Method and device for generating equipment data processing model

Abstract

The present application discloses a method and apparatus for generating a device data processing model, relating to the field of smart home / intelligent home technology. The method comprises: splitting a set of multi-type single-dimensional indicator parameters according to device type to obtain a set of single-type single-dimensional indicator parameters; obtaining single-type single-dimensional indicator parameters corresponding to a target device type based on the set of single-type single-dimensional indicator parameters; merging the single-type single-dimensional indicator parameters corresponding to the target device type into a set of single-type multi-dimensional indicator parameters according to data processing logic; obtaining data processing logic code corresponding to each single-type multi-dimensional indicator parameter in the set of single-type multi-dimensional indicator parameters, and generating a target device data processing model for the target device type based on the obtained first set of data processing logic codes. The present invention solves the technical problem of low efficiency in calculating indicator parameters for smart home devices.

Description

Technical Field

[0001] The present application relates to the field of smart home / intelligent home technology, and more specifically, to a method and apparatus for generating a device data processing model. Background Art

[0002] With the rapid development of Internet of Things technology, the use of smart home devices has become more and more common. By collecting various indicator parameters of smart home devices during operation through the network, users can understand the operating status of smart home devices in real time. The data information of smart home devices during operation includes but is not limited to electricity consumption, water consumption, device status data, geographic location information, etc. within a specified time.

[0003] However, related technologies often use the same data processing logic to calculate the same metrics for different categories of smart home devices. For example, when calculating the power consumption of a water heater and a refrigerator, the same logic code can be used to calculate both. However, when data calculation tasks are too concentrated and the metrics are highly coupled, the failure of any one calculation task can cause the entire application to fail.

[0004] In addition, as the types of smart home devices increase, the number of indicator parameters of different types of smart home devices is also increasing, which means that the logical codes for calculating different indicator parameters are also relatively numerous. When the number of logical codes reaches a certain level, there may be problems such as inconsistent data indicator caliber and inability to determine which data processing logic to use, resulting in technical problems of low efficiency in the process of calculating the indicator parameters of smart home devices.

[0005] To address the above-mentioned problems, no effective solutions have been proposed so far. Summary of the Invention

[0006] The embodiments of the present application provide a method and apparatus for generating a device data processing model to at least solve the technical problem of low efficiency in calculating indicator parameters of smart home devices.

[0007] According to one aspect of an embodiment of the present application, a method for generating a device data processing model is provided, comprising: splitting a set of multi-type single-dimensional indicator parameters according to device type to obtain a set of single-type single-dimensional indicator parameters, wherein each multi-type single-dimensional indicator parameter is an indicator parameter on a single dimension of multiple different device types, and each single-type single-dimensional indicator parameter is an indicator parameter on a single dimension of a device type; obtaining a single-type single-dimensional indicator parameter corresponding to a target device type according to a set of single-type single-dimensional indicator parameters, obtaining a single-type single-dimensional indicator parameter corresponding to the target device type, wherein different single-type single-dimensional indicator parameters corresponding to the target device type are indicator parameters on different single dimensions of the target device type; merging the single-type single-dimensional indicator parameters corresponding to the target device type into a set of single-type multi-dimensional indicator parameters according to data processing logic. Dimension indicator parameters, wherein each single-type multi-dimensional indicator parameter is an indicator parameter on multiple dimensions of the target device type, and each single-type multi-dimensional indicator parameter is an indicator parameter obtained by executing the same data processing logic on the operating data on each dimension of the multiple dimensions of the target device type; obtaining the data processing logic code corresponding to each single-type multi-dimensional indicator parameter in a group of single-type multi-dimensional indicator parameters, and obtaining a first group of data processing logic codes in total, and generating a target device data processing model of the target device type based on the first group of data processing logic codes, wherein each data processing logic code is used to execute the same data processing logic in the corresponding single-type multi-dimensional indicator parameter, and the target device data processing model is used to determine the indicator parameters on multiple dimensions in each single-type multi-dimensional indicator parameter based on the operating data of the device of the target device type.

[0008] Optionally, the single-type single-dimensional indicator parameters corresponding to the target device type are merged into a group of single-type multi-dimensional indicator parameters according to the data processing logic, including: when the single-type single-dimensional indicator parameters corresponding to the target device type include a first part of single-type single-dimensional indicator parameters that are allowed to be merged and a second part of single-type single-dimensional indicator parameters that cannot be merged, the first part of single-type single-dimensional indicator parameters are merged according to the data processing logic to obtain a group of single-type multi-dimensional indicator parameters; the above method also includes: obtaining the data processing logic code corresponding to each single-type single-dimensional indicator parameter in the second part of single-type single-dimensional indicator parameters to obtain a second group of data processing logic codes; based on the first group of data processing logic codes, generating a target device data processing model for the target device type, including: determining the first group of data processing logic codes and the second group of data processing logic codes as the codes in the target device data processing model.

[0009] Optionally, the single-type single-dimensional indicator parameters corresponding to the above-mentioned target device types are merged into a set of single-type multi-dimensional indicator parameters according to the data processing logic, including: when the single-type single-dimensional indicator parameters corresponding to the target device type are all single-type single-dimensional indicator parameters allowed to be merged, the single-type single-dimensional indicator parameters corresponding to the target device type are merged according to the data processing logic to obtain a set of single-type multi-dimensional indicator parameters.

[0010] Optionally, the above-mentioned obtaining of single-type single-dimensional indicator parameters corresponding to the target device type based on a group of single-type single-dimensional indicator parameters includes: obtaining a first group of single-type single-dimensional indicator parameters corresponding to the target device type from a group of single-type single-dimensional indicator parameters, wherein the single-type single-dimensional indicator parameters corresponding to the target device type include the first group of single-type single-dimensional indicator parameters, and different single-type single-dimensional indicator parameters in the first group of single-type single-dimensional indicator parameters are indicator parameters on different single dimensions of the target device type.

[0011] Optionally, the above-mentioned obtaining of single-type single-dimensional indicator parameters corresponding to the target device type based on a group of single-type single-dimensional indicator parameters includes: obtaining a first group of single-type single-dimensional indicator parameters corresponding to the target device type from a group of single-type single-dimensional indicator parameters, wherein different single-type single-dimensional indicator parameters in the first group of single-type single-dimensional indicator parameters are indicator parameters on different single dimensions of the target device type; obtaining a second group of single-type single-dimensional indicator parameters corresponding to the target device type from a predetermined set of single-type single-dimensional indicator parameters, wherein different single-type single-dimensional indicator parameters in the second group of single-type single-dimensional indicator parameters are indicator parameters on different single dimensions of the target device type, and each single-type single-dimensional indicator parameter in the single-type single-dimensional indicator parameter set is an indicator parameter on a single dimension of a device type; wherein the single-type single-dimensional indicator parameters corresponding to the target device type include the first group of single-type single-dimensional indicator parameters and the second group of single-type single-dimensional indicator parameters.

[0012] Optionally, after converting a set of data processing logic codes into a target device data processing model of the target device type, the above method also includes: obtaining a set of operating data corresponding to each data processing logic code in the first set of data processing logic codes from the operating data of the device of the target device type; inputting a set of operating data corresponding to each data processing logic code into the target device data processing model to obtain the current result of each single-type multi-dimensional indicator parameter in a set of single-type multi-dimensional indicator parameters.

[0013] Optionally, the above-mentioned inputting a group of operating data corresponding to each data processing logic code into the target device data processing model to obtain the current result of each single-type multi-dimensional indicator parameter in a group of single-type multi-dimensional indicator parameters includes: when the i-th group of operating data corresponding to the i-th data processing logic code in the first group of data processing logic codes is obtained, the i-th group of operating data is input into the i-th data processing logic code in the target device data processing model, where i is a positive integer greater than or equal to 1; when the single-type multi-dimensional indicator parameter corresponding to the i-th data processing logic code is the indicator parameter on N dimensions of the target device type, and the i-th group of operating data includes N parts of operating data corresponding to the N dimensions, respectively, using the i-th data processing logic code to execute the same data processing logic on each part of the N parts of the operating data to obtain the current result of the indicator parameter on N dimensions of the target device type, where N is a positive integer greater than or equal to 2.

