Detailed Description
For a clearer understanding of technical features, objects, and effects of the present application, a detailed description of specific embodiments of the present application will be made with reference to the accompanying drawings.
The embodiment of the application provides an industrial carbon chain analysis tracking system and method based on identification analysis.
Referring to fig. 1, fig. 1 is a schematic block diagram of an industrial carbon chain analysis tracking system based on identification analysis according to an embodiment of the present application, including: the system comprises an identification analysis module, a blockchain module, a factor data management module, a carbon accounting model design module and an engine module;
the identification analysis module is used for managing unique identity codes of the entity object and the virtual object so as to facilitate the identification of the system;
the block chain module is used for recording and managing transaction record information and asset tracking information so as to ensure the non-tamper property and transparency of the data;
The factor data management module is used for managing various data factors related to carbon emission and recording, maintaining and updating the various data factors;
a carbon accounting model design module for designing a carbon emission model organizing carbon and a carbon emission model of product carbon;
the engine module includes: a carbon emission accounting engine, a carbon inventory report generation engine and a product carbon footprint traceability engine;
the carbon emission accounting engine is used for generating carbon emission data based on the input data, the designed carbon emission model of the tissue carbon and the carbon emission model of the product carbon and inputting the carbon emission data into the carbon inventory report generation engine;
the carbon inventory report generation engine is used for generating a carbon emission report, and a user can perform the carbon inventory report generation on the carbon inventory report;
the product carbon footprint tracing engine is used for inquiring carbon emission data of product carbon, tracing the source of the data and verifying the authenticity of the data.
Specifically, the identification analysis module is used for managing unique identity codes of the entity object and the virtual object so as to facilitate the identification of the system; the blockchain module is used for recording and managing information such as transaction records, asset tracking and the like so as to ensure the non-tamper property and transparency of the data; a factor data management module responsible for managing factor data related to carbon emissions, comprising: recording, maintaining and updating; the carbon accounting model design module is used for determining carbon sources and flows of tissue carbon, defining the range of accounting, and designing a carbon emission model of tissue carbon, and is also used for designing a carbon emission model of product carbon, including the whole life cycle of the product. The modules together construct a system supporting analysis, calculation, storage, inquiry and traceability of carbon emission data so as to better understand and manage carbon emission conditions, thereby promoting sustainable development and achieving environmental protection targets.
In particular, the organised carbon emissions are mainly derived from the energy consumption and production processes organised in daily operations. Energy consumption is one of the main sources of organized carbon emissions, especially the use of fossil fuels such as coal, oil, and natural gas, etc., producing large amounts of carbon dioxide emissions. The product carbon footprint refers to the total amount of greenhouse gas emissions produced throughout the life cycle of the product carbon. There are also challenges in product carbon footprint calculation and management. First, complex supply chains and multiple production links are involved, resulting in relatively complex collection and organization of data. Enterprises need to cooperate with suppliers and partners to collect and verify data together so as to ensure the accuracy and reliability of accounting results.
The identification analysis module comprises: the system comprises a data acquisition sub-module, a searching sub-module, an updating sub-module, a deleting identification sub-module and a function sub-module for providing safety encryption and decryption of the identification;
the user identifies different identification information through the data acquisition sub-module, and registers the identification information to an identification system for each stage of the product;
the user inquires the identification information through the searching sub-module;
updating the identification information through the updating sub-module;
Deleting the identification information through the deletion identification submodule;
controlling the read-write permission of the identification information through the functional sub-module;
the identity resolution module is compatible with existing Verification Authorization Approval (VAA) and identity management systems to ensure smooth integration and collaborative work.
Specifically, the identification analysis module not only manages the carbon emission related identification, but also provides the functions of secure encryption and decryption of the data fields in the identification so as to effectively control the read-write permission of the data.
