Digital twinborn system based on communication module and construction method of digital twinborn model

Abstract

The invention provides a digital twin system based on a communication module and a construction method of a digital twin model. The system comprises a communication module and digital twinning firmware, the digital twinning firmware comprises an operating system layer, a driver library layer and an interface service layer, and the interface service layer is deployed with a digital twinning service supporting construction of a digital twinning model for any physical peripheral; wherein the digital twinning service acquires multi-dimensional sensing data of any physical peripheral through the communication module, and processes the multi-dimensional sensing data by using at least one digital twinning component built in the driving library layer under a target operating system adopted by the operating system layer, so as to construct a digital twinning model of the physical peripheral. According to the method and the device, a hardware network for transmitting data by the physical peripherals can be fused with a software network during construction of the digital twin model, so that the real-time validity of the data during construction of the digital twin model of any physical peripheral is improved, and the efficient and accurate construction of the digital twin model of any physical peripheral is ensured.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of data processing technology, and specifically to a digital twin system based on a communication module and a method for constructing a digital twin model. Background Art

[0002] As an emerging technology, digital twin technology can be widely used in industrial manufacturing, medical health, urban planning, traffic management and other fields to significantly promote changes in the design, production, maintenance and repair of physical products.

[0003] Existing digital twin systems are usually implemented through pure software on the server side. The server side uses Internet of Things technology to obtain various relevant entity data generated by a physical entity during the operation and operation process, and performs simulation operations on various relevant entity data to build a corresponding digital twin model for the physical entity.

[0004] However, in existing digital twin systems, the data transmission network for physical entities and the data processing network when the server builds the digital twin model are separated in hardware and software, which limits the real-time and effectiveness of the synchronous distribution of relevant entity data when the digital twin model is built, and cannot guarantee the accurate construction of the digital twin model. Summary of the Invention

[0005] The embodiments of the present application provide a digital twin system and a method for constructing a digital twin model based on a communication module, integrating digital twin technology into the communication module, improving the real-time validity of data when constructing a digital twin model of any physical peripheral, and ensuring the efficient and accurate construction of a digital twin model of any physical peripheral.

[0006] In a first aspect, an embodiment of the present application provides a digital twin system based on a communication module, the system comprising: a communication module and a digital twin firmware, the digital twin firmware comprising an operating system layer, a driver library layer and an interface service layer, the interface service layer being deployed with a digital twin service that supports building a digital twin model for any physical peripheral; wherein,

[0007] The digital twin service obtains multi-dimensional sensor data of any physical peripheral through the communication module, and processes the multi-dimensional sensor data using at least one digital twin component built into the driver library layer under the target operating system adopted by the operating system layer to construct a digital twin model of the physical peripheral.

[0008] In a second aspect, an embodiment of the present application provides a method for constructing a digital twin model, which is applied to the digital twin system based on the communication module provided in the first aspect above, and the method includes:

[0009] Acquire multi-dimensional sensor data from any physical peripheral;

[0010] Determining behavior prediction data of the physical peripheral device based on the multi-dimensional sensing data;

[0011] A digital twin model of the physical peripheral is constructed based on the multidimensional sensing data and the behavior prediction data.

[0012] In a third aspect, an embodiment of the present application provides a device for constructing a digital twin model, which is configured in the digital twin system for the communication module provided in the first aspect above, and the device includes:

[0013] Data acquisition module, used to obtain multi-dimensional sensor data of any physical peripheral;

[0014] a behavior prediction module, configured to determine behavior prediction data of the physical peripheral device based on the multi-dimensional sensing data;

[0015] A model building module is used to build a digital twin model of the physical peripheral based on the multidimensional sensing data and the behavior prediction data.

[0016] In a fourth aspect, an embodiment of the present application provides an electronic device, the electronic device comprising:

[0017] A processor and a memory, the memory being used to store a computer program, and the processor being used to call and run the computer program stored in the memory to execute the method for constructing a digital twin model provided in the second aspect of the present application.

[0018] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium for storing a computer program, wherein the computer program enables a computer to execute the method for constructing a digital twin model as provided in the second aspect of the present application.

[0019] In the sixth aspect, an embodiment of the present application provides a computer program product, including a computer program / instructions, characterized in that when the computer program / instructions are executed by a processor, it implements the method for constructing a digital twin model provided in the second aspect of the present application.

[0020] The embodiment of the present application provides a method for constructing a digital twin system and a digital twin model based on a communication module, which combines a communication module with a digital twin firmware. The digital twin firmware includes an operating system layer, a driver library layer, and an interface service layer. The interface service layer is deployed with a digital twin service that supports the construction of a digital twin model for any physical peripheral, thereby integrating digital twin technology into the communication module. Then, the digital twin service can directly obtain the multidimensional sensor data of any physical peripheral through the communication module, and use at least one digital twin component built into the driver library layer to process the multidimensional sensor data under the target operating system adopted by the operating system layer to construct a digital twin model of the physical peripheral, so that the hardware network for transmitting data of the physical peripheral is integrated with the software network when constructing the digital twin model, thereby improving the real-time validity of data when constructing a digital twin model of any physical peripheral, ensuring the efficient and accurate construction of the digital twin model of any physical peripheral, and expanding the applicable scenarios of the digital twin model under the Internet of Things where the communication module is located. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0022] Figure 1 A schematic diagram of the principle of a digital twin system based on a communication module provided in an embodiment of the present application;

[0023] Figure 2 An exemplary schematic diagram of a communication module provided in an embodiment of the present application;

[0024] Figure 3 A schematic diagram of the digital twin service provided in this application embodiment;

[0025] Figure 4 A flowchart of a method for constructing a digital twin model provided in an embodiment of the present application;

[0026] Figure 5 A flowchart of another method for constructing a digital twin model provided in an embodiment of the present application;

[0027] Figure 6 A block diagram of the principles of a device for constructing a digital twin model provided in an embodiment of the present application;

[0028] Figure 7 This is a schematic block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0030] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way are interchangeable where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0031] Considering that the digital twin system implemented by pure software on the server side limits the real-time and effectiveness of the synchronous issuance of relevant data when the digital twin model of any physical peripheral is constructed, the accurate construction of the digital twin model cannot be guaranteed. Therefore, the embodiment of the present application designs a digital twin system based on a communication module, combining the communication module with the digital twin firmware, which includes an operating system layer, a driver library layer and an interface service layer. The interface service layer is deployed with a digital twin service that supports the construction of a digital twin model for any physical peripheral, thereby integrating the digital twin technology into the communication module. Then, the digital twin service can directly obtain the multidimensional sensor data of any physical peripheral through the communication module, and use at least one digital twin component built into the driver library layer to process the multidimensional sensor data under the target operating system adopted by the operating system layer to construct a digital twin model of the physical peripheral, so that the hardware network for transmitting data of the physical peripheral is integrated with the software network when the digital twin model is constructed, thereby improving the real-time effectiveness of the data when constructing the digital twin model of any physical peripheral, and ensuring the efficient and accurate construction of the digital twin model of any physical peripheral.

