Carbon monitoring data quality inspection method, device, equipment, medium and product

Abstract

The invention provides a carbon monitoring data quality inspection method, device and equipment, a medium and a product, relates to the technical field of carbon monitoring data processing, and aims to solve the problem that targeted quality inspection cannot be performed on carbon monitoring data by a general technology. The carbon monitoring data quality inspection method comprises the following steps: acquiring an original data set; the original data set is a set of carbon monitoring data required by the target application scene; inputting the original data set into a pre-configured data conversion model to output a standardized data set; the standardized data set comprises monitoring data of at least one index; determining a quality inspection threshold value of the pre-selected index data according to the pre-selected index data in the standardized data set; the pre-selected index data is monitoring data of indexes in the standardized data set; and performing quality inspection on the pre-selected index data according to the quality inspection threshold, and determining a quality inspection result of the pre-selected index data.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of carbon monitoring data processing, and particularly relates to a carbon monitoring data quality inspection method and device, equipment, medium and product. BACKGROUND

[0002] Cities are the main source of global greenhouse gas emissions, so accurate monitoring of carbon monitoring data such as carbon emissions and carbon fluxes in cities is crucial in the process of achieving carbon peak and carbon neutrality, and is of great significance for formulating effective emission reduction strategies and achieving the goal of carbon peak and carbon neutrality.

[0003] At present, the existing technology mainly uses a general rule system or technical method to ensure the quality of data, and through the integration of various monitoring means and the introduction of big data and artificial intelligence technology, the quality of the original data of urban carbon monitoring is significantly improved.

[0004] However, the problem of how to conduct targeted quality inspection on carbon monitoring data still cannot be solved. SUMMARY

[0005] The embodiments of the present disclosure provide a carbon monitoring data quality inspection method, device, equipment, medium and product, aiming to solve the problem of how to conduct quality inspection on carbon monitoring data in a specific application scenario.

[0006] To achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0007] In a first aspect, a carbon monitoring data quality inspection method is provided, comprising: obtaining an original data set; the original data set is a set of carbon monitoring data required for a target application scenario; inputting the original data set into a pre-configured data conversion model to output a standardized data set; the standardized data set includes monitoring data of at least one index; determining a quality inspection threshold of preselected index data according to the preselected index data in the standardized data set; the preselected index data is the monitoring data of the index in the standardized data set; and performing quality inspection on the preselected index data according to the quality inspection threshold to determine the quality inspection result of the preselected index data.

[0008] In some embodiments, the pre-configured data conversion model is determined by: identifying the representation attribute of the data in the original data set, and determining the standard of the representation attribute; the representation attribute includes at least one of the data unit, the data acquisition frequency and the data acquisition accuracy; determining the data conversion model according to the representation attribute and the standard of the representation attribute; the data conversion model is configured to convert the input data into data conforming to the standard of the representation attribute according to the standard of the representation attribute.

[0009] In some embodiments, the obtaining the original data set comprises: determining, according to the carbon monitoring data and the target application scenario, carbon monitoring data required by the target application scenario in the carbon monitoring data as the original data set.

[0010] In some embodiments, the determining the quality inspection threshold according to the pre-selected index data in the standardized data set comprises: determining a harmonic mean of the pre-selected index data as a historical reference value; and determining the quality inspection threshold according to the historical reference value.

[0011] In some embodiments, the determining the quality inspection threshold according to the historical reference value comprises: determining a value range and a value interval of the quality inspection threshold according to the historical reference value; determining a plurality of estimated quality inspection thresholds within the value range of the quality inspection threshold according to the value range and the value interval of the quality inspection threshold; the minimum estimated quality inspection threshold is the minimum value of the quality inspection threshold; the intervals of the plurality of estimated quality inspection thresholds are the value interval of the quality inspection threshold; determining an evaluation value corresponding to each estimated quality inspection threshold, and determining the estimated quality inspection threshold as the quality inspection threshold in a case where the evaluation value corresponding to the estimated quality inspection threshold is in a preset interval.

[0012] In some embodiments, the evaluation value corresponding to the estimated quality inspection threshold satisfies the following formula:

[0013]

[0014] wherein, KS is the evaluation value corresponding to the estimated quality inspection threshold; count{X i is the number of the pre-selected index data within the estimated quality inspection threshold range; and n is the number of the pre-selected index data.

[0015] In some embodiments, the quality inspecting the pre-selected index data according to the quality inspection threshold and determining a quality inspection result of the pre-selected index data comprises: determining that the quality inspection result of the pre-selected index data is passed in a case where the pre-selected index data is less than or equal to the quality inspection threshold.

[0016] In a second aspect, a carbon monitoring data quality inspection device is provided, which comprises a communication unit and a processing unit.

[0017] The communication unit is configured to obtain an original data set; the original data set is a set of carbon monitoring data required by a target application scenario.

