Data processing method, device, equipment and storage medium

Abstract

The present disclosure provides a data processing method, device, equipment and storage medium, which can be applied to the field of carbon neutrality technology. The method includes: based on the resource statistical data of the target subject, determining the lease duration and lease label of each lessee in the target subject, wherein the target subject includes multiple lessees and rental objects corresponding to each lessee; for each lessee, determining the lease type of the lessee based on the lease duration; when the lease label of the lessee indicates that the lessee is an external lease, based on the carbon emission division rule corresponding to the lease type, dividing the carbon emission data of the lessee into emission ranges, generating lease emission data, and storing the lease emission data in the carbon emission storage unit corresponding to the lessee.

Description

Technical Field

[0001] The present disclosure relates to the field of carbon neutrality technology, and more specifically, to a data processing method, device, equipment and storage medium. Background Art

[0002] At present, when relevant enterprises manage greenhouse gas emission data, since the enterprise may be the operator of multiple subsidiaries, they usually use operational control rights to manage the emission data of each subsidiary so as to store data of different emission ranges accordingly.

[0003] In the process of realizing the concept of the present disclosure, the inventors found that there are at least the following problems in the related technology: in the process of managing the emission data of multiple subsidiaries, due to the leasing relationship between the subsidiaries, it is difficult to accurately divide the emission data into emission ranges, resulting in low efficiency in the management of emission data. Summary of the invention

[0004] In view of this, the present disclosure provides a data processing method, apparatus, device and storage medium.

[0005] One aspect of the present disclosure provides a data processing method, comprising: determining the lease duration and lease tag of each lessee in the target subject based on resource statistical data of the target subject, wherein the target subject includes multiple lessees and a rental object corresponding to each lessee; for each of the lessees, determining the lease type of the lessee based on the lease duration; in a case where the lease tag of the lessee indicates that the lessee is an external lease, dividing the carbon emission data of the lessee into emission ranges based on the carbon emission division rules corresponding to the lease type, generating lease emission data, and storing the lease emission data in a carbon emission storage unit corresponding to the lessee.

[0006] According to an embodiment of the present disclosure, the above-mentioned determination of the lease type of the lessee based on the above-mentioned lease duration includes: when the above-mentioned lease duration is greater than the preset duration, determining the above-mentioned lease type as a capital lease; when the above-mentioned lease duration is less than or equal to the above-mentioned preset duration, determining the above-mentioned lease type as an operating lease.

[0007] According to an embodiment of the present disclosure, the carbon emission data of the lessee is divided into emission ranges based on the carbon emission classification rules corresponding to the lease type to generate the lessee emission data, including: when the lease type is the capital lease, the emission range of the carbon emission data is divided based on the gas emission source to generate the lessee emission data; when the lease type is the operating lease, the emission range of the carbon emission data is marked as a preset range to obtain the lessee emission data.

[0008] According to an embodiment of the present disclosure, the above method also includes: when the lease tag of the above lessee indicates that the above lessee is an internal lease, determining the rental object corresponding to the above lessee from the above target entity; marking the emission range of the above carbon emission data as a preset range to obtain rental emission data; and storing the above rental emission data in a carbon emission storage unit corresponding to the above rental object.

[0009] According to an embodiment of the present disclosure, before determining the rental object corresponding to the above-mentioned lessee from the above-mentioned target entity, it also includes: when the leasing tag of the above-mentioned lessee indicates that the above-mentioned lessee is an internal lease, based on the carbon emission classification rules corresponding to the above-mentioned lease type, the carbon emission data of the above-mentioned lessee is divided into emission ranges, and the leasing emission data is generated, so as to store the above-mentioned leasing emission data in the carbon emission storage unit corresponding to the above-mentioned lessee.

[0010] According to an embodiment of the present disclosure, after storing the rental emission data in the carbon emission storage unit corresponding to the rental object, the method further includes: deleting the rental emission data stored in the carbon emission storage unit corresponding to the lessee object.

[0011] According to an embodiment of the present disclosure, the above method also includes: obtaining resource activity data of the above lessee; determining multiple gas emission sources in the above resource activity data, wherein the above gas emission sources include direct emission sources and indirect emission sources; combining the carbon emission data corresponding to each of the above gas emission sources in the above resource activity data to obtain the carbon emission data of the above lessee.

[0012] Another aspect of the present disclosure provides a data processing device, including: a lessee determination module, for determining the lease duration and lease tag of each lessee object in the target subject based on resource statistical data of the target subject, wherein the target subject includes multiple lessees and a rental object corresponding to each lessee object; a type determination module, for determining the lease type of the lessee object based on the lease duration for each lessee object; and a lessee data storage module, for dividing the carbon emission data of the lessee object into emission ranges based on the carbon emission division rules corresponding to the lease type, generating lessee emission data, when the lease tag of the lessee object indicates that the lessee object is externally leased, so as to store the lessee emission data in a carbon emission storage unit corresponding to the lessee object.