[0014] According to another aspect of an embodiment of the present application, a device for generating a device data processing model is also provided, including: a first splitting unit, used to split a group of multi-type single-dimensional indicator parameters according to the device type to obtain a group of single-type single-dimensional indicator parameters, wherein each multi-type single-dimensional indicator parameter is an indicator parameter on a single dimension of multiple different device types, and each single-type single-dimensional indicator parameter is an indicator parameter on a single dimension of a device type; a first acquisition unit, used to obtain the single-type single-dimensional indicator parameter corresponding to the target device type based on a group of single-type single-dimensional indicator parameters, and obtain the single-type single-dimensional indicator parameter corresponding to the target device type, wherein the different single-type single-dimensional indicator parameters corresponding to the target device type are indicator parameters on different single dimensions of the target device type; a first processing unit, used to process the single-type single-dimensional indicator parameter corresponding to the target device type according to the data processing logic The plurality of indicators are compiled and merged into a group of single-type multi-dimensional indicator parameters, wherein each single-type multi-dimensional indicator parameter is an indicator parameter on multiple dimensions of the target device type, and each single-type multi-dimensional indicator parameter is an indicator parameter obtained by executing the same data processing logic on the operating data on each dimension of the multiple dimensions of the target device type; a second processing unit is used to obtain the data processing logic code corresponding to each single-type multi-dimensional indicator parameter in a group of single-type multi-dimensional indicator parameters, and a first group of data processing logic codes is obtained in total; and a target device data processing model of the target device type is generated based on the first group of data processing logic codes, wherein each data processing logic code is used to execute the same data processing logic in the corresponding single-type multi-dimensional indicator parameter, and the target device data processing model is used to determine the indicator parameters on multiple dimensions in each single-type multi-dimensional indicator parameter according to the operating data of the device of the target device type.

[0015] According to another aspect of the embodiments of the present application, a computer-readable storage medium is provided, in which a computer program is stored, wherein the computer program is configured to execute the method for generating the device data processing model when running.

[0016] According to another aspect of an embodiment of the present application, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the method for generating the device data processing model through the computer program.

[0017] In an embodiment of the present application, the multi-type, single-dimensional indicator parameters of different device types with high coupling are split to obtain single-type, single-dimensional indicator parameters of the target device type. The data processing logic corresponding to the indicator parameters of the target device type in different dimensions is then merged to obtain a first set of data processing logic code, and a target data processing model is generated. Utilizing this target device data processing model, the current results of each single-type, multi-dimensional indicator parameter corresponding to the target device type can be obtained simultaneously, resolving the technical issue of low efficiency in calculating indicator parameters for smart home devices in related technologies, and achieving the technical effect of improving the efficiency of calculating indicator parameters for the target device type. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments or related technical descriptions. Obviously, for ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0020] Figure 1 is a schematic diagram of a hardware environment for an optional method for generating a device data processing model according to an embodiment of the present application;

[0021] Figure 2 is a flowchart of an optional method for generating a device data processing model according to an embodiment of the present application;

[0022] Figure 3 is a schematic diagram of an optional method for generating a device data processing model according to an embodiment of the present application;

[0023] Figure 4 is a schematic diagram of an optional method for determining codes in a target device data processing model according to an embodiment of the present application;

[0024] Figure 5 This is a schematic diagram of an optional method for obtaining a single-type, single-dimensional indicator parameter of a target device type according to an embodiment of the present application;

[0025] Figure 6 is an overall schematic diagram of an optional method for generating a device data processing model according to an embodiment of the present application;

[0026] Figure 7 This is a schematic diagram of an optional method for establishing an application ledger according to an embodiment of the present application;

[0027] Figure 8 This is a structural block diagram of an optional device data processing model generation apparatus according to an embodiment of the present application;

[0028] Figure 9 This is a structural block diagram of an optional electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.

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

[0031] According to one aspect of an embodiment of the present application, a method for generating a device data processing model is provided. The method for generating a device data processing model is widely used in smart home (Smart Home), smart home, smart home device ecology, smart residential (Intelligence House) ecology and other whole-house intelligent digital control application scenarios. Optionally, in this embodiment, the method for generating the device data processing model can be applied to Figure 1 In the hardware environment shown in FIG. 1 , which is composed of a terminal 102 and a server 104. Figure 1 As shown, the server 104 is connected to the terminal 102 via a network, and can be used to provide services (such as application services, etc.) for the terminal or the client installed on the terminal. Cloud computing and / or edge computing services can be configured on the server or independently of the server to provide data computing services for the server 104.

[0032] The aforementioned network may include, but is not limited to, at least one of the following: a wired network and a wireless network. The aforementioned wired network may include, but is not limited to, at least one of the following: a wide area network, a metropolitan area network, and a local area network. The aforementioned wireless network may include, but is not limited to, at least one of the following: Wi-Fi (Wireless Fidelity) and Bluetooth. The terminal 102 may be, but is not limited to, a PC, a mobile phone, a tablet computer, a smart air conditioner, a smart range hood, a smart refrigerator, a smart oven, a smart stove, a smart washing machine, a smart water heater, a smart washing machine, a smart dishwasher, a smart projection device, a smart TV, a smart clothes drying rack, smart curtains, a smart audio and video player, a smart socket, a smart speaker, a smart fresh air device, smart kitchen and bathroom equipment, smart bathroom equipment, a smart robot vacuum, a smart window cleaning robot, a smart robot mop, a smart air purifier, a smart steamer, a smart microwave oven, a smart kitchen appliance, a smart purifier, a smart water dispenser, a smart door lock, etc.

[0033] The method for generating a device data processing model according to the embodiment of the present application may be executed by the server 104, by the smart device 102, or jointly by the server 104 and the smart device 102. The method for generating a device data processing model according to the embodiment of the present application may be executed by the smart device 102 or by a client installed thereon.

[0034] Taking the method for generating the device data processing model in this embodiment executed by the server 104 as an example, Figure 2 FIG. 1 is a flow chart of an optional method for generating a device data processing model according to an embodiment of the present application, such as Figure 2 As shown, the process of the method may include the following steps:

[0035] Step S202: Split a set of multi-type single-dimensional indicator parameters according to device type to obtain a set of single-type single-dimensional indicator parameters, where each multi-type single-dimensional indicator parameter is an indicator parameter on a single dimension of multiple different device types, and each single-type single-dimensional indicator parameter is an indicator parameter on a single dimension of a single device type;

[0036] In order to better understand the meaning of terms such as multi-type single-dimensional indicator parameters and single-type single-dimensional warranty parameters in the embodiments of this application, the following explains them using smart water heaters and smart refrigerators as examples.

[0037] Assumptions Figure 3 In the example, smart device C1 is a smart water heater, and smart device C2 is a smart air conditioner. The index parameters describing the smart water heater include but are not limited to power consumption, water consumption, flow loss, heating speed, heating efficiency, etc.; the index parameters describing the smart air conditioner include but are not limited to power consumption, flow loss, energy efficiency ratio, heating efficiency, etc. Therefore, the power consumption of the smart water heater and the power consumption of the smart air conditioner belong to the index parameters of the same dimension. Since the smart water heater and the smart air conditioner are of different device types, the power consumption of the smart water heater and the power consumption of the smart air conditioner can also constitute a multi-type single-dimensional index parameter.

[0038] The power consumption, water consumption, flow loss, heating speed, and heating efficiency of a smart water heater each belong to a single-type, single-dimensional indicator parameter. Similarly, the power consumption, flow loss, energy efficiency ratio, and heating efficiency of a smart air conditioner each belong to a single-type, single-dimensional indicator parameter. Each indicator parameter in each multi-type, single-dimensional indicator parameter has the same type, but each single-type, single-dimensional indicator parameter belongs to a different type of smart device.

