Carbon footprint accounting method supporting real-time data synchronization and edge device

Abstract

The invention discloses a carbon footprint accounting method supporting real-time data synchronization and an edge device. The method comprises the following steps: configuring an intelligent adapter interface of an edge device so as to carry out acquisition and protocol analysis on heterogeneous data from a plurality of source systems and realize data synchronization between the plurality of source systems and the edge device; carrying out identification, classification, standardization processing and fusion on the acquired data based on the configuration information of the intelligent adaptive interface; in response to user interaction operation, constructing a carbon footprint accounting process model, matching the fused data with a corresponding unit of the carbon footprint accounting process model, and receiving parameterized configuration of a user for each process step in the carbon footprint accounting process model; and on the basis of the fused data, performing real-time calculation and analysis on direct carbon emission and indirect carbon emission in the production process by utilizing calculation logic set by a carbon footprint accounting process model. According to the scheme, the enterprise carbon footprint checking cost is reduced.

Description

Technical Field

[0001] This invention belongs to the field of online energy efficiency monitoring in data centers, and specifically relates to a carbon footprint accounting method and edge device that supports real-time data synchronization. Background Technology

[0002] Carbon footprint is increasingly becoming a crucial indicator for measuring greenhouse gas emissions from products, activities, or individuals throughout their lifecycle. Globally, carbon footprint accounting and management have become a focal point. Digital tools can help achieve more accurate and comprehensive emissions measurement and reduction. They can rigorously measure, track, and reduce environmental footprint across business sources, promoting transparency and providing a single, accurate source for decision-making. Several carbon footprint calculators are available that can translate carbon footprint estimates into more understandable formats, enabling individuals and businesses to better understand their environmental impact and make informed decisions.

[0003] Currently, carbon footprint accounting faces two main challenges. First, from a technical perspective, product carbon footprint accounting heavily relies on manual reporting, resulting in low efficiency and slow timeliness. This hinders both enterprise self-assessment and institutional verification and certification. There is an urgent need to introduce digital and intelligent technologies to achieve real-time calculation and management of product carbon footprints, enabling enterprises to quickly conduct organizational carbon verification and product carbon footprint assessments, accurately calculate carbon emissions throughout the product's lifecycle, and support carbon reduction, control, and green transformation. Second, from a mechanism perspective, product carbon footprint accounting involves various data related to enterprise production, operations, and energy activities. Enterprises face significant risks of core data leakage. There is a pressing need to utilize edge computing to conduct data aggregation, analysis, and calculation on-site within enterprises, uploading only the carbon footprint results to alleviate enterprise concerns and simultaneously building a background database of carbon footprint data. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a carbon footprint accounting method and edge device that supports real-time data synchronization, thereby solving the technical problems of existing carbon footprint accounting methods, such as reliance on manual labor, low efficiency, potential data security risks, and complex model construction.

[0005] To solve the above-mentioned technical problems, the present invention adopts the following technical solution.

[0006] This invention first discloses a carbon footprint accounting method that supports real-time data synchronization, the method comprising the following steps: Step 1: Configure the intelligent adaptation interface of the edge device to collect and parse heterogeneous data from multiple source systems, and realize data synchronization between multiple source systems and the edge device based on timestamp or message queue mechanism; Step 2: Based on the configuration information of the intelligent adaptation interface, identify and classify the collected data, standardize the classified data, and merge the data from multiple source systems through time information and work order information; Step 3: In response to user interaction, construct a carbon footprint accounting process model, match the fused data with the corresponding unit of the carbon footprint accounting process model, and receive the user's parameterized configuration for each process step in the carbon footprint accounting process model. Step 4: Based on the fused data, the direct and indirect carbon emissions during the production process are calculated and analyzed in real time using the calculation logic set by the carbon footprint accounting process model.