[0013] Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, which are used to implement the above method when executed.

[0014] Another aspect of the present disclosure provides a computer program product, the computer program product comprising computer executable instructions, and the instructions are used to implement the above method when executed.

[0015] According to the embodiments of the present disclosure, the lease duration and lease tag of the lessee are determined based on the resource statistical data of the target subject. The lease type of the lessee is determined based on the lease duration, so that the emission range of the carbon emission data is divided based on the lease type. Since it is convenient to determine the lease relationship between the lessee and the leased object based on the resource statistical data, the emission range of the carbon emission data is divided based on the lease duration and the lease tag, so that the division result is more accurate, and the management efficiency of the carbon emission data is effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and other objects, features and advantages of the present disclosure will become more apparent through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, in which:

[0017] Figure 1 A schematic diagram of carbon emission classification range according to an embodiment of the present disclosure is schematically shown;

[0018] Figure 2 An exemplary system architecture for a data processing method and apparatus to which the present disclosure may be applied is schematically shown;

[0019] Figure 3 A flowchart schematically shows a data processing method according to an embodiment of the present disclosure;

[0020] Figure 4 A schematic diagram of carbon emission range division according to a data processing method according to an embodiment of the present disclosure is schematically shown;

[0021] Figure 5 A flowchart schematically shows a data processing method according to another embodiment of the present disclosure;

[0022] Figure 6 A block diagram schematically shows a data processing device according to an embodiment of the present disclosure; and

[0023] Figure 7 A block diagram of an electronic device suitable for implementing a data processing method according to an embodiment of the present disclosure is schematically shown. DETAILED DESCRIPTION

[0024] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are exemplary only and are not intended to limit the scope of the present disclosure. In the following detailed description, for ease of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, it is apparent that one or more embodiments may also be implemented without these specific details. In addition, in the following description, descriptions of known structures and technologies are omitted to avoid unnecessary confusion of the concepts of the present disclosure.

[0025] The terms used herein are only for describing specific embodiments and are not intended to limit the present disclosure. The terms "comprise", "include", etc. used herein indicate the existence of the features, steps, operations and / or components, but do not exclude the existence or addition of one or more other features, steps, operations or components.

[0026] All terms (including technical and scientific terms) used herein have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0027] When using expressions such as "at least one of A, B, and C, etc.", they should generally be interpreted according to the meaning of the expression commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include but is not limited to a system having A alone, B alone, C alone, A and B, A and C, B and C, and / or A, B, C, etc.).

[0028] In the embodiments of the present disclosure, the collection, updating, analysis, processing, use, transmission, provision, disclosure, storage, etc. of the data involved (for example, including but not limited to user personal information) are in compliance with the provisions of relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. In particular, necessary measures are taken for user personal information to prevent illegal access to user personal information data and maintain the security of user personal information, network security, and national security.

[0029] In the embodiments of the present disclosure, the user's authorization or consent is obtained before obtaining or collecting the user's personal information.

[0030] According to the greenhouse gas protocol, Figure 1 As shown in Figure 1, emission sources can be divided according to the emissions of different facilities of the enterprise. Among them, greenhouse gases include carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulfur hexafluoride (SF6) and hydrogen trifluoride (HF3).

[0031] Scope 1 (direct emissions): Direct greenhouse gas emissions from sources owned or controlled by the reporting entity. This could be emissions directly from manufacturing products, such as factory fumes, emissions from equipment on owned property and owned vehicles. This does not include the burning of biomass.

[0032] Scope 2 (indirect emissions): Includes greenhouse gas emissions from purchased electricity, steam, and heating / cooling. These emissions actually occur at the facility where the electricity, steam, cooling, or heating is generated. However, as a consumer of energy, the consumer is still responsible for the greenhouse gas emissions being generated.

[0033] Scope 3 (indirect emissions): refers to emissions from sources that are not owned by the reporting company and are not directly controlled by the reporting company. However, they are related to the company's activities, specifically upstream and downstream activities. This is usually considered to be the company's supply chain, so the emissions caused by suppliers, outsourced activities and employee travel and commuting within the supply chain. Use a carbon management platform to manage greenhouse gases generated by transportation and distribution in the supply chain.

[0034] In related technologies, carbon emission sources are divided based on the boundaries of corporate operating rights, while some companies are managed by financial control rights rather than operational control rights. Therefore, it is not convenient for companies with financial control rights to divide the scope of carbon emission data and manage carbon emission data.

[0035] The embodiments of the present disclosure provide a data processing method, a data processing device, an electronic device, a computer-readable storage medium, and a computer program product. The method includes: determining the lease duration and lease tag of each lessee in the target subject based on the resource statistical data of the target subject, wherein the target subject includes multiple lessees and a rental object corresponding to each lessee; for each lessee, determining the lease type of the lessee based on the lease duration; when the lease tag of the lessee indicates that the lessee is an external lease, dividing the carbon emission data of the lessee into emission ranges based on the carbon emission division rules corresponding to the lease type, generating lease emission data, and storing the lease emission data in the carbon emission storage unit corresponding to the lessee. .