[0039] In this embodiment, a set of multi-type single-dimensional indicator parameters can be, but is not limited to, Figure 3 P1, P2...P5 shown in (a), where P1, P2...P5 belong to indicator parameters in different dimensions, such as power consumption, water consumption, heating efficiency, etc. The two indicator parameters P in P1 1-1 and P 1-2 are the indicator parameters of smart device C1 and smart device C2 in a single dimension, for example, P 1-1 and P 1-2 They are the power consumption of smart device C1 and smart device C2 respectively.

[0040] In related technologies, two indicator parameters that have no correlation but affect each other's results are usually called coupling indicators, for example, the power consumption of a smart water heater and the power consumption of a smart air conditioner, the heating efficiency of a smart water heater and the heating efficiency of a smart air conditioner, etc., and the same data processing logic is usually used to calculate the coupling indicators. However, since the time when the server collects the power consumption of the smart water heater and the time when the server collects the power consumption of the smart air conditioner may be different during actual operation, the time when the power consumption of the smart water heater and the time when the server collects the power consumption of the smart air conditioner may be inaccurate, or the time when the power consumption of the smart water heater and the time when the server collects the power consumption of the smart air conditioner may not be accurate, or the problem of not being able to collect the power consumption of the smart water heater and the time when the server collects the power consumption of the smart air conditioner on time may occur.

[0041] In order to avoid the above problems, in the embodiment of the present application, a group of multi-type single-dimensional indicator parameters of different device types are split according to the device type, for example, Figure 3 The multiple indicator parameters in P1, P2...P5 shown in (a) are split to obtain Figure 3 A set of single-type and single-dimensional indicator parameters P of the smart device C1 shown in (b) 1-1 、P 2-1 ...P 5-1 , and a set of single-type single-dimensional indicator parameters P of smart device C2 1-2 、P 2-2 ...P 5-2 .

[0042] It is easy to understand that the number and type of indicator parameters in the smart device C1 and the smart device C2 in this embodiment are only an example and are not limited thereto. For example, P 1-1 、P 2-1 ...P n-1 , where n is any positive integer greater than or equal to 2.

[0043] Step S204: obtaining a single-type, single-dimensional indicator parameter corresponding to the target device type based on a set of single-type, single-dimensional indicator parameters, wherein different single-type, single-dimensional indicator parameters corresponding to the target device type are indicator parameters on different single dimensions of the target device type;

[0044] Assuming that the target device is smart device C1, and the device type of C1 is a water heater, according to the device type of the water heater, the two groups of single-type single-dimensional indicator parameters P are split 1-1 、P 2-1 ...P 5-1 and P 1-2 、P 2-2 ...P 5-2 Get the single-type, single-dimension indicator parameter P of the smart device C11-1 、P 2-1 ...P 5-1 .

[0045] Similarly, assuming that the target device is smart device C2, and the device type of C2 is air conditioning, according to the device type of water heater, the two groups of single-type single-dimensional indicator parameters P are split 1-1 、P 2-1 ...P 5-1 and P 1-2 、P 2-2 ...P 5-2 Get the single-type single-dimension indicator parameter P of the smart device C2 1-2 、P 2-2 ...P 5-2 .

[0046] Step S206: Merge the single-type, single-dimensional indicator parameters corresponding to the target device type into a set of single-type, multi-dimensional indicator parameters according to the data processing logic, wherein each single-type, multi-dimensional indicator parameter is an indicator parameter for multiple dimensions of the target device type, and each single-type, multi-dimensional indicator parameter is an indicator parameter obtained by executing the same data processing logic on the operating data for each dimension of the multiple dimensions of the target device type;

[0047] Assume that the single-type single-dimensional index parameter P of the smart water heater 1-1 、P 2-1 ...P 5-1 The data processing logic (computation logic) of P 1-1 、P 2-1 ...P 5-1 Indicator parameters with the same or partially identical calculation logic are merged, for example, Figure 3 As shown in (c), P 1-1 、P 2-1 Merge into a single-type multi-dimensional indicator parameter, and 3-1 、P 4-1 、P 5-1 Merge into another single-type multi-dimensional indicator parameter.

[0048] In this embodiment, P 1-1 It can be but not limited to the power consumption of smart water heaters, P 2-1 It can be but not limited to the heating efficiency of smart water heaters. 1-1 and P 2-1 In the process of , the same data processing logic needs to be executed. In other words, by executing the same logic code, two indicator parameters P can be generated at the same time. 1-1 and P 2-1Similarly, by executing another piece of the same logic code, three indicator parameters P can be generated at the same time. 3-1 、P 4-1 and P 5-1 .

[0049] It should be noted that P 1-1 and P 2-1 They belong to the index parameters of two different dimensions of smart water heaters, P 3-1 、P 4-1 and P 5-1 The indicator parameters of three different dimensions are also obtained separately, but by executing the same logical code, P can be obtained at the same time. 1-1 and P 2-1 The current result of P 3-1 、P 4-1 and P 5-1 The current results.

[0050] Step S208, obtain the data processing logic code corresponding to each single-type multi-dimensional indicator parameter in a set of single-type multi-dimensional indicator parameters, and obtain a first set of data processing logic codes, and generate a target device data processing model of the target device type based on the first set of data processing logic codes, wherein each data processing logic code is used to execute the same data processing logic in the corresponding single-type multi-dimensional indicator parameter, and the target device data processing model is used to determine the indicator parameters on multiple dimensions in each single-type multi-dimensional indicator parameter based on the operating data of the device of the target device type.

[0051] Assume that, by executing the logic code code1, P 1-1 and P 2-1 The current result of P can be obtained by executing the logic code code2. 3-1 、P 4-1 and P 5-1 Then, based on a set of data processing logic codes composed of logic codes code1 and code2, a target device data processing model for smart device C1 can be generated.

[0052] Using the same method, the indicator parameter P in the smart device C2 can also be 1-2 、P 2-2 ...P 5-2 The parameters are merged into a set of single-type multi-dimensional indicator parameters, and the target device data processing model of the smart device C2 is generated according to the data processing logic code corresponding to each single-type multi-dimensional indicator parameter.

[0053] It's easy to understand that the logic codes code1 and code2 in this embodiment are merely examples and are not limiting. In other words, in actual application scenarios, different numbers of logic codes can be assigned to different smart devices based on the division method within a set of single-type, multi-dimensional indicator parameters. These different numbers of logic codes can then be combined into a first set of data processing logic codes, ultimately yielding a target device data processing model corresponding to the smart device.

[0054] Through the above-mentioned embodiments provided by this application, by splitting the multi-type, single-dimensional indicator parameters of different device types with high coupling, a single-type, single-dimensional indicator parameter of the target device type is obtained, and then the data processing logic corresponding to the indicator parameters of the target device type on different dimensions is merged to obtain a first set of data processing logic code, and a target data processing model is generated. Using this target device data processing model, the current result of each single-type, multi-dimensional indicator parameter corresponding to the target device type can be obtained simultaneously, solving the technical problem of low efficiency in the process of calculating the indicator parameters of smart home devices in the related art, and achieving the technical effect of improving the efficiency of calculating the indicator parameters of the target device type.

[0055] As an optional example, the single-type, single-dimensional indicator parameters corresponding to the target device type are merged into a set of single-type, multi-dimensional indicator parameters according to the data processing logic, including:

[0056] In a case where the single-type single-dimensional indicator parameters corresponding to the target device type include a first portion of single-type single-dimensional indicator parameters that are allowed to be merged and a second portion of single-type single-dimensional indicator parameters that cannot be merged, merging the first portion of single-type single-dimensional indicator parameters according to the data processing logic to obtain a set of single-type multi-dimensional indicator parameters;

[0057] The above method also includes: obtaining the data processing logic code corresponding to each single-type single-dimensional indicator parameter in the second part of the single-type single-dimensional indicator parameters to obtain a second group of data processing logic codes; generating a target device data processing model of the target device type based on the first group of data processing logic codes, including: determining the first group of data processing logic codes and the second group of data processing logic codes as the codes in the target device data processing model.

