Two-dimensional code traceability assisted product carbon footprint tracking method, system and equipment

Abstract

The invention discloses a two-dimensional code traceability assisted product carbon footprint tracking method, system and device, and relates to the technical field of carbon emission management. The method comprises the following steps: acquiring a full life cycle of a target product and creating a storage chain; generating and binding a unique two-dimensional code; a writing instruction is generated when the two-dimensional code is triggered; calling preposed carbon emission data, and reading environmental parameters of scanning nodes; performing evolutionary analysis in combination with the environmental parameters and the emission data to generate update data; associating the preposed data and then writing into the storage space; and performing carbon footprint tracking management through the two-dimensional code and the updated chain. The technical problems that in a traditional carbon footprint calculation method, due to data splitting, dynamic updating lagging and boundary definition fuzziness, carbon emission accounting is inaccurate, and tracking efficiency is low are solved, and a carbon footprint dynamic evolution mechanism combining a two-dimensional code identification binding period storage chain and environment context parameter real-time collection is adopted. The technical effect of improving the real-time performance, the accuracy and the traceability of the carbon footprint accounting data is achieved.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of carbon emission management, and in particular to a product carbon footprint tracking method, system and device assisted by two-dimensional code traceability. BACKGROUND

[0002] Precise quantification and reliable management of product carbon footprint have become the core cornerstone of promoting green and low-carbon transformation. At present, although the internationally accepted life cycle assessment (LCA) method provides a theoretical framework, it still faces significant challenges in practical application: its calculation relies heavily on static average emission factors and lagging databases, making it difficult to capture the dynamic differences of individual products in real manufacturing, circulation and use processes; data is mostly manually entered and macro-estimated, resulting in low granularity and transparency; and it focuses mainly on the production stage, lacking real-time collection and dynamic correlation of whole life cycle data such as raw material procurement, transportation, use and disposal, leading to fragmented carbon emission data and low tracking efficiency, which has become a bottleneck for enterprises to cope with green trade barriers. SUMMARY

[0003] The application provides a product carbon footprint tracking method, system and device assisted by two-dimensional code traceability, which solves the technical problems of inaccurate carbon emission calculation and low tracking efficiency caused by data fragmentation, dynamic update lag and ambiguous boundary definition in traditional carbon footprint calculation methods.

[0004] In view of the above problems, the application provides a product carbon footprint tracking method, system and device assisted by two-dimensional code traceability.

[0005] In a first aspect of the application, a product carbon footprint tracking method assisted by two-dimensional code traceability is provided, which comprises: obtaining the whole life cycle of a target product, and creating a cycle storage chain according to the whole life cycle, wherein the cycle storage chain is configured with a storage space one-to-one mapped with the whole life cycle, and the storage space is a one-time write space; generating a unique two-dimensional code identifier of the target product when the target product is in the manufacturing process, and binding the two-dimensional code identifier with the cycle storage chain; if a first authority subject triggers the two-dimensional code identifier in any life cycle, generating a write instruction; reading environmental context parameters of a scanning node after calling carbon emission data of a preceding chain node in the cycle storage chain according to the write instruction, wherein the environmental context parameters include location data, transportation mode, energy composition and real-time carbon emission factor; performing carbon footprint evolution analysis based on the environmental context parameters and the carbon emission data, establishing node update data; associating the node update data with data of the preceding chain node, and writing into the mapped storage space; and performing carbon footprint tracking management according to the two-dimensional code identifier and the updated cycle storage chain.

[0006] In a second aspect of the present application, a product carbon footprint tracking system assisted by a two-dimensional code traceability is provided, and the system comprises: The chain creation module obtains a full life cycle of a target product, and creates a cycle storage chain according to the full life cycle, wherein a storage space that is one-to-one mapped with the full life cycle is configured in the cycle storage chain, and the storage space is a one-time write space. The identification binding module generates a unique two-dimensional code identification of the target product when the target product is in the manufacturing process, and binds the two-dimensional code identification with the cycle storage chain. The identification triggering module generates a write instruction if a first authority triggers the two-dimensional code identification in any life cycle. The data reading module reads environmental context parameters of a scanned node after calling carbon emission data of a previous chain node in the cycle storage chain according to the write instruction, wherein the environmental context parameters include location data, transportation mode, energy composition, and real-time carbon emission factor. The evolution analysis module performs carbon footprint evolution analysis based on the environmental context parameters and the carbon emission data, and establishes node update data. The tracking management module writes the node update data into the mapped storage space after associating the node update data with data of the previous chain node, and performs carbon footprint tracking management according to the two-dimensional code identification and the updated cycle storage chain.

[0007] In a third aspect of the present application, an electronic device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the following steps when executing the computer program: The chain creation module obtains a full life cycle of a target product, and creates a cycle storage chain according to the full life cycle, wherein a storage space that is one-to-one mapped with the full life cycle is configured in the cycle storage chain, and the storage space is a one-time write space. The identification binding module generates a unique two-dimensional code identification of the target product when the target product is in the manufacturing process, and binds the two-dimensional code identification with the cycle storage chain. The identification triggering module generates a write instruction if a first authority triggers the two-dimensional code identification in any life cycle. The data reading module reads environmental context parameters of a scanned node after calling carbon emission data of a previous chain