[0018] The processing unit is configured to input the original data set into a pre-configured data conversion model to output a standardized data set; the standardized data set comprises monitoring data of at least one index.

[0019] The processing unit is further configured to determine a quality inspection threshold of the preselected index data according to the preselected index data in the standardized data set, the preselected index data being monitoring data of an index in the standardized data set.

[0020] The processing unit is further configured to perform quality inspection on the preselected index data according to the quality inspection threshold, and determine a quality inspection result of the preselected index data.

[0021] In a third aspect, a carbon monitoring data quality inspection device is provided, which includes a memory and a processor. The memory is configured to store computer-executable instructions, and the processor is connected to the memory through a bus. When the carbon monitoring data quality inspection device is running, the processor executes the computer-executable instructions stored in the memory, so that the carbon monitoring data quality inspection device performs the carbon monitoring data quality inspection method in the first aspect and any possible implementation manner thereof.

[0022] The carbon monitoring data quality inspection device can be an electronic device or a part of the electronic device, such as a chip system in the electronic device. The chip system is configured to support the electronic device to implement the functions involved in the first aspect and any possible implementation manner thereof, for example, to acquire and / or determine the data and / or information involved in the carbon monitoring data quality inspection method. The chip system includes a chip and can also include other discrete devices or circuit structures.

[0023] In a fourth aspect, a computer-readable storage medium is provided, which includes computer-executable instructions. When the computer-executable instructions are running on a computer, the computer-executable instructions make the computer perform the carbon monitoring data quality inspection method in the first aspect.

[0024] In a fifth aspect, a computer program product is also provided, which includes computer programs or instructions. When the computer instructions are running on a carbon monitoring data quality inspection device, the computer instructions make the carbon monitoring data quality inspection device perform the carbon monitoring data quality inspection method in the first aspect.

[0025] It should be noted that the computer instructions can be stored on the computer-readable storage medium in whole or in part. The computer-readable storage medium can be packaged together with the processor of the carbon monitoring data quality inspection device, or can be packaged separately from the processor of the carbon monitoring data quality inspection device, and the embodiments of the present application do not limit this.

[0026] The second aspect, the third aspect, the fourth aspect and the fifth aspect in the present application can refer to the detailed description of the first aspect.

[0027] In the embodiments of the present application, the name of the carbon monitoring data quality inspection device does not constitute a limitation on the device or functional module itself, and in actual implementation, these devices or functional modules can appear with other names. For example, the receiving unit can also be referred to as a receiving module, a receiver, etc. As long as the functions of each device or functional module are similar to those of the present application, they belong to the scope of the claims of the present application and their equivalents.

[0028] The present application provides a carbon monitoring data quality inspection method, which can obtain an original data set; the original data set is a set of carbon monitoring data required by a target application scenario. Subsequently, the original data set can also be input into a pre-configured data conversion model to output a standardized data set; the standardized data set includes monitoring data of at least one index. Then, the preselected index data in the standardized data set can also be used to determine the quality inspection threshold of the preselected index data; the preselected index data is the monitoring data of the index in the standardized data set. Then, the preselected index data can also be quality inspected according to the quality inspection threshold to determine the quality inspection result of the preselected index data.

[0029] As can be seen from the above, the present scheme realizes the automatic determination of the original data set as the standardized data set by inputting the original data set into the pre-configured data conversion model and outputting the standardized data. The present scheme also determines the required monitoring data set through the application scenario of the monitoring data, and then determines the quality inspection threshold based on the historical reference value, and adds the historical data to the quality inspection standard, thereby solving the problem of quality inspection of data in a specific application scenario. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 A structural schematic diagram of a carbon monitoring data quality inspection system provided by an embodiment of the present application;

[0031] Figure 2 A hardware structural schematic diagram of a carbon monitoring data quality inspection device provided by an embodiment of the present application;

[0032] Figure 3 A flowchart of a carbon monitoring data quality inspection method provided by an embodiment of the present application;

[0033] Figure 4 A flowchart of another carbon monitoring data quality inspection method provided by an embodiment of the present application;

[0034] Figure 5 A structural schematic diagram of a carbon monitoring data quality inspection device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0035] With reference to the drawings and the embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only part of the embodiments of the present application, but not all the embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of the present application.

[0036] It should be noted that in the embodiments of the present application, the words such as "exemplary" or "for example" are used to mean serving as an example, illustration, or description. Any embodiment or design solution described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or having more advantages than other embodiments or design solutions. Rather, the words such as "exemplary" or "for example" are used in the specific manner to present the relevant concept.

[0037] In order to clearly describe the technical solutions of the embodiments of the present application, in the embodiments of the present application, the words "first", "second", etc. are used to distinguish the same or similar items with basically the same function and role, and those skilled in the art can understand that the words "first", "second", etc. are not used to limit the quantity and execution order.