The blockchain module includes: the system comprises a monitoring sub-module, a storage sub-module and a functional sub-module;
the monitoring submodule is used for monitoring the running states of the network and the nodes of the blockchain and providing an alarm mechanism so as to ensure the stable and reliable running of the network;
the monitoring sub-module is also used for verifying whether the carbon emission data is tampered;
the storage sub-module is used for storing the data in a decentralization mode and providing a verification function that the data cannot be tampered with;
the function submodule is used for providing various functions of the management blockchain intelligent contract, and comprises the following steps: uploading, publishing, auditing, installing, initializing, setting and upgrading rights, and is also used for supporting the joining of dynamic alliance members, the exiting of existing alliance members and configuring voting strategies of an alliance chain.
In particular, the method comprises the steps of,
the factor data management module comprises: a factor storage sub-module, a factor updating sub-module, and a factor verification sub-module;
the factor storage sub-module is used for managing and storing emission factors related to carbon emission calculation, and the emission factors comprise: basic energy factors, basic material carbon emission factors and various influence coefficients;
the factor updating sub-module is used for managing and updating source information of the emission factors;
the factor verification submodule is used for verifying the accuracy and compliance of the emission factor data.
In particular, the task of the factor data management module is to ensure the accuracy and real-time of these data to support the carbon emissions accounting and analysis process. The factor data management module is responsible for managing factors related to carbon emission calculations, including, but not limited to: basic energy factor, basic material carbon emission factor and various influence coefficient parameters. The module is also responsible for managing and updating the source information of these factors, ensuring the accuracy and timeliness of these data factors to support the accuracy and reliability of the carbon emission calculations. The following are key aspects of the factor data management module: 1. factor data collection: a) Various emission factor data relating to carbon emissions are collected. Such data may include emissions factors for different energy types, material production emissions factors, transportation emissions factors, and the like. 2. Factor data sources: a) The source of the emission factor data is determined, such as environmental sector, industry standard, scientific research, etc. b) Ensuring that the source of the factor data is reliable and trusted. 3. Factor data classification: a) The collected emissions factor data is classified for use by different campaign phases or product types. b) Each emission factor is assigned an appropriate label and classification. 4. Factor data validation: a) The accuracy and compliance of the emissions factor data is verified. b) And checking whether the factor data meets international standards or regulatory requirements. 5. Factor data update and maintenance: a) Emission factor data is updated periodically to reflect recent scientific research, technological development, and regulatory changes. b) A maintenance function of the factor data is provided to update and replace outdated data. 6. Custom factors: a) Allowing users to customize emissions factor data to meet specific organizational or project requirements. b) And providing the input and management functions of the custom factors. 7. Factor data storage: a) Secure factor data storage is provided to ensure the integrity and availability of data. b) Consider a data backup and restore mechanism. 8. Factor data version management: a) Different versions of the factor data are recorded in order to trace back the change of the data. b) Ensuring that the correct factor version is used. 9. Factor data sharing: a) Mechanisms are provided to share factor data to other organizations or items to facilitate sustainable sharing and collaboration of data. 10. Factor data compliance: a) Compliance of factor data, particularly data relating to environmental regulations and carbon emission standards, is ensured. 11. And (3) data export: a) A factor data export function is provided so that a user can export data into different formats, such as CSV, excel, etc.
The carbon accounting model design module comprises; the system comprises a user interface sub-module, a model design sub-module, a data management sub-module, a model verification sub-module and a display sub-module;
the data management submodule is used for classifying the carbon emission data to generate a classification result;
a user interacts with the system through the user interface sub-module to obtain the classification result, and creates the carbon emission model through the model design sub-module and configures carbon emission factors of the corresponding model; the carbon emission model includes a plurality of active phases of carbon emission models;
verifying the carbon emission models of the plurality of active phases through the model verification sub-module; the carbon emission accounting engine drives the carbon emission models of the plurality of activity stages to calculate and determine carbon emission data; the model verification submodule tests the verified carbon emission model through the carbon emission data to generate a test result of the carbon emission model so as to keep the accuracy of the carbon emission model; the model verification sub-module transmits the test result of the carbon emission model and the corresponding carbon emission data to the display sub-module;
The display sub-module receives the data transmitted by the model verification sub-module and presents the data to a user in a visual mode; the visualization method comprises the following steps: reports, charts and dashboards.