[0058] like Figure 4 As shown, assuming that the target device is smart device C1, the single-type single-dimensional indicator parameters corresponding to smart device C1 include but are not limited to P 1-1 、P 2-1 ...P 5-1 , where P 1-1 、P 2-1 ...P 5-1The first part of the single-type single-dimension index parameter P that is allowed to be merged is included 1-1 、P 2-1 、P 3-1 、P 4-1 , and the second part of the single-type single-dimensional indicator parameter P that cannot be merged 5-1 , then the code in the target device data processing model of the smart device C1 is determined by executing the following steps, specifically including:

[0059] S41, according to the data processing logic, the first part of the single-type single-dimensional indicator parameters P corresponding to the smart device C1 1-1 、P 2-1 、P 3-1 、P 4-1 Merge into two single-type multi-dimensional indicator parameters;

[0060] like Figure 4 As shown, P 1-1 、P 2-1 Merge into a single-type multi-dimensional indicator parameter, and 3-1 、P 4-1 Merge into another single-type multi-dimensional indicator parameter, and form a set of single-type multi-dimensional indicator parameters by combining two single-type multi-dimensional indicator parameters.

[0061] S42, obtain P 1-1 、P 2-1 The corresponding data processing logic code code1, and P 3-1 、P 4-1 The corresponding data processing logic code code2, and code1 and code2 form the first set of data processing logic code;

[0062] S43, obtain P 5-1 The corresponding data processing logic code code3 is used as the second set of data processing logic code;

[0063] S44 , determining the code in the target device data processing model of the smart device C1 according to the first set of data processing logic codes and the second set of data processing logic codes.

[0064] As another optional example, the single-type, single-dimensional indicator parameters corresponding to the target device type are merged into a set of single-type, multi-dimensional indicator parameters according to data processing logic, including:

[0065] When the single-type single-dimensional indicator parameters corresponding to the target device type are all single-type single-dimensional indicator parameters that are allowed to be merged, the single-type single-dimensional indicator parameters corresponding to the target device type are merged according to the data processing logic to obtain a set of single-type multi-dimensional indicator parameters.

[0066] For details, please refer to Figure 3 As shown in (c), assuming that the target device C1 has a set of single-type and single-dimensional indicator parameters P 1-1 、P 2-1 、P 3-1 、P 4-1 、P 5-1 All are single-type and single-dimension indicator parameters that can be merged, and P 1-1 、P 2-1 Merge into a single-type multi-dimensional indicator parameter, and 3-1 、P 4-1 、P 5-1 Merge into another single-type multi-dimensional indicator parameter.

[0067] Get P 1-1 、P 2-1 The corresponding data processing logic code code1, and P 3-1 、P 4-1 、P 5-1 The corresponding data processing logic code code2 is generated, and code1 and code2 are combined into a first group of data processing logic codes, and the first group of data processing logic codes is determined as the codes in the target device data processing model of the target device C1.

[0068] It should be noted that the number of single-type single-dimensional indicator parameters corresponding to smart devices of different device types is different. For each type of smart device, the different numbers of single-type single-dimensional indicator parameters corresponding to it can be merged into different numbers of single-type multi-dimensional indicator parameters according to the data processing logic of the single-type single-dimensional indicator parameters.

[0069] By adopting the above method, by merging the single-type and single-dimensional indicator parameters that are allowed to be merged, the same data processing logic is executed to obtain indicator parameters of two different dimensions at the same time, which not only improves the accuracy of the indicator parameters, but also achieves the technical effect of improving the efficiency of calculating the indicator parameters of the target device type.

[0070] As an optional example, the above-mentioned obtaining the single-type single-dimensional indicator parameter corresponding to the target device type according to the set of single-type single-dimensional indicator parameters includes:

[0071] A first group of single-type single-dimensional indicator parameters corresponding to the target device type is obtained from a group of single-type single-dimensional indicator parameters, wherein the single-type single-dimensional indicator parameters corresponding to the target device type include the first group of single-type single-dimensional indicator parameters, and different single-type single-dimensional indicator parameters in the first group of single-type single-dimensional indicator parameters are indicator parameters on different single dimensions of the target device type.

[0072] like Figure 3 As shown in the figure, after splitting a set of multi-type single-dimensional indicator parameters according to the device type, a set of single-type single-dimensional indicator parameters P is obtained. 1-1 、P 2-1 ...P 5-1 , P 1-1 、P 2-1 ...P 5-1 , depending on the type of target device, from P 1-1 、P 2-1 ...P 5-1 , P 1-1 、P 2-1 ...P 5-1 Get the first set of single-type single-dimension indicator parameters P corresponding to the target device 1-1 、P 2-1 ...P 5-1 .

[0073] Among them, the first group of single-type single-dimensional indicator parameters P 1-1 、P 2-1 ...P 5-1 The different single-type single-dimensional indicator parameters in are indicator parameters on different single dimensions of the smart device C1, for example, P 1-1 、P 2-1 ...P 5-1 are the power consumption, water consumption, flow loss, heating speed, and heating efficiency of the smart water heater, and P 1-1 、P 2-1 ...P 5-1 These are indicator parameters of different dimensions of smart water heaters.

[0074] It should be noted that, in addition to the above-mentioned set of single-type single-dimensional indicator parameters P directly from the split 1-1 、P 2- 1...P 5-1 , P 1-1 、P 2-1 ...P 5-1 Get the first set of single-type single-dimension indicator parameters P corresponding to the target device 1-1 、P 2- 1...P 5-1 In addition, you can also obtain the single-type and single-dimensional indicator parameters corresponding to the target device type in the following way:

[0075] Obtaining a first group of single-type single-dimensional indicator parameters corresponding to the target device type from a group of single-type single-dimensional indicator parameters, wherein different single-type single-dimensional indicator parameters in the first group of single-type single-dimensional indicator parameters are indicator parameters on different single dimensions of the target device type;

[0076] Obtaining a second set of single-type, single-dimensional indicator parameters corresponding to the target device type from a predetermined set of single-type, single-dimensional indicator parameters, wherein different single-type, single-dimensional indicator parameters in the second set of single-type, single-dimensional indicator parameters are indicator parameters on different single dimensions of the target device type, and each single-type, single-dimensional indicator parameter in the set of single-type, single-dimensional indicator parameters is an indicator parameter on a single dimension of a device type;

[0077] The single-type single-dimensional indicator parameters corresponding to the target device type include a first group of single-type single-dimensional indicator parameters and a second group of single-type single-dimensional indicator parameters.

[0078] like Figure 5 As shown, according to the implementation method in the above embodiment, a first group of single-type single-dimensional indicator parameters P corresponding to the target device type is obtained from a group of single-type single-dimensional indicator parameters. 1-1 、P 2-1 ...P 5-1 Then, a second set of single-type single-dimensional indicator parameters P corresponding to the target device type is obtained from the predetermined single-type single-dimensional indicator parameter set. 6-1 、P 7-1 、P 8-1 .

[0079] According to the first set of single-type single-dimensional indicator parameters and the second set of single-type single-dimensional indicator parameters, the single-type single-dimensional indicator parameter P corresponding to the target device type is obtained. 1-1 、P 2-1 ...P 5-1 , P 6-1 、P 7-1 、P 8-1 .

[0080] It should be noted that the second group of single-type single-dimensional indicator parameters P 6-1 、P 7-1 、P 8-1 It can be, but is not limited to, an indicator parameter unique to the smart device C1, and the data processing logic corresponding to this type of indicator parameter is quite different from the first group of single-type, single-dimensional indicator parameters. For example, the energy efficiency ratio of a smart air conditioner belongs to an indicator parameter unique to this type of device, and the data processing logic for calculating the energy efficiency ratio is different from that for calculating the above indicator parameter P. 1-1 、P 2-1 ...P 5-1 There are big differences between them.

[0081] Furthermore, for the second group of single-type single-dimensional indicator parameters P 6-1 、P 7-1 、P 8-1For example, it is also possible to optimize the corresponding data processing logic so that the optimized data processing logic can meet the current business needs, improve the calculation efficiency of such data indicators, and enhance the adaptability of the data processing logic.