[0032] Figure 1 The schematic diagram of the principle of a digital twin system based on a communication module provided in the embodiment of the present application. Figure 1 As shown, the digital twin system based on the communication module may include a communication module 110 and a digital twin firmware 120.

[0033] Among them, the digital twin firmware 120 may include an operating system layer, a driver library layer and an interface service layer, and the interface service layer may be deployed with a digital twin service that supports building a digital twin model for any physical peripheral.

[0034] Specifically, the digital twin service can obtain the multi-dimensional sensor data of any physical peripheral through the communication module, and process the multi-dimensional sensor data using at least one digital twin component built into the driver library layer under the target operating system adopted by the operating system layer to build a digital twin model of the physical peripheral.

[0035] In some implementations, communication module 110, as an integrated hardware component, can be used to enable data transmission between a device and a network or other devices. This module integrates a communication chip, radio frequency circuitry, protocol stack, and interface circuitry into a single module, simplifying the design process for device networking and enabling widespread application in various scenarios within the Internet of Things (IoT).

[0036] In this application, the communication module 110 serves as the hardware foundation for obtaining relevant peripheral data when building a digital twin model for any physical peripheral and can be deployed at the system hardware layer. By establishing a communication connection with any physical peripheral through the communication module 110, various relevant peripheral data of the physical peripheral during operation and operation can be obtained as multi-dimensional sensor data of the physical peripheral.

[0037] Physical peripherals can be any actual physical object produced or designed in fields such as industrial manufacturing, healthcare, urban planning, and traffic management. Multidimensional sensory data from physical peripherals can include data on shape, temperature, humidity, pressure, operating status, position changes, and other aspects detected in real time by various sensors configured on the physical peripherals during their operation and performance.

[0038] Specifically, if Figure 2 As shown, the communication module 110 can be composed of a core module and various peripheral interfaces. The core module can include a baseband chip, flash storage, RAM storage, a power management module, and a radio frequency module. The baseband chip integrates a central processing unit (CPU), a graphics processing unit (GPU), a channel encoder, a digital signal processor, a modem, and an interface module to implement relevant data processing and transmission.

[0039] For example, the core module can use the Qualcomm Kryo 460 octa-core 64-bit processor, including two Cortex-A76 cores with a main frequency of 2.0GHz and six Cortex-A55 cores with a main frequency of 1.8GHz. It is a multi-network standard intelligent 5G Sub-6GHz module with a built-in Qualcomm AdrenoTM 619 GPU and an Android 13 operating system. It has powerful performance and rich multimedia functions. It adopts 3GPP Release 15 technology, supports 5GNSA and SA modes, is backward compatible with 4G / 3G networks, and also supports IEEE802.11a / b / g / n / ac / ax-ready wireless transmission protocols and Bluetooth 5.1 technology.

[0040] Furthermore, the baseband chip utilizes a Qualcomm Kryo 460 octa-core 64-bit CPU and Adreno™ 619 GPU, integrating a dedicated computational vision DSP to support neural networks and video post-processing. System boot code is embedded in the baseband chip, which reads the bootloader from the Flash memory and executes it from the RAM memory.

[0041] Flash storage can use 1024GB eMMC non-volatile storage to store boot programs, applications, and communication processing programs, and provide storage resources for external services.

[0042] The RAM storage can use 16GB LPDDR4X random access memory for running the Android operating system.

[0043] The RF module is responsible for sending and receiving RF signals. The baseband chip integrates a set of controllers for controlling the RF module, which are used to convert digital signals into wireless communication signals and send them, as well as convert received wireless communication signals into digital signals.

[0044] The power management module can ensure the stable operation of the entire module, control the power-on and power-off timing and power consumption, and ensure the stability and reliability of the system.

[0045] It should be noted that the various hardware structures actually used in the core module of the communication module 110 introduced above are just examples, and this application does not limit them.

[0046] In addition, the peripheral interfaces in the communication module 110 may include a camera interface, a subscriber identity module (SIM) card interface, an antenna interface, a universal asynchronous receiver / transmitter (UART) interface, a general-purpose input / output (GPIO) interface, an integrated circuit bus (I2C) interface, a global navigation satellite system (GNSS) interface, a Bluetooth (BT) interface, a wireless local area network (WIFI) interface, a liquid crystal display (LCD) interface, an audio interface, a serial peripheral interface (SPI), a universal serial bus (USB) interface, a power interface, a memory card (SD) interface, and a TYPE-C interface, so as to accurately collect relevant sensor data of the physical peripherals in any dimension.

[0047] For example, the camera interface may use four groups of 4-lane MIPI CSI with a maximum rate of 1.5 Gbps / lane and support Bayer / YUV formats.

[0048] The SIM card interface can use two sets of (U)SIM interfaces, (U)SIM1 supports 5G / 4G / 3G networks, and (U)SIM2 only supports 4G / 3G networks.

[0049] The antenna interface can include 4 sets of cellular antennas, 2 sets of Wi-Fi antennas and 1 set of GNSS antenna.

[0050] The UART interface can include 3 groups of UART interfaces, one of which supports hardware flow control with a maximum rate of 4.0Mbps, and the other two groups are used as debugging interfaces.

[0051] The GPIO interface can be used to connect and drive light emitting diodes (LEDs), buzzers, relays, etc. It can also be used to read key files, switch status, and pin level status of external integrated circuits (ICs).

[0052] The I2C interface can support the I2C serial bus, simplifying the rigid printed circuit board (PCB) wiring of the hardware circuit, reducing system costs and improving system reliability.

[0053] The GNSS interface can support multiple satellite positioning systems such as GPS / BeiDou / GLONASS to meet the needs of fast and accurate positioning in different environments.

[0054] The BT interface can support the access of Bluetooth devices and supports Bluetooth 5.1 technology.

[0055] The WIFI interface can support the access of WIFI devices and supports Wi-Fi 6, Wi-Fi 6E and 802.11ax-ready protocols.

[0056] The LCD interface can support MIPI_DSI0 and MIPI_DSI1 in the Display Serial Interface (DSI) under the Mobile Industry Processor Interface (MIPI), and dual-screen display is optional.

[0057] The audio interface can be used in conjunction with an external audio Codec chip to provide audio device access function.

[0058] The SPI interface can be a high-speed full-duplex synchronous communication bus that is electrically connected to the core module and only occupies four wires on the pins, saving the pins of the chip and saving space on the PCB layout, providing convenience and being simple and easy to use.

