Equipment modeling method and device, electronic equipment and storage medium

Abstract

The invention relates to an equipment modeling method and device, electronic equipment and a storage medium. The method comprises the steps that in response to detected object model generation operation, a first data dictionary of target equipment is generated, the target equipment is first equipment or a part contained in the first equipment, and the first data dictionary comprises description information of data needed when an object model is generated; and based on the first data dictionary, determining a target object model corresponding to the target device. According to the method, the labor cost is reduced, and the object model creation efficiency is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a device modeling method, apparatus, electronic device and storage medium. Background Art

[0002] A physical model is a type of information model. It is a digital semantic description of a physical entity. It can abstract physical devices into digital models and describe what the physical device is, what it can do, and what information it can provide to the outside world from three dimensions: attributes, services, and events.

[0003] In related technologies, when creating a physical model of a physical device, technicians model the device according to the structure of the physical device, analyze which components are on the physical device, what data these components have, whether these data belong to attributes or events, and what capabilities these component modules can provide to the outside world. Different components of the physical device are defined from three dimensions: attributes, services, and events, and then data is manually entered to create a physical model. This way of creating a physical model has high labor costs and low efficiency in creating a physical model. Summary of the invention

[0004] In order to overcome the problems existing in the related art, the present disclosure provides a device modeling method, apparatus, electronic device and storage medium.

[0005] According to a first aspect of an embodiment of the present disclosure, a device modeling method is provided, the method comprising:

[0006] In response to detecting a physical model generation operation, generating a first data dictionary of a target device, the target device being a first device or a component included in the first device, the first data dictionary including description information of data required when generating the physical model;

[0007] Based on the first data dictionary, a target object model corresponding to the target device is determined.

[0008] In some embodiments, determining the target object model corresponding to the target device based on the first data dictionary includes:

[0009] comparing the first data dictionary with a second data dictionary, wherein the second data dictionary is a data dictionary stored locally on the first device;

[0010] When the first data dictionary and the second data dictionary are different, updating the object model of the target device based on the first data dictionary to obtain the target object model;

[0011] When the first data dictionary and the second data dictionary are the same, the object model of the target device is determined to be the target object model.

[0012] In some embodiments, updating the object model of the target device based on the first data dictionary to obtain the target object model includes:

[0013] Uploading the first data dictionary to a second device, where the second device is used to update the object model of the target device based on the first data dictionary;

[0014] receiving a physical model update signal sent by the second device;

[0015] Based on the physical model update signal, the physical model of the target device is updated to obtain the target physical model.

[0016] In some embodiments, generating a first data dictionary of the target device includes:

[0017] The first data dictionary is generated by a target application installed in the first device.

[0018] In some embodiments, the method further comprises:

[0019] When the target application is started, determining that the object model generation operation is detected; or,

[0020] When a switching operation on a preset file in the target application is detected, it is determined that the object model generation operation is detected.

[0021] In some embodiments, after determining the target object model corresponding to the target device based on the first data dictionary, the method further includes:

[0022] Collecting target data, where the target data is used to update metadata of the target object model;

[0023] The target data is sent to the second device.

[0024] In some embodiments, the method further comprises:

[0025] receiving collection indication information sent by the second device, where the collection indication information is used to indicate at least one of whether to collect data, a type of collected data, and a frequency of collecting data;

[0026] The target data to be collected:

[0027] Based on the collection instruction information, the target data is collected.

[0028] In some embodiments, generating a first data dictionary of the target device includes:

[0029] A first data dictionary corresponding to a preset module in the target device is generated.

[0030] In some embodiments, when the target device is a first device, the preset module includes at least a motor module and a network module in the first device;

[0031] When the target device is a component, the preset module at least includes a non-slave number sensor module and an electronically controlled configuration generating slave number sensor module.

[0032] According to a second aspect of an embodiment of the present disclosure, a device modeling apparatus is provided, the apparatus comprising:

[0033] A data dictionary generation module is configured to generate a first data dictionary of a target device in response to detecting a physical model generation operation, wherein the target device is a first device or a component included in the first device, and the first data dictionary includes description information of data required when generating the physical model;

[0034] The object model determination module is configured to determine the target object model corresponding to the target device based on the first data dictionary.