[0036] Figure 2 The following schematically shows an exemplary system architecture for the data processing method and apparatus to which the present disclosure can be applied. It should be noted that: Figure 2 What is shown is merely an example of a system architecture to which the embodiments of the present disclosure can be applied, in order to help those skilled in the art understand the technical content of the present disclosure, but it does not mean that the embodiments of the present disclosure cannot be used in other devices, systems, environments or scenarios.

[0037] like Figure 2 As shown, the system architecture 200 according to this embodiment may include terminal devices 201, 202, 203, a network 204 and a server 205. The network 204 is used to provide a medium for communication links between the terminal devices 201, 202, 203 and the server 205. The network 204 may include various connection types, such as wired and / or wireless communication links, etc.

[0038] The user can use the terminal devices 201, 202, 203 to interact with the server 205 through the network 204 to receive or send messages, etc. Various communication client applications can be installed on the terminal devices 201, 202, 203, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients and / or social platform software, etc. (only as examples).

[0039] The terminal devices 201 , 202 , and 203 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers.

[0040] The server 205 may be a server that provides various services, such as a background management server (only an example) that provides support for websites browsed by users using the terminal devices 201, 202, and 203. The background management server may analyze and process the received data such as user requests, and feed back the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal device.

[0041] It should be noted that the data processing method provided in the embodiment of the present disclosure can generally be executed by the server 205. Accordingly, the data processing device provided in the embodiment of the present disclosure can generally be set in the server 205. The data processing method provided in the embodiment of the present disclosure can also be executed by a server or server cluster that is different from the server 205 and can communicate with the terminal device 201, 202, 203 and / or the server 205. Accordingly, the data processing device provided in the embodiment of the present disclosure can also be set in a server or server cluster that is different from the server 205 and can communicate with the terminal device 201, 202, 203 and / or the server 205. Alternatively, the data processing method provided in the embodiment of the present disclosure can also be executed by the terminal device 201, 202, or 203, or it can also be executed by other terminal devices different from the terminal device 201, 202, or 203. Accordingly, the data processing device provided in the embodiment of the present disclosure can also be set in the terminal device 201, 202, or 203, or it can be set in other terminal devices different from the terminal device 201, 202, or 203.

[0042] It should be understood that Figure 2 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0043] Figure 3 The flowchart of the data processing method according to the embodiment of the present disclosure is schematically shown.

[0044] like Figure 3 As shown, the method includes operations S310 to S330.

[0045] In operation S310, based on the resource statistical data of the target subject, the lease duration and lease tag of each tenant object in the target subject are determined, wherein the target subject includes multiple tenant objects and a rental object corresponding to each tenant object.

[0046] In operation S320, for each lessee object, a lease type of the lessee object is determined based on the lease duration.

[0047] In operation S330, when the lessee tag of the lessee object indicates that the lessee object is an external lease, the carbon emission data of the lessee is divided into emission ranges based on the carbon emission division rules corresponding to the lease type, and the lease emission data is generated to store the lease emission data in the carbon emission storage unit corresponding to the lessee object.

[0048] According to an embodiment of the present disclosure, the target entity may be a certain enterprise group, and the target entity includes a plurality of lessees and a rental object corresponding to each lessee. Specifically, the lessees and the rental objects may be subsidiaries of the enterprise group, or other companies outside the enterprise group, or other assets that can be rented or leased.

[0049] According to an embodiment of the present disclosure, when the organizational boundary setting principle of the target entity is the equity method or financial control right, the resource statistical data of the target entity is obtained. The resource statistical data may be a financial report of the target entity. Specifically, the financial report records the information of all assets of the target entity.

[0050] According to an embodiment of the present disclosure, the data of each lessee is retrieved from the resource statistical data, and then the lease duration and lease tag of each lessee are determined. The lease duration is the duration for which the lessee leases the assets of the lessor. The lease tag is marked when the lessee leases the assets, and the lease tags include internal lease and external lease. If the asset leased by the lessee is an asset within the enterprise group, the lease tag of the lessee is determined to be an internal lease. If it is not an asset within the enterprise group, the lease tag is determined to be an external lease.

[0051] According to an embodiment of the present disclosure, for each lessee, the lease type of the lessee is determined based on the lease duration. Among them, the lease types include capital lease and operating lease. If the lease duration is longer, it means that the lessee may make some modifications to the leased assets, and the lessee will bear all risks and obtain all returns. Therefore, the lease type with a longer lease duration is determined to be a capital lease. If the lease duration is shorter, it means that the lessee only has the right to operate the leased assets, and the lessee will not bear any risks and will not obtain any returns. Therefore, the lease type with a shorter lease duration is determined to be a capital lease.