[0038] As described in the background, cities are the main source of global greenhouse gas emissions, therefore, accurately monitoring carbon monitoring data such as carbon emissions and carbon flux of cities is crucial in the process of achieving carbon peak and carbon neutralization, and is of great significance for formulating effective emission reduction strategies and achieving the goal of carbon peak and carbon neutralization.

[0039] However, the existing technology mainly has two problems, one is that the business pertinence is insufficient, the existing method mainly adopts a general rule system or technical method to ensure the uniqueness, integrity, effectiveness, standardization, consistency and stability of data, but the data quality control rules of data in different business scenarios are often deeply related to the business, and the existing technology cannot solve the problem of ensuring data quality in specific business scenarios at present; the second is that when the obtained data needs to be processed and applied, there is a lack of corresponding data processing and quality warning method to ensure the data quality in different business scenarios.

[0040] From the above, it can be seen that the general technology cannot solve the problem of quality inspection of data in specific application scenarios.

[0041] To solve the above problems, the application provides a carbon monitoring data quality inspection method, which can obtain an original data set; the original data set is a set of carbon monitoring data required by a target application scenario. Then, the original data set can be input into a pre-configured data conversion model to output a standardized data set; the standardized data set includes monitoring data of at least one index. Then, a preselected index data quality inspection threshold can be determined according to preselected index data in the standardized data set; the preselected index data is monitoring data of an index in the standardized data set. Then, the preselected index data can be inspected according to the quality inspection threshold to determine a quality inspection result of the preselected index data.

[0042] As can be seen from the above, the application automatically determines the original data set as the standardized data set by inputting the original data set into the pre-configured data conversion model and outputting the standardized data. The application determines the required monitoring data set according to the application scenario of the monitoring data, and then determines the quality inspection threshold based on the historical reference value, and adds the historical data to the quality inspection standard, thereby solving the problem of quality inspection of data in a specific application scenario.

[0043] The implementation environment of the carbon monitoring data quality inspection method can be a carbon monitoring data quality inspection system provided by the application.

[0044] Figure 1 A structural schematic diagram of a carbon monitoring data quality inspection system provided by the application is shown in FIG. 1. Figure 1 As shown in FIG. 1, the carbon monitoring data quality inspection system includes a carbon monitoring data quality inspection device 101 and a data storage device 102.

[0045] The carbon monitoring data quality inspection device 101 and the data storage device 102 are in communication connection.

[0046] In actual application, the carbon monitoring data quality inspection device 101 can be connected to any number of data storage devices 102. For ease of understanding, Figure 1 For example, one carbon monitoring data quality inspection device 101 is connected to one data storage device 102.

[0047] In the application, the data storage device 102 is configured to provide data (for example, carbon monitoring data) for carbon monitoring data quality inspection to the carbon monitoring data quality inspection device 101, so that the carbon monitoring data quality inspection device 101 performs quality inspection of the monitoring data according to the data sent by the data storage device 102.

[0048] Optionally, the entity devices of the carbon monitoring data quality inspection device 101 and the data storage device 102 can be servers, terminals or other types of electronic devices, and the application does not limit the types of the devices.

[0049] Optionally, the terminal described above can refer to a device providing voice and / or data connectivity for a user, a handheld device having wireless connection capability, or other processing devices connected to a wireless modem. The wireless terminal can communicate with one or more core networks via a radio access network (RAN). The wireless terminal can be a mobile terminal, such as a mobile telephone (also known as a "cellular" telephone) and a computer having a mobile terminal, and can also be a portable, pocket, handheld, computer-included or car-mounted moving apparatus, which exchanges language and / or data with a radio access network, such as a mobile phone, a tablet computer, a notebook computer, a netbook computer, a personal digital assistant (PDA).

[0050] Optionally, the server described above can be one server in a server cluster (composed of multiple servers), can also be a chip in the server, can also be a system on a chip in the server, and can also be implemented through a virtual machine (VM) deployed on a physical machine, and the embodiments of the present application do not limit this.

[0051] Optionally, the carbon monitoring data quality inspection equipment 101 and the data storage equipment 102 can be two devices independently arranged with each other, or can be integrated in the same device. When the carbon monitoring data quality inspection equipment 101 and the data storage equipment 102 are integrated in the same device, the data storage equipment 102 can be a storage module (such as a database, etc.) of the carbon monitoring data quality inspection equipment 101.

[0052] It is easy to understand that when the carbon monitoring data quality inspection equipment 101 and the data storage equipment 102 are integrated in the same device, the communication mode between the carbon monitoring data quality inspection equipment 101 and the data storage equipment 102 is the communication between the internal modules of the device. In this case, the communication process between the two is the same as the communication process between the carbon monitoring data quality inspection equipment 101 and the data storage equipment 102 when they are independent of each other.

[0053] For ease of understanding, the carbon monitoring data quality inspection equipment 101 and the data storage equipment 102 are taken as examples for illustration.