[0059] The USB interface can provide 2 sets of USB interfaces, support USB 3.1 specification, is backward compatible with USB 2.0, and supports USB OTG mode.

[0060] The power interface can be used to supply power using an external power source.

[0061] The SD card interface can support the SD 3.0 specification and 4-bit Secure Digital Input and Output (SDIO) card.

[0062] The TYPE-C port can be used for power supply and main serial port, through which command interaction and firmware download are performed.

[0063] It should be noted that the various hardware structures actually adopted by the peripheral interfaces in the communication module 110 introduced above are merely examples, and this application does not limit them.

[0064] As embedded software running on the hardware of the communication module 110, the array twin firmware 120 may include an operating system layer, a driver library layer, and an interface service layer.

[0065] Among them, the operating system layer, as the software layer closest to the hardware of the communication module 110, can use a target operating system to manage the multi-dimensional sensor data of any physical peripheral obtained through the communication module 110, and provide basic services such as multi-task scheduling, file system, network protocol station, etc. for upper-level applications.

[0066] For example, the operating system layer in this application can adopt the Android Android 13 operating system.

[0067] Furthermore, the driver library layer can directly operate hardware registers or control physical peripherals through the bus, shielding hardware details and providing a standardized interface to the operating system. In this application, the driver library layer can have multiple open source digital twin components built into it to provide various data processing functions in the digital twin service.

[0068] For example, the multiple digital twin components built into the driver library layer may include but are not limited to Unreal Engine, OpenMETA, CesiumJS, OpenLayers, Leaflet, Snapdragon Neural Processing Engine (SNPE) driver, encryption algorithm library and other driver libraries, thereby providing various data processing functions in digital twin services.

[0069] Among them, Unreal Engine can be a high-performance open source engine that is widely used in fields such as virtual reality, film production, and architectural visualization.

[0070] OpenMETA is an open source tool for modeling and simulation that supports multi-domain systems engineering and can be used for the development and research of digital twins.

[0071] CesiumJS is an open source JavaScript library for creating 3D globes and 2D maps in web browsers without the need for plugins. It leverages WebGL capabilities for hardware-accelerated graphics and is cross-platform, cross-browser, and tuned for dynamic data visualization.

[0072] OpenLayers is also an open source map JavaScript library that makes it easy to place dynamic maps in any web page. It can display map tiles, vector data and markers loaded from any source, allowing you to further utilize various geographic information.

[0073] Leaflet is an open source JavaScript library with only 42KB of code that can realize interactive map functions on mobile devices.

[0074] The SNPE driver is the Snapdragon Neural Processing Engine, on which one or more neural network models trained with the Caffe deep learning framework, Caffe2, or TensorFlow, an open source framework for machine learning and deep learning, can run without connecting to the cloud.

[0075] The encryption algorithm library may include conventional symmetric encryption algorithms and asymmetric encryption algorithms such as the Data Encryption Standard (DES), the Secure Hash Algorithm (SHA), and the RSA public key encryption algorithm.

[0076] It should be noted that the digital twin component built into the driver library layer introduced above is an example, and other digital twin components can also be built in, and this application does not limit this.

[0077] Therefore, the driver library layer can further encapsulate the software development kit (SDK) of the above digital twin components to provide external services through the interface service layer in the form of an application program interface (API) in accordance with the specifications of the digital twin service, thereby improving the development efficiency of the digital twin system and lowering the development threshold.

[0078] It is understandable that according to the personalized needs of digital twin services and in accordance with the specifications of digital twin services, developers can be supported to develop multiple new drivers (that is, new digital twin components) within the driver library layer, thereby achieving the scalability of the digital twin components built into the driver library layer.

[0079] The interface service layer can deploy digital twin services that support building corresponding digital twin models for any physical peripheral, shielding the implementation details of various data processing functions provided by the driver library layer. Based on the functional SDK encapsulated by the driver library layer for various digital twin components, a unified API interface can be provided to the outside world to ensure the successful implementation of the digital twin service.

[0080] It can be understood that for the API interface provided by the interface service layer to the digital twin service deployed therein, it can support calling the corresponding API interface to perform various functional configurations on the digital twin service to complete the accurate construction of the digital twin model of any physical peripheral.

[0081] Specifically, after obtaining the multi-dimensional sensor data of any physical peripheral through the communication module 110, the digital twin service can run under the target operating system actually adopted by the operating system layer, and use the multiple digital twin components built into the driver library layer to process the multi-dimensional sensor data of the physical peripheral accordingly, judge the real-time operation and running status of the physical peripheral, and simulate and analyze the real-time status of the physical peripheral, thereby constructing a digital twin model of the physical peripheral.

[0082] The technical solution provided by the embodiment of the present application combines the communication module and the digital twin firmware. The digital twin firmware includes an operating system layer, a driver library layer and an interface service layer. The interface service layer is deployed with a digital twin service that supports the construction of a digital twin model for any physical peripheral, thereby integrating the digital twin technology into the communication module. Then, the digital twin service can directly obtain the multi-dimensional sensor data of any physical peripheral through the communication module, and use at least one digital twin component built into the driver library layer to process the multi-dimensional sensor data under the target operating system adopted by the operating system layer to build a digital twin model of the physical peripheral, so that the hardware network for transmitting data of the physical peripheral is integrated with the software network when the digital twin model is constructed, thereby improving the real-time validity of the data when constructing the digital twin model of any physical peripheral, ensuring the efficient and accurate construction of the digital twin model of any physical peripheral, and expanding the applicable scenarios of the digital twin model under the Internet of Things where the communication module is located.

[0083] As an optional implementation scheme in this application, considering that the various digital twin components built into the driver library layer support the implementation of various data processing functions involved in building a corresponding digital twin model for any physical peripheral, the interface service layer shields the implementation details of the various data processing functions provided by the driver library layer. Based on the functional SDK encapsulated by the driver library layer for various digital twin components, a unified API interface can be provided to the outside world to support the successful implementation of the digital twin service building a corresponding digital twin model for any physical peripheral.

[0084] Then, in order to ensure the accurate construction of the digital twin model, the data processing functions represented by the various digital twin components built into the driver library layer, such as Figure 3 As shown, this application can divide the digital twin service deployed at the interface service layer into three parts: physical entities connected in pairs, digital twins, and digital twin engines.

[0085] At this time, for the specific process of the digital twin service building a corresponding digital twin model for any physical peripheral, the physical entity can obtain the multi-dimensional sensor data of any physical peripheral through the communication module, and transmit the multi-dimensional sensor data to the digital twin and the digital twin engine; the digital twin engine determines the behavior prediction data of the physical peripheral based on the multi-dimensional sensor data, and transmits the behavior prediction data to the digital twin; the digital twin builds a digital twin model of the physical peripheral based on the multi-dimensional sensor data and the behavior prediction data.

