An intelligent vehicle living digital twin control method and its system

Abstract

The present invention discloses an intelligent vehicle living digital twin control method and system, which includes presetting a high-precision digital model according to the physical entities of vehicle living devices equipped with communication protocols, and the user activates the vehicle living devices and is automatically and invisibly connected to the vehicle living digital twin cloud platform; generating a spatial environment digital model according to the physical environment and the high-precision digital model, and matching corresponding behavior data to generate a digital twin model, uploading the user operation data to the vehicle living digital twin cloud platform and converting it into instructions to be sent to the vehicle living devices, which receive the instructions and complete the device operations, and returning the device operation data to the vehicle living digital twin cloud platform, and the vehicle living digital twin cloud platform recommends usage suggestions according to the user operation data. The present invention can automatically generate a digital twin model of a vehicle living space environment with high fidelity, enabling users to view and control vehicle living devices efficiently and intuitively as if they were in the actual physical space when using in-vehicle Internet of Things devices, thereby realizing intelligent suggestions.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent control of the Internet of Vehicles in automobiles, and particularly to an intelligent vehicle living digital twin control method and system thereof. Background Art

[0002] Digital twin refers to the simulation process of reflecting physical entities, processes or systems through digital models. Digital twin models can simulate, predict and optimize the behavior of physical entities. At present, digital twin technology is mostly used in the industrial field, which can optimize production line efficiency, improve equipment maintenance plans and enhance product quality. With the development of technology and industry integration, digital twin technology has gradually entered fields such as urban planning, architecture, healthcare and home life. Vehicle living refers to a way of living inside a vehicle or a type of living style, which is the basis of the third in-vehicle space. Therefore, the application of digital twin technology to vehicle living devices has gradually received extensive attention. Automobile users can intuitively view, monitor and control corresponding vehicle living devices through digital twin models, realizing an intelligent third in-vehicle space.

[0003] In the prior art, the types of devices covered by the in-vehicle Internet of Things are few, and most of the interfaces of current in-vehicle Internet of Things devices adopt traditional user interface designs, that is, the product situation is described by means of text and controls. This results in the fact that traditional in-vehicle Internet of Things devices often have a relatively low level of intelligence, and users cannot search for required products or monitor product changes as intuitively and efficiently as in the real physical space.

[0004] Therefore, how to automatically generate a digital twin model of a highly restored vehicle living space environment, enabling automobile users to feel as if they are in the actual physical space when using in-vehicle Internet of Things devices, thereby efficiently and intuitively viewing and controlling corresponding vehicle living devices, and realizing intelligent service suggestions and recommendations through big data algorithms has become an urgent problem to be solved nowadays. Summary of the Invention

[0005] In order to solve the above problems, the present invention proposes an intelligent vehicle living digital twin control method and system thereof, which can achieve intuitive and efficient interconnection of vehicle living devices, automatically generate a digital twin model of a highly restored vehicle living space environment, enable automobile users to efficiently and intuitively view and control corresponding vehicle living devices, and at the same time realize intelligent service suggestions and recommendations through big data algorithms, bringing convenient and personalized vehicle living experiences to automobile users, and enhancing the intelligent level of automobiles and user experience through real-time vehicle living environment monitoring and remote control functions.

[0006] To achieve the above object, the present invention is realized through the following technical solutions:

[0007] An intelligent vehicle living digital twin control method of the present invention includes:

[0008] After the vehicle interior device is equipped with a communication protocol, a high-precision digital model is preset according to the physical entity of the vehicle interior device and stored in the vehicle interior digital twin cloud platform;

[0009] The user activates the vehicle interior device, and the vehicle interior device is automatically and invisibly connected to the vehicle interior digital twin cloud platform;

[0010] A spatial environment digital model is generated according to the physical environment of the vehicle interior device and the corresponding high-precision digital model. The spatial environment digital model and the behavior data of the vehicle interior device are matched through the communication protocol to generate a digital twin model and stored in the vehicle interior digital twin cloud platform;

[0011] The digital twin model is displayed to the user through the vehicle machine interface. The user operation data of the vehicle machine interface is uploaded to the vehicle interior digital twin cloud platform. The user operation data is converted into an instruction through the communication protocol, and the instruction is sent to the vehicle interior device;

[0012] The vehicle interior device receives the instruction and completes the corresponding device operation, and returns the device operation data to the vehicle interior digital twin cloud platform and synchronously displays it on the vehicle machine interface;

[0013] The vehicle interior digital twin cloud platform recommends corresponding usage suggestions according to the user operation data.

[0014] A further improvement of the present invention is that the vehicle interior devices have the same device model, the corresponding high-precision digital models are the same, and the corresponding high-precision digital model codes are the same.