[0054] The carbon monitoring data quality inspection equipment in the carbon monitoring data quality inspection system includes elements such as Figure 2 The hardware structure of the carbon monitoring data quality inspection equipment will be introduced below by taking the carbon monitoring data quality inspection device shown in Figure 2

[0055] Figure 2 A hardware structure schematic diagram of a carbon monitoring data quality inspection device provided by the embodiments of the present application is shown in Figure 2 ​As shown, the carbon monitoring data quality inspection device includes a processor 201, a memory 202, a communication interface 203, and a bus 204. The processor 201, the memory 202, and the communication interface 203 can be connected through the bus 204.

[0056] The processor 201 is a control center of the carbon monitoring data quality inspection device, and can be one processor or a collective term of multiple processing elements. For example, the processor 201 can be a general central processing unit (CPU), or other general-purpose processors, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0057] As an embodiment, the processor 201 can include one or more CPUs, such as the CPU0 and the CPU1 shown in FIG. 1. Figure 2

[0058] The memory 202 can be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (RAM) or other type of dynamic storage device that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program codes in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto.

[0059] In a possible implementation, the memory 202 can exist independently of the processor 201, and the memory 202 can be connected to the processor 201 through the bus 204, for storing instructions or program codes. When the processor 201 invokes and executes the instructions or program codes stored in the memory 202, the carbon monitoring data quality inspection method provided in the embodiments of the present application can be implemented.

[0060] In the embodiments of the present application, the software programs stored in the memory 202 of the carbon monitoring data quality inspection device are different, and therefore the functions implemented by the carbon monitoring data quality inspection device are different. The functions performed by each device will be described in combination with the flowcharts below.

[0061] In another possible implementation, the memory 202 can also be integrated with the processor 201.

[0062] ​The communication interface 203 is configured to connect the carbon monitoring data quality inspection device to other devices via a communication network, which can be an Ethernet, a wireless access network, a wireless local area network (WLAN), or the like. The communication interface 203 can include a receiving unit for receiving data and a sending unit for sending data.

[0063] The bus 204 can be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus, an extended industry standard architecture (EISA) bus, or the like. The bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, Figure 2 Only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0064] It should be noted that Figure 2 The structure shown in the figure does not constitute a limitation on the carbon monitoring data quality inspection device, except Figure 2 The carbon monitoring data quality inspection device can include more or fewer components than those shown in the figure, or combine certain components, or different component arrangements.

[0065] The carbon monitoring data quality inspection method provided by the embodiment of the present application will be described in detail below with reference to the accompanying drawings.

[0066] The carbon monitoring data quality inspection method provided by the embodiment of the present application is applied to Figure 1 The carbon monitoring data quality inspection device 101 in the carbon monitoring data quality inspection system shown in the figure, such as Figure 3 The carbon monitoring data quality inspection method provided by the embodiment of the present application includes:

[0067] S301, the carbon monitoring data quality inspection device acquires an original data set.

[0068] The original data set is a set of carbon monitoring data required by the target application scenario.

[0069] Specifically, in order to perform quality inspection on the carbon monitoring data for a specific application scenario, it is necessary to determine the required set of carbon monitoring data according to the application scenario of the carbon monitoring data.

[0070] Optionally, the determination of the required data range can be based on expert experience.

[0071] Optionally, the original data set can be stored in a database.

[0072] For example, the application scenario is urban industry carbon monitoring or urban carbon source and carbon sink total amount monitoring.

[0073] In S302, the carbon monitoring data quality inspection equipment inputs the original data set into the pre-configured data conversion model to output a standardized data set.

[0074] The standardized data set includes monitoring data of at least one index.

[0075] Specifically, in order to perform quality inspection on carbon monitoring data for a specific application scenario, after obtaining a monitoring data set under the specific application scenario, the original data is converted into standardized data through a pre-configured data conversion model based on data in the original data set.

[0076] For example, in some embodiments, the pre-configured data conversion model is determined by identifying a representation attribute of data in the original data set and determining a standard of the representation attribute. The data conversion model is configured to convert input data into data meeting the standard of the representation attribute according to the standard of the representation attribute.

[0077] The representation attribute includes at least one of a data unit, a data collection frequency, and a data collection accuracy.

[0078] For example, when the application scenario is urban carbon source and carbon sink total amount monitoring, the activity level data unit of energy consumption is unified as tons, the activity level data collection frequency of energy consumption is unified as quarterly, and the activity level data collection accuracy of energy consumption is unified as three decimal places.

[0079] Optionally, the representation attribute can also be a data value, a data bit, and / or a data collection time, etc.

[0080] Optionally, the pre-configured data conversion model can also have another function of performing corresponding data conversion and classification according to the basic structure of data and the basic type of data.

[0081] For example, the basic structure includes structured data or unstructured data, etc. The basic type includes activity level or emission factor, etc.

[0082] Optionally, when inputting the model, the data in the original data set can be mapped into the model based on the original data set through the function of the database.

[0083] As known from the above embodiments, the original data can be ensured not to be affected, and the effect of saving storage space is achieved.