[0035] In some embodiments, the physical model determination module is configured to:

[0036] comparing the first data dictionary with a second data dictionary, wherein the second data dictionary is a data dictionary stored locally on the first device;

[0037] When the first data dictionary and the second data dictionary are different, updating the object model of the target device based on the first data dictionary to obtain the target object model;

[0038] When the first data dictionary and the second data dictionary are the same, the object model of the target device is determined to be the target object model.

[0039] In some embodiments, the physical model determination module is configured to:

[0040] Uploading the first data dictionary to a second device, where the second device is used to update the object model of the target device based on the first data dictionary;

[0041] receiving a physical model update signal sent by the second device;

[0042] Based on the physical model update signal, the physical model of the target device is updated to obtain the target physical model.

[0043] In some embodiments, the data dictionary generation module is configured to generate the first data dictionary through a target application installed in the first device.

[0044] In some embodiments, the apparatus further comprises:

[0045] an operation determination module, configured to determine that the object model generation operation is detected when the target application is started; or

[0046] The operation determination module is configured to determine that the object model generation operation is detected when a switching operation on a preset file in the target application is detected.

[0047] In some embodiments, the apparatus further comprises:

[0048] A data collection module is configured to collect target data, wherein the target data is used to update the metadata of the target object model;

[0049] The data uploading module is configured to send the target data to the second device.

[0050] In some embodiments, the apparatus further comprises:

[0051] an indication information receiving module, configured to receive collection indication information sent by the second device, wherein the collection indication information is used to indicate at least one of whether to collect data, the type of collected data, and the frequency of collecting data;

[0052] The data acquisition module is configured to acquire target data based on the acquisition indication information and send the target data to the second device.

[0053] In some embodiments, the data dictionary generation module is configured to generate a first data dictionary corresponding to a preset module in the target device.

[0054] In some embodiments, when the target device is a first device, the preset module includes at least a motor module and a network module in the first device;

[0055] When the target device is a component, the preset module at least includes a non-slave number sensor module and an electronically controlled configuration generating slave number sensor module.

[0056] According to a third aspect of an embodiment of the present disclosure, there is provided an electronic device, including:

[0057] processor;

[0058] a memory for storing processor-executable instructions;

[0059] The processor is configured to execute the method as described in the first aspect of the embodiment of the present disclosure.

[0060] According to a fourth aspect of an embodiment of the present disclosure, a non-temporary computer-readable storage medium is provided. When instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method described in the first aspect of the embodiment of the present disclosure.

[0061] The above method of the present disclosure has the following beneficial effects:

[0062] The method provided by the embodiment of the present disclosure automatically generates a first data dictionary of a target device in response to a physical model generation operation. The first data dictionary includes description information of data required when generating the physical model. Then, based on the first data dictionary, a target physical model corresponding to the target device is determined. In this process, the physical model is automatically generated without manual data entry, thereby reducing labor costs and improving the efficiency of creating physical models.

[0063] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0065] Figure 1 is a flow chart of a device modeling method according to an exemplary embodiment;

[0066] Figure 2 is a flow chart of a device modeling method according to an exemplary embodiment;

[0067] Figure 3 is a schematic diagram showing the interaction between an Internet of Things platform and an automation software platform according to an exemplary embodiment;

[0068] Figure 4 is a flow chart of a device modeling method according to an exemplary embodiment;

[0069] Figure 5 is a flow chart of a device modeling method according to an exemplary embodiment;

[0070] Figure 6 is a block diagram of a device modeling apparatus according to an exemplary embodiment;

[0071] Figure 7 It is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0072] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. Instead, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0073] In the related art, the method of creating object models based on manual input has high labor costs and low efficiency in creating object models. It can only implement top-down modeling solutions, that is, it can only model through input data, and cannot implement bottom-up modeling, that is, it cannot automatically collect data and automatically model. Moreover, the equipment modeling solutions in the related art do not support modeling of multi-level tree structures, which makes it difficult to model complex physical equipment and increases the difficulty of managing object models.