[0007] The present invention further includes the following preferred embodiments: The process of collecting and parsing heterogeneous data from multiple source systems further includes: Configure the built-in intelligent adapter interface of the edge device to determine the connection information and protocol type of different data sources, including the enterprise's energy management system EMS, production execution system MES, and enterprise resource planning system ERP. Configure the communication address and register information of specific meters to enable them to recognize multiple meter data formats. For configured MES or ERP systems, set their API interface address or database connection information to obtain work order and BOM list data through these interfaces; for PDF format invoices and ledger data, configure specific file import paths to perform automated collection, format conversion and loading of data from different sources, and uniformly convert them into JSON or XML structures.

[0008] The process of identifying and classifying the collected data further includes: All data transmitted from the addresses of meters configured with the Modbus protocol are automatically identified and classified as structured time-series energy consumption data. All JSON data obtained from the configured MES system API interface is automatically identified and classified as semi-structured production and operation data.

[0009] The standardization process for the classified data further includes: The collected heterogeneous data from multiple sources is cleaned, transformed, and integrated to form a unified formatted data for carbon footprint accounting, including automatic removal of outliers, imputation of missing values, and unit conversion.

[0010] The real-time calculation and analysis of direct and indirect carbon emissions during the production process further includes: Calculate the carbon emissions from the combustion of fossil fuels during the production process. :

[0011] in, fuel Consumption amount, fuel The average lower heating value, fuel Carbon emission factors; Calculate the indirect emissions from purchased electricity and steam energy. :

[0012] in, For purchasing energy from outside The activity data is the consumption. For corresponding energy The power grid or thermal emission factors; Calculate the total carbon footprint of the product :

[0013] in, , and These are carbon emissions from the raw materials and transportation stages, respectively.

[0014] After real-time calculation and analysis of direct and indirect carbon emissions during the production process, it also includes: Enable the shared key token encryption mechanism to encrypt the carbon footprint accounting results data and upload it through a secure channel.

[0015] This invention also discloses an edge computing device supporting real-time data synchronization that utilizes the aforementioned carbon footprint accounting method supporting real-time data synchronization, comprising: The interface configuration module is used to configure the intelligent adaptation interface to collect and parse heterogeneous data from multiple source systems, and to realize data synchronization between multiple source systems and edge devices based on timestamp or message queue mechanisms. The data processing module is used to identify and classify the collected data based on the configuration information of the intelligent adaptation interface, standardize the classified data, and merge data from multiple source systems through time information and work order information. The carbon footprint accounting model construction module is used to construct a carbon footprint accounting process model in response to user interaction operations, match the fused data with the corresponding units of the carbon footprint accounting process model, and receive the user's parameterized configuration for each process step in the carbon footprint accounting process model.

[0016] The carbon emission calculation module is used to calculate and analyze the direct and indirect carbon emissions in the production process in real time based on the fused data and using the calculation logic set by the carbon footprint accounting process model.

[0017] The hardware architecture of the device includes: Core processor module, data acquisition interface module, storage module, power supply module, and casing; The embedded software architecture of the device includes: Driver and operating system layer: responsible for hardware drivers and providing the Linux runtime environment; The data service layer includes: The southbound interface service, including the Modbus and OPCUA protocol stack, is used to collect data from the hardware interface.

[0018] The northbound interface service provides a RESTful API interface to synchronize data with the enterprise's MES and ERP systems and securely report the results to the cloud platform. Data processing middleware is used to perform data cleaning, transformation, and fusion tasks.

[0019] The core application layer includes: A low-code model engine is used to parse and execute carbon footprint accounting process model configuration files generated by users through the web interface. Carbon emission calculator, used to perform carbon emission calculations, with a built-in, updatable database of emission factors; Performance and management, including: The web server has a built-in lightweight web server that provides a localized configuration management interface and carbon asset management dashboard. Users can access the device's IP address through a browser to perform model building and data visualization operations. Security services are used for user authentication, TLS / SSL encryption of data transmission, and token generation and verification of shared results.

[0020] Accordingly, this application also discloses a terminal, including a processor and a storage medium; The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the aforementioned carbon footprint accounting method that supports real-time data synchronization.

[0021] Accordingly, this application also discloses a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the aforementioned carbon footprint accounting method supporting real-time data synchronization.