[0084] S303, the carbon monitoring data quality inspection equipment determines the quality inspection threshold of the pre-selected index data according to the pre-selected index data in the standardized data set.

[0085] The pre-selected index data is the monitoring data of the index in the standardized data set.

[0086] Specifically, in order to quality inspect the pre-selected index data according to the quality inspection threshold, the quality inspection threshold needs to be determined first.

[0087] For example, the pre-selected index data is carbon flux or carbon emission.

[0088] S304, the carbon monitoring data quality inspection equipment quality inspects the pre-selected index data according to the quality inspection threshold, and determines the quality inspection result of the pre-selected index data.

[0089] Specifically, in order to determine the quality inspection result of the pre-selected index data, the pre-selected index data needs to be quality inspected according to the quality inspection threshold after the quality inspection threshold is determined.

[0090] Specifically, the specific process of quality inspecting the pre-selected index data according to the quality inspection threshold is described in detail in some embodiments below, which is not repeated here.

[0091] In some embodiments, the original data set is obtained, specifically including:

[0092] The carbon monitoring data quality inspection equipment determines the carbon monitoring data required by the target application scenario in the carbon monitoring data as the original data set according to the carbon monitoring data and the target application scenario.

[0093] Specifically, in order to screen out the initial data under the specific application scenario and determine it as the original data set, the data required by the application scenario in the carbon monitoring data needs to be determined as the original data set according to the carbon monitoring data and the application scenario of the carbon monitoring data.

[0094] Optionally, when determining the original data set, the original data set can be virtually mapped based on the carbon monitoring data by using the function of the database.

[0095] As can be seen from the above embodiments, when determining the original data set, the use of the data set virtually mapped by the multi-source and multi-structure monitoring data can ensure that the original data is not affected, and the effect of saving storage space is achieved.

[0096] In some embodiments, the quality inspection threshold of the pre-selected index data is determined according to the pre-selected index data in the standardized data set, specifically including:

[0097] The carbon monitoring data quality inspection equipment determines the harmonic mean of the pre-selected index data as the historical reference value.

[0098] Specifically, in order to determine the quality inspection threshold according to the historical reference value, the historical reference value needs to be determined first.

[0099] For example, the harmonic mean satisfies the following formula:

[0100]

[0101] wherein, is the harmonic mean; n is the number of pre-selected index data; X i is the i-th pre-selected index data.

[0102] The carbon monitoring data quality inspection equipment determines the quality inspection threshold according to the historical reference value.

[0103] Specifically, in order to perform quality inspection on the standardized data according to the quality inspection threshold, the quality inspection threshold needs to be determined first according to the historical reference value.

[0104] Specifically, the specific process of determining the quality inspection threshold according to the historical reference value is described in detail in some embodiments below, and will not be repeated here.

[0105] As can be seen from the above embodiments, the influence of data with small values is eliminated by the harmonic mean, which can ensure the adaptability of the historical reference value and better represent the entire set of data.

[0106] In some embodiments, determining the quality inspection threshold according to the historical reference value specifically includes:

[0107] The carbon monitoring data quality inspection equipment determines the value range of the quality inspection threshold and the value interval of the quality inspection threshold according to the historical reference value.

[0108] Specifically, in order to determine an accurate quality inspection threshold according to the selected multiple estimated quality inspection thresholds, the value range of the quality inspection threshold and the value interval of the quality inspection threshold need to be determined first to determine the multiple estimated quality inspection thresholds.

[0109] For example, the minimum value of the quality inspection threshold M is 0, and the maximum value is The value interval of the quality inspection threshold is

[0110] The carbon monitoring data quality inspection equipment determines multiple estimated quality inspection thresholds within the value range of the quality inspection threshold according to the value range of the quality inspection threshold and the value interval of the quality inspection threshold.

[0111] Wherein, the minimum estimated quality inspection threshold is the minimum value of the quality inspection threshold; the interval of the multiple estimated quality inspection thresholds is the value interval of the quality inspection threshold.

[0112] Specifically, in order to select a suitable quality inspection threshold, a plurality of candidate estimated quality inspection thresholds need to be determined first, so as to determine a suitable quality inspection threshold from the plurality of estimated quality inspection thresholds.

[0113] For example, the minimum value of the quality inspection threshold M is 0, and the maximum value is The value interval of the quality inspection threshold is When M is equal to 0, the value of M is arranged according to the interval of , that is, the plurality of estimated quality inspection thresholds are 0,

[0114]

[0115] The carbon monitoring data quality inspection equipment determines the evaluation value corresponding to the plurality of estimated quality inspection thresholds, and determines the estimated quality inspection threshold as the quality inspection threshold in the case that the evaluation value corresponding to the estimated quality inspection threshold is in the preset interval.

[0116] Specifically, in order to perform quality inspection on the pre-selected index data through the quality inspection threshold, the quality inspection threshold needs to be determined according to the evaluation value corresponding to the estimated quality inspection threshold.