[0074] The device modeling method provided by the embodiment of the present disclosure can not only realize bottom-up automatic modeling, but also support multi-level tree modeling, that is, it can model the entire physical device, and can also model each component in the physical device separately.

[0075] The device modeling method provided in the embodiment of the present disclosure involves a device end and a cloud end, and the modeling of the device end is realized through the interaction between the device end and the cloud end. The device end can be a physical device that can be modeled, such as a mobile phone, a tablet computer, a laptop computer, a smart home device, a wearable device, a production equipment, etc., and the cloud end is the device where the Internet of Things platform is located. The device modeling process is described below by taking the device end as the first device and the cloud end as the second device as an example.

[0076] Figure 1 is a flowchart of a device modeling method according to an exemplary embodiment, which is executed by a first device, see Figure 1 , the method comprises the following steps:

[0077] Step S101 , in response to detecting a physical model generation operation, generating a first data dictionary of a target device, the target device being a first device or a component included in the first device, the first data dictionary including description information of data required when generating the physical model.

[0078] The object model generation operation is used to indicate automatic generation of an object model, and generating an object model includes generating an initial object model or updating an already generated object model. When generating an object model, it is necessary to first understand what the target device is, what it can do, and what information it can provide to the outside. In order to understand this information, it is necessary to generate a first data dictionary, which includes description information of the data required when generating the object model. The description information can be a definition and description of the required data. For example, the description information includes the type of the required data, the data structure, and other information used to describe the required data.

[0079] The target device may be the first device or a component included in the first device, for example, the component may be a module or device in the first device. That is, the embodiment of the present disclosure may model the first device itself or a component in the first device.

[0080] Step S102: determining a target object model corresponding to the target device based on the first data dictionary.

[0081] After obtaining the first data dictionary, a target object model can be generated based on the first data dictionary. The target object model can be an initial object model or an updated object model of an already generated object model. The metadata in the target object model is the data described by the description information in the first data dictionary.

[0082] The method provided by the embodiment of the present disclosure automatically generates a first data dictionary of a target device in response to a physical model generation operation. The first data dictionary includes description information of data required when generating the physical model. Then, based on the first data dictionary, a target physical model corresponding to the target device is determined. In this process, the physical model is automatically generated without manual data entry, thereby reducing labor costs and improving the efficiency of creating physical models.

[0083] Figure 2 is a flowchart of a device modeling method according to an exemplary embodiment, which is executed by a first device, see Figure 2 , the method comprises the following steps:

[0084] Step S201 , in response to detecting a physical model generation operation, generating a first data dictionary of a target device through a target application installed in a first device.

[0085] The target application is an application installed in the first device. For example, the target application may be an automation software platform, industrial control software, or other software that supports automatic generation of object models.

[0086] In some embodiments, when the target application is started, it indicates that the first device and the components in the first device need to work. In order to avoid the physical model not existing or the physical model being wrong at this time, when the target application is started, it is determined that a physical model generation operation is detected so that the physical model can be generated subsequently. Alternatively, when a switching operation to a preset file in the target application is detected, it is determined that a physical model generation operation is detected, wherein the preset file can be a project file, that is, since the first device executes different projects, the various parameters of the first device and the various parameters of the components in the first device will be adjusted for suitability, so that the adjusted first device or components can better execute the corresponding project. Therefore, when a switching operation to a preset file in the target application is detected, it is determined that a physical model generation operation is detected.

[0087] In some embodiments, a first data dictionary corresponding to a preset module in a target device is generated. That is, the first data dictionary includes description information of data related to the preset model. Optionally, when the target device is a first device, the preset module includes at least a motor module and a network module in the first device; when the target device is a component, the preset module includes at least a non-slave number sensor module and an electronic control configuration generating a slave number sensor module. Of course, the preset module can also be other modules in the target device, and the embodiments of the present disclosure are not limited to this.