[0015] A further improvement of the present invention is that the physical environment is obtained by scanning the surrounding space environment of the vehicle interior device through in-vehicle and out-of-vehicle cameras, and the physical environment is uploaded to the vehicle interior digital twin cloud platform.

[0016] A further improvement of the present invention is that the communication protocol sends the field information of the vehicle interior device to the vehicle interior digital twin cloud platform, and the vehicle interior digital twin cloud platform automatically matches the corresponding high-precision digital model of the vehicle interior device according to the field information.

[0017] A further improvement of the present invention is that the generating a spatial environment digital model according to the physical environment of the vehicle interior device and the corresponding high-precision digital model, matching the spatial environment digital model and the behavior data of the vehicle interior device through the communication protocol, generating a digital twin model and storing it in the vehicle interior digital twin cloud platform specifically includes:

[0018] According to the physical environment of the vehicle interior device and the corresponding high-precision digital model, the spatial environment data of the vehicle interior device is obtained;

[0019] Determine the interpolation surface at each data point in the spatial environment data based on the radial basis function:

[0020]

[0021] In the formula, s(x) represents the value of the interpolation surface at the current data point x; n represents the number of adjacent data points of the current data point; δ represents the three-dimensional interpolation coefficient; φ represents the radial basis function; x represents the current data point; x j represents the j-th adjacent data point of the current data point; ||x - x j || represents the distance between the current data point and the j-th adjacent data point; p(x) represents the interpolation stability coefficient at the current data point x; Σ represents the summation symbol;

[0022] Determine the interpolation surfaces at all data points in the spatial environment data, and construct the digital model of the spatial environment of the vehicle interior device;

[0023] After obtaining the digital model of the spatial environment, based on the network optimization algorithm, optimize the digital model of the spatial environment by adjusting the positions of each data point to generate multiple optimized data points. The expression of the optimized data point is:

[0024]

[0025] In the formula, x' represents the optimized data point; x represents the current data point; α represents the smoothing intensity coefficient; n represents the number of adjacent data points of the current data point; x j represents the j-th adjacent data point of the current data point; Σ represents the summation symbol;

[0026] Based on the optimized data points, perform corresponding optimization on the digital model of the spatial environment;

[0027] Match the digital model of the spatial environment and the behavior data of the vehicle interior device through the communication protocol to generate a digital twin model and store it in the vehicle interior digital twin cloud platform.

[0028] A further improvement of the present invention is that: the in-vehicle interface is a three-dimensional visualization user interface, and the user can view the usage status of the vehicle interior device and automatically control the working status of the vehicle interior device through the in-vehicle interface.

[0029] A further improvement of the present invention is that: the vehicle interior digital twin cloud platform identifies and recommends usage suggestions for the vehicle interior device according to the user operation data through big data algorithms, and triggers an alarm device when the vehicle interior device has an abnormality, specifically including:

[0030] Perform a cleaning operation on the user operation data to remove noise and outliers in the user operation data, and generate target operation data;

[0031] Extract operation features from the target operation data and construct a usage recommendation recognition model;

[0032] Based on the usage recommendation recognition model, identify the usage recommendations of the vehicle living equipment according to the operation features:

[0033] y t =f(F t ,θ)

[0034] In the formula, y t represents the usage recommendation of the t-th identified vehicle living equipment; f represents the usage recommendation recognition function; F t represents the t-th operation feature; θ represents the usage recommendation recognition model parameter;

[0035] Determine the loss function corresponding to the usage recommendation recognition model, adjust the usage recommendation recognition model parameter based on the optimization algorithm, minimize the loss function, and determine the optimal usage recommendation recognition model parameter:

[0036]

[0037] In the formula, θ * represents the optimal usage recommendation recognition model parameter; arg min θ represents the θ value output when the expression takes the minimum value; N represents the total number of operation features; represents the standard usage recommendation label corresponding to the t-th operation feature; y t represents the usage recommendation of the t-th identified vehicle living equipment; L represents the loss function; Σ represents the summation symbol;

[0038] Identify and recommend the usage recommendations of the vehicle living equipment according to the user operation data, and trigger an alarm device when the vehicle living equipment has an abnormality.

[0039] An intelligent vehicle living digital twin control system of the present invention includes:

[0040] A data management and storage module, which is used to collect, manage and store the required digital twin data, and perform storage, indexing, backup and recovery operations on the digital twin data;

[0041] A model creation and update module, which is used to create and update a digital twin model according to the physical entity of the vehicle living equipment, and perform parameter configuration, training and optimization on the digital twin model;

[0042] The data analysis and optimization module is used to analyze and optimize the digital twin data. It analyzes the digital twin data through machine learning algorithms and optimization algorithms, identifies potential problems, and provides decision-making suggestions for users.