Specifically, the accounting model design tool in the carbon accounting model design module is helpful for organizing and defining key parameters and model settings related to carbon emission, and helping to organize and design and establish a model and a method suitable for carbon emission accounting.
For example: the organizational carbon accounting model design tool allows a user to configure and manage the carbon emissions of the organization, including defining and configuring carbon inflow and outflow of the organization carbon. The main function of this tool is to generate a computational model for use by the carbon emissions accounting engine by explicitly defining the input and output of the carbon source stream, the range of accounting, and the way the factors are referenced, and to provide a data entry interface to the user to facilitate the user's input of relevant data. This helps the user more conveniently record and manage the organised carbon emission data, as follows: 1. data collection and preparation: a) Collecting carbon emission data related to an organization, including information on various aspects of energy use, transportation, raw material purchase, waste management and the like; b) Acquiring energy consumption data of an organization, including the use conditions of electric power, natural gas, fuel and the like; c) Collecting transportation data, including related information such as cargo transportation, staff commute and the like; d) Acquiring raw material purchase data, including raw material types, sources and quantities; e) Waste management data is collected including waste type, treatment method, etc. 2. Data analysis and classification: a) The collected data is analyzed to determine the carbon emission sources for different activities and flows. b) The data is classified into different active phases, such as production, transportation, purchasing, waste management, etc. 3. Configuring model a) using a carbon accounting model design tool, creating a model for each activity stage b) configuring carbon emission factors for each model, which factors describe the carbon emission levels of each activity, which can be determined from industry standards or from data within an organization. 4. Establishing model association: a) Establishing association between models to reflect interaction and dependency between different activity phases; 5. user interface design: a) A user entry interface is developed that allows a user to enter activity level data, such as production lot, transportation mileage, energy consumption, etc., as needed. 6. Model verification: a) Checking the accuracy of the model, and ensuring that the configured carbon emission factors and data are input correctly b) performing model test to verify whether the model can accurately calculate the carbon emission of the organization. 7. Calculation and tracking: a) Calculating, using a carbon emission calculation engine, an organized carbon emission b) based on the configured model, periodically tracking and updating data to maintain accuracy of the model and timely reflect the organized carbon emission changes 8: a) The organized carbon emission data is presented to the user in a visual manner, typically by report, chart or dashboard. 9. Monitoring and improvement: a) Monitoring the carbon emission trend of the organization, identifying potential opportunities for improvement, and developing emission reduction strategies to reduce carbon emissions and improve environmental sustainability. In performing the above operations, the following method needs to be followed: the interface and configuration functions of the tool are used to ensure that tissue boundaries, carbon influx and carbon efflux are accurately defined. Standards and regulations are followed to ensure compliance and accuracy of the data. The data and model are updated periodically to reflect changes within the organization. After accounting, the results are reviewed and analyzed to understand the carbon emissions of the tissue. The data and accounting results are saved periodically for future reference and report generation.