[0088] It should be noted that in some embodiments, the data of the production site can be classified, and standardized physical models can be established for different categories of data. In this case, when it is necessary to generate a physical model corresponding to a certain category of data, the descriptive information included in the generated first data dictionary is the descriptive information related to the data of this category, so that the physical model corresponding to the data of this category is subsequently generated based on the first data dictionary. For the overall first device, a link relationship can be established between the physical models corresponding to different categories of data, so that the classification of data is clearer and the physical models corresponding to different categories of data are more unified, which improves data interoperability and the efficiency of data interaction.

[0089] Step S202 : comparing the first data dictionary and the second data dictionary, wherein the second data dictionary is a data dictionary stored locally on the first device.

[0090] Among them, the second data dictionary includes description information of data in the generated object model. In the disclosed embodiment, when the first data dictionary and the second data dictionary are the same, it means that the description information of the data required for generating the object model has not changed, and the object model is still generated based on the original data. Therefore, the object model of the target device is determined to be the target object model; when the first data dictionary and the second data dictionary are different, it means that the description information of the data required for generating the object model has changed, and the object model needs to be generated based on the new data. Therefore, based on the first data dictionary, the object model of the target device is updated to obtain the target object model. The process of updating the object model refers to steps S203-S205.

[0091] It should be noted that the embodiment of the present disclosure is described by taking the example of determining whether it is necessary to update the physical model of the target device when the physical model has been generated. In another embodiment, when the physical model has not been created, that is, when the second data dictionary does not exist, the physical model of the target device is generated directly based on the first data dictionary.

[0092] It should be noted that when the first data dictionary and the second data dictionary are different, the first data dictionary is used to overwrite the second data dictionary and the first data dictionary is saved locally. When the object model generation operation is detected next time, the first data dictionary this time will be the second data dictionary next time.

[0093] Step S203: when the first data dictionary and the second data dictionary are different, the first data dictionary is uploaded to the second device, and the second device is used to update the object model of the target device based on the first data dictionary.

[0094] In the disclosed embodiment, the physical model of the target device is stored in the second device in addition to the first device. When the physical model of the target device needs to be updated, the second device can update the physical model of the target device and then send the updated physical model to the first device. Therefore, the first data dictionary is uploaded to the second device, and then the second device updates the physical model of the target device based on the first data dictionary.

[0095] Step S204: receiving a physical model update signal sent by the second device.

[0096] After updating the physical model of the target device, the second device sends a physical model update signal to the second device, the physical model update signal is used to instruct the first device to update the physical model of the target device, and the first device receives the physical model update signal. Optionally, the physical model update signal includes a physical model service file, and the physical model service file is used to describe the updated physical model.

[0097] Step S205: based on the physical model update signal, update the physical model of the target device to obtain the target physical model.

[0098] The first device updates the physical model of the target device based on the physical model update signal to obtain an updated target physical model.

[0099] Step S206: collect target data and send the target data to the second device, where the target data is used to update metadata of the target object model.

[0100] In the disclosed embodiment, the first device may automatically collect target data and send the target data to the second device.

[0101] In some embodiments, target data is collected through a target application, wherein when collecting target data, the target application can establish an association relationship between the collected target data and metadata in the target object model, thereby reducing the manual configuration and customized development costs of data collection and realizing automatic data collection.

[0102] In some embodiments, in order to better control data collection and avoid the first device automatically collecting data that does not meet the requirements, the second device sends collection instruction information to the first device, the first device receives the collection instruction information sent by the second device, and collects target data based on the collection instruction information. The collection instruction information is used to indicate at least one of whether to collect data, the type of data collected, and the frequency of collecting data.

[0103] Optionally, the second device is provided with a collection switch for each type of data, and when the collection switch for a certain type of data is turned on, it is determined that the data of this type needs to be collected.

[0104] Optionally, for data reporting, the data indication information is also used to indicate what types of data are reported. Therefore, the target data may also be sent to the second device based on the data indication information.

[0105] In the embodiment of the present disclosure, the collection and reporting of data are controlled by collecting indication information, so that the control of data collection and data reporting is more flexible.