[0052] According to the embodiment of the present disclosure, when the lease tag of the lessee object indicates that the lessee object is an external lease, it means that when analyzing and storing the carbon emission data of the lessee object, there will be no conflict with the carbon emission data of other lessees or rented objects in the target subject. Therefore, the carbon emission data of the lessee object can be directly divided into emission ranges based on the carbon emission division rules corresponding to the lease type.

[0053] According to the embodiments of the present disclosure, different types of tenants correspond to different carbon emission classification rules. Among them, the carbon emission classification rules are public standard classification rules and can be obtained from open source websites. After the carbon emission data of the tenant is divided into emission ranges, the tenant emission data is generated and stored in the storage unit corresponding to the tenant to facilitate the management of the carbon emission data.

[0054] According to the embodiments of the present disclosure, the lease duration and lease tag of the lessee are determined based on the resource statistical data of the target subject. The lease type of the lessee is determined based on the lease duration, so that the emission range of the carbon emission data is divided based on the lease type. Since it is convenient to determine the lease relationship between the lessee and the leased object based on the resource statistical data, the emission range of the carbon emission data is divided based on the lease duration and the lease tag, so that the division result is more accurate, and the management efficiency of the carbon emission data is effectively improved.

[0055] According to an embodiment of the present disclosure, the lease type of the lessee is determined based on the lease duration, including: when the lease duration is greater than a preset duration, determining the lease type as a capital lease; when the lease duration is less than or equal to the preset duration, determining the lease type as an operating lease.

[0056] According to an embodiment of the present disclosure, the preset duration may be determined based on the asset type of the leased asset. For example, if the asset type is a building, the preset duration may be set to one year. If the asset type is a vehicle, the preset duration may be set to half a year.

[0057] According to the embodiment of the present disclosure, it is determined whether the lease duration is greater than the preset duration. If it is greater, it means that the lessee may have made some modifications to the leased assets, and the lessee will bear all risks and obtain all returns. Therefore, the lease type is determined to be a capital lease, and a capital lease is completely a lessee in financial accounting.

[0058] According to an embodiment of the present disclosure, if the lease duration is less than or equal to the preset duration, it means that the lessee only has the right to operate the leased assets, and the lessee will not bear any risk or receive any return. Therefore, the lease type is determined to be an operating lease. Specifically, all leases of non-capital lease types belong to operating leases.

[0059] According to an embodiment of the present disclosure, when determining the lease duration of a lessee, resource statistical data may be queried. The resource statistical data records the start lease time and the end lease time of each lessee, and the lease duration may be calculated based on the start lease time and the end lease time. By obtaining the lease duration from the resource statistical data, it is convenient to manage the carbon emission data of each lessee.

[0060] According to an embodiment of the present disclosure, based on the carbon emission classification rules corresponding to the lease type, the carbon emission data of the lessee is divided into emission ranges to generate the lessee's emission data, including: when the lease type is a capital lease, the emission range of the carbon emission data is divided based on the gas emission source to generate the lessee's emission data; when the lease type is an operating lease, the emission range of the carbon emission data is marked as a preset range to obtain the lessee's emission data.

[0061] According to the embodiments of the present disclosure, when the lease type is a capital lease, the lessee has ownership and financial control. Therefore, the emission range of carbon emission data is divided based on the gas emission source, and the emission of fuel combustion is included in scope one, and the emission of purchased electricity is included in scope two, so as to obtain the lessee emission data.

[0062] According to an embodiment of the present disclosure, when the lease type is an operating lease, the lessee has no ownership or financial control. Therefore, the emission range of the carbon emission data is marked as a preset range. Among them, the preset range is range three. Specifically, the emissions from fuel combustion and the use of purchased electricity are included in range three to obtain the lessee's emission data.

[0063] According to an embodiment of the present disclosure, the carbon emission data of the lessee is divided into emission ranges according to the lease type, so that the emission range division is more reasonable and it is convenient to manage the divided lessee emission data.

[0064] According to an embodiment of the present disclosure, the data processing method also includes: when the lessee tag of the lessee object indicates that the lessee object is internally leased, determining the rental object corresponding to the lessee object from the target entity; marking the emission range of the carbon emission data as a preset range to obtain rental emission data; and storing the rental emission data in a carbon emission storage unit corresponding to the rental object.

[0065] According to an embodiment of the present disclosure, when the lease tag of the lessee object indicates that the lessee object is internally leased, it means that the asset leased by the lessee object is an asset within the enterprise group. Therefore, the rental object corresponding to the lessee object should be an object in the target subject. Specifically, based on the information of the lessee object, the rental object corresponding to the lessee object can be determined from the target subject.

[0066] According to the embodiment of the present disclosure, from the perspective of the leased object, the emission range of the carbon emission data all belongs to the third range, so the carbon emission data of the lessee is marked as the third range, thereby obtaining the lease emission data. Then, the lease emission data is directly stored in the carbon emission storage unit corresponding to the leased object, and there is no need to generate the lessee emission data, which effectively simplifies the data management process and facilitates the management of the lease emission data.