[0086] Specifically, for any physical peripheral device for which the digital twin service constructs a digital twin model, the present application can pre-establish a corresponding communication connection between the communication module deployed at the hardware layer and the physical peripheral device. Then, the physical entity can obtain the multi-dimensional sensor data detected in real time by the physical peripheral device during operation and operation through the communication module at the hardware layer. Then, in order to ensure the accurate construction of the digital twin model, the physical entity can transmit the obtained multi-dimensional sensor data of the physical peripheral device to the digital twin and the digital twin engine.

[0087] Furthermore, after receiving multidimensional sensor data detected in real time by the physical peripheral, the digital twin engine can store and back up this multidimensional sensor data. This shows that the digital twin engine can store in real time the multidimensional sensor data detected by the physical peripheral at every moment during its operation and running. The digital twin engine then conducts in-depth analysis of the stored multidimensional sensor data of the physical peripheral within the current time period to determine the physical peripheral's potential operating status, including its potential trends and patterns. This allows it to predict various possible behaviors of the physical peripheral, obtain predicted behavior data, and transmit this predicted behavior data to the digital twin.

[0088] As a result, the digital twin can not only obtain multidimensional sensory data from the physical peripheral, but also obtain behavioral prediction data for the physical peripheral. Therefore, to ensure the accurate construction of the digital twin model, the digital twin can analyze the multidimensional sensory data of the physical peripheral to determine the physical peripheral's specific morphological structure and actual operating status. Furthermore, the digital twin can also analyze the physical peripheral's behavioral prediction data to determine the specific functional structure and functional execution status that the physical peripheral can support for executing various behaviors. In this way, through a comprehensive analysis of the physical peripheral's specific morphological structure and actual operating status, as well as its specific functional structure and functional execution status, a digital model that fully maps to the physical peripheral is constructed, serving as the digital twin model of the physical peripheral.

[0089] In another case, considering that the digital twin service can provide a corresponding service interface (that is, API interface) based on at least one digital twin component built into the driver library layer, it can be seen that according to the data processing functions represented by each digital twin component built into the driver library layer, the digital twin service can provide multiple different service interfaces to ensure the implementation of different functions of the digital twin service.

[0090] Exemplarily, the service interface provided by the digital twin service to the outside world may include a human-computer interaction interface, which supports the digital twin service and external users to perform corresponding diversified interactions on the digital twin model of any physical peripheral through the human-computer interaction interface.

[0091] In this application, after constructing a corresponding digital twin model for any physical peripheral, the digital twin transmits the digital twin model to the digital twin engine. The digital twin engine then displays the digital twin model externally through the human-computer interaction interface in the service interface, obtains external control data for the digital twin model, and transmits it to the digital twin. The digital twin controls the digital twin model to perform corresponding response actions based on the external control data; and / or transmits the external control data to the physical entity, which then controls the physical peripheral to perform corresponding response actions based on the external control data.

[0092] Specifically, for the digital twin model of any physical peripheral, the digital twin service can support external users to intuitively view the digital twin model through the various service interfaces provided to the outside world, and manipulate the digital twin model to simulate and execute various functions that can be achieved by the physical peripheral. Based on the simulation results of the digital twin model, the production parameters of the physical peripheral can be continuously debugged or the digital twin model can be updated to ensure the optimization of the physical peripheral and the digital twin model in different scenarios.

[0093] Therefore, after receiving the digital twin model of any physical peripheral, the digital twin engine can display the digital twin model to external users through the human-computer interaction interface in the external service interface, and support external users to perform corresponding manipulation operations on the digital twin model through the human-computer interaction interface. Thus, for various manipulation operations performed by external users on the digital twin model, the digital twin engine can obtain external manipulation data for the digital twin model. This external manipulation data can represent the specific manipulation operations instructed by the external user on the corresponding part of the digital twin model, which can directly instruct the manipulation of the digital twin model or indirectly instruct the manipulation of the physical peripheral corresponding to the digital twin model.

[0094] Therefore, the digital twin engine can transmit external control data for the digital twin model to the digital twin. The digital twin analyzes the external control data to determine whether the external control data indicates the control of the digital twin model or the operation of the physical peripheral. If the external control data indicates the control of the digital twin model, the digital twin can directly control the digital twin model to perform the corresponding response action according to the specific control operation represented by the external control data. If the external control data indicates the control of the physical peripheral, the digital twin can transmit the external control data to the physical entity, and the physical entity will generate the corresponding peripheral remote control instruction according to the specific control operation represented by the external control data, and send the peripheral remote control instruction to the physical peripheral through the communication module, thereby controlling the physical peripheral to perform the corresponding response action.

[0095] It is understood that after the physical peripheral performs the corresponding response action, the digital twin service can once again obtain the multi-dimensional sensor data of the physical peripheral through the communication module, thereby optimizing the constructed digital twin model according to the above-mentioned digital twin model construction process. After the digital twin model performs the corresponding response operation, the digital twin service can compare and analyze the actual response results of the digital twin model with the ideal results of this operation, thereby optimizing the digital twin model. Based on this, the digital twin service can support the continuous optimization of the digital twin model of any physical peripheral, ensuring the accurate construction of the digital twin model.

[0096] In some possible implementations, in order to ensure the implementation of different functions of physical entities, digital twins and digital twin engines for digital twin services, by analyzing the correlation between the three parts of the physical entity, digital twins and digital twin engines and the data processing functions represented by various digital twin components built into the driver library layer, data function modules related to physical peripherals can be configured in the physical entity, data function modules related to digital twin models can be configured in the digital twin, and other data function modules involved in the digital twin service to build a corresponding digital twin model for any physical peripheral can be configured in the digital twin engine.

[0097] For example, Figure 3 As shown, for data processing functions such as data acquisition, transmission, action response, etc. related to physical peripherals, the physical entities in the digital twin service may include but are not limited to a data acquisition module, a first data transmission module, a first virtual-reality interface module, and an action execution module.

[0098] Specifically, the data acquisition module is responsible for collecting multi-dimensional sensor data from any physical peripheral during operation and performance in real time through the communication module deployed at the hardware layer. The interfaces supported by the communication module for data acquisition may include, but are not limited to, UART, GPIO, I2C, GNSS, BT, WIFI, LCD, audio, SPI, and USB.

[0099] The first data transmission module is responsible for transmitting the multi-dimensional sensor data of any physical peripheral acquired by the data acquisition module to the digital twin engine, which stores a large amount of multi-dimensional sensor data of the physical peripheral during the entire operation and operation process, so as to facilitate subsequent data analysis and monitoring of the physical peripheral in the digital world.