[0117] Optionally, the evaluation value can be a Kolmogorov-Smirnov (KS) value in machine learning.

[0118] For example, the preset interval can be [51%, 75%].

[0119] For example, in some embodiments, the evaluation value corresponding to the estimated quality inspection threshold satisfies the following formula:

[0120]

[0121] Wherein, KS is the evaluation value corresponding to the estimated quality inspection threshold; count{X i in the estimated quality inspection threshold range} is the number of pre-selected index data in the estimated quality inspection threshold range; and n is the number of pre-selected index data.

[0122] As can be seen from the above embodiments, by using the KS value, it can be determined whether the selected threshold is reasonable, and a quality inspection threshold with better discrimination ability can be determined, thereby enhancing the quality inspection ability of the pre-selected index data.

[0123] In some embodiments, the pre-selected index data is quality inspected according to the quality inspection threshold, and the quality inspection result of the pre-selected index data is determined, specifically including:

[0124] The carbon monitoring data quality inspection equipment determines that the quality inspection result of the pre-selected index data is passed in the case that the pre-selected index data is less than or equal to the quality inspection threshold.

[0125] Specifically, in order to determine whether the pre-selected index data quality inspection passes, it is necessary to determine whether the pre-selected index data is less than or equal to the quality inspection threshold.

[0126] Optionally, the pre-selected index data that fails the quality inspection can also be marked for visual display for reference by relevant staff.

[0127] Optionally, the data that fails the verification can be marked in red, or the data that fails the verification can be displayed in bold, or the data that passes the quality inspection can be marked, such as green, without limitation.

[0128] Figure 4 Another flowchart of a carbon monitoring data quality inspection method provided by an embodiment of the present application is shown in FIG. 6. Figure 4 As shown in FIG. 6, the carbon monitoring data quality inspection method includes:

[0129] S401, data access checking and parsing.

[0130] Specifically, the data access checking and parsing specifically includes:

[0131] S4011, data application scenario identification.

[0132] Specifically, the application scenario is determined, and the original data set is determined from the carbon monitoring data according to the application scenario.

[0133] S4012, data basic format and type checking.

[0134] For example, the basic format can be structured data or unstructured data; the type can be activity level or emission factor.

[0135] S4013, data structure parsing and attribute identification.

[0136] Specifically, the data structure and attribute are the representation attributes of the data in the present application.

[0137] S402, self-discovered data structure configuration and model construction.

[0138] The constructed model is a pre-configured data conversion model in the present application.

[0139] Specifically, the self-discovered data structure configuration and model construction specifically includes:

[0140] S4021, data unit conversion configuration.

[0141] For example, the activity level data unit of energy consumption is unified as tons.

[0142] S4022, data frequency conversion configuration.

[0143] Exemplarily, the activity level data collection frequency of the energy consumption is unified as quarterly.

[0144] S4023, data precision conversion configuration.

[0145] Exemplarily, the activity level data collection precision of the energy consumption is unified as three decimal places.

[0146] S403, heterogeneous data processing.

[0147] Specifically, the heterogeneous data processing specifically includes:

[0148] S4031, heterogeneous data mapping.

[0149] Specifically, it is to map the data in the original data set in the model of step S402 (i.e. the pre-configured data conversion model in the present application) based on the original data set.

[0150] S4032, heterogeneous data conversion processing.

[0151] Specifically, the model of step S402 is called, i.e. steps S4021, S4022 and S4023 are sequentially executed.

[0152] S4033, data set construction.

[0153] Specifically, the data output by the model is constructed as a standardized data set.

[0154] S404, quality inspection early warning based on a reference value.

[0155] The reference value is the historical reference value in the present application.

[0156] Specifically, the quality inspection early warning based on the reference value specifically includes:

[0157] S4041, calculating a historical reference value of the data.

[0158] Optionally, the harmonic mean of the data is determined as the historical reference value.

[0159] S4042, setting a quality inspection threshold based on the historical reference value.

[0160] Specifically, a plurality of estimated quality inspection thresholds are determined.

[0161] S4043, calculating a KS value of the data.

[0162] Specifically, the KS value (i.e. the evaluation value in the present application) of each estimated quality inspection threshold is calculated.

[0163] S4044, the KS value is located in the interval of 51% to 75%.

[0164] Specifically, if the KS value is in the interval of 51% to 75%, S4051 is executed, and if not, S4042 is executed, and the next estimated quality inspection threshold is reselected.

[0165] S405, quality inspection result marking and early warning visualization.

[0166] Specifically, the quality inspection result marking and early warning visualization specifically includes:

[0167] S4051, data quality marking.

[0168] Specifically, the quality inspection result of each data is marked.

[0169] S4052, data quality early warning.

[0170] Specifically, early warning is performed according to the quality inspection result of the data.

[0171] S4053, visualization of quality inspection and early warning results.