[0067] Figure 4A schematic diagram of carbon emission range division according to the data processing method of an embodiment of the present disclosure is schematically shown.

[0068] like Figure 4 As shown, the target entity 410 includes four lessees, namely the first lessee 411, the second lessee 412, the third lessee 413, and the fourth lessee 414. Among them, the asset leased by the first lessee 411 is a store 415 that is not in the organizational boundary. The store 415 is not an asset of the target entity and is an external lease. Therefore, the emission range of the store 415 is determined to be the first range and the second range.

[0069] The assets leased by the second lessee 412 are the first subsidiary 416 and the second subsidiary 417 within the organizational boundary. The assets of the target entities of the first subsidiary 416 and the second subsidiary 417 are owned by the target entity, and belong to internal leasing. Therefore, the emission scope of the first subsidiary 416 and the second subsidiary 417 is determined as the third scope.

[0070] The assets leased by the third lessee 413 are a warehouse 418 and a non-equity tricycle 419 that are not in the organizational boundary. The warehouse 418 and the non-equity tricycle 419 are not assets of the target entity and are external leases. Therefore, the emission ranges of the warehouse 418 and the non-equity tricycle 419 are determined to be the first range and the second range.

[0071] The asset leased by the fourth lessee 414 is an office building 420 that is not located in the organizational boundary. The office building 420 is not an asset of the target entity but is leased externally. Therefore, the emission scope of the office building 420 is determined to be the first scope and the second scope.

[0072] According to an embodiment of the present disclosure, before determining the rental object corresponding to the lessee object from the target subject, it also includes: when the lessee tag of the lessee object characterizes that the lessee object is internally leased, based on the carbon emission classification rules corresponding to the lease type, the carbon emission data of the lessee is divided into emission ranges, and the leased emission data is generated, so as to store the leased emission data in the carbon emission storage unit corresponding to the lessee object.

[0073] According to the embodiment of the present disclosure, before determining the lease object corresponding to the lessee object from the target subject, it is still necessary to divide the carbon emission data of the lessee object into emission ranges based on the carbon emission division rules corresponding to the lease type, generate the lease emission data, and store it in the carbon emission storage unit corresponding to the lessee object. The division process is the same as the above process and will not be repeated here.

[0074] According to the embodiments of the present disclosure, although the lessee and the lessor correspond to each other in terms of carbon emission data, duplicate storage may occur. However, in the process of data management, the divided carbon emission data still needs to be stored in the corresponding carbon emission storage unit first, so as to reduce data loss and ensure data integrity.

[0075] According to an embodiment of the present disclosure, after storing the rental emission data in the carbon emission storage unit corresponding to the rental object, it also includes: deleting the rental emission data stored in the carbon emission storage unit corresponding to the lessee object.

[0076] According to the embodiment of the present disclosure, after the rental emission data is stored in the carbon emission storage unit corresponding to the rental object, it indicates that the storage of the carbon emission data has been completed. Therefore, the lessee emission data corresponding to the rental emission data can be eliminated, thereby avoiding duplicate data recording and making the process of managing carbon emission data clearer.

[0077] Figure 5 The flowchart schematically shows a data processing method according to another embodiment of the present disclosure.

[0078] like Figure 5 As shown, the method includes operations S510 to S580.

[0079] In operation S510, based on the resource statistical data of the target subject, the lease duration and lease tag of each tenant object in the target subject are determined, wherein the target subject includes multiple tenant objects and a rental object corresponding to each tenant object.

[0080] In operation S520, for each lessee object, a lease type of the lessee object is determined based on the lease duration.

[0081] In operation S530, based on the carbon emission classification rule corresponding to the lease type, the carbon emission data of the lessee is classified into emission ranges to generate the lessee emission data, and the lessee emission data is stored in the carbon emission storage unit corresponding to the lessee.

[0082] In operation S540, it is determined whether the lease tag of the lease object indicates that the lease object is internally leased.

[0083] In operation S550, when the tenant tag of the tenant object indicates that the tenant object is internally leased, a rental object corresponding to the tenant object is determined from the target subject.

[0084] In operation S560, the emission range of the carbon emission data is marked as a preset range to obtain rental emission data.

[0085] In operation S570, the rental emission data is stored in a carbon emission storage unit corresponding to the rental object.

[0086] In operation S580, the lessee emission data stored in the carbon emission storage unit corresponding to the lessee is deleted.

[0087] According to an embodiment of the present disclosure, in the process of storing the carbon emission data of the lessee, the carbon emission data must first be divided into emission ranges based on the lease type of the lessee to generate the lessee emission data. After the lessee emission data is stored, the rental emission data corresponding to the lessee emission data is generated and stored. After the storage is completed, the stored lessee emission data is deleted to avoid duplicate data recording, making the process of managing carbon emission data clearer. This not only reduces the loss of data, but also ensures the integrity of the data.

