit, adapted to perform data cleaning and formatting processing on the original real-time data of each physical entity to obtain target real-time data of the physical entity, wherein the target real-time data includes one or more state data; A coding unit, adapted to obtain geographic location information and time information of the physical entity, encode the geographic location information and time information to generate a spatiotemporal code, associate the target real-time data of the physical entity with the spatiotemporal code, and obtain the spatiotemporal coded real-time data of the physical entity; The construction unit is suitable for constructing a data twin corresponding to the physical entity based on the spatiotemporal encoded real-time data of the physical entity, so as to monitor the state of the physical entity in real time based on the data twin corresponding to the physical entity.

9. A computing device comprising: at least one processor; and A memory storing program instructions, wherein the program instructions are configured to be processed by the at least one processor, and the program instructions include instructions for processing the method according to any one of claims 1 to 7.

10. A computer program product comprising a computer program / instructions, wherein: When the computer program / instructions are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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