For example: the product carbon accounting model design tool provides full lifecycle configuration functions for the relevant product, including carbon input and output scenarios at various stages. The main function of the tool is to create a model for calculating the carbon footprint of a product by configuring process models of the raw material acquisition, production, packaging, distribution, use and disposal of the product. This helps the carbon emissions calculation engine track the carbon footprint data of the product and allows the user to input activity level data during the calculation process as follows: 1. and (3) data collection: carbon emission data is collected for each stage of the full life cycle of the product, including raw material acquisition, production, packaging, distribution, use, and disposal. 2. And (3) configuring a process model: a process model is created for each lifecycle stage using a function or interface built into the tool. These models describe the carbon input and output conditions for each stage, and the associated processes and activities. 3. Carbon emission factor: carbon emission factors for each process model are associated, which describe the carbon emissions for each event. These factors may be determined based on industry standards or organization internal data. 4. Generating a model: and generating a measuring and calculating model of the carbon footprint of the product by the tool according to the configured process model and the carbon emission related factors. This model will cover the entire life cycle of the product. 5. User interface design: a user entry interface is created so that a user can enter activity level data, such as data for a particular production lot or energy consumption for a use phase, when needed. 6. And (3) model checking: ensuring that the configured model meets the accuracy and consistency criteria of the carbon emission calculations. This may involve data input and output of the verification and inspection model. 7. Calculation and tracking: using the carbon emissions calculation engine, a carbon footprint of the product is calculated from the model. At the same time, activity level data entered by the user is tracked to ensure accuracy of the calculation. 8. The results are presented: the carbon footprint data of the product is presented to the user in the form of a graph or report so that they can understand the carbon emissions of the product. In performing the above-described configuration and data input operations, the following method needs to be followed: the use of a data entry interface for the tool ensures accurate entry of relevant data for each lifecycle stage. The data is checked and validated to ensure its accuracy and compliance. The calculation methods and formulas provided by the tool were followed in order to calculate carbon emissions and carbon footprint. After accounting, the results are reviewed and analyzed to see the carbon emissions of the product at different stages. The data and accounting results are saved periodically for future reference and report generation.
The carbon emission accounting engine in the engine module is used for executing actual carbon emission calculation and registering the carbon emission data into the identification analysis module;
the carbon emissions accounting engine setting an alarm threshold to monitor changes in the carbon emissions data;
the user tracks carbon emission data of the product carbon through a product carbon footprint tracing engine in the engine module and the identification analysis module; the carbon emission data of the product carbon covers the life cycle of the product carbon;
the product carbon footprint tracing engine correlates and records identification information of product carbon, identification information of organization carbon and corresponding carbon emission data on the blockchain module; the engine module is connected with the blockchain module, and a user can acquire associated carbon emission data through the identification information.
Specifically, the carbon emissions accounting engine allows carbon emissions calculations to be made based on an organizational carbon model, a carbon footprint model of the product, user-entered activity data, and carbon emission factor data. These calculation data, calculation processes, and related formulas are then stored on the blockchain module to ensure the security and traceability of the data. Eventually, the calculation results will be registered in the industrial internet identification resolution system in order to more broadly track and manage the carbon emission data. This helps the transparency, tamper resistance and trustworthiness of the data while providing greater traceability and compliance.
For example: the specific operation steps of organizing carbon emission accounting are as follows: 1. acquiring carbon source flow information in the tissue carbon model a) opening the tissue carbon model design tool or platform. b) A carbon model of the organization is entered to access carbon source flow information including carbon emission source flow, activity level data, etc. for various activities and processes within the organization. 2. Acquiring factor data from carbon source flow information a) determining which activities and processes require corresponding carbon emission factor data b) acquiring emission factor data applicable to those activities and processes using a tool or data source based on the carbon source flow information. Such data may come from government agencies, scientific institutions, industry standards, or other trusted data sources. 3.
Identification resolution is used to obtain carbon emission data a) for a particular activity, if the relevant product model has registered carbon emission data in the identification hierarchy, identification resolution tools may be used to retrieve such data. The identification resolution tool will associate the product model with the carbon emission data b) for a particular activity, if the relevant product model has registered carbon emission data in the identification hierarchy, the identification resolution tool can be used to retrieve such data. The identity resolution tool will associate 4) the product model with the carbon emission data, validating the data a) if the carbon emission data is obtained using identity resolution, submitting these data to the blockchain module to validate its integrity and authenticity b) the blockchain module will verify that the data has been tampered with and ensure that it is from a trusted source 5. Using platform provided or user entered factor data a) if the carbon emission data passes in identity resolution and blockchain validation, these data can be used for carbon emission calculations b) if there is no available carbon emission data or the data is not validated, default factor data provided by the platform can be used or the user can enter his own data 6. User entered activity level data a) the user can enter activity level data within the organization including energy consumption, raw materials, shipping etc. related data b) ensure that the accuracy and integrity of the data 7. The blockchain validation a) submits calculation results to the blockchain module to validate its integrity and authenticity when calculating the carbon emission. The blockchain module records the calculation results and verifies 8. Summarizing and reporting a) summarizing and calculating the carbon emission data of the organization, including the data of identification analysis and user input and the factor data provided by the platform b) generating a carbon emission report so as to report the carbon emission condition of the organization to the internal and external related parties. This helps support the organizational carbon management and sustainability goals.