[0100] The first virtual-reality interface module maintains a communication connection with the second virtual-reality interface module in the digital twin, and is responsible for real-time data interaction between the physical entity and the digital twin, ensuring that the relevant data status between the physical peripherals facing the physical entity and the digital twin model facing the digital twin is consistent, thereby supporting the digital twin to build a highly accurate digital twin model for the physical peripherals to simulate the actual operation of the physical peripherals under different conditions, so that the digital twin can conduct various experiments and tests that can be achieved by the physical peripherals on the digital twin model, thereby exploring the optimal solution for the production optimization of the physical peripherals.

[0101] When the first virtual-reality interface module obtains external control data for instructing the physical peripheral to perform a related response operation, the action execution module is responsible for outputting corresponding action execution information to the physical peripheral according to the specific control action indicated by the external control data, thereby controlling the physical peripheral to perform the corresponding response action. For example, the output action execution information may include outputting a pulse signal to control the physical peripheral to drive a stepper motor, or outputting an audio or video signal to control the physical peripheral to play corresponding audio or video content.

[0102] For the data processing functions such as data synchronization, model construction, model optimization, etc. of the digital twin model of any physical peripheral, the digital twin in the digital twin service may include but is not limited to a second virtual-reality interface module, a second data transmission module, a model construction module, a simulation operation module, and a diagnosis and prediction module.

[0103] Specifically, the second virtual-reality interface module maintains a communication connection with the first virtual-reality interface module in the physical entity, responsible for real-time data exchange between the physical entity and the digital twin, ensuring that the relevant data states between the physical peripherals facing the physical entity and the digital twin model facing the digital twin are consistent. As a result, the digital twin can obtain multi-dimensional sensor data from any physical peripheral through the second virtual-reality interface module, allowing the digital twin to build a highly accurate digital twin model for the physical peripheral, so that the digital twin model can accurately reflect the specific operating status of the physical peripheral.

[0104] The second data transmission module is responsible for transmitting the relevant model description data generated by the digital twin during the construction and optimization process of the digital twin model to the digital twin engine, which stores the above-mentioned relevant model description data to facilitate the subsequent presentation of the digital twin model in the digital world and the simulation of related operations of the physical peripherals. In addition, the digital twin engine can predict the possible actions of the physical peripherals by analyzing the multi-dimensional sensor data of the physical peripherals and the relevant model description data of the digital twin model to obtain the behavior prediction data of the physical peripherals. Therefore, the second data transmission module can also be responsible for receiving the behavior prediction data about the physical peripherals issued by the digital twin engine to support the digital twin to optimize the digital twin model.

[0105] The model construction module is responsible for building a digital twin model of the physical peripheral by comprehensively analyzing the multi-dimensional sensor data of the physical peripheral obtained by the second virtual-reality interface module and the behavior prediction data of the physical peripheral received by the second data transmission module through mathematical modeling and simulation technology.

[0106] It should be noted that to ensure efficient and accurate construction of digital twin models, different modeling approaches can be used to build corresponding digital twin models for physical peripherals based on their characteristics and requirements. For example, the model building module can use one or more of the digital twin components represented by drivers such as the Unreal Engine, OpenMETA, CesiumJS, OpenLayers, and Leaflet built into the driver library layer.

[0107] The simulation operation module controls the digital twin model to perform corresponding response operations by obtaining the external control data of the digital twin model and the behavior prediction data of the physical peripherals, so as to simulate the actual operation of the physical peripherals and obtain the specific simulation operation results of the digital twin model under different conditions, so as to test whether there are performance problems with the digital twin model.

[0108] The diagnostic and prediction module is responsible for diagnosing and analyzing the actual operation of the digital twin model simulating physical peripherals. By comparing and analyzing the specific simulation results and expected operation results of the digital twin model under different conditions, it can predict and diagnose possible performance defects of the digital twin model under different conditions, continuously obtain details to be adjusted for the digital twin model, and then continuously optimize the constructed digital twin model through the model construction module, so that the digital twin model can achieve optimal performance or meet specific constraints.

[0109] For data processing functions such as data storage, data analysis, data calculation, model presentation, and model manipulation that may be experienced from physical peripherals to digital twin models, the digital twin engine may include but is not limited to data storage modules, analysis service modules, human-computer interaction modules, knowledge base modules, intelligent computing modules, algorithm library modules, configuration management modules, security management modules, and log modules.

[0110] Specifically, the data storage module can use a corresponding database, such as an SQLite database, to store the multidimensional sensor data transmitted in real time by the physical entity through the first data transmission module and the related model data transmitted by the digital twin through the second data transmission module, thereby providing a real and comprehensive data foundation for the analysis service module and the model construction module in the digital twin.

[0111] The analysis service module conducts in-depth analysis of various storage data in the data storage module, extracts key operating information related to physical peripherals, predicts various action behaviors supported by physical peripherals, obtains behavior prediction data of physical peripherals, stores and backs it up through the data storage module, and transmits it to the digital twin to optimize the digital twin model.

[0112] The human-computer interaction module is responsible for presenting and displaying the digital twin model of the physical peripherals and providing external users with an intuitive and friendly visual interactive interface, thereby realizing the three-dimensional presentation of the digital twin model and the real-time interaction function of external users with the digital twin model.

[0113] The knowledge base module can store knowledge related to digital twin technology and provide a search function so that external users can query it at any time during use. In addition, external users can also import new knowledge into the knowledge base for future reference.

[0114] The intelligent computing module can provide computing power for all other modules and realize various functions required for digital twin services through intelligent computing.

[0115] The algorithm library module has built-in some common algorithms needed to build a digital twin system, including: finite element analysis (FEA), calculation of fluid dynamics (CFD), linear regression, decision tree and random forest, neural network, gradient descent, Kalman filter, Monte Carlo simulation, model predictive control (MPC), etc.

[0116] The configuration management module is responsible for the configuration management of various parameters in the entire digital twin service.

[0117] The security management module is responsible for the security management of the entire digital twin service, including permission management, account management, etc.

[0118] The log module is responsible for logging and querying the entire digital twin service.

[0119] The technical solution provided by the embodiment of the present application is that the physical entity in the digital twin service can directly obtain the multi-dimensional sensor data of any physical peripheral through the communication module, and the digital twin engine in the digital twin service determines the behavior prediction data of the physical peripheral based on the multi-dimensional sensor data, and the digital twin body constructs a digital twin model of the physical peripheral based on the multi-dimensional sensor data and the behavior prediction data, so that the hardware network for transmitting data of the physical peripheral is integrated with the software network when constructing the digital twin model, thereby improving the real-time validity of the data when constructing the digital twin model of any physical peripheral, ensuring the efficient and accurate construction of the digital twin model of any physical peripheral, and expanding the applicable scenarios of the digital twin model in the Internet of Things where the communication module is located.