[0172] Specifically, the quality inspection result and the early warning result are visualized and displayed.

[0173] The above mainly describes the scheme provided by the embodiments of the present application from the perspective of the method. In order to implement the above functions, it contains the hardware structure and / or software module corresponding to the execution of each function. Those skilled in the art should easily realize that, in combination with the units and algorithm steps of the examples described in the embodiments disclosed herein, the present application can be realized in the form of hardware or a combination of hardware and computer software. Whether a certain function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present application.

[0174] The embodiments of the present application can divide the functional modules of the carbon monitoring data quality inspection device according to the above method examples. For example, each functional module can be divided according to each function, or two or more functions can be integrated in one processing module. The above integrated module can be realized in the form of hardware or in the form of a software functional module. Optionally, the division of the modules in the embodiments of the present application is illustrative, and is only a logical functional division. Actual implementation can have another division manner.

[0175] Figure 5 A structural schematic diagram of a carbon monitoring data quality inspection device provided by an embodiment of the present application is shown. As shown in the figure, Figure 5 The carbon monitoring data quality inspection device includes a communication unit 501 and a processing unit 502.

[0176] The communication unit 501 is configured to obtain an original data set, which is a set of carbon monitoring data required by a target application scenario.

[0177] The processing unit 502 is configured to input the original data set into a preconfigured data conversion model to output a standardized data set, which includes monitoring data of at least one index.

[0178] The processing unit 502 is further configured to determine a quality inspection threshold of preselected index data in the standardized data set according to the preselected index data.

[0179] The processing unit 502 is further configured to perform quality inspection on the preselected index data according to the quality inspection threshold to determine a quality inspection result of the preselected index data.

[0180] In some embodiments, the preconfigured data conversion model is determined by identifying a representation attribute of data in the original data set and determining a standard of the representation attribute, wherein the representation attribute includes at least one of a data unit, a data acquisition frequency, and a data acquisition accuracy; and determining the data conversion model according to the representation attribute and the standard of the representation attribute, wherein the data conversion model is configured to convert input data into data meeting the standard of the representation attribute according to the standard of the representation attribute.

[0181] In some embodiments, the processing unit 502 is specifically configured to determine, according to the carbon monitoring data and the target application scenario, carbon monitoring data required by the target application scenario in the carbon monitoring data as the original data set.

[0182] In some embodiments, the processing unit 502 is specifically configured to:

[0183] The harmonic mean of the preselected index data is determined as the historical reference value.

[0184] The quality inspection threshold is determined according to the historical reference value.

[0185] In some embodiments, the processing unit 502 is specifically configured to:

[0186] The value range and the value interval of the quality inspection threshold are determined according to the historical reference value.

[0187] A plurality of estimated quality inspection thresholds are determined in the value range of the quality inspection threshold according to the value range and the value interval of the quality inspection threshold, wherein the smallest estimated quality inspection threshold is the minimum value of the quality inspection threshold, and the intervals of the plurality of estimated quality inspection thresholds are the value interval of the quality inspection threshold.

[0188] The evaluation value corresponding to the estimated quality inspection threshold is determined, and in a case where the evaluation value corresponding to the estimated quality inspection threshold is in a preset interval, the estimated quality inspection threshold is determined as the quality inspection threshold.

[0189] In some embodiments, the evaluation value corresponding to the estimated quality inspection threshold satisfies the following formula:

[0190]

[0191] wherein KS is the evaluation value corresponding to the estimated quality inspection threshold; count{X i count{X

[0192] In some embodiments, the processing unit 502 is specifically configured to: in a case where the preselected index data is less than or equal to the quality inspection threshold, determine that the quality inspection result of the preselected index data is passed.

[0193] The embodiments of the present application also provide a computer readable storage medium, which includes computer execution instructions, and when the computer execution instructions run on a computer, the computer is caused to execute the carbon monitoring data quality inspection method provided by the above-described embodiments.

[0194] The embodiments of the present application also provide a computer program, which can be directly loaded into a memory and contains software codes, and the computer program can be loaded and executed by a computer to realize the carbon monitoring data quality inspection method provided by the above-described embodiments.

[0195] Those skilled in the art can realize that, in one or more examples described above, the functions described in the present application can be realized by hardware, software, firmware or any combination thereof. When realized by software, these functions can be stored in a computer readable medium or transmitted as one or more instructions or codes on a computer readable medium. The computer readable medium includes a computer readable storage medium and a communication medium, wherein the communication medium includes any medium that facilitates the transmission of a computer program from one place to another. The storage medium can be any available medium that can be accessed by a general or special purpose computer.

[0196] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above functional modules is taken as an example for illustration, and in actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above.