[0082] As an optional example, after converting a set of data processing logic codes into a target device data processing model of the target device type, the method further includes:

[0083] Acquire, from the operating data of a device of the target device type, a set of operating data corresponding to each data processing logic code in the first set of data processing logic codes;

[0084] A set of operating data corresponding to each data processing logic code is input into the target device data processing model to obtain the current result of each single-type multi-dimensional indicator parameter in a set of single-type multi-dimensional indicator parameters.

[0085] When the target device data processing model of the target device type is obtained by the method in the above embodiment, the acquired operation data of the smart device C1 includes, for example, the power consumption, water consumption, heating efficiency, etc. of the smart water heater.

[0086] like Figure 3 As shown in (c), it is assumed that by inputting the operating data of the smart device C1 into the logic code code1 in the first set of data processing logic codes, the current results of the heating speed and heating efficiency of the smart device C1 (smart water heater) can be calculated at the same time; by inputting the operating data of the smart device C1 into the logic code code2 in the first set of data processing logic codes, the current results of the power consumption, water consumption and flow loss of the smart device C1 (smart water heater) can be calculated at the same time.

[0087] Among them, the logical codes code1 and code2 can also be understood as an application for calculating the indicator parameters of smart devices. Assuming that calculating the electricity consumption of a smart water heater is a workflow, the relationship between the workflow and the application can be, but is not limited to, an intersection relationship, that is, one workflow can correspond to multiple applications, and one application can have multiple workflows.

[0088] By inputting the operating data of the device of the target device type into the target device data processing model and executing each data processing logic code in the first set of data processing logic codes, the current result of each single-type multi-dimensional indicator parameter of the target device can be obtained.

[0089] As an optional example, a set of running data corresponding to each data processing logic code is input into the target device data processing model to obtain the current result of each single-type multi-dimensional indicator parameter in a set of single-type multi-dimensional indicator parameters, including:

[0090] When an i-th set of operating data corresponding to the i-th data processing logic code in the first set of data processing logic codes is obtained, inputting the i-th set of operating data into the i-th data processing logic code in the data processing model of the target device, where i is a positive integer greater than or equal to 1;

[0091] When the single-type multi-dimensional indicator parameters corresponding to the i-th data processing logic code are indicator parameters on N dimensions of the target device type, and the i-th group of operating data includes N parts of operating data corresponding to the N dimensions, the i-th data processing logic code is used to execute the same data processing logic on each of the N parts of operating data to obtain the current results of the indicator parameters on N dimensions of the target device type, where N is a positive integer greater than or equal to 2.

[0092] By looping through the above steps, the current result of each single-type multi-dimensional indicator parameter in a set of single-type multi-dimensional indicator parameters can be obtained.

[0093] Exemplarily, when the current results of various indicator parameters of the target device are obtained by utilizing the target device data processing model, the target device can also be controlled according to the current results of the various indicator parameters. For example, when the heating efficiency of the air conditioner exceeds the efficiency threshold (for example, exceeds 2.11), the air conditioner is adjusted to the energy-saving operation mode.

[0094] It should be noted that for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by this application.

[0095] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the relevant technology, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM (Read-Only Memory, Read-Only Memory) / RAM (Random Access Memory, Random Access Memory), a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0096] According to another aspect of the embodiments of the present application, there is also provided a device data processing model generation apparatus for implementing the above-mentioned device data processing model generation method. Figure 8 This is a structural block diagram of an optional device data processing model generation device according to an embodiment of the present application, such as Figure 8 As shown, the device may include:

[0097] A first splitting unit 802 is configured to split a set of multi-type single-dimensional indicator parameters according to device type to obtain a set of single-type single-dimensional indicator parameters, wherein each multi-type single-dimensional indicator parameter is an indicator parameter on a single dimension of multiple different device types, and each single-type single-dimensional indicator parameter is an indicator parameter on a single dimension of a single device type;

[0098] In order to better understand the meaning of terms such as multi-type single-dimensional indicator parameters and single-type single-dimensional warranty parameters in the embodiments of this application, the following explains them using smart water heaters and smart refrigerators as examples.

[0099] Assumptions Figure 3 In the example, smart device C1 is a smart water heater, and smart device C2 is a smart air conditioner. The index parameters describing the smart water heater include but are not limited to power consumption, water consumption, flow loss, heating speed, heating efficiency, etc.; the index parameters describing the smart air conditioner include but are not limited to power consumption, flow loss, energy efficiency ratio, heating efficiency, etc. Therefore, the power consumption of the smart water heater and the power consumption of the smart air conditioner belong to the index parameters of the same dimension. Since the smart water heater and the smart air conditioner are of different device types, the power consumption of the smart water heater and the power consumption of the smart air conditioner can also constitute a multi-type single-dimensional index parameter.

[0100] The power consumption, water consumption, flow loss, heating speed, and heating efficiency of a smart water heater each belong to a single-type, single-dimensional indicator parameter. Similarly, the power consumption, flow loss, energy efficiency ratio, and heating efficiency of a smart air conditioner each belong to a single-type, single-dimensional indicator parameter. Each indicator parameter in each multi-type, single-dimensional indicator parameter has the same type, but each single-type, single-dimensional indicator parameter belongs to a different type of smart device.

[0101] In this embodiment, a set of multi-type single-dimensional indicator parameters can be, but is not limited to, Figure 3 P1, P2...P5 shown in (a), where P1, P2...P5 belong to indicator parameters in different dimensions, such as power consumption, water consumption, heating efficiency, etc. The two indicator parameters P in P1 1-1 and P 1-2 are the indicator parameters of smart device C1 and smart device C2 in a single dimension, for example, P 1-1 and P 1-2 They are the power consumption of smart device C1 and smart device C2 respectively.

[0102] In related technologies, two indicator parameters that have no correlation but affect each other's results are usually called coupling indicators, for example, the power consumption of a smart water heater and the power consumption of a smart air conditioner, the heating efficiency of a smart water heater and the heating efficiency of a smart air conditioner, etc., and the same data processing logic is usually used to calculate the coupling indicators. However, since the time when the server collects the power consumption of the smart water heater and the time when the server collects the power consumption of the smart air conditioner may be different during actual operation, the time when the power consumption of the smart water heater and the time when the server collects the power consumption of the smart air conditioner may be inaccurate, or the time when the power consumption of the smart water heater and the time when the server collects the power consumption of the smart air conditioner may not be accurate, or the problem of not being able to collect the power consumption of the smart water heater and the time when the server collects the power consumption of the smart air conditioner on time may occur.

[0103] In order to avoid the above problems, in an embodiment of the present application, a set of multi-type single-dimensional indicator parameters of different device types are split according to the device type, for example, Figure 3 The multiple indicator parameters in P1, P2...P5 shown in (a) are split to obtain Figure 3 A set of single-type and single-dimensional indicator parameters P of the smart device C1 shown in (b) 1-1 、P 2-1 ...P 5-1 , and a set of single-type single-dimensional indicator parameters P of smart device C2 1-2 、P 2-2 ...P 5-2 .

[0104] It is easy to understand that the number and type of indicator parameters in the smart device C1 and the smart device C2 in this embodiment are only an example and are not limited thereto. For example, P 1-1 、P 2-1 ...P n-1 , where n is any positive integer greater than or equal to 2.

[0105] The first acquisition unit 804 is connected to the first splitting unit 802, and is used to obtain the single-type single-dimensional indicator parameters corresponding to the target device type based on a set of single-type single-dimensional indicator parameters, wherein the different single-type single-dimensional indicator parameters corresponding to the target device type are indicator parameters on different single dimensions of the target device type.

[0106] Assuming that the target device is smart device C1, and the device type of C1 is a water heater, according to the device type of the water heater, the two groups of single-type single-dimensional indicator parameters P are split 1-1 、P 2-1 ...P 5-1 and P 1-2 、P 2-2 ...P 5-2 Get the single-type, single-dimension indicator parameter P of the smart device C1 1-1 、P 2-1 ...P 5-1 .