[0022] The beneficial effects of this invention are as follows: Compared with existing technologies, this invention provides a carbon footprint accounting method and edge device that supports real-time data synchronization, constructs a digital and intelligent carbon footprint accounting model for products, achieves accurate, real-time, and traceable data of various types, explores mutual recognition with authoritative verification agencies, and reduces the cost of carbon footprint verification for enterprises. This invention can help enterprises quickly complete carbon footprint accounting, lower technical barriers and security concerns, generate carbon footprint analysis and accounting reports, meet the relevant requirements for carbon information disclosure in green supply chains and international trade, and enhance the competitiveness of enterprises going global. Simultaneously, it promotes enterprises to carry out energy-saving renovations of key equipment and production lines based on carbon footprint management, apply for green factory status, and accelerate green transformation. It develops scalable and applicable carbon footprint edge computing devices, promotes the incubation and transformation of research results, and forms new revenue points. Based on carbon footprint management, it explores the potential for carbon reduction and decarbonization in enterprises, guides enterprises to implement carbon emission reduction and carbon trading, and facilitates energy efficiency services. At the same time, it strengthens carbon footprint management, guides the industrial chain to coordinate green and low-carbon transformation, and gradually accumulates carbon footprint data for key industry products. Attached Figure Description

[0023] Figure 1 This is a schematic diagram of the edge computing device supporting real-time data synchronization in this invention. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0025] The embodiments described in this application are merely some, not all, embodiments of the present invention. Based on the spirit of the present invention, other embodiments obtained by those skilled in the art without inventive effort are all within the protection scope of the present invention.

[0026] Currently, product carbon footprint accounting heavily relies on manual reporting, resulting in low efficiency and poor timeliness, which is detrimental to both enterprise self-assessment and institutional verification and certification. Furthermore, product carbon footprint accounting involves various data related to enterprise production, operations, and energy activities, raising concerns about the leakage of significant amounts of core data. This invention addresses the problems of low efficiency and core data leakage in existing product carbon footprint accounting systems by connecting to enterprise energy management and production management systems to obtain data on raw materials, energy, and production activities. Through lightweight carbon footprint accounting modeling, it achieves product carbon footprint accounting and provides a lightweight hardware and software device for online carbon footprint accounting edge computing. Designed for export trading companies, it enables accurate measurement of carbon emissions throughout the entire product production process. Deployed locally, it interacts in real-time with relevant data from enterprise production, operations, and energy activities. Utilizing a general product carbon footprint accounting process model, it calculates carbon emissions over the entire lifecycle, making enterprise data usable but not visible, sharing only the carbon footprint results and mitigating the risk of core data leakage.

[0027] This invention utilizes edge computing devices to achieve seamless integration with enterprise production and operation systems, automated processing of multi-source heterogeneous data, and flexible construction and real-time calculation of carbon footprint models based on Life Cycle Assessment (LCA) principles. Through intelligent adaptation interface technology for data integration, it develops intelligent adaptation interfaces supporting data integration with different brands and versions of energy management systems and production management systems; it constructs widely compatible data exchange formats and protocols, as well as middleware suitable for automatic data acquisition, conversion, and loading; and it employs a data consistency algorithm between edge devices and third-party systems based on a data synchronization mechanism. Through multi-source heterogeneous data processing technology for carbon footprint activities, it automatically identifies and classifies structured, semi-structured, and unstructured data; it converts multi-source heterogeneous data into a unified format for carbon footprint accounting through data cleaning, conversion, and integration processes; and it achieves an efficient data storage and performance optimization solution suitable for edge computing, meeting the performance requirements of carbon footprint accounting processing. Through a convenient carbon footprint model construction tool, it allows for the adjustment and expansion of models according to different industries and product characteristics; it constructs basic data units, target model units, work order information units, and carbon emission calculation units to support carbon footprint accounting; and it uses a shared key token encryption mechanism for the carbon footprint accounting process model and carbon footprint results.