[0043] The identity security verification module is used to protect the security of the vehicle living digital twin platform, verify user identities, control access, and perform data encryption and security auditing on the digital twin data.

[0044] The integration module is used to provide integration interfaces with external systems and applications, and perform data exchange and sharing with other systems.

[0045] A further improvement of the present invention is that the system further includes a vehicle display module, which is used to perform three-dimensional visual display on the digital twin model, vehicle living device connection, digital twin data, and their analysis and optimization results.

[0046] The beneficial effects of the present invention are as follows: The present invention proposes an intelligent vehicle living digital twin control method and system. After the vehicle living device is equipped with a communication protocol, according to the physical entity of the vehicle living device, a high-precision digital model is preset and stored in the vehicle living digital twin cloud platform; the user activates the vehicle living device, and the vehicle living device is automatically and invisibly connected to the vehicle living digital twin cloud platform; a spatial environment digital model is generated according to the physical environment of the vehicle living device and the corresponding high-precision digital model, and the spatial environment digital model and the behavior data of the vehicle living device are matched through the communication protocol to generate a digital twin model and store it in the vehicle living digital twin cloud platform; the user operation data on the vehicle interface is uploaded to the vehicle living digital twin cloud platform, the user operation data is converted into an instruction through the communication protocol, and the instruction is sent to the vehicle living device; the vehicle living device receives the instruction and completes the corresponding device operation, and returns the device operation data to the vehicle living digital twin cloud platform, and the device operation data is displayed on the vehicle interface; the vehicle living digital twin cloud platform recommends corresponding usage suggestions according to the user operation data, so as to realize intuitive and efficient interconnection of vehicle living devices, and use the three-dimensional space model screen as the user operation interface on the vehicle system, which is intuitive, convenient to operate, and more similar to the human feeling in the real physical space. It can automatically generate a digital twin model of the vehicle living space environment with high fidelity, enabling automotive users to feel like they are in the actual physical space when using in-vehicle Internet of Things devices, and thus efficiently and intuitively view and control the corresponding vehicle living devices. It has lower requirements for the overall computing power demand and is easier to implement in actual vehicle scenarios. It also realizes intelligent service suggestions and recommendations through big data algorithms, creates an intelligent in-vehicle third space, brings convenient and personalized vehicle living experiences to automotive users, and improves the intelligent level of the vehicle and the user experience through real-time vehicle living environment monitoring and remote control functions. Brief Description of the Drawings

[0047] Figure 1Schematic flowchart of an intelligent vehicle and home digital twin control method provided by an embodiment of the present invention;

[0048] Figure 2 Schematic structural diagram of an intelligent vehicle and home digital twin control system provided by an embodiment of the present invention;

[0049] Figure 3 Schematic hardware structure diagram of an electronic device provided by an embodiment of the present invention. Detailed implementation manners

[0050] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0051] Refer to Figure 1 , which is a schematic flowchart of an intelligent vehicle and home digital twin control method provided by an embodiment of the present invention. Figure 1 The execution subject of the method shown may be a software and / or hardware device. The execution subject of the present application may include, but is not limited to, at least one of the following: user equipment, network equipment, etc. Among them, the user equipment may include, but is not limited to, a computer, a smart phone, a personal digital assistant (Personal Digital Assistant, abbreviated as: PDA), and the above-mentioned electronic equipment, etc. The network equipment may include, but is not limited to, a single network server, a server group composed of multiple network servers, or a cloud composed of a large number of computers or network servers based on cloud computing. Among them, cloud computing is a type of distributed computing, which is composed of a group of loosely coupled computers to form a super virtual computer. This embodiment does not make any restrictions. It includes steps S1 to S6, specifically as follows:

[0052] S1, after the vehicle and home equipment is equipped with a communication protocol, a high-precision digital model is preset according to the physical entity of the vehicle and home equipment and stored in the vehicle and home digital twin cloud platform;

[0053] S2, the user activates the vehicle and home equipment, and the vehicle and home equipment is automatically and invisibly connected to the vehicle and home digital twin cloud platform;

[0054] S3, a spatial environment digital model is generated according to the physical environment of the vehicle and home equipment and the corresponding high-precision digital model, and the spatial environment digital model and the behavior data of the vehicle and home equipment are matched through the communication protocol to generate a digital twin model and store it in the vehicle and home digital twin cloud platform;

[0055] In S4, the digital twin model is presented to the user through the in-vehicle head unit interface, and the user operation data of the in-vehicle head unit interface is uploaded to the vehicle living digital twin cloud platform. The user operation data is converted into instructions through the communication protocol, and the instructions are sent to the vehicle living devices;

[0056] In S5, the vehicle living devices receive the instructions and complete the corresponding device operations, and return the device operation data to the vehicle living digital twin cloud platform and synchronously display it on the in-vehicle head unit interface;

[0057] In S6, the vehicle living digital twin cloud platform recommends corresponding usage suggestions according to the user operation data.