[0197] In several embodiments provided in the present application, it should be understood that the disclosed apparatus and method can be implemented by other manners. For example, the apparatus embodiments described above are merely illustrative, for example, the division of the modules or units is merely a logical function division, and actual implementation can have another division manner. For example, multiple units or components can be combined or integrated into another apparatus, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, apparatuses or units, which can be electrical, mechanical or other forms. The units described as separate components can be or can not be physically separated, and the components shown as units can be one physical unit or multiple physical units, that is, can be located in one place or can be distributed to multiple different places. Some or all units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0198] In addition, each functional unit in the embodiments of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit. When the integrated unit is realized in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of the present application essentially or the part that contributes to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions to make an apparatus (which can be a single chip, a chip, etc.) or a processor execute all or part of the steps of the method described in the embodiments of the present application. The storage medium mentioned above includes: a U disk, a mobile hard disk, a ROM, a RAM, a magnetic disk or an optical disk, and various program code storage media.

[0199] The above description is merely a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or replacements within the technical scope disclosed in the present application can be easily thought by those skilled in the art, and should be covered in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for carbon monitoring data quality inspection, characterized in that, The method comprises: obtaining an original data set; the original data set is a set of carbon monitoring data required by a target application scenario; inputting the original data set into a pre-configured data conversion model to output a standardized data set; the standardized data set comprises monitoring data of at least one index; determining a quality inspection threshold of preselected index data in the standardized data set according to the preselected index data; the preselected index data is monitoring data of an index in the standardized data set; performing quality inspection on the preselected index data according to the quality inspection threshold to determine a quality inspection result of the preselected index data.

2. The method of claim 1, wherein, The pre-configured data conversion model is determined by the following method: identifying a representation attribute of data in the original data set and determining a standard of the representation attribute; the representation attribute comprises at least one of a data unit, a data acquisition frequency and a data acquisition accuracy; determining the data conversion model according to the representation attribute and the standard of the representation attribute; the data conversion model is configured to convert input data into data meeting the standard of the representation attribute according to the standard of the representation attribute.

3. The method of claim 1, wherein, The original data set is obtained by: determining carbon monitoring data required by the target application scenario from the carbon monitoring data as the original data set according to the carbon monitoring data and the target application scenario.

4. The method of claim 1, wherein, The quality inspection threshold of the preselected index data is determined by: determining a harmonic mean of the preselected index data as a historical reference value; determining the quality inspection threshold according to the historical reference value.

5. The method of claim 1, wherein, The quality inspection threshold is determined according to the historical reference value by: determining a value range of the quality inspection threshold and a value interval of the quality inspection threshold according to the historical reference value; determining a plurality of estimated quality inspection thresholds in the value range of the quality inspection threshold according to the value range of the quality inspection threshold and the value interval of the quality inspection threshold; the smallest estimated quality inspection threshold is the minimum value of the quality inspection threshold; the intervals of the plurality of estimated quality inspection thresholds are the value interval of the quality inspection threshold; determining evaluation values corresponding to the plurality of estimated quality inspection thresholds; in a case where the evaluation values corresponding to the estimated quality inspection thresholds are in a preset interval, the estimated quality inspection threshold is determined as the quality inspection threshold.

6. The method of claim 5, wherein, The evaluation values corresponding to the estimated quality inspection thresholds satisfy the following formula: wherein KS is an evaluation value corresponding to the estimated quality inspection threshold; count{X i is the number of the pre-selected index data in the estimated quality inspection threshold range; and n is the number of the pre-selected index data.

7. The method of claim 1, wherein, The quality inspection result of the preselected index data is determined by: in a case where the preselected index data is less than or equal to the quality inspection threshold, determining that the quality inspection result of the preselected index data is passed.

8. A carbon monitoring data quality inspection device, characterized in that, The method comprises: a communication unit and a processing unit; the communication unit is configured to obtain an original data set; the original data set is a set of carbon monitoring data required by a target application scenario; the processing unit is configured to input the original data set into a pre-configured data conversion model to output a standardized data set; the standardized data set comprises monitoring data of at least one index; The processing unit is further configured to determine a quality inspection threshold of the pre-selected index data according to the pre-selected index data in the standardized data set, the pre-selected index data being monitoring data of an index in the standardized data set; The processing unit is further configured to perform quality inspection on the pre-selected index data according to the quality inspection threshold, and determine a quality inspection result of the pre-selected index data.

9. A carbon monitoring data quality inspection device, characterized by, The carbon monitoring data quality inspection device comprises: a processor and a memory; The memory is configured to store one or more programs, the one or more programs comprising computer execution instructions, when the carbon monitoring data quality inspection device is running, the processor executes the computer execution instructions stored in the memory, so that the carbon monitoring data quality inspection device executes the method in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, When the computer execution instructions stored in the computer readable storage medium are executed by the processor of the carbon monitoring data quality inspection device, the carbon monitoring data quality inspection device can execute the method in any one of claims 1 to 7.

11. A computer program product, characterised in that, The computer program product comprises: a computer program or instructions, when the computer program or instructions are running on a computer, so that the computer executes the method in any one of claims 1 to 7.

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