[0106] The method provided by the embodiment of the present disclosure automatically generates a first data dictionary of a target device in response to a physical model generation operation. The first data dictionary includes description information of data required when generating the physical model. Then, based on the first data dictionary, a target physical model corresponding to the target device is determined. In this process, the physical model is automatically generated without manual data entry, thereby reducing labor costs and improving the efficiency of creating physical models.

[0107] For example, when creating physical models and configuring data collection for three types of data, namely fault logs, sensors, and equipment configuration parameters, it takes an average of one hour to complete the physical model creation and data collection for one piece of production equipment manually, while it takes less than five minutes to complete the physical model creation and data collection for one piece of production equipment using the method provided in the embodiments of the present disclosure.

[0108] In one example, the object model includes at least one of a public object model and a private object model. For example, when the target device is a first device, the object model of the first device includes a public object model and a private object model. For another example, when the target device is a sensor, the object model of the first device includes a private object model.

[0109] Take the creation of a production equipment object model as an example. The object model of the production equipment includes a public object model and a private object model. The process of generating the initial object model is described in Figure 3 The schematic diagram of the interaction between the Internet of Things platform and the automation software platform shown in the figure, first, the Internet of Things platform generates a public object model, the automation software platform generates a private object model, and uploads the private object model to the Internet of Things platform, the Internet of Things platform receives the private object model, and integrates the public object model and the private object model to obtain a complete object model of the production equipment, and then the Internet of Things platform sends the object model to the automation software platform, or the automation software platform actively pulls the object model from the Internet of Things platform. Among them, the Internet of Things platform is located in the second device, and the automation software platform is located in the first device.

[0110] In one example, the target device is a production equipment, and a physical model corresponding to the equipment configuration parameters is generated as an example, see Figure 4 The flowchart of the equipment modeling method shown is that an automation software platform is installed in the production equipment. When the automation software platform is started, or when a switching operation of a project file in the automation software platform is detected, the production equipment maps various parameters of the click module / network module through the automation software platform, automatically generates a first data dictionary, and then compares the first data dictionary with the second data dictionary stored locally. When the first data dictionary and the second data dictionary are the same, the collected data is uploaded; when the first data dictionary and the second data dictionary are different, the first data dictionary overwrites the second data dictionary, and the first data dictionary is used to overwrite the second data dictionary and saved locally, and then the first data dictionary is uploaded to the Internet of Things platform. After receiving the first data dictionary, the Internet of Things platform sends a physical model update signal (new physical model service file) to the production equipment. The production equipment receives the physical model update signal, and then updates the physical model of the production equipment based on the physical model update signal, and then uploads the collected data.

[0111] In one example, the target device is a sensor in a production device, and a physical model corresponding to the sensor data is generated as an example, see Figure 5 The flowchart of the equipment modeling method shown in the figure, an automation software platform is installed in the production equipment, when the automation software platform is started, or when the switching operation of the project file in the automation software platform is detected, the production equipment maps various parameters of the non-slave sensor module (Reseka, intelligent electric batch, light source, etc.) through the automation software platform, automatically generates a first data dictionary, and then compares the first data dictionary with the second data dictionary stored locally (the second data dictionary includes the description information corresponding to the non-slave sensor module). When the first data dictionary and the second data dictionary are the same, the collected data is uploaded periodically; when the first data dictionary and the second data dictionary are different, The electronic control configuration generates various parameters of the slave station and sensor modules (electricity meter, three-phase electricity meter, hygrothermometer, etc.) to generate a third data dictionary, and the first data dictionary and the third data dictionary are used to cover the second data dictionary, and the first data dictionary and the third data dictionary are used to cover the second data dictionary and saved locally. Then, the first data dictionary and the third data dictionary are uploaded to the Internet of Things platform. After receiving the first data dictionary and the third data dictionary, the Internet of Things platform sends a physical model update signal (new physical model service file) to the production equipment. The production equipment receives the physical model update signal, and then updates the physical model of the sensor based on the physical model update signal. After that, the collected data is uploaded.