[0058] It can be understood that the present invention provides an intelligent vehicle living digital twin control method, which quickly creates a digital model of the device physical entity through the in-vehicle camera and the vehicle living digital twin cloud platform. At the same time, the behavior data of the device is collected through the self-developed communication protocol and injected into the digital model to generate a digital twin model. Thus, the corresponding vehicle living devices can be intuitively monitored and controlled through the vehicle living digital twin cloud platform, which is more in line with the user's intuitive feeling in the real space.

[0059] It should be noted that the user can freely select and match the devices equipped with the specified communication protocol. The self-developed communication protocol refers to the protocol designed and developed by oneself to realize communication between devices or systems. This self-developed communication protocol defines communication rules, data formats, transmission methods, interaction processes, etc., to ensure the effective exchange of information and mutual operation between different devices or systems. And the self-developed communication protocol has advantages such as customization, high optimization, security, and flexibility. The present invention aims to propose a self-developed communication protocol with encrypted communication means and an authentication mechanism for safe and stable mutual communication between devices.

[0060] Among them, encrypted communication refers to using a secure encryption algorithm to protect the confidentiality of communication data. The secure encryption algorithm can be the Advanced Encryption Standard (AES), so as to ensure that the data cannot be read by unauthorized persons or devices during the transmission process. Authentication refers to confirming the authorization authenticity of the device through the authentication mechanism in the communication protocol. This authentication can use digital certificates, keys, or tokens, etc.

[0061] Among them, the device models of the vehicle living devices are the same, the corresponding high-precision digital models are the same, and the corresponding high-precision digital model codes are the same.

[0062] In practical applications, after the vehicle living equipment installs the specified communication protocol, users can monitor and control in-vehicle electrical equipment without feeling, such as refrigerators, TVs, washing machines, etc. in the RV. Since the vehicle living equipment has been equipped with the specified communication protocol, when the control permission is opened on one side of the vehicle and the control permission and transmission field information can be called through the specified communication protocol, where these field information can be authentication information, device type information, security credentials, network parameters, control instructions, etc., device control can be realized through the vehicle living digital twin cloud platform.

[0063] It should be noted that the vehicle living equipment equipped with the specified communication protocol can be divided according to the product model. Before leaving the factory, the physical entities of these vehicle living equipment will be scanned in advance, and corresponding high-precision digital models will be generated in the modeling software according to these physical entities and stored synchronously in the vehicle living digital twin cloud platform. The high-precision digital models corresponding to the vehicle living equipment of the same device model are the same, and the corresponding high-precision digital model codes are the same.

[0064] Among them, the physical environment is obtained by scanning the surrounding space environment of the vehicle living equipment through the in-vehicle and out-of-vehicle cameras, and the physical environment is uploaded to the vehicle living digital twin cloud platform. The communication protocol sends the field information of the vehicle living equipment to the vehicle living digital twin cloud platform, and the vehicle living digital twin cloud platform automatically matches the high-precision digital model corresponding to the vehicle living equipment according to the field information.

[0065] It can be understood that after the user activates the vehicle living equipment equipped with the specified communication protocol, the vehicle living equipment and the vehicle living digital twin cloud platform can be automatically connected without feeling. The communication protocol can send field information such as authentication information, device type information, security credentials, network parameters, control instructions, etc. corresponding to the vehicle living equipment to the vehicle living digital twin cloud platform. The vehicle living digital twin cloud platform can automatically match the high-precision digital model corresponding to the vehicle living equipment, and at the same time call the in-vehicle and out-of-vehicle cameras to scan the space environment where the vehicle living equipment is located to generate the corresponding physical environment. Combining with the high-precision digital model, the corresponding space environment digital model is generated through an automated modeling program and stored in the vehicle living digital twin cloud platform. Combining with the device behavior data in the vehicle living digital twin cloud platform and automatically matching through the communication protocol, a corresponding digital twin model can be generated. It should be noted that both the device behavior data and the digital twin model are stored in the data management and storage module of the intelligent vehicle living digital twin control system.