[0120] The following will provide a detailed description of the specific operational steps performed by the digital twin system based on the communication module from obtaining the corresponding multi-dimensional sensor data from the physical peripherals to building the corresponding digital twin model.

[0121] Figure 4 This is a flowchart of a method for constructing a digital twin model provided in an embodiment of the present application. This embodiment is mainly applied to the digital twin system based on the communication module provided in the above embodiment. Figure 4 , the method may specifically include the following steps:

[0122] S410: Acquire multi-dimensional sensor data of any physical peripheral device.

[0123] For the accurate construction of a digital twin model of any physical peripheral, this application can pre-establish a corresponding communication connection between the communication module deployed at the hardware layer and the physical peripheral. Thus, the communication module at the hardware layer can collect various relevant peripheral data of the physical peripheral during operation and operation in real time as multi-dimensional sensor data of the physical peripheral.

[0124] Physical peripherals can be any actual physical object produced or designed in fields such as industrial manufacturing, healthcare, urban planning, and traffic management. Multidimensional sensory data from physical peripherals can include data on shape, temperature, humidity, pressure, operating status, position changes, and other aspects detected in real time by various sensors configured on the physical peripherals during their operation and performance.

[0125] S420 , determining behavior prediction data of the physical peripheral device based on the multi-dimensional sensing data.

[0126] Considering that physical peripherals can perform operations and operations in multiple dimensions, it means that physical peripherals support the execution of multiple actions. Therefore, in order to ensure the accurate construction of the digital twin model, after obtaining the multi-dimensional sensor data of the physical peripherals, this application can conduct an in-depth analysis of the large amount of multi-dimensional sensor data obtained by the physical peripherals in real time during the current period to determine the potential operating trends and operating rules of the physical peripherals and other operating states, thereby predicting the various actions that the physical peripherals may perform and obtaining the behavior prediction data of the physical peripherals, so that the subsequently constructed digital twin model can fully simulate the various behaviors of the physical peripherals.

[0127] S430, builds a digital twin model of the physical peripheral based on the multi-dimensional sensor data and behavior prediction data.

[0128] In order to ensure the accurate construction of the digital twin model, this application can analyze the multi-dimensional sensor data of the physical peripherals to determine the specific morphological structure and current actual operating status of the physical peripherals. On this basis, this application can also analyze the behavior prediction data of the physical peripherals to determine the specific functional structure and functional execution status of the physical peripherals that can support the execution of various action behaviors. In this way, by comprehensively analyzing the specific morphological structure and actual operating status of the physical peripherals, as well as the specific functional structure and functional execution status, a digital model that is completely mapped to the physical peripheral is constructed as the digital twin model of the physical peripheral.

[0129] In some possible implementations, in order to ensure the accuracy of the digital twin model, during the real-time operation of the physical peripheral, this application will usually combine the various actions of the physical peripheral to continuously optimize the digital twin model. Therefore, this application can construct a digital twin model of any physical peripheral in the following way: based on multi-dimensional sensor data, build a corresponding three-dimensional virtual model for the physical peripheral; run the three-dimensional virtual model based on the behavior prediction data to obtain the corresponding model operation results; based on the model operation results, optimize the three-dimensional virtual model to obtain a digital twin model of the physical peripheral.

[0130] Specifically, for the multi-dimensional sensor data of any physical peripheral, this application can perform in-depth analysis of the multi-dimensional sensor data to determine the specific morphological structure and current actual operating status of the physical peripheral, thereby preliminarily constructing a three-dimensional virtual model of the physical peripheral.

[0131] Taking into account that physical peripherals support the execution of multiple action behaviors, it is also required that the digital twin model of the physical peripherals also support the successful simulation of various action behaviors of the physical peripherals. Therefore, for the behavior prediction data of the physical peripherals, the present application can conduct an in-depth analysis of the behavior prediction data to determine the information of multiple action behaviors that the physical peripherals can support. Then, based on the preliminary constructed three-dimensional virtual model, the three-dimensional virtual model can be controlled to fully execute various behaviors that the physical peripherals can support according to each action behavior, thereby completing the simulation of various behaviors of the physical peripherals and obtaining the corresponding model operation results. The model operation results can indicate whether the three-dimensional virtual model has successfully simulated each action behavior that the physical peripherals can support, as well as the reasons why a certain action behavior has not successfully completed the simulation, so as to subsequently optimize the three-dimensional virtual model.

[0132] Therefore, by comparing and analyzing the information on whether each action behavior represented in the model operation results is successfully simulated and the expected simulation state of each action behavior, we can determine the details that need to be adjusted when the three-dimensional virtual model cannot successfully simulate a certain action behavior, and thereby optimize the three-dimensional virtual model to obtain a digital twin model of the physical peripheral, so that the digital twin model can successfully simulate various action behaviors of the physical peripheral.

[0133] The technical solution provided by the embodiments of this application first obtains multidimensional sensor data from any physical peripheral device to determine the behavior prediction data of the physical peripheral device. Then, by comprehensively analyzing the multidimensional sensor data and behavior prediction data of the physical peripheral device, a digital twin model of the physical peripheral device is constructed. This improves the real-time data validity when constructing the digital twin model of any physical peripheral device, ensures the efficient and accurate construction of the digital twin model of any physical peripheral device, and expands the applicable scenarios of the digital twin model in the Internet of Things where the communication module is located.

[0134] As an optional implementation scheme in this application, it is considered that the digital twin service can provide a corresponding service interface (that is, API interface) to the outside based on at least one digital twin component built into the driver library layer. It can be seen that according to the data processing functions represented by each digital twin component built into the driver library layer, the digital twin service can provide a variety of different service interfaces to the outside to ensure the different functions of the digital twin service. Then, for the digital twin model of any physical peripheral, the human-computer interaction interface in the service interface provided by the digital twin service can support the diversified interaction of external users with the digital twin model of any physical peripheral.

[0135] Therefore, based on the successful construction of the above-mentioned digital twin model, this application can also provide a detailed description of the diverse interactive operations of the digital twin model.

[0136] Figure 5 A flowchart of another method for constructing a digital twin model provided in an embodiment of the present application, which method may specifically include the following steps:

[0137] S510: Acquire multi-dimensional sensor data of any physical peripheral device.

[0138] S520 , determining behavior prediction data of the physical peripheral device based on the multi-dimensional sensing data.

[0139] S530 builds a digital twin model of physical peripherals based on multi-dimensional sensor data and behavior prediction data.

[0140] S540 displays the digital twin model externally and obtains external control data for the digital twin model.

[0141] After building a corresponding digital twin model for any physical peripheral, the present application can display the digital twin model externally through the human-computer interaction interface provided by the digital twin service, and present the digital twin model to external users to support external users to intuitively view the digital twin model and manipulate the digital twin model to simulate the execution of various functions that can be executed by the physical peripheral.