[0028] The carbon footprint accounting method supporting real-time data synchronization disclosed in this invention includes the following steps: Step 1: Configure the intelligent adaptation interface of the edge device to collect and parse heterogeneous data from multiple source systems, and realize data synchronization between multiple source systems and the edge device based on timestamp or message queue mechanism.

[0029] This invention enables data exchange with existing enterprise energy management systems (EMS), manufacturing execution systems (MES), enterprise resource planning systems (ERP), etc., through the intelligent adapter interface built into the edge device.

[0030] During the device deployment phase, the intelligent adaptation interface is first configured to determine the connection information and protocol types for different data sources. The device's built-in multi-protocol parsing module supports industrial communication protocols such as Modbus, OPC UA, and MQTT. It configures the communication addresses and register information of specific meters (such as electricity, steam, and natural gas meters) to enable them to recognize the data formats of more than 20 mainstream brands on the market, laying the foundation for subsequent identification of structured energy data.

[0031] Adaptive configurations are implemented for different data sources. For existing MES or ERP systems, their API interface addresses or database connection information need to be set to obtain semi-structured data such as work orders and BOM (Bill of Materials) through these interfaces. For unstructured data such as PDF format invoices and ledgers, specific file import paths are configured. Based on these configurations, the data middleware of the edge devices automatically collects, converts, and loads data from different sources, and uniformly converts it into JSON or XML structures for subsequent processing.

[0032] To ensure the accuracy of the collected data, a data synchronization mechanism based on timestamps or message queues is adopted. This mechanism guarantees data consistency between the edge computing device and various source systems such as enterprise ERP and MES, providing a reliable data foundation for subsequent data fusion and accurate accounting. The specific implementation is as follows: The entire data synchronization process is marked using the `sync_status` field ("1" for pending synchronization, "2" for successful synchronization, and "3" for failed synchronization). Data in a specified status is filtered using the `getListResultDtoByMIdAndStatus` method. Then, data is synchronized in batches using `tenant_code` (company identifier) ​​and `mId` (material identifier) ​​as grouping keys. During synchronization, a "master data first, related data follow" strategy is adopted. First, `uploadProductionResult` synchronizes the master data of the production results, then `uploadProductionModel` synchronizes the related product model data (including basic product information, BOM list, and process data). If synchronization fails, an exception is caught, triggering a status write-back. Subsequent retries can be implemented based on the "3" status data, with the retry trigger condition: (current status == "3") ∩ (number of retries < 3) (3 is the default threshold).

[0033] Step 2: Based on the configuration information of the intelligent adaptation interface, identify and classify the collected data, standardize the classified data, and merge the data from multiple source systems through time information and work order information.

[0034] The identification and classification function of this invention is based on an automated process that combines the preliminary configuration completed in step 1 with internal rule execution. Pre-defined classification rules are executed according to the configured interface information. For example, all data received from meter addresses configured with the Modbus protocol is automatically identified and classified as structured time-series energy consumption data. All JSON data obtained from the configured MES system API interface is automatically identified and classified as semi-structured production and operation data. Through this rule-based judgment based on data source configuration, automated and efficient identification and classification of multi-source heterogeneous data is achieved without relying on complex machine learning models.

[0035] After the data is correctly identified and classified, the device will standardize it. The collected multi-source heterogeneous data needs to be cleaned, transformed, and integrated to form uniformly formatted data for carbon footprint accounting. This process includes automatically removing outliers, imputing missing values, and performing unit conversions. For example, the device will convert energy consumption in different units (such as m³, t, L) into standard energy units (MJ or kWh) to form a unified format for carbon footprint accounting and ensure the automation and accuracy of the process.

[0036] Data from different systems is aligned and associated with time and work order ID. By connecting with the enterprise's MES and other related systems, the start and end times of product production are obtained, and the data collected by energy consumption meters within this time period are accurately matched to achieve precise attribution of energy consumption to specific product batches.

[0037] Step 3: In response to user interaction, construct a carbon footprint accounting process model, match the fused data with the corresponding unit of the carbon footprint accounting process model, and receive the user's parameterized configuration for each process step in the carbon footprint accounting process model.