[0066] Among them, generating a space environment digital model according to the physical environment and the corresponding high-precision digital model of the vehicle living equipment, and matching the space environment digital model and the device behavior data of the vehicle living equipment through the communication protocol to generate a digital twin model and store it in the vehicle living digital twin cloud platform, specifically including:

[0067] Obtain the spatial environment data of the vehicle interior equipment according to the physical environment of the vehicle interior equipment and the corresponding high-precision digital model;

[0068] Based on the radial basis function, determine the interpolation surface at each data point in the spatial environment data:

[0069]

[0070] In the formula, s(x) represents the value of the interpolation surface at the current data point x; n represents the number of adjacent data points of the current data point; δ represents the three-dimensional interpolation coefficient; φ represents the radial basis function; x represents the current data point; x j represents the j-th adjacent data point of the current data point; ||x - x j || represents the distance between the current data point and the j-th adjacent data point; p(x) represents the interpolation stability coefficient at the current data point x; Σ represents the summation symbol;

[0071] Determine the interpolation surfaces at all data points in the spatial environment data, and construct the digital model of the spatial environment of the vehicle interior equipment;

[0072] After obtaining the digital model of the spatial environment, based on the network optimization algorithm, optimize the digital model of the spatial environment by adjusting the position of each data point to generate multiple optimized data points. The expression of the optimized data point is:

[0073]

[0074] In the formula, x' represents the optimized data point; x represents the current data point; α represents the smoothing intensity coefficient; n represents the number of adjacent data points of the current data point; x j represents the j-th adjacent data point of the current data point; Σ represents the summation symbol;

[0075] Based on the optimized data points, perform corresponding optimization on the digital model of the spatial environment;

[0076] Match the digital model of the spatial environment and the behavior data of the vehicle interior equipment through the communication protocol, generate the digital twin model and store it in the vehicle interior digital twin cloud platform.

[0077] Among them, the in-vehicle interface is a three-dimensional visual user interface, and the user can view the usage status of the vehicle interior equipment and automatically control the working status of the vehicle interior equipment through the in-vehicle interface.

[0078] In practical applications, users can enter the vehicle-home digital twin cloud platform through the in-vehicle system interface and view the usage status and control situation of the added devices through a three-dimensional visualization user interface, such as the opening, closing, timing, etc. of the devices; they can also set through the automation program of the vehicle-home digital twin cloud platform, such as turning on a certain device at a specified time and turning off a certain device at the same time, etc. All operation data of the users will be uploaded to the vehicle-home digital twin cloud platform and converted into instructions that can be understood by the devices through a specified communication protocol. The vehicle-home devices receive these instructions and complete the corresponding device operations.

[0079] Furthermore, the device operation data is displayed through the user interface of the in-vehicle system or the mobile terminal, and users can intuitively complete remote monitoring, control, etc. of the devices through the three-dimensional user interface according to their personal needs.

[0080] Among them, the vehicle-home digital twin cloud platform uses big data algorithms to identify and recommend usage suggestions for vehicle-home devices based on user operation data, and triggers an alarm device when an abnormality occurs in the vehicle-home devices, specifically including:

[0081] Perform a cleaning operation on the user operation data to remove noise and outliers in the user operation data and generate target operation data;

[0082] Extract operation features from the target operation data and construct a usage suggestion recognition model;

[0083] Based on the usage suggestion recognition model, identify the usage suggestions for vehicle-home devices according to the operation features:

[0084] y t =f(F t ,θ)

[0085] In the formula, y t represents the usage suggestion of the t-th identified vehicle-home device; f represents the usage suggestion recognition function; F t represents the t-th operation feature; θ represents the usage suggestion recognition model parameter;

[0086] Determine the loss function corresponding to the usage suggestion recognition model, adjust the usage suggestion recognition model parameters based on the optimization algorithm, minimize the loss function, and determine the optimal usage suggestion recognition model parameters:

[0087]

[0088] In the formula, θ * represents the optimal usage suggestion recognition model parameter; arg min θ represents the θ value output when the expression takes the minimum value; N represents the total number of operation features; represents the standard usage suggestion label corresponding to the t-th operation feature; y tIt represents the usage suggestion of the t-th identified vehicle interior device; L represents the loss function; Σ represents the summation symbol;

[0089] Identify and recommend the usage suggestions of vehicle interior devices based on user operation data, and trigger the alarm device when the vehicle interior device has an abnormality.

[0090] It can be understood that for the collected user operation data, including the device viewing and setting data of the user on the in-vehicle interface, the vehicle interior digital twin cloud platform can identify potential problems using big data algorithms and provide targeted decision-making suggestions for users, such as providing intelligent vehicle interior control suggestions; at the same time, the vehicle interior digital twin cloud platform can also customize the warning value, and when the vehicle interior device has an abnormality or reaches the preset threshold, the system can trigger the alarm and notification functions.