[0142] Therefore, the present application can obtain external user manipulation data on the digital twin model by detecting various manipulation operations performed by the external user on the digital twin model in real time through the human-computer interaction interface. The external manipulation data can represent the specific manipulation operations instructed by the external user on the corresponding parts of the digital twin model, which can directly instruct the manipulation of the digital twin model or indirectly instruct the manipulation of the physical peripherals corresponding to the digital twin model.

[0143] S550: Control the digital twin model and / or physical peripherals to perform corresponding response actions according to the external control data.

[0144] For the external control data of the external user to the digital twin model, this application can analyze the external control data to determine whether the external control data indicates the control of the digital twin model or the operation of the physical peripheral device, so as to control the digital twin model and / or the physical peripheral device to perform corresponding response actions respectively.

[0145] In some possible implementations, for external manipulation of digital twin models and / or physical peripherals, the present application can be implemented in the following manner: if the external manipulation data is peripheral behavior simulation data, the digital twin model is run according to the peripheral behavior simulation data to obtain the corresponding model response results to optimize the digital twin model; if the external manipulation data is peripheral operation data, the physical peripheral is controlled to perform the corresponding response action according to the peripheral operation data.

[0146] In other words, by analyzing the external control data, it is possible to determine whether the external control data is peripheral behavior simulation data or peripheral operation data. Peripheral behavior simulation data can instruct the digital twin model to simulate the execution of a certain action of the physical peripheral, while peripheral operation data can instruct the physical peripheral to perform a certain action.

[0147] Therefore, if the external control data is peripheral behavior simulation data, then the present application can control the digital twin model to simulate and execute the corresponding response action according to the specific action behavior indicated this time by analyzing the specific action behavior simulated by the digital twin model indicated by the peripheral behavior simulation data, and obtain the corresponding model response result. In this way, the information on whether the action behavior is successfully simulated represented in the model response result and the expected simulation state of the action behavior are compared and analyzed to determine whether the digital twin model successfully simulates and executes the action behavior, as well as the details to be adjusted when the digital twin model cannot successfully simulate and execute the action behavior, so as to optimize the digital twin model.

[0148] If the external control data is peripheral operation data, then the present application can generate corresponding peripheral remote control instructions by analyzing the specific action behavior indicated by the external control data, and output the corresponding action execution information to the physical peripheral through the communication module in the form of the peripheral remote control instructions, thereby controlling the physical peripheral to perform the corresponding response action.

[0149] It is understood that after the physical peripheral performs the corresponding response action, the digital twin service can once again obtain the multi-dimensional sensor data of the physical peripheral through the communication module, thereby optimizing the constructed digital twin model according to the above-mentioned digital twin model construction process. After the digital twin model performs the corresponding response operation, the digital twin service can compare and analyze the actual response results of the digital twin model with the ideal results of this operation, thereby optimizing the digital twin model. Based on this, the digital twin service can support the continuous optimization of the digital twin model of any physical peripheral, ensuring the accurate construction of the digital twin model.

[0150] The technical solution provided in the embodiments of the present application can obtain external control data of the external user for the digital twin model for any physical peripheral device by displaying the digital twin model to the outside, thereby controlling the digital twin model and / or the physical peripheral device to perform corresponding response actions, thereby realizing diversified interaction and control of the digital twin model and / or the physical peripheral device, and ensuring the optimization and update of the digital twin model.

[0151] Figure 6 This is a principle block diagram of a device for constructing a digital twin model provided in an embodiment of the present application. This embodiment is mainly configured in the digital twin system based on the communication module provided in the above embodiment. Figure 6 As shown, the apparatus 600 may include:

[0152] Data acquisition module 610, used to acquire multi-dimensional sensor data of any physical peripheral device;

[0153] A behavior prediction module 620, configured to determine behavior prediction data of the physical peripheral device based on the multi-dimensional sensing data;

[0154] The model construction module 630 is used to construct a digital twin model of the physical peripheral device based on the multi-dimensional sensing data and the behavior prediction data.

[0155] In some implementations, the model building module 630 may be specifically configured to:

[0156] constructing a corresponding three-dimensional virtual model for the physical peripheral device based on the multi-dimensional sensing data;

[0157] running the three-dimensional virtual model according to the behavior prediction data to obtain corresponding model running results;

[0158] According to the model operation results, the three-dimensional virtual model is optimized to obtain a digital twin model of the physical peripheral.

[0159] In some implementations, the digital twin model construction device 600 may further include an external control module. The external control module may be used to:

[0160] Displaying the digital twin model externally and obtaining external control data for the digital twin model;

[0161] The digital twin model and / or the physical peripheral device are controlled to perform corresponding response actions according to the external manipulation data.

[0162] In some implementations, the external control module may be specifically used to:

[0163] If the external manipulation data is peripheral behavior simulation data, running the digital twin model according to the peripheral behavior simulation data to obtain a corresponding model response result to optimize the digital twin model;

[0164] If the external manipulation data is peripheral device operation data, the physical peripheral device is controlled to perform a corresponding response action according to the peripheral device operation data.

[0165] In the embodiments of the present application, multidimensional sensor data of any physical peripheral is first obtained to determine the behavior prediction data of the physical peripheral. Then, a digital twin model of the physical peripheral is constructed by comprehensively analyzing the multidimensional sensor data and the behavior prediction data of the physical peripheral. This improves the real-time data validity when constructing the digital twin model of any physical peripheral, ensures the efficient and accurate construction of the digital twin model of any physical peripheral, and expands the applicable scenarios of the digital twin model in the Internet of Things where the communication module is located.

[0166] It should be understood that the device embodiment and the method embodiment may correspond to each other, and similar descriptions may refer to the method embodiment. To avoid repetition, they will not be described here. Specifically, Figure 6 The device 600 shown can execute any method embodiment provided in the present application, and the aforementioned and other operations and / or functions of each module in the device 600 are respectively for implementing the corresponding processes in each method of the embodiment of the present application. For the sake of brevity, they will not be repeated here.

[0167] The above describes the device 600 of the embodiment of the present application from the perspective of functional modules in conjunction with the accompanying drawings. It should be understood that the functional module can be implemented in hardware form, can be implemented by instructions in software form, and can also be implemented by a combination of hardware and software modules. Specifically, the steps of the method embodiment in the embodiment of the present application can be completed by the hardware integrated logic circuit and / or software form instructions in the processor, and the steps of the method disclosed in the embodiment of the present application can be directly embodied as being executed by a hardware decoding processor, or can be executed by a combination of hardware and software modules in the decoding processor. Optionally, the software module can be located in a mature storage medium in the art such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, etc. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps in the above method embodiment in conjunction with its hardware.