Specifically, the carbon inventory report generation engine is used to generate reports on carbon emissions inventory and accounting so that organizations can learn their carbon footprints and management practices. This engine helps the user create various reports on carbon emissions, including summary, detailed, and other relevant information, to meet different needs and uses. Report template addition, editing, deletion, and search functions are provided to enable a user to manage report templates. Meanwhile, a report is generated by the calculation result generated by the carbon emission accounting engine, and the export function of the report is supported.
Specifically, a product carbon footprint traceability engine: for tracing the carbon footprint of a product from production to consumption to help businesses and consumers better understand the environmental impact of the product. Allowing the user to track the carbon emission data of the product, cover the entire life cycle of the product, and perform traceability through the identification system. In addition, the accuracy and the credibility of the traceability data are verified through a blockchain technology. Helping users to know the environmental influence of products and ensuring the safety of data, and the specific operation steps comprise: 1. integration of an identification system: a) Associating identification information (unique tag, serial number, or other identifier) of the product or organization with the carbon emission data: b) This may be accomplished through an API or data import function of the identification hierarchy. 2. Carbon emission data recording: a) Recording the carbon emission data for each product with corresponding identification information on the blockchain using the product carbon footprint traceability engine module b) ensures the non-tamperability and traceability of the data. 3. Identification verification a) a user can query the carbon emissions of a product by means of identification information b) data trace data c) input identification information, and then use the engine module to connect with the blockchain module to obtain the carbon emissions data associated with the identification. And a) a user can trace back carbon emission data of the product to check the source and the history record of the carbon emission data, b) an engine module provides a data tracing function through a block chain module and displays related data history records. 5. Data verification a) for a particular identified product, the user can verify the authenticity of the carbon emission data associated therewith b) the engine module provides verification functionality through the blockchain recorded data to ensure that the data has not been tampered with. 6. Report generation a) a user may generate an identification-based product carbon footprint report b) an engine module generates a report using the blockchain recorded data and identification information, visually presenting the carbon emission data of the product. 7. Data export a) provides the functionality to export carbon emission data and reports as files (e.g., PDF, excel) for sharing or archiving with stakeholders. 8. Data security and privacy protection a) appropriate data security measures are taken, including encryption, access control and backup, to protect the security and privacy of carbon emission data. 9. Monitoring and improving a) periodically reviewing data in a blockchain to ensure data integrity and compliance b) ensuring accuracy and consistency of identification information to prevent errors or duplicate records.