[0091] See Figure 2 , which is a schematic structural diagram of an intelligent vehicle interior digital twin control system provided by an embodiment of the present invention. The intelligent vehicle interior digital twin control system includes:

[0092] A data management and storage module, which is used to collect, manage, and store the required digital twin data, and perform storage, indexing, backup, and recovery operations on the digital twin data;

[0093] A model creation and update module, which is used to create and update the digital twin model according to the physical entity of the vehicle interior device, and perform parameter configuration, training, and optimization on the digital twin model;

[0094] A data analysis and optimization module, which is used to analyze and optimize the digital twin data, analyze the digital twin data through machine learning algorithms and optimization algorithms, identify potential problems, and provide decision-making suggestions for users;

[0095] An identity and security verification module, which is used to protect the security of the vehicle interior digital twin platform, verify the user identity and control access, and perform data encryption and security auditing on the digital twin data;

[0096] An integration module, which is used to provide integration interfaces with external systems and application programs, and perform data exchange and sharing with other systems.

[0097] It can be understood that the intelligent vehicle-home digital twin control system includes multiple modules, and each module has response capabilities. The data management and storage module is used to collect, manage, and store the data required for digital twins, including device information, device data, model data, etc. This module has functions such as data storage, data indexing, data backup, and data recovery; the model creation and update module is used to create and update digital twin models to reflect the physical systems or devices in the real world. This module has functions such as modeling tools, model parameter configuration, model training, and optimization; the data analysis and optimization module is used to analyze and optimize digital twin data, identify potential problems, and provide decision-making suggestions for users, such as providing intelligent home control suggestions. This module has data analysis tools, machine learning algorithms, optimization algorithms, and decision support tools, etc.; the identity and security verification module is used to protect the security of the data and functions of the digital twin platform, and has functions such as user identity verification, access control, data encryption, and security auditing; the integration module is used to provide integration interfaces with external systems and application programs, and then conduct data exchange and sharing with other systems. The multiple modules together form the intelligent vehicle-home digital twin control system, which can achieve device communication, automatic creation and optimization of models, cloud storage and computing, ensure data security, and provide external interfaces.

[0098] Among them, the intelligent vehicle-home digital twin control system of the present invention further includes a vehicle-mounted display module for three-dimensional visual display of the digital twin model, vehicle-home device connection, digital twin data, and its analysis and optimization results.

[0099] In practical applications, compared with existing vehicle-home inter-control products, the present invention provides customized functions. By building its own communication protocol and customized vehicle-mounted user interface, it can meet the needs of specific applications, achieve a wider range of device access, and at the same time have high integration. Through the self-built communication protocol, deep integration and seamless communication with intelligent devices can be achieved. Users can directly control and monitor devices on the vehicle-mounted system, providing a more convenient and integrated user experience.

[0100] Figure 2 The device in the illustrated embodiment can correspondingly be used to execute Figure 1 the steps in the illustrated method embodiment, and its implementation principle and technical effects are similar, which will not be elaborated here.

[0101] See Figure 3 , which is a schematic diagram of the hardware structure of an electronic device provided by an embodiment of the present invention. The electronic device 30 includes: a processor 31, a memory 32, and a computer program; among them

[0102] The memory 32 is used to store the computer program, and this memory can also be a flash memory. The computer program is, for example, an application program, a functional module, etc. that implement the above method.

[0103] A processor 31 is configured to execute the computer program stored in the memory to implement each step performed by the device in the above method. For specific details, reference may be made to the relevant descriptions in the foregoing method embodiments.

[0104] Optionally, the memory 32 may be independent or integrated with the processor 31.

[0105] When the memory 32 is a device independent of the processor 31, the device may further include:

[0106] A bus 33 for connecting the memory 32 and the processor 31.

[0107] The present invention further provides a readable storage medium storing a computer program, which when executed by a processor is used to implement the methods provided in the above various embodiments.

[0108] Among them, the readable storage medium may be a computer storage medium or a communication medium. The communication medium includes any medium facilitating the transmission of a computer program from one place to another. The computer storage medium may be any available medium accessible by a general-purpose or special-purpose computer. For example, the readable storage medium is coupled to the processor so that the processor can read information from and write information to the readable storage medium. Of course, the readable storage medium may also be a component of the processor. The processor and the readable storage medium may be located in an application specific integrated circuit (ASIC). Additionally, the ASIC may be located in a user device. Of course, the processor and the readable storage medium may also exist as discrete components in a communication device. The readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0109] The present invention further provides a program product including execution instructions stored in a readable storage medium. At least one processor of the device can read the execution instructions from the readable storage medium, and the execution of the execution instructions by at least one processor causes the device to implement the methods provided in the above various embodiments.