[0038] The scalable model architecture is adjusted according to the characteristics of different industries and products, and a convenient low-code model building tool is provided, allowing users to quickly build carbon footprint accounting process models based on the process flow of different products through interactive operation.

[0039] This invention provides a variety of pre-set modules, including basic data units, target model units, work order information units, and carbon emission calculation units. Users do not need to write complex code; they can simply combine these modules on a graphical interface by dragging and dropping according to the specific product's production process to quickly establish a carbon footprint accounting process model that conforms to the company's actual production process.

[0040] After building the process model framework, the user matches the data source processed and integrated in step 2 with the specific units in the model. For example, the user maps the identified and classified data stream of "cumulative electricity consumption of production line 1" to the energy consumption calculation unit of the final assembly process in the model. The entire model construction follows the life cycle assessment (LCA) principle, and the user can flexibly define the accounting boundaries according to the actual situation, such as each stage from raw material acquisition and manufacturing to product delivery, to ensure that the model can accurately reflect the entire carbon emission process of a specific product.

[0041] To ensure the flexibility and accuracy of the calculations, users can parameterize each process step in the model, such as setting relevant parameters for material balance and energy balance.

[0042] Step 4: Based on the fused data, the direct and indirect carbon emissions during the production process are calculated and analyzed in real time using the calculation logic set by the carbon footprint accounting process model.

[0043] Once the model is built, real-time calculations are performed to quantify the greenhouse gas emissions of the product throughout its entire lifecycle.

[0044] First, the carbon footprint accounting process model, whose parameters were configured by the user in step 3, is loaded. Then, the preprocessed and fused data from step 2 is called, such as energy activity data precisely attributed to a specific work order. Combined with emission factors from its internally integrated, third-party updated national and industry background databases, and based on the calculation logic set in the model, carbon emission calculations are performed to quantify the direct and indirect emissions of the product during the production process.

[0045] The formula for calculating carbon emissions is: Direct emissions calculation: Carbon emissions from the combustion of fossil fuels during the production process. The calculation is as follows:

[0046] in, fuel Consumption amount, fuel The average lower heating value, fuel Carbon emission factors.

[0047] Indirect emissions calculation: Indirect emissions from purchased electricity, steam, and other energy sources are calculated as follows:

[0048] in, For purchasing energy from outside Activity data (consumption) such as electricity. For corresponding energy The power grid or thermal emission factors.

[0049] Total carbon footprint calculation: The total carbon footprint of a product within the defined accounting boundaries. The sum of emissions from each stage:

[0050] in, . and These are carbon emissions from the raw materials and transportation stages, respectively. The data are derived from the Bill of Materials (BOM) and logistics information, and are calculated by multiplying them by the corresponding emission factors.

[0051] After the calculations are completed, the raw calculated values ​​are processed to generate structured, high-precision carbon footprint accounting results. This generation process integrates the calculated emissions from each stage with the production and operation data from step 2. The generated results include a series of key parameters, such as: product identifiers, production batches, and accounting timestamps associated with work order information; the product lifecycle accounting boundaries defined in the model of step 3; and detailed carbon emission parameters, including sub-items such as raw materials, direct emissions, and indirect emissions, and the final total carbon footprint (CFP) value. Finally, this structured result data is used to automatically generate detailed carbon footprint analysis and accounting reports, and is updated in real time to a locally deployed carbon asset management dashboard, helping enterprises strengthen their carbon asset management.

[0052] In a further preferred embodiment, to achieve data encryption and secure sharing, when the carbon footprint calculation results generated in step 4 need to be provided externally (e.g., for export trade certification or integration with a carbon footprint public service platform), the device will activate a shared key token encryption mechanism. Only the final carbon footprint result data is encrypted and uploaded through a secure channel, while the detailed production and energy data supporting the calculation are retained locally. This mechanism realizes the core concept of data being usable but invisible, completely eliminating enterprises' security concerns.