[0112] Figure 6 is a block diagram of a device modeling apparatus according to an exemplary embodiment. Figure 6 , the device comprises:

[0113] The data dictionary generation module 601 is configured to generate a first data dictionary of a target device in response to detecting a physical model generation operation, where the target device is a first device or a component included in the first device, and the first data dictionary includes description information of data required when generating the physical model;

[0114] The object model determination module 602 is configured to determine a target object model corresponding to the target device based on the first data dictionary.

[0115] In some embodiments, the object model determination module 602 is configured to:

[0116] Comparing the first data dictionary with the second data dictionary, wherein the second data dictionary is a data dictionary stored locally on the first device;

[0117] When the first data dictionary and the second data dictionary are different, updating the object model of the target device based on the first data dictionary to obtain the target object model;

[0118] When the first data dictionary and the second data dictionary are the same, the object model of the target device is determined to be the target object model.

[0119] In some embodiments, the object model determination module 602 is configured to:

[0120] Uploading the first data dictionary to the second device, the second device being used to update the object model of the target device based on the first data dictionary;

[0121] Receiving a physical model update signal sent by a second device;

[0122] Based on the object model update signal, the object model of the target device is updated to obtain the target object model.

[0123] In some embodiments, the data dictionary generation module 601 is configured to generate a first data dictionary through a target application installed in the first device.

[0124] In some embodiments, the apparatus further comprises:

[0125] an operation determination module, configured to determine, when the target application is started, that an object model generation operation is detected; or,

[0126] The operation determination module is configured to determine that a physical model generation operation is detected when a switching operation on a preset file in a target application is detected.

[0127] In some embodiments, the apparatus further comprises:

[0128] A data collection module is configured to collect target data, and the target data is used to update metadata of the target object model;

[0129] The data upload module is configured to send target data to the second device.

[0130] In some embodiments, the apparatus further comprises:

[0131] an indication information receiving module, configured to receive collection indication information sent by the second device, where the collection indication information is used to indicate at least one of whether to collect data, the type of collected data, and the frequency of collecting data;

[0132] The data collection module is configured to collect target data based on the collection indication information and send the target data to the second device.

[0133] In some embodiments, the data dictionary generation module 601 is configured to generate a first data dictionary corresponding to a preset module in the target device.

[0134] In some embodiments, when the target device is a first device, the preset module includes at least a motor module and a network module in the first device;

[0135] When the target device is a component, the preset module at least includes a non-slave number sensor module and an electronic control configuration generating a slave number sensor module.

[0136] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0137] An embodiment of the present disclosure further provides an electronic device, comprising: a processor; and a memory for storing instructions executable by the processor; wherein the processor is configured to execute the device modeling method in the above embodiment.

[0138] Figure 7 is a block diagram of an electronic device 700 according to an exemplary embodiment.

[0139] Reference Figure 7 , the electronic device 700 may include one or more of the following components: a processing component 702 , a memory 704 , a power component 706 , a multimedia component 708 , an audio component 710 , an input / output (I / O) interface 712 , a sensor component 714 , and a communication component 716 .

[0140] The processing component 702 generally controls the overall operation of the electronic device 700, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 702 may include one or more processors 720 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 702 may include one or more modules to facilitate the interaction between the processing component 702 and other components. For example, the processing component 702 may include a multimedia module to facilitate the interaction between the multimedia component 708 and the processing component 702.

[0141] The memory 704 is configured to store various types of data to support operations on the electronic device 700. Examples of such data include instructions for any application or method operating on the electronic device 700, contact data, phone book data, messages, pictures, videos, etc. The memory 704 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0142] The power supply component 706 provides power to various components of the electronic device 700. The power supply component 706 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the electronic device 700.

[0143] The multimedia component 708 includes a screen that provides an output interface between the electronic device 700 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 708 includes a front camera and / or a rear camera. When the electronic device 700 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0144] The audio component 710 is configured to output and / or input audio signals. For example, the audio component 710 includes a microphone (MIC), and when the electronic device 700 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 704 or sent via the communication component 716. In some embodiments, the audio component 710 also includes a speaker for outputting audio signals.