For example, product carbon footprint tracking accounts for specific operational steps: 1. factor data a) of acquisition process first, a specific process and a corresponding input object in a raw material acquisition stage of acquisition data. This may include raw material acquisition, processing, transportation, etc. b) if the raw material model used in the process has registered carbon emission data in the identification system, identification parsing may be performed to acquire such data. Identification resolution is a process of retrieving related data by means of a unique identification of an identification system c) using an identification resolution tool or system, carbon emission data related to the feedstock model is retrieved based on the unique identification of the input. The data may include the carbon emission factor of the raw material and the related information d) after acquiring the identification parsed carbon emission data, the data is passed to the blockchain module for verification. Blockchain modules may be used to ensure the non-tamper-resistance and integrity of data; the blockchain module verifies whether the data has been recorded on the blockchain in the past and whether the data has been tampered with. If the data is validated, the data may continue to be used. e) The blockchain module verifies whether the data has been recorded on the blockchain in the past and whether the data has been tampered with. If the data is validated, the data may continue to be used. The blockchain module verifies whether the data has been recorded on the blockchain in the past and whether the data has been tampered with. If the data is validated, the data f) can be used to continue the transportation of the input, and carbon emission factor data associated with the transportation can be obtained. These factor data typically include the carbon emissions g) during the transportation of the raw materials from the collection site to the factory or production site, recording and documenting all acquired data, including identification of the source, date and related information of the parsed carbon emissions data, the back-up factor data and the transportation factor data 2. Identification registration a) of the product of this stage using an identification system, unique identification b) of the product is generated for each stage of the product using the identification system, associated factor data and time stamps 3. Certification a) is performed using a blockchain module, identification information and factor data are stored on the blockchain, ensuring non-compliance and transparency of the data, the stored information may include 4. Data aggregate of carbon emissions per product unit number a) aggregate raw material acquisition stage, production stage, packaging stage, distribution stage (if applicable), use stage (if applicable), carbon emissions data b) of the product are calculated, typically with reference to a functional unit of the product (e.g. per sigma) of the product, carbon emissions per sigma (sigma) of the input/sigma (sigma) of the product, factor data (sigma) are taken into account, registering the carbon emission data of the unit number of the product with the related identification information and factor data and checking b) the checking process ensures the safety and traceability of the data. Product carbon footprint tracking is a comprehensive process requiring that data and information be correlated across stages of the footprint in order to generate a trusted carbon footprint report and data.
For example, the specific operation steps for single product carbon emission data trace are as follows: 1. combination product carbon emission identification: and combining to generate a unique identifier of the product according to the information of the name, the model, the place of production, the manufacturer, the year of production and the like of the product. This identification will be used to identify carbon emission data for the query product in the system. 2. Using an identification resolution tool: the generated product identification is entered into the tool using an identification resolution tool or system to retrieve carbon emission data associated with the product. The tool will query the identification hierarchy for data related to the identification. 3. Displaying the data carried by the identification: if the identification is successfully parsed, the tool displays the data carried by the identification to the user. Such data may include product information (name, model, place of production, manufacturer, year of production), carbon emission data for each lifecycle stage, place of production information, certification authorities, sources of calculation factors, etc. 4. Submitting the identification information to the blockchain module: the user may choose to submit the identification information to the blockchain module for data authentication. The blockchain module will receive the identification information, verify and record on the blockchain. 5. And (3) data authentication: the blockchain module will authenticate the submitted identification information to determine if the data has not been tampered with. If the data is authenticated, the system will display a message to the user that the data has not been tampered with. If the data does not pass the authentication, the system enables the message showing that the data is tampered to the user to pass the steps, and the user can trace back and verify the carbon emission data of the product by using the unique identification of the product so as to ensure the credibility and traceability of the data. This helps consumers better understand the carbon footprint of the product in order to make more sustainable purchasing decisions.
For example, the specific operation steps of the traceability of the carbon emission data of the raw materials of the product are as follows: 1. and (3) identifying the carbon emission of the raw materials of the combined product: and combining and generating unique identifiers of raw materials of the product according to the information of the name, the model, the place of production, the manufacturer, the year of production and the like of the product. This identification will be used to identify carbon emission data for the raw materials of the query product in the system. 2. Using an identification resolution tool: the generated product raw material identification is entered into the tool using an identification resolution tool or system to retrieve carbon emission data associated with the raw material. The tool will query the identification hierarchy for data related to the identification. 3. Displaying the data carried by the identification: if the identification is successfully parsed, the tool displays the data carried by the identification to the user. Such data may include information about the raw materials of the product (name, model number, place of production, manufacturer, year of production), carbon emission data for each lifecycle stage, place of production information, certification authorities, sources of calculation factors, and other information related to the raw materials. 4. Submitting the identification information to the blockchain module: the user may choose to submit the identification information to the blockchain module for data authentication. The blockchain module will receive the identification information, verify and record on the blockchain. 5. And (3) data authentication: the blockchain module will authenticate the submitted identification information to determine if the data has not been tampered with. If the data is authenticated, the system will display a message to the user that the data has not been tampered with. If the data is not authenticated, the system will display a message to the user that the data has been tampered with. 6. The process identifies the absence of: if the identification does not exist in the identification system, the system displays the carbon footprint free traceability information of the product raw material to the user. 7. The user clicks on the raw materials of the product: if the user clicks on information about the raw material of the product, which will be part of the product, the user can continue to trace back and view the carbon emission data of the raw material. Through the above steps, the user can trace back and verify the carbon emission data of the raw material using the unique identification of the raw material of the product to ensure the credibility and traceability of the data. This helps organizations and consumers to better understand the raw material source and carbon footprint of the product in order to make more sustainable decisions.