[0110] In an embodiment of the above device, it should be understood that the processor may be a central processing unit (CPU for short), or other general-purpose processors, digital signal processors (DSP for short), application specific integrated circuits (ASIC for short), etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the method disclosed in combination with the present invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules in the processor.

[0111] Through the introduction of the above embodiments, the present invention proposes a vehicle living innovation scenario through the intelligent vehicle living digital twin control method and its system, and proposes an optimized solution including a self-developed communication protocol and a self-developed digital twin cloud platform for various aspects of vehicle limitations. At the same time, based on the algorithm computing power support of the cloud platform, intelligent device monitoring and service recommendation in the vehicle living scenario can be realized. Specifically, after the vehicle living device is equipped with a communication protocol, a high-precision digital model is preset according to the physical entity of the vehicle living device and stored in the vehicle living digital twin cloud platform; the user activates the vehicle living device, and the vehicle living device is automatically and invisibly connected to the vehicle living digital twin cloud platform; a spatial environment digital model is generated according to the physical environment of the vehicle living device and the corresponding high-precision digital model, and the spatial environment digital model and the behavior data of the vehicle living device are matched through the communication protocol to generate a digital twin model and store it in the vehicle living digital twin cloud platform; the user operation data on the vehicle machine interface is uploaded to the vehicle living digital twin cloud platform, and the user operation data is converted into an instruction through the communication protocol and sent to the vehicle living device; the vehicle living device receives the instruction and completes the corresponding device operation, and returns the device operation data to the vehicle living digital twin cloud platform, and displays the device operation data on the vehicle machine interface; the vehicle living digital twin cloud platform recommends corresponding usage suggestions according to the user operation data, so as to realize intuitive and efficient connection of vehicle living devices, and use the three-dimensional space model screen as the user operation interface on the vehicle machine system, which is intuitive, easy to operate, and more similar to the human experience in the real physical space. It can automatically generate a digital twin model of the vehicle living space environment with high fidelity, making the vehicle users feel like they are in the actual physical space when using in-vehicle Internet of Things devices, and then efficiently and intuitively view and control the corresponding vehicle living devices, with lower requirements for the overall computing power, easier to implement in the actual vehicle scenario, and realize intelligent service suggestions and recommendations through big data algorithms, creating an intelligent in-vehicle third space, bringing convenient and personalized vehicle living experiences to vehicle users, and improving the vehicle intelligence level and user experience through real-time vehicle living environment monitoring and remote control functions.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A smart car-housing digital twin control method, characterized in that: include: After the vehicle-housing equipment is equipped with the self-developed communication protocol, a high-precision digital model is preset according to the physical entity of the vehicle-housing equipment and stored in the vehicle-housing digital twin cloud platform; The self-developed communication protocol is a protocol designed and developed by the self-developed team to realize communication between devices or systems. It defines the communication rules, data format, transmission method and interaction process. It is a communication protocol with encrypted communication means and identity authentication mechanism. The user activates the vehicle-home device, and the vehicle-home device is automatically connected to the vehicle-home digital twin cloud platform without any sense; Generate a spatial environment digital model according to the physical environment of the vehicle-dwelling device and the corresponding high-precision digital model, match the spatial environment digital model and the behavior data of the vehicle-dwelling device through the self-developed communication protocol, generate a digital twin model and store it in the vehicle-dwelling digital twin cloud platform; The digital twin model is displayed to the user through the vehicle-machine interface, the user operation data of the vehicle-machine interface is uploaded to the vehicle-home digital twin cloud platform, the user operation data is converted into instructions through the self-developed communication protocol, and the instructions are sent to the vehicle-home device; The vehicle-housing device receives the instruction and completes the corresponding device operation, and returns the device operation data to the vehicle-housing digital twin cloud platform and displays it synchronously on the vehicle-machine interface; The car-home digital twin cloud platform recommends corresponding usage suggestions based on the user operation data.

2. The intelligent vehicle-housing digital twin control method according to claim 1 is characterized in that: The vehicle-housing equipment has the same device model, the same corresponding high-precision digital model, and the same corresponding high-precision digital model code.

3. The intelligent vehicle-housing digital twin control method according to claim 1 is characterized in that: The physical environment is obtained by scanning the surrounding space environment of the vehicle-residence device through cameras inside and outside the vehicle, and the physical environment is uploaded to the vehicle-residence digital twin cloud platform.

4. The intelligent vehicle-housing digital twin control method according to claim 1 is characterized in that: The self-developed communication protocol sends the field information of the vehicle-residence device to the vehicle-residence digital twin cloud platform, and the vehicle-residence digital twin cloud platform automatically matches the high-precision digital model corresponding to the vehicle-residence device according to the field information.