[0168] Figure 7 This is a schematic block diagram of an electronic device provided in an embodiment of the present application.

[0169] like Figure 7 As shown, the electronic device 700 may include:

[0170] The memory 710 and the processor 720 are configured to store computer programs and transmit the program code to the processor 720. In other words, the processor 720 can call and run the computer program from the memory 710 to implement the method in the embodiment of the present application.

[0171] For example, the processor 720 may be configured to execute the above method embodiments according to instructions in the computer program.

[0172] In some embodiments of the present application, the processor 720 may include but is not limited to:

[0173] General-purpose processor, digital signal processor (DSP), application-specific integrated circuit (ASIC), field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware components, etc.

[0174] In some embodiments of the present application, the memory 710 includes but is not limited to:

[0175] Volatile memory and / or non-volatile memory. Non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory can be random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of RAM are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct RAM bus random access memory (DR RAM).

[0176] In some embodiments of the present application, the computer program may be divided into one or more modules, which are stored in the memory 710 and executed by the processor 720 to implement the method provided by the present application. The one or more modules may be a series of computer program instruction segments capable of implementing specific functions, and the instruction segments are used to describe the execution process of the computer program in the electronic device.

[0177] like Figure 7 As shown, the electronic device may further include:

[0178] The transceiver 730 may be connected to the processor 720 or the memory 710 .

[0179] The processor 720 may control the transceiver 730 to communicate with other devices. Specifically, the processor 720 may send information or data to other devices or receive information or data sent by other devices. The transceiver 730 may include a transmitter and a receiver. The transceiver 730 may further include one or more antennas.

[0180] It should be understood that the various components in the electronic device are connected via a bus system, wherein the bus system includes not only a data bus but also a power bus, a control bus and a status signal bus.

[0181] The present application also provides a computer storage medium having a computer program stored thereon, which, when executed by a computer, enables the computer to perform the method of the above-mentioned method embodiment. In other words, the present application also provides a computer program product containing instructions, which, when executed by a computer, enables the computer to perform the method of the above-mentioned method embodiment.

[0182] When software is used for implementation, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function according to the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center via a wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) method. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a digital video disc (DVD)), or a semiconductor medium (e.g., a solid state drive (SSD)).

[0183] Those skilled in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0184] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the modules is merely a logical function division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0185] Modules described as separate components may or may not be physically separate, and components displayed as modules may or may not be physical modules, i.e., they may be located in one place or distributed across multiple network elements. Some or all of the modules may be selected based on actual needs to achieve the purpose of the present embodiment. For example, the functional modules in the various embodiments of the present application may be integrated into a processing module, or each module may exist physically separately, or two or more modules may be integrated into a single module.

[0186] The above are only specific embodiments of the present application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A digital twin system based on a communication module, characterized in that: include: Communication module and digital twin firmware, the digital twin firmware includes an operating system layer, a driver library layer and an interface service layer, the interface service layer is deployed with a digital twin service that supports building a digital twin model for any physical peripheral; wherein, The digital twin service obtains multi-dimensional sensor data of any physical peripheral through the communication module, and processes the multi-dimensional sensor data using at least one digital twin component built into the driver library layer under the target operating system adopted by the operating system layer to construct a digital twin model of the physical peripheral.

2. The system according to claim 1, wherein: The digital twin service is divided into two-to-two connected physical entities, digital twins and digital twin engines based on at least one digital twin component built into the driver library layer; wherein, The physical entity obtains multidimensional sensor data of any physical peripheral through the communication module, and transmits the multidimensional sensor data to the digital twin and the digital twin engine; The digital twin engine determines behavior prediction data of the physical peripheral device based on the multi-dimensional sensor data, and transmits the behavior prediction data to the digital twin; The digital twin constructs a digital twin model of the physical peripheral based on the multi-dimensional sensing data and the behavior prediction data.

3. The system according to claim 2, characterized in that The digital twin service provides a corresponding service interface based on at least one digital twin component built into the driver library layer; wherein, The digital twin engine displays the digital twin model externally through the human-computer interaction interface in the service interface, and obtains external control data for the digital twin model and transmits it to the digital twin; The digital twin controls the digital twin model to perform corresponding response actions according to the external control data; and / or, The external control data is transmitted to the physical entity, and the physical entity controls the physical peripheral device to perform a corresponding response action according to the external control data.

4. The system according to claim 1, wherein: The communication module is deployed at the system hardware layer.

5. A method for constructing a digital twin model, characterized in that: Applied to the digital twin system based on the communication module according to any one of claims 1 to 4, the method comprises: Acquire multi-dimensional sensor data from any physical peripheral; Determining behavior prediction data of the physical peripheral device based on the multi-dimensional sensing data; A digital twin model of the physical peripheral is constructed based on the multidimensional sensing data and the behavior prediction data.

6. The method according to claim 5, characterized in that The constructing of a digital twin model of the physical peripheral device based on the multi-dimensional sensing data and the behavior prediction data includes: constructing a corresponding three-dimensional virtual model for the physical peripheral device based on the multi-dimensional sensing data; running the three-dimensional virtual model according to the behavior prediction data to obtain corresponding model running results; According to the model operation results, the three-dimensional virtual model is optimized to obtain a digital twin model of the physical peripheral.

7. The method according to claim 5, characterized in that The method further comprises: Displaying the digital twin model externally and obtaining external control data for the digital twin model; The digital twin model and / or the physical peripheral device are controlled to perform corresponding response actions according to the external manipulation data.

8. The method according to claim 7, characterized in that The controlling the digital twin model and / or the physical peripheral device to perform a corresponding response action according to the external manipulation data includes: If the external manipulation data is peripheral behavior simulation data, running the digital twin model according to the peripheral behavior simulation data to obtain a corresponding model response result to optimize the digital twin model; If the external manipulation data is peripheral device operation data, the physical peripheral device is controlled to perform a corresponding response action according to the peripheral device operation data.

9. A device for constructing a digital twin model, characterized in that: In the digital twin system based on the communication module according to any one of claims 1 to 4, the device includes: Data acquisition module, used to obtain multi-dimensional sensor data of any physical peripheral; a behavior prediction module, configured to determine behavior prediction data of the physical peripheral device based on the multi-dimensional sensing data; A model building module is used to build a digital twin model of the physical peripheral based on the multidimensional sensing data and the behavior prediction data.

10. An electronic device, characterized in that: include: A processor and a memory, the memory being used to store a computer program, and the processor being used to call and run the computer program stored in the memory to execute the method for constructing a digital twin model according to any one of claims 5 to 8.

11. A computer-readable storage medium, characterized in that Used to store a computer program, which enables a computer to execute the method for constructing a digital twin model as described in any one of claims 5 to 8.

Images