[0088] According to an embodiment of the present disclosure, the data processing method also includes: obtaining resource activity data of the lessee; determining multiple gas emission sources in the resource activity data, wherein the gas emission sources include direct emission sources and indirect emission sources; and combining the carbon emission data corresponding to each gas emission source in the resource activity data to obtain the carbon emission data of the lessee.

[0089] According to an embodiment of the present disclosure, resource activity data of the lessee is obtained, wherein the resource activity data may be data generated by the user when using electricity, water and gas, or data generated by the factory when burning fuel. It should be noted that the resource activity data are all obtained from open source websites, and are authorized and agreed by the user, and include but are not limited to notifying the user to read the user agreement (notification) before the user uses the function, and signing the agreement (authorization) including authorization-related user information.

[0090] According to an embodiment of the present disclosure, multiple gas emission sources in resource activity data are determined. In the process of determination, it is necessary to judge whether the greenhouse gases emitted in the resource activity data are direct emissions or indirect emissions, and then determine the gas emission sources. For example: in the resource activity data, it is determined that there are greenhouse gases generated by vehicle driving, and then the corresponding gas emission sources are determined to be direct emission sources. In the resource activity data, it is determined that there are greenhouse gases generated by the use of air conditioners, and then the corresponding gas emission sources are determined to be indirect emission sources.

[0091] According to an embodiment of the present disclosure, the carbon emission data corresponding to each gas emission source in the resource activity data is combined to obtain the carbon emission data of the lessee, wherein the carbon emission data includes the specific emission mode and the gas emission source corresponding to the emission mode, so as to facilitate the subsequent analysis and management of the carbon emission data.

[0092] Figure 6 The block diagram schematically shows a data processing device according to an embodiment of the present disclosure.

[0093] like Figure 6 As shown, the data processing device 600 includes a tenant determination module 610 , a type determination module 620 and a tenant data storage module 630 .

[0094] The lease determination module 610 is used to determine the lease duration and lease tag of each tenant object in the target subject based on the resource statistical data of the target subject, wherein the target subject includes multiple tenant objects and a rental object corresponding to each tenant object.

[0095] The type determination module 620 is configured to determine the lease type of each lessee based on the lease duration.

[0096] The lessee data storage module 630 is used to divide the carbon emission data of the lessee into emission ranges based on the carbon emission classification rules corresponding to the lease type when the lessee tag of the lessee object indicates that the lessee object is externally leased, and generate the lessee emission data so as to store the lessee emission data in the carbon emission storage unit corresponding to the lessee object.

[0097] According to an embodiment of the present disclosure, the type determination module 620 includes a first type determination submodule and a second type determination submodule.

[0098] The first type determination submodule is used to determine the lease type as a capital lease when the lease duration is greater than a preset duration;

[0099] The second type determination submodule is used to determine the lease type as an operating lease when the lease duration is less than or equal to a preset duration.

[0100] According to an embodiment of the present disclosure, the tenant data storage module 630 includes a first range partitioning submodule and a second range partitioning submodule.

[0101] The first range division submodule is used to divide the emission range of carbon emission data based on the gas emission source to generate lessee emission data when the lease type is a capital lease.

[0102] The second range division submodule is used to mark the emission range of the carbon emission data as a preset range to obtain the lessee's emission data when the lease type is an operating lease.

[0103] According to an embodiment of the present disclosure, the data processing device 600 further includes an object determination module, a range marking module, and a rental data storage module.

[0104] The object determination module is used to determine the rental object corresponding to the tenant object from the target subject when the tenant tag of the tenant object indicates that the tenant object is internally leased.

[0105] The range marking module is used to mark the emission range of carbon emission data as a preset range to obtain rental emission data.

[0106] The rental data storage module is used to store the rental emission data in the carbon emission storage unit corresponding to the rental object.

[0107] According to an embodiment of the present disclosure, the data processing device 600 further includes a range partitioning module.

[0108] The range division module is used to divide the emission range of the carbon emission data of the lessee based on the carbon emission division rules corresponding to the lease type when the lessee tag of the lessee indicates that the lessee is internally leased, and generate the leased emission data, so as to store the leased emission data in the carbon emission storage unit corresponding to the lessee.

[0109] According to an embodiment of the present disclosure, the data processing device 600 further includes a data deletion module.

[0110] The data deletion module is used to delete the lessee emission data stored in the carbon emission storage unit corresponding to the lessee.

[0111] According to an embodiment of the present disclosure, the data processing device 600 further includes a data acquisition module, an emission determination module and a data determination module.

[0112] The data acquisition module is used to obtain the resource activity data of the tenant object.

[0113] The emission determination module is used to determine multiple gas emission sources in resource activity data, wherein the gas emission sources include direct emission sources and indirect emission sources.

[0114] The data determination module is used to combine the carbon emission data corresponding to each gas emission source in the resource activity data to obtain the carbon emission data of the lessee.