5. The intelligent vehicle-housing digital twin control method according to claim 1 is characterized in that: The method of generating a space environment digital model according to the physical environment of the vehicle-dwelling device and the corresponding high-precision digital model, matching the space environment digital model and the behavior data of the vehicle-dwelling device through the self-developed communication protocol, generating a digital twin model and storing it in the vehicle-dwelling digital twin cloud platform, specifically includes: Obtaining spatial environment data of the vehicle-dwelling device according to the physical environment of the vehicle-dwelling device and the corresponding high-precision digital model; Based on the radial basis function, an interpolation surface at each data point in the spatial environment data is determined: Where s(x) represents the value of the interpolation surface at the current data point x; n represents the number of adjacent data points of the current data point; δ represents the three-dimensional interpolation coefficient; φ represents the radial basis function; x represents the current data point; x j Represents the jth adjacent data point of the current data point; ||xx j || represents the distance between the current data point and the jth adjacent data point; p(x) represents the interpolation stability coefficient at the current data point x; Σ represents the summation symbol; Determine the interpolation surfaces at all data points in the spatial environment data, and construct a digital model of the spatial environment of the vehicle-dwelling device; after obtaining the digital model of the spatial environment, optimize the digital model of the spatial environment by adjusting the position of each data point based on a network optimization algorithm to generate a plurality of optimized data points, wherein the expression of the optimized data point is: In the formula, x' represents the optimized data point; x represents the current data point; α represents the smoothing strength coefficient; n represents the number of adjacent data points of the current data point; x j represents the jth adjacent data point of the current data point; Σ represents the summation symbol; Optimizing the digital model of the space environment accordingly based on the optimized data points; The digital model of the spatial environment and the behavioral data of the vehicle-residence equipment are matched through the self-developed communication protocol to generate a digital twin model and store it in the vehicle-residence digital twin cloud platform.

6. The intelligent vehicle-housing digital twin control method according to claim 1, characterized in that: The vehicle-machine interface is a three-dimensional visual user interface, and the user can view the usage status of the vehicle-residence equipment and automatically control the working status of the vehicle-residence equipment through the vehicle-machine interface.

7. The intelligent vehicle-housing digital twin control method according to claim 1 is characterized in that: The vehicle-home digital twin cloud platform identifies and recommends usage suggestions for the vehicle-home equipment based on the user operation data through a big data algorithm, and triggers an alarm device when an abnormality occurs in the vehicle-home equipment, specifically including: Performing a cleaning operation on the user operation data to remove noise and abnormal values ​​in the user operation data and generate target operation data; Extracting operation features from the target operation data and constructing a usage suggestion recognition model; Based on the usage suggestion identification model, identifying usage suggestions for the vehicle-housing device according to the operation characteristics: y t =f(F t ,i) In the formula, y t represents the usage suggestion of the t-th identified vehicle-housing device; f represents the usage suggestion identification function; F t represents the tth operational feature; θ represents the model parameters identified using the proposal; Determine a loss function corresponding to the usage suggestion recognition model, adjust the usage suggestion recognition model parameters based on an optimization algorithm, minimize the loss function, and determine the optimal usage suggestion recognition model parameters: In the formula, θ * Indicates the optimal use of recommended identification model parameters; argmin θ It represents the value of θ output when the expression takes the minimum value; N represents the total number of operation features; represents the standard usage recommendation label corresponding to the t-th operation feature; y t represents the usage suggestion of the t-th identified vehicle-housing equipment; L represents the loss function; Σ represents the summation symbol; The use suggestions of the vehicle-dwelling equipment are identified and recommended according to the user operation data, and an alarm device is triggered when an abnormality occurs in the vehicle-dwelling equipment.

8. A control system for a smart vehicle-housing digital twin control method according to any one of claims 1 to 7, characterized in that: include: A data management and storage module is used to collect, manage and store the required digital twin data, and to store, index, back up and restore the digital twin data; A model creation and update module is used to create and update a digital twin model based on the physical entity of the vehicle-housing equipment, and to perform parameter configuration, training and optimization on the digital twin model; A data analysis and optimization module is used to analyze and optimize the digital twin data, analyze the digital twin data through machine learning algorithms and optimization algorithms, identify potential problems and provide decision-making suggestions for users; An identity security verification module is used to protect the security of the car-home digital twin platform, verify user identity and control access, and perform data encryption and security audit on the digital twin data; Integration module, which is used to provide integration interface with external systems and applications, and to exchange and share data with other systems.

9. The control system according to claim 8, characterized in that: The system also includes a vehicle-machine display module for three-dimensionally visualizing the digital twin model, vehicle-home equipment connections, digital twin data, and analysis and optimization results thereof.

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