[0107] Similarly, assuming that the target device is smart device C2, and the device type of C2 is air conditioning, according to the device type of water heater, the two groups of single-type single-dimensional indicator parameters P are split 1-1 、P 2-1 ...P 5-1 and P 1-2 、P 2-2 ...P 5-2 Get the single-type single-dimension indicator parameter P of the smart device C2 1-2 、P 2-2 ...P 5-2 .

[0108] The first processing unit 806 is connected to the first acquisition unit 804, and is used to merge the single-type single-dimensional indicator parameters corresponding to the target device type into a group of single-type multi-dimensional indicator parameters according to the data processing logic, wherein each single-type multi-dimensional indicator parameter is an indicator parameter on multiple dimensions of the target device type, and each single-type multi-dimensional indicator parameter is an indicator parameter obtained by executing the same data processing logic on the operating data on each dimension of the multiple dimensions of the target device type.

[0109] Assume that the single-type single-dimensional index parameter P of the smart water heater 1-1 、P2-1 ...P 5-1 The data processing logic (computation logic) of P 1-1 、P 2-1 ...P 5-1 Indicator parameters with the same or partially identical calculation logic are merged, for example, Figure 3 As shown in (c), P 1-1 、P 2-1 Merge into a single-type multi-dimensional indicator parameter, and 3-1 、P 4-1 、P 5-1 Merge into another single-type multi-dimensional indicator parameter.

[0110] In this embodiment, P 1-1 It can be but not limited to the power consumption of smart water heaters, P 2-1 It can be but not limited to the heating efficiency of smart water heaters. 1-1 and P 2-1 In the process of , the same data processing logic needs to be executed. In other words, by executing the same logic code, two indicator parameters P can be generated at the same time. 1-1 and P 2-1 Similarly, by executing another piece of the same logic code, three indicator parameters P can be generated at the same time. 3-1 、P 4-1 and P 5-1 .

[0111] It should be noted that P 1-1 and P 2-1 They belong to the index parameters of two different dimensions of smart water heaters, P 3-1 、P 4-1 and P 5-1 The indicator parameters of three different dimensions are also obtained separately, but by executing the same logical code, P can be obtained at the same time. 1-1 and P 2-1 The current result of P 3-1 、P 4-1 and P 5-1 The current results.

[0112] The second processing unit 808 is connected to the first processing unit 806, and is used to obtain the data processing logic code corresponding to each single-type multi-dimensional indicator parameter in a set of single-type multi-dimensional indicator parameters, and obtain a first set of data processing logic codes in total, and generate a target device data processing model of the target device type based on the first set of data processing logic codes, wherein each data processing logic code is used to execute the same data processing logic in the corresponding single-type multi-dimensional indicator parameter, and the target device data processing model is used to determine the indicator parameters on multiple dimensions in each single-type multi-dimensional indicator parameter based on the operating data of the device of the target device type.

[0113] Assume that, by executing the logic code code1, P 1-1 and P 2-1 The current result of P can be obtained by executing the logic code code2. 3-1 、P 4-1 and P 5-1 Then, based on a set of data processing logic codes composed of logic codes code1 and code2, a target device data processing model for smart device C1 can be generated.

[0114] Using the same method, the indicator parameter P in the smart device C2 can also be 1-2 、P 2-2 ...P 5-2 The parameters are merged into a set of single-type multi-dimensional indicator parameters, and the target device data processing model of the smart device C2 is generated according to the data processing logic code corresponding to each single-type multi-dimensional indicator parameter.

[0115] It's easy to understand that the logic codes code1 and code2 in this embodiment are merely examples and are not limiting. In other words, in actual application scenarios, different numbers of logic codes can be assigned to different smart devices based on the division method within a set of single-type, multi-dimensional indicator parameters. These different numbers of logic codes can then be combined into a first set of data processing logic codes, ultimately yielding a target device data processing model corresponding to the smart device.

[0116] By applying the device data processing model generation device to the above-mentioned embodiment provided in this application, the multi-type single-dimensional indicator parameters of different device types with high coupling are split to obtain single-type single-dimensional indicator parameters of the target device type, and then the data processing logic corresponding to the indicator parameters on different dimensions of the target device type is merged to obtain a first set of data processing logic code, and a target data processing model is generated. Utilizing this target device data processing model, the current result of each single-type multi-dimensional indicator parameter corresponding to the target device type can be obtained simultaneously, solving the technical problem of low efficiency in calculating the indicator parameters of smart home devices in the related art, and achieving the technical effect of improving the efficiency of calculating the indicator parameters of the target device type.

[0117] It should be noted that the first splitting unit 802 in this embodiment can be used to execute the above step S202, the first acquisition unit 804 in this embodiment can be used to execute the above step S204, the first processing unit 806 in this embodiment can be used to execute the above step S206, and the second processing unit 808 in this embodiment can be used to execute the above step S208.

[0118] By applying the above-mentioned apparatus to the method for generating the device data processing model, the multi-type, single-dimensional indicator parameters of different highly coupled device types are split to obtain single-type, single-dimensional indicator parameters of the target device type. The data processing logic corresponding to the indicator parameters of the different dimensions of the target device type is then merged to obtain a first set of data processing logic code, and a target data processing model is generated. Utilizing this target device data processing model, the current results for each single-type, multi-dimensional indicator parameter corresponding to the target device type can be simultaneously obtained, resolving the technical issue of low efficiency in calculating indicator parameters for smart home devices in related technologies and achieving the technical effect of improving the efficiency of calculating indicator parameters for the target device type.

[0119] Optionally, the above device includes:

[0120] a third processing unit, configured to, when the single-type single-dimensional indicator parameters corresponding to the target device type include a first portion of single-type single-dimensional indicator parameters that are allowed to be merged and a second portion of single-type single-dimensional indicator parameters that cannot be merged, merge the first portion of single-type single-dimensional indicator parameters according to a data processing logic to obtain a set of single-type multi-dimensional indicator parameters;

[0121] a fourth processing unit, configured to obtain a data processing logic code corresponding to each single-type single-dimensional indicator parameter in the second part of the single-type single-dimensional indicator parameters, to obtain a second set of data processing logic codes;

[0122] Generating a target device data processing model of the target device type according to the first set of data processing logic codes includes: determining the first set of data processing logic codes and the second set of data processing logic codes as codes in the target device data processing model.

[0123] Optionally, the first processing unit 806 includes:

[0124] The merging module is used to merge the single-type, single-dimensional indicator parameters corresponding to the target device type according to the data processing logic when the single-type, single-dimensional indicator parameters corresponding to the target device type are all single-type, single-dimensional indicator parameters allowed to be merged, so as to obtain a set of single-type, multi-dimensional indicator parameters.

[0125] Optionally, the first obtaining unit 804 includes:

[0126] The first acquisition module is used to obtain a first group of single-type single-dimensional indicator parameters corresponding to the target device type from a group of single-type single-dimensional indicator parameters, wherein the single-type single-dimensional indicator parameters corresponding to the target device type include the first group of single-type single-dimensional indicator parameters, and different single-type single-dimensional indicator parameters in the first group of single-type single-dimensional indicator parameters are indicator parameters on different single dimensions of the target device type.

[0127] Optionally, the first obtaining unit 804 further includes:

[0128] A second acquisition module is configured to acquire a first group of single-type single-dimensional indicator parameters corresponding to the target device type from a group of single-type single-dimensional indicator parameters, wherein different single-type single-dimensional indicator parameters in the first group of single-type single-dimensional indicator parameters are indicator parameters on different single dimensions of the target device type;

[0129] a third acquisition module, configured to acquire a second set of single-type single-dimensional indicator parameters corresponding to the target device type from a predetermined set of single-type single-dimensional indicator parameters, wherein different single-type single-dimensional indicator parameters in the second set of single-type single-dimensional indicator parameters are indicator parameters on different single dimensions of the target device type, and each single-type single-dimensional indicator parameter in the set of single-type single-dimensional indicator parameters is an indicator parameter on a single dimension of a device type;

[0130] The single-type single-dimensional indicator parameters corresponding to the target device type include a first group of single-type single-dimensional indicator parameters and a second group of single-type single-dimensional indicator parameters.