[0053] The beneficial effects of this invention are as follows: Compared with existing technologies, this invention provides a carbon footprint accounting method and edge device that supports real-time data synchronization, constructs a digital and intelligent carbon footprint accounting model for products, achieves accurate, real-time, and traceable data of various types, explores mutual recognition with authoritative verification agencies, and reduces the cost of carbon footprint verification for enterprises. This invention can help enterprises quickly complete carbon footprint accounting, lower technical barriers and security concerns, generate carbon footprint analysis and accounting reports, meet the relevant requirements for carbon information disclosure in green supply chains and international trade, and enhance the competitiveness of enterprises going global. Simultaneously, it promotes enterprises to carry out energy-saving renovations of key equipment and production lines based on carbon footprint management, apply for green factory status, and accelerate green transformation. It develops scalable and applicable carbon footprint edge computing devices, promotes the incubation and transformation of research results, and forms new revenue points. Based on carbon footprint management, it explores the potential for carbon reduction and decarbonization in enterprises, guides enterprises to implement carbon emission reduction and carbon trading, and facilitates energy efficiency services. At the same time, it strengthens carbon footprint management, guides the industrial chain to coordinate green and low-carbon transformation, and gradually accumulates carbon footprint data for key industry products.

[0054] This invention can be a system, method, and / or computer program product. This invention also discloses an edge computing device supporting real-time data synchronization based on the aforementioned carbon footprint accounting method, comprising: The interface configuration module is used to configure the intelligent adaptation interface to collect and parse heterogeneous data from multiple source systems, and to realize data synchronization between multiple source systems and edge devices based on timestamp or message queue mechanisms. The data processing module is used to identify and classify the collected data based on the configuration information of the intelligent adaptation interface, standardize the classified data, and merge data from multiple source systems through time information and work order information. The carbon footprint accounting model construction module is used to construct a carbon footprint accounting process model in response to user interaction operations, match the fused data with the corresponding units of the carbon footprint accounting process model, and receive the user's parameterized configuration for each process step in the carbon footprint accounting process model.

[0055] The carbon emission calculation module is used to calculate and analyze the direct and indirect carbon emissions in the production process in real time based on the fused data and using the calculation logic set by the carbon footprint accounting process model.

[0056] like Figure 1 As shown, the prototype hardware of the edge device of the present invention mainly includes: Core processor module: Select an embedded computing platform (such as Raspberry Pi 5) with at least 4 ARM Cortex-A76 CPUs and 4GB RAM, running a streamlined Linux operating system (such as Yocto or Ubuntu Core).

[0057] Data acquisition interface module: 1 RJ45 Ethernet interface for connecting to the enterprise's internal LAN and exchanging data with MES and ERP systems. 2 RS485 interfaces for connecting to smart meters and natural gas flow meters in the field via Modbus protocol. 1 Wi-Fi / Bluetooth module for wireless data transmission and temporary debugging.

[0058] Storage module: Built-in 64GB eMMC flash memory for storing embedded operating system, applications, configuration files, and local cached carbon footprint data.

[0059] Power module: Supports 24VDC industrial power input, with an operating temperature range of -20 to 70℃.

[0060] Housing: It adopts a metal housing with an IP54 protection rating, which is suitable for industrial site environments.

[0061] Embedded software architecture is divided into four layers: Driver and operating system layer: responsible for hardware drivers and providing a stable Linux operating environment.

[0062] Data service layer: Southbound interface service: Includes implementations of protocol stacks such as Modbus and OPCUA, responsible for collecting data from hardware interfaces.

[0063] Northbound Interface Service: Provides a RESTful API interface for data synchronization with enterprise MES / ERP systems and secure reporting of results to the cloud platform.

[0064] Data processing middleware: performs the data cleaning, transformation, and fusion tasks in step 2.

[0065] Core application layer: Low-code model engine: Parses and executes carbon footprint accounting process model configuration files (stored in JSON format) generated by users through drag-and-drop via the web interface.

[0066] Carbon Emission Calculator: Implements all the calculation formulas in step 4, with a built-in updatable emission factor database (GB / T24067-2024).