[0115] According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits, or at least part of the functions of any one of them can be implemented in one module. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be split into multiple modules for implementation. According to the embodiments of the present invention, any one or more of the modules, submodules, units, and subunits can be at least partially implemented as hardware circuits, such as field programmable gate arrays (FPGAs), programmable logic arrays (PLAs), systems on chips, systems on substrates, systems on packages, application specific integrated circuits (ASICs), or can be implemented by hardware or firmware in any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in any appropriate combination of any of them. Alternatively, according to the embodiments of the present invention, one or more of the modules, submodules, units, and subunits can be at least partially implemented as computer program modules, and when the computer program modules are run, the corresponding functions can be performed.

[0116] For example, any multiple of the tenant determination module 610, the type determination module 620, and the tenant data storage module 630 can be combined in one module / unit / sub-unit for implementation, or any one of the modules / units / sub-units can be split into multiple modules / units / sub-units. Alternatively, at least part of the functions of one or more of these modules / units / sub-units can be combined with at least part of the functions of other modules / units / sub-units and implemented in one module / unit / sub-unit. According to an embodiment of the present disclosure, at least one of the tenant determination module 610, the type determination module 620, and the tenant data storage module 630 can be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on a chip, a system on a substrate, a system on a package, an application specific integrated circuit (ASIC), or can be implemented by hardware or firmware such as any other reasonable way of integrating or packaging the circuit, or implemented in any one of the three implementation methods of software, hardware, and firmware, or in an appropriate combination of any of them. Alternatively, at least one of the tenant determination module 610 , the type determination module 620 , and the tenant data storage module 630 may be at least partially implemented as a computer program module, and when the computer program module is executed, a corresponding function may be performed.

[0117] It should be noted that the data processing system part in the embodiments of the present disclosure corresponds to the data processing method part in the embodiments of the present disclosure. The description of the data processing system part specifically refers to the data processing method part, which will not be repeated here.

[0118] Figure 7A block diagram of an electronic device suitable for implementing a data processing method according to an embodiment of the present disclosure is schematically shown. Figure 7 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0119] like Figure 7 As shown, the electronic device 700 according to an embodiment of the present disclosure includes a processor 701, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage part 708 to a random access memory (RAM) 703. The processor 701 may include, for example, a general-purpose microprocessor (e.g., a CPU), an instruction set processor and / or a related chipset and / or a special-purpose microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 701 may also include an onboard memory for caching purposes. The processor 701 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0120] In RAM 703, various programs and data required for the operation of electronic device 700 are stored. Processor 701, ROM 702 and RAM 703 are connected to each other via bus 704. Processor 701 performs various operations of the method flow according to the embodiment of the present disclosure by executing the program in ROM 702 and / or RAM 703. It should be noted that the program can also be stored in one or more memories other than ROM 702 and RAM 703. Processor 701 can also perform various operations of the method flow according to the embodiment of the present disclosure by executing the program stored in the one or more memories.

[0121] According to an embodiment of the present disclosure, the electronic device 700 may further include an input / output (I / O) interface 705, which is also connected to the bus 704. The system 700 may further include one or more of the following components connected to the I / O interface 705: an input section 706 including a keyboard, a mouse, etc.; an output section 707 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, a modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 710 as needed, so that a computer program read therefrom is installed into the storage section 708 as needed.

[0122] According to an embodiment of the present disclosure, the method flow according to an embodiment of the present disclosure can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable storage medium, and the computer program contains a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 709, and / or installed from the removable medium 711. When the computer program is executed by the processor 701, the above-mentioned functions defined in the system of the embodiment of the present disclosure are executed. According to an embodiment of the present disclosure, the system, equipment, device, module, unit, etc. described above can be implemented by a computer program module.

[0123] The present disclosure also provides a computer-readable storage medium, which may be included in the device / apparatus / system described in the above embodiments; or may exist independently without being assembled into the device / apparatus / system. The above computer-readable storage medium carries one or more programs, and when the above one or more programs are executed, the method according to the embodiment of the present disclosure is implemented.

[0124] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium. For example, it may include, but is not limited to: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device.

[0125] For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include the ROM 702 and / or the RAM 703 described above and / or one or more memories other than the ROM 702 and the RAM 703 .

[0126] The embodiments of the present disclosure also include a computer program product, which includes a computer program, which contains program code for executing the method provided by the embodiments of the present disclosure. When the computer program product runs on an electronic device, the program code is used to enable the electronic device to implement the data processing method provided by the embodiments of the present disclosure.

[0127] When the computer program is executed by the processor 701, the above functions defined in the system / device of the embodiment of the present disclosure are executed. According to the embodiment of the present disclosure, the system, device, module, unit, etc. described above can be implemented by a computer program module.