[0131] Optionally, the above device further includes:

[0132] a second acquiring unit, configured to acquire, from the operating data of a device of the target device type, a set of operating data corresponding to each data processing logic code in the first set of data processing logic codes;

[0133] The fifth processing unit is used to input a set of operating data corresponding to each data processing logic code into the target device data processing model to obtain the current result of each single-type multi-dimensional indicator parameter in a set of single-type multi-dimensional indicator parameters.

[0134] Optionally, the fifth processing unit includes:

[0135] a first processing module configured to, upon obtaining an i-th set of operating data corresponding to the i-th data processing logic code in the first set of data processing logic codes, input the i-th set of operating data into the i-th data processing logic code in the data processing model of the target device, where i is a positive integer greater than or equal to 1;

[0136] The second processing module is used to use the i-th data processing logic code to execute the same data processing logic on each of the N parts of the operating data when the single-type multi-dimensional indicator parameter corresponding to the i-th data processing logic code is the indicator parameter on the N dimensions of the target device type, and the i-th group of operating data includes N parts of the operating data corresponding to the N dimensions, to obtain the current result of the indicator parameter on the N dimensions of the target device type, wherein N is a positive integer greater than or equal to 2.

[0137] It should be noted that the examples and functional scenarios implemented by the above modules and corresponding steps are the same, but are not limited to the contents disclosed in the above embodiments. It should be noted that the above modules as part of the device can be run on Figure 1 The hardware environment shown can be implemented through software or hardware, wherein the hardware environment includes a network environment.

[0138] According to another aspect of the embodiments of the present application, a storage medium is further provided. Optionally, in this embodiment, the storage medium can be used to execute the program code of any of the above-mentioned methods for generating a device data processing model in the embodiments of the present application.

[0139] Optionally, in this embodiment, the above-mentioned storage medium may be located on at least one network device among the multiple network devices in the network shown in the above-mentioned embodiment.

[0140] Optionally, in this embodiment, the storage medium is configured to store program codes for executing the following steps:

[0141] S1, splitting a set of multi-type single-dimensional indicator parameters according to device type to obtain a set of single-type single-dimensional indicator parameters, wherein each of the multi-type single-dimensional indicator parameters is an indicator parameter on a single dimension of multiple different device types, and each of the single-type single-dimensional indicator parameters is an indicator parameter on a single dimension of a single device type;

[0142] S2, obtaining a single-type, single-dimensional indicator parameter corresponding to the target device type according to the set of single-type, single-dimensional indicator parameters, wherein different single-type, single-dimensional indicator parameters corresponding to the target device type are indicator parameters on different single dimensions of the target device type;

[0143] S3, merging the single-type, single-dimensional indicator parameters corresponding to the target device type into a set of single-type, multi-dimensional indicator parameters according to data processing logic, wherein each of the single-type, multi-dimensional indicator parameters is an indicator parameter on multiple dimensions of the target device type, and each of the single-type, multi-dimensional indicator parameters is an indicator parameter obtained by executing the same data processing logic on the operating data on each of the multiple dimensions of the target device type;

[0144] S4. Obtain the data processing logic code corresponding to each single-type multi-dimensional indicator parameter in the set of single-type multi-dimensional indicator parameters, and obtain a first set of data processing logic codes in total. Based on the first set of data processing logic codes, generate a target device data processing model of the target device type, wherein each copy of the data processing logic code is used to execute the same data processing logic in the corresponding single-type multi-dimensional indicator parameter, and the target device data processing model is used to determine the indicator parameters on multiple dimensions in each single-type multi-dimensional indicator parameter based on the operating data of the device of the target device type.

[0145] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, which will not be described in detail in this embodiment.

[0146] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media that can store program codes, such as a USB flash drive, a ROM, a RAM, a mobile hard disk, a magnetic disk, or an optical disk.

[0147] According to another aspect of an embodiment of the present application, an electronic device for implementing the above-mentioned method for generating a device data processing model is also provided. The electronic device may be a server, a terminal, or a combination thereof.

[0148] Figure 9 is a structural block diagram of an optional electronic device according to an embodiment of the present application, such as Figure 9As shown, it includes a processor 902, a communication interface 904, a memory 906 and a communication bus 908, wherein the processor 902, the communication interface 904 and the memory 906 communicate with each other through the communication bus 908, wherein,

[0149] Memory 906, for storing computer programs;

[0150] The processor 902 is configured to execute the computer program stored in the memory 906 to implement the following steps:

[0151] S1, splitting a set of multi-type single-dimensional indicator parameters according to device type to obtain a set of single-type single-dimensional indicator parameters, wherein each of the multi-type single-dimensional indicator parameters is an indicator parameter on a single dimension of multiple different device types, and each of the single-type single-dimensional indicator parameters is an indicator parameter on a single dimension of a single device type;

[0152] S2, obtaining a single-type, single-dimensional indicator parameter corresponding to the target device type according to the set of single-type, single-dimensional indicator parameters, wherein different single-type, single-dimensional indicator parameters corresponding to the target device type are indicator parameters on different single dimensions of the target device type;

[0153] S3, merging the single-type, single-dimensional indicator parameters corresponding to the target device type into a set of single-type, multi-dimensional indicator parameters according to data processing logic, wherein each of the single-type, multi-dimensional indicator parameters is an indicator parameter on multiple dimensions of the target device type, and each of the single-type, multi-dimensional indicator parameters is an indicator parameter obtained by executing the same data processing logic on the operating data on each of the multiple dimensions of the target device type;

[0154] S4. Obtain the data processing logic code corresponding to each single-type multi-dimensional indicator parameter in the set of single-type multi-dimensional indicator parameters, and obtain a first set of data processing logic codes in total. Based on the first set of data processing logic codes, generate a target device data processing model of the target device type, wherein each copy of the data processing logic code is used to execute the same data processing logic in the corresponding single-type multi-dimensional indicator parameter, and the target device data processing model is used to determine the indicator parameters on multiple dimensions in each single-type multi-dimensional indicator parameter based on the operating data of the device of the target device type.

[0155] In this embodiment, the communication bus can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 9 The communication interface is used for communication between the electronic device and other devices.

[0156] The memory may include RAM, or may include non-volatile memory, such as at least one disk memory. Alternatively, the memory may also be at least one storage device located away from the aforementioned processor.

[0157] As an example, the memory 906 may include, but is not limited to, the first splitting unit 802, the first obtaining unit 804, the first processing unit 806, and the second processing unit 808 in the device data processing model generation device. Furthermore, the memory 906 may also include, but is not limited to, other module units in the device data processing model generation device, which will not be described in detail in this example.

[0158] The above-mentioned processor can be a general-purpose processor, including but not limited to: CPU (Central Processing Unit), NP (Network Processor), etc.; it can also be DSP (Digital Signal Processing), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0159] Optionally, the specific examples in this embodiment may refer to the examples described in the above embodiments, and this embodiment will not be described in detail here.

[0160] It can be understood by those skilled in the art that Figure 9The structure shown is for illustration only. The device for implementing the above-mentioned method for generating the device data processing model may be a terminal device, which may be a smart phone (such as an Android phone, an iOS phone, etc.), a tablet computer, a PDA, a mobile Internet device (Mobile Internet Devices, MID), a PAD, and other terminal devices. Figure 9 It does not limit the structure of the above electronic device. For example, the electronic device may also include Figure 9 More or fewer components (such as network interfaces, display devices, etc.) shown in, or with Figure 9 Different configurations shown.

[0161] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a computer-readable storage medium, which can include: a flash drive, ROM, RAM, a magnetic disk or an optical disk, etc.

[0162] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0163] If the integrated units in the above embodiments are implemented in the form of software functional units and sold or used as independent products, they can be stored in the above-mentioned computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the relevant technology, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling one or more computer devices (which can be personal computers, servers or network devices, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application.