[0145] I / O interface 712 provides an interface between processing component 702 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0146] The sensor assembly 714 includes one or more sensors for providing various aspects of status assessment for the electronic device 700. For example, the sensor assembly 714 can detect the open / closed state of the electronic device 700, the relative positioning of components, such as the display and keypad of the electronic device 700, and the sensor assembly 714 can also detect the position change of the electronic device 700 or a component of the electronic device 700, the presence or absence of user contact with the electronic device 700, the orientation or acceleration / deceleration of the electronic device 700, and the temperature change of the electronic device 700. The sensor assembly 714 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 714 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 714 may also include an acceleration sensor, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0147] The communication component 716 is configured to facilitate wired or wireless communication between the electronic device 700 and other devices. The electronic device 700 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 716 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 716 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0148] In an exemplary embodiment, the electronic device 700 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

[0149] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 704 including instructions, and the instructions can be executed by a processor 720 of an electronic device 700 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0150] The embodiments of the present disclosure also provide a non-temporary computer-readable storage medium. When instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute the device modeling method in the above embodiments.

[0151] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed in this disclosure. The specification and examples are to be considered exemplary only, and the true scope and spirit of the present invention are indicated by the following claims.

[0152] It should be understood that the present invention is not limited to the exact construction that has been described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. A device modeling method, characterized in that: The method comprises: In response to detecting a physical model generation operation, generating a first data dictionary of a target device, the target device being a first device or a component included in the first device, the first data dictionary including description information of data required when generating the physical model; Based on the first data dictionary, a target object model corresponding to the target device is determined.

2. The method according to claim 1, characterized in that The determining, based on the first data dictionary, a target object model corresponding to the target device includes: comparing the first data dictionary with a second data dictionary, wherein the second data dictionary is a data dictionary stored locally on the first device; When the first data dictionary and the second data dictionary are different, updating the object model of the target device based on the first data dictionary to obtain the target object model; When the first data dictionary and the second data dictionary are the same, the object model of the target device is determined to be the target object model.

3. The method according to claim 2, characterized in that The updating the object model of the target device based on the first data dictionary to obtain the target object model includes: Uploading the first data dictionary to a second device, where the second device is used to update the object model of the target device based on the first data dictionary; receiving a physical model update signal sent by the second device; Based on the physical model update signal, the physical model of the target device is updated to obtain the target physical model.

4. The method according to claim 1, characterized in that: The generating a first data dictionary of the target device comprises: The first data dictionary is generated by a target application installed in the first device.

5. The method according to claim 4, characterized in that The method further comprises: When the target application is started, determining that the object model generation operation is detected; or, When a switching operation on a preset file in the target application is detected, it is determined that the object model generation operation is detected.

6. The method according to claim 1, characterized in that After determining the target object model corresponding to the target device based on the first data dictionary, the method further includes: Collecting target data, where the target data is used to update metadata of the target object model; The target data is sent to the second device.

7. The method according to claim 6, characterized in that The method further comprises: receiving collection indication information sent by the second device, where the collection indication information is used to indicate at least one of whether to collect data, a type of collected data, and a frequency of collecting data; The target data to be collected includes: Based on the collection instruction information, the target data is collected.

8. The method according to claim 1, characterized in that The generating a first data dictionary of the target device comprises: A first data dictionary corresponding to a preset module in the target device is generated.

9. The method according to claim 8, characterized in that When the target device is a first device, the preset module at least includes a motor module and a network module in the first device; When the target device is a component, the preset module at least includes a non-slave number sensor module and an electronically controlled configuration generating slave number sensor module.

10. A device modeling apparatus, characterized in that: The device comprises: A data dictionary generation module is configured to generate a first data dictionary of a target device in response to detecting a physical model generation operation, wherein the target device is a first device or a component included in the first device, and the first data dictionary includes description information of data required when generating the physical model; The object model determination module is configured to determine the target object model corresponding to the target device based on the first data dictionary.

11. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to execute the method as claimed in any one of claims 1 to 9.

12. A non-transitory computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method as claimed in any one of claims 1 to 9.

Images