[0128] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices, magnetic storage devices, etc. In another embodiment, the computer program may also be transmitted and distributed in the form of signals on a network medium, and downloaded and installed through the communication part 709, and / or installed from the removable medium 711. The program code contained in the computer program may be transmitted using any appropriate network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0129] According to an embodiment of the present disclosure, the program code for executing the computer program provided by the embodiment of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level process and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages ​​include, but are not limited to, Java, C++, python, "C" language or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on the remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, using an Internet service provider to connect through the Internet).

[0130] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram may represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box may also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions. It can be understood by those skilled in the art that the features recorded in the various embodiments and / or claims of the present disclosure can be combined and / or combined in a variety of ways, even if such a combination or combination is not explicitly recorded in the present disclosure. In particular, without departing from the spirit and teaching of the present disclosure, the features described in the various embodiments and / or claims of the present disclosure may be combined and / or combined in a variety of ways. All of these combinations and / or combinations fall within the scope of the present disclosure.

[0131] The embodiments of the present disclosure are described above. However, these embodiments are only for illustrative purposes and are not intended to limit the scope of the present disclosure. Although the embodiments are described above separately, this does not mean that the measures in the various embodiments cannot be used in combination to advantage. The scope of the present disclosure is defined by the attached claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art may make a variety of substitutions and modifications, which should all fall within the scope of the present disclosure.

Claims

1. A data processing method, comprising: Determine the lease duration and lease tag of each tenant object in the target subject based on the resource statistical data of the target subject, wherein the target subject includes multiple tenant objects and a rental object corresponding to each tenant object; For each of the lessees, determining the lease type of the lessee based on the lease duration, wherein the lease type includes an operating lease and a capital lease; In the case where the lessee tag of the lessee object indicates that the lessee object is an external lease, based on the carbon emission classification rule corresponding to the lease type, the carbon emission data of the lessee object is divided into emission ranges to generate lease emission data, so as to store the lease emission data in the carbon emission storage unit corresponding to the lessee object, wherein the lessee object that does not belong to the target subject asset is an external lease; The step of dividing the carbon emission data of the lessee into emission ranges based on the carbon emission classification rules corresponding to the lease type to generate the lessee emission data includes: In the case where the lease type is the capital lease, dividing the emission range of the carbon emission data based on the gas emission source to generate the lessee emission data; In the case where the lease type is the operating lease, the emission range of the carbon emission data is marked as a preset range to obtain the lessee emission data.

2. The method according to claim 1, wherein: The determining the lease type of the lessee based on the lease duration includes: When the lease term is longer than the preset term, determining the lease type as a capital lease; When the lease duration is less than or equal to the preset duration, the lease type is determined to be an operating lease.

3. The method according to claim 1, further comprising: In the case where the lease tag of the lease object indicates that the lease object is internally leased, determining a rental object corresponding to the lease object from the target subject, wherein the lease object belonging to the target subject asset is internally leased; Marking the emission range of the carbon emission data as a preset range to obtain rental emission data; The rental emission data is stored in a carbon emission storage unit corresponding to the rental object.

4. The method according to claim 3, wherein: Before determining the rental object corresponding to the lessee object from the target subject, the method further includes: In the case where the lessee tag of the lessee indicates that the lessee is internally leased, based on the carbon emission classification rule corresponding to the lease type, the carbon emission data of the lessee is divided into emission ranges to generate lease emission data, so as to store the lease emission data in a carbon emission storage unit corresponding to the lessee.

5. The method according to claim 4, wherein: After storing the rental emission data in the carbon emission storage unit corresponding to the rental object, the method further includes: The lessee emission data stored in the carbon emission storage unit corresponding to the lessee object is deleted.

6. The method according to claim 1, further comprising: Obtain resource activity data of the lessee; determining a plurality of gas emission sources in the resource activity data, wherein the gas emission sources include direct emission sources and indirect emission sources; The carbon emission data corresponding to each of the gas emission sources in the resource activity data are combined to obtain the carbon emission data of the lessee.

7. A data processing device, comprising: A leasing determination module, configured to determine the leasing duration and leasing tag of each leasing object in the target subject based on the resource statistical data of the target subject, wherein the target subject includes multiple leasing objects and a leasing object corresponding to each leasing object; A type determination module, configured to determine, for each of the lessees, a lease type of the lessee based on the lease duration, wherein the lease type includes an operating lease and a capital lease; A lessee data storage module, for dividing the carbon emission data of the lessee into emission ranges based on the carbon emission classification rules corresponding to the lease type, generating lessee emission data, and storing the lessee emission data in a carbon emission storage unit corresponding to the lessee, when the lessee tag of the lessee object indicates that the lessee object is an external lease, wherein the lessee object that does not belong to the target subject asset is an external lease; Wherein, the leased data storage module includes: The first range division submodule is used to divide the emission range of carbon emission data based on the gas emission source to generate lessee emission data when the lease type is capital lease; The second range division submodule is used to mark the emission range of the carbon emission data as a preset range to obtain the lessee's emission data when the lease type is an operating lease.

8. An electronic device comprising: one or more processors; a memory for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, enables the processor to implement the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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