[0067] Performance and Management: Web Server: A lightweight web server (such as Nginx) is built-in, providing a localized configuration management interface and carbon asset management dashboard. Users can access the device's IP address via a browser to perform model building and data visualization operations.

[0068] Security services: responsible for user authentication, TLS / SSL encryption of data transmission, and token generation and verification of shared results.

[0069] Based on a specific implementation process example, calculate the carbon footprint of a batch of transformers produced.

[0070] (1) Model building: Through the Web interface, maintenance personnel can drag and drop the corresponding process modules according to the production process (winding, assembly, impregnation, testing, etc.) of the transformer model, and associate the required energy (electricity) and material (copper wire, silicon steel sheet) data sources for each process.

[0071] (2) Automatic data collection: The MES system pushes a new work order to the edge device via API, which includes the product model, quantity and planned production time (e.g., 08:00-16:00 on November 10, 2025).

[0072] The system collects the readings of the main electricity meters of the winding machine and the impregnation workshop in real time via RS485 interface according to the work order time, with a time resolution of 1 minute.

[0073] (3) Real-time calculation: After the work order ends at 16:00, the system automatically calculates the total electricity consumption AD_elec during that time period. The system obtains the real-time emission factor EF(grid, elec) of the power grid through the Internet API. According to formula E indirect =AD_elec×EF(grid, elec), calculates the carbon emissions from electricity consumption.

[0074] Meanwhile, the material consumption is obtained from the BOM list and multiplied by the corresponding upstream emission factor. The total carbon footprint of this batch of products is then obtained by summing the results.

[0075] (4) Result Display and Upload: The calculation result (e.g., 0.494tCO2) is updated in real time to the local carbon asset management dashboard. Simultaneously, a JSON data entry containing the work order number, product model, total carbon footprint, and timestamp is generated, encrypted using a preset token, and uploaded to the company's cloud-based carbon management platform via HTTPS for archiving and annual report generation. Throughout the process, detailed energy consumption and production cycle data are stored locally and not reported.

[0076] Based on the spirit of this invention, those skilled in the art will readily conceive of a computer program product derived from the aforementioned carbon footprint accounting method supporting real-time data synchronization. The computer program product may include a computer-readable storage medium on which computer-readable program instructions are loaded to enable a processor to implement various aspects of this disclosure. That is, this application also includes a terminal comprising a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the aforementioned carbon footprint accounting method supporting real-time data synchronization.

[0077] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example, but not limited to, electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination of the foregoing. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0078] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0079] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing the status information of the computer-readable program instructions to implement various aspects of this disclosure.

[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for accounting of carbon footprint supporting real-time data synchronization, characterized in that, The method comprises the following steps: Step 1: configuring the intelligent adaptation interface of the edge device to collect and protocol-analyze heterogeneous data from multiple source systems, and to realize data synchronization between the multiple source systems and the edge device based on a timestamp or a message queue mechanism; Step 2: based on the configuration information of the intelligent adaptation interface, identifying and classifying the collected data, standardizing the classified data, and fusing the data from the multiple source systems through time information and work order information; Step 3: in response to a user interaction operation, constructing a carbon footprint accounting process model, matching the fused data with corresponding units of the carbon footprint accounting process model, and receiving user parameterized configuration of each process step in the carbon footprint accounting process model; Step 4: based on the fused data, using the calculation logic set by the carbon footprint accounting process model to perform real-time calculation and analysis on direct carbon emissions and indirect carbon emissions in the production process.

2. The carbon footprint accounting method supporting real-time data synchronization according to claim 1, characterized in that, The collection and protocol analysis of the heterogeneous data from the multiple source systems further comprise: configuring the intelligent adaptation interface built-in the edge device to determine the connection information and protocol type of different data sources, including the enterprise energy management system (EMS), the manufacturing execution system (MES), and the enterprise resource planning system (ERP), configuring the communication address and register information of specific meters to identify multiple meter data formats; for the configured MES or ERP system, setting the API interface address or database connection information, and obtaining work order and BOM list data through the interfaces; for PDF format bills and account data, configuring a specific file import path, and performing automatic collection, format conversion and loading on data from different sources, and uniformly converting to JSON or XML structure.