[0164] In the above embodiments of the present application, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0165] In the several embodiments provided in this application, it should be understood that the disclosed client can be implemented in other ways. Among them, the device embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, and can be electrical or other forms.

[0166] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected based on actual needs to achieve the purpose of the solution provided in this embodiment.

[0167] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0168] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for generating a device data processing model, characterized in that: include: Splitting a set of multi-type single-dimensional indicator parameters according to device type to obtain a set of single-type single-dimensional indicator parameters, wherein each of the multi-type single-dimensional indicator parameters is an indicator parameter on a single dimension of multiple different device types, and each of the single-type single-dimensional indicator parameters is an indicator parameter on a single dimension of a single device type; Obtaining, according to the set of single-type single-dimensional indicator parameters, single-type single-dimensional indicator parameters corresponding to the target device type, wherein different single-type single-dimensional indicator parameters corresponding to the target device type are indicator parameters on different single dimensions of the target device type; Merging the single-type, single-dimensional indicator parameters corresponding to the target device type into a set of single-type, multi-dimensional indicator parameters according to data processing logic, wherein each of the single-type, multi-dimensional indicator parameters is an indicator parameter on multiple dimensions of the target device type, and each of the single-type, multi-dimensional indicator parameters is an indicator parameter obtained by executing the same data processing logic on the operating data on each of the multiple dimensions of the target device type; Obtain the data processing logic code corresponding to each single-type multi-dimensional indicator parameter in the set of single-type multi-dimensional indicator parameters, and obtain a first set of data processing logic codes in total; and generate a target device data processing model of the target device type based on the first set of data processing logic codes, wherein each copy of the data processing logic code is used to execute the same data processing logic in the corresponding single-type multi-dimensional indicator parameter, and the target device data processing model is used to determine the indicator parameters on multiple dimensions in each single-type multi-dimensional indicator parameter based on the operating data of the device of the target device type.

2. The method according to claim 1, characterized in that Merging the single-type single-dimensional indicator parameters corresponding to the target device type into a set of single-type multi-dimensional indicator parameters according to data processing logic, including: when the single-type single-dimensional indicator parameters corresponding to the target device type include a first portion of single-type single-dimensional indicator parameters that are allowed to be merged and a second portion of single-type single-dimensional indicator parameters that cannot be merged, merging the first portion of single-type single-dimensional indicator parameters according to the data processing logic to obtain the set of single-type multi-dimensional indicator parameters; The method further includes: obtaining a data processing logic code corresponding to each single-type single-dimensional indicator parameter in the second part of single-type single-dimensional indicator parameters to obtain a second group of data processing logic codes; Generating a target device data processing model for the target device type according to the first set of data processing logic codes includes: determining the first set of data processing logic codes and the second set of data processing logic codes as codes in the target device data processing model.

3. The method according to claim 1, characterized in that The single-type, single-dimensional indicator parameters corresponding to the target device type are merged into a set of single-type, multi-dimensional indicator parameters according to the data processing logic, including: When the single-type single-dimensional indicator parameters corresponding to the target device type are all single-type single-dimensional indicator parameters allowed to be merged, the single-type single-dimensional indicator parameters corresponding to the target device type are merged according to the data processing logic to obtain the set of single-type multi-dimensional indicator parameters.

4. The method according to claim 1, wherein The acquiring, according to the set of single-type single-dimensional indicator parameters, the single-type single-dimensional indicator parameters corresponding to the target device type includes: A first group of single-type single-dimensional indicator parameters corresponding to the target device type is obtained from the group of single-type single-dimensional indicator parameters, wherein the single-type single-dimensional indicator parameters corresponding to the target device type include the first group of single-type single-dimensional indicator parameters, and different single-type single-dimensional indicator parameters in the first group of single-type single-dimensional indicator parameters are indicator parameters on different single dimensions of the target device type.

5. The method according to claim 1, wherein The acquiring, according to the set of single-type single-dimensional indicator parameters, the single-type single-dimensional indicator parameters corresponding to the target device type includes: Obtaining a first group of single-type single-dimensional indicator parameters corresponding to the target device type from the group of single-type single-dimensional indicator parameters, wherein different single-type single-dimensional indicator parameters in the first group of single-type single-dimensional indicator parameters are indicator parameters on different single dimensions of the target device type; Obtaining a second group of single-type, single-dimensional indicator parameters corresponding to the target device type from a predetermined set of single-type, single-dimensional indicator parameters, wherein different single-type, single-dimensional indicator parameters in the second group of single-type, single-dimensional indicator parameters are indicator parameters on different single dimensions of the target device type, and each single-type, single-dimensional indicator parameter in the single-type, single-dimensional indicator parameter set is an indicator parameter on a single dimension of a device type; The single-type single-dimensional indicator parameters corresponding to the target device type include the first group of single-type single-dimensional indicator parameters and the second group of single-type single-dimensional indicator parameters.

6. The method according to claim 1, characterized in that After converting the set of data processing logic codes into a target device data processing model of the target device type, the method further includes: Acquire, from the operating data of a device of the target device type, a set of operating data corresponding to each data processing logic code in the first set of data processing logic codes; A set of operating data corresponding to each data processing logic code is input into the target device data processing model to obtain a current result of each single-type multi-dimensional indicator parameter in the set of single-type multi-dimensional indicator parameters.

7. The method according to claim 6, characterized in that Inputting a set of operating data corresponding to each data processing logic code into the target device data processing model to obtain a current result of each single-type multi-dimensional indicator parameter in the set of single-type multi-dimensional indicator parameters includes: Upon obtaining an i-th set of operating data corresponding to the i-th data processing logic code in the first set of data processing logic codes, inputting the i-th set of operating data into the i-th data processing logic code in the target device data processing model, where i is a positive integer greater than or equal to 1; When the single-type multi-dimensional indicator parameters corresponding to the i-th data processing logic code are indicator parameters on N dimensions of the target device type, and the i-th group of operating data includes N parts of operating data corresponding to the N dimensions, the i-th data processing logic code is used to execute the same data processing logic on each of the N parts of operating data to obtain the current results of the indicator parameters on the N dimensions of the target device type, where N is a positive integer greater than or equal to 2.

8. A device for generating a device data processing model, characterized in that: include: A first splitting unit is configured to split a set of multi-type single-dimensional indicator parameters according to device type to obtain a set of single-type single-dimensional indicator parameters, wherein each of the multi-type single-dimensional indicator parameters is an indicator parameter on a single dimension of multiple different device types, and each of the single-type single-dimensional indicator parameters is an indicator parameter on a single dimension of a single device type; A first acquiring unit is configured to acquire, based on the set of single-type single-dimensional indicator parameters, single-type single-dimensional indicator parameters corresponding to the target device type, wherein different single-type single-dimensional indicator parameters corresponding to the target device type are indicator parameters on different single dimensions of the target device type; a first processing unit, configured to merge the single-type, single-dimensional indicator parameters corresponding to the target device type into a set of single-type, multi-dimensional indicator parameters according to data processing logic, wherein each of the single-type, multi-dimensional indicator parameters is an indicator parameter on multiple dimensions of the target device type, and each of the single-type, multi-dimensional indicator parameters is an indicator parameter obtained by executing the same data processing logic on operating data on each of the multiple dimensions of the target device type; The second processing unit is used to obtain the data processing logic code corresponding to each single-type multi-dimensional indicator parameter in the set of single-type multi-dimensional indicator parameters, to obtain a first set of data processing logic codes, and to generate a target device data processing model of the target device type based on the first set of data processing logic codes, wherein each copy of the data processing logic code is used to execute the same data processing logic in the corresponding single-type multi-dimensional indicator parameter, and the target device data processing model is used to determine the indicator parameters on multiple dimensions in each of the single-type multi-dimensional indicator parameters based on the operating data of the device of the target device type.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program executes the method according to any one of claims 1 to 7 when executed.

10. An electronic device comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method according to any one of claims 1 to 7 through the computer program.

Images