It should be noted that: in the device provided in the above embodiment, when implementing the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to implement all or part of the functions described above. In addition, the embodiments of the apparatus and the method provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the embodiments of the method are detailed in the method embodiments, which are not repeated herein.
The application also discloses electronic equipment. Referring to fig. 2, fig. 2 is a schematic structural diagram of an electronic device according to the disclosure in an embodiment of the present application. The electronic device 500 may include: at least one processor 501, at least one network interface 504, a user interface 503, a memory 505, at least one communication bus 502.
Wherein a communication bus 502 is used to enable connected communications between these components.
The user interface 503 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 503 may further include a standard wired interface and a standard wireless interface.
The network interface 504 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
Wherein the processor 501 may include one or more processing cores. The processor 501 connects various parts throughout the server using various interfaces and lines, performs various functions of the server and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 505, and invoking data stored in the memory 505. Alternatively, the processor 501 may be implemented in hardware in at least one of digital signal processing (DigitalSignalProcessing, DSP), field programmable gate array (Field-ProgrammableGateArray, FPGA), and programmable logic array (ProgrammableLogicArray, PLA). The processor 501 may integrate one or a combination of several of a central processor (CentralProcessingUnit, CPU), an image processor (GraphicsProcessingUnit, GPU), a modem, etc. The CPU mainly processes an operating system, a user interface, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 501 and may be implemented by a single chip.
The memory 505 may include a random access memory (RandomAccessMemory, RAM) or a Read-only memory (rom).
Optionally, the memory 505 comprises a non-transitory computer readable medium (non-transitoroompter-readabblestonemam). Memory 505 may be used to store instructions, programs, code sets, or instruction sets. The memory 505 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described various method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. The memory 505 optionally also includes, but is not limited to, at least one storage device located remotely from the aforementioned processor 501. Referring to fig. 2, an operating system, a network communication module, a user interface module, and an application program of an industrial carbon chain resolution tracking method based on identification resolution may be included in the memory 505 as a computer storage medium.
In the electronic device 500 shown in fig. 2, the user interface 503 is mainly used for providing an input interface for a user, and acquiring data input by the user; and the processor 501 may be configured to invoke an application program in the memory 505 that stores an industrial carbon chain resolution tracking method based on identification resolution, which when executed by the one or more processors 501, causes the electronic device 500 to perform the method as in one or more of the embodiments described above. It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required in the present application.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
In the several embodiments provided herein, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as a division of units, merely a division of logic functions, and there may be additional divisions in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. In addition, the coupling or direct coupling or communication connection shown or discussed with each other includes, but is not limited to, an indirect coupling or communication connection via some service interface, device or unit, including but not limited to electrical or other forms.
Elements illustrated as separate elements include, but are not limited to, or may not be physically separate, and elements shown as elements include, but are not limited to, or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, and also include, but are not limited to, each unit being physically present alone, or two or more units being integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone goods, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution, in the form of a software product stored in a memory, including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned memory includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a magnetic disk or an optical disk.
The above are merely exemplary embodiments of the present disclosure and are not intended to limit the scope of the present disclosure. That is, equivalent changes and modifications are contemplated by the teachings of this disclosure, which fall within the scope of the present disclosure. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure.
This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a scope and spirit of the disclosure being indicated by the claims.