3. The carbon footprint accounting method of claim 2, wherein, The identification and classification of the collected data further comprise: automatically identifying and classifying all data transmitted from meter addresses configured as Modbus protocol as structured time series energy consumption data; automatically identifying and classifying all JSON data obtained from the configured MES system API interface as semi-structured production and operation data.

4. The carbon footprint accounting method of claim 3, wherein, The standardization processing of the classified data further comprises: cleaning, converting and integrating the collected multi-source heterogeneous data to form unified formatted data for carbon footprint accounting, including automatically removing outliers, imputing missing values, and performing unit conversion.

5. The carbon footprint accounting method of claim 4, wherein, The real-time calculation and analysis of direct carbon emissions and indirect carbon emissions in the production process further comprise: Calculating carbon emissions from the combustion of fossil fuels in a production process : wherein, consumption of fuel , average low heating value of fuel , carbon emission factor of fuel ; Calculating indirect emissions from purchased electricity, steam energy production : wherein, purchased energy activity data, i.e. consumption, corresponding energy grid or heat emission factor; Calculating the total carbon footprint of a product : wherein, , and are the carbon emissions for the raw material and transportation phases, respectively.

6. The carbon footprint accounting method of claim 5, wherein, after the real-time calculation and analysis of direct carbon emissions and indirect carbon emissions in the production process, further comprising: enabling a shared key token encryption mechanism to encrypt the carbon footprint accounting result data and upload it through a secure channel.

7. An edge computing device supporting real-time data synchronization, characterized by comprise: an interface configuration module for configuring the intelligent adaptation interface to collect and protocol-analyze heterogeneous data from multiple source systems, and to realize data synchronization between the multiple source systems and the edge device based on a timestamp or a message queue mechanism; The data processing module is configured to identify and classify the collected data based on the configuration information of the intelligent adaptation interface, to standardize the classified data, and to fuse the data from multiple source systems through time information and work order information. The accounting model construction module is configured to construct a carbon footprint accounting process model in response to a user interaction operation, to match the fused data with corresponding units of the carbon footprint accounting process model, and to receive a user's parameterized configuration of each process step in the carbon footprint accounting process model. The carbon emission calculation module is configured to calculate and analyze direct carbon emissions and indirect carbon emissions in a production process in real time based on the fused data and using a calculation logic set by the carbon footprint accounting process model.

8. The edge computing device that supports real-time data synchronization according to claim 7, wherein, The hardware architecture of the device includes: a core processor module, a data acquisition interface module, a storage module, a power module, and a housing. The embedded software architecture of the device includes: a driver and operating system layer responsible for hardware drivers and providing a Linux operating environment; a data service layer including: a southbound interface service containing Modbus and OPCUA protocol stacks for collecting data from hardware interfaces; a northbound interface service for providing a RESTful API interface, synchronizing data with enterprise MES and ERP systems, and reporting results to a cloud platform securely; a data processing middleware for performing data cleaning, conversion, and fusion tasks; a core application layer including: a low-code model engine for parsing and executing carbon footprint accounting process model configuration files generated by user operations through a web interface; a carbon emission calculator for performing carbon emission calculations, with an embedded and updatable emission factor database; a performance and management layer including: a web server with a built-in lightweight web server providing a localized configuration management interface and a carbon asset management dashboard, allowing users to access the device IP address through a browser for model construction and data visualization operations; a security service for user authentication, TLS / SSL encryption for data transmission, and token generation and verification for shared results.

9. A terminal comprising a processor and a storage medium; characterized in that: the storage medium is configured to store instructions; the processor is configured to operate according to the instructions to perform the steps of the carbon footprint accounting method supporting real-time data synchronization according to any one of claims 1-6.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the steps of the carbon footprint accounting method supporting real-time data synchronization according to any one of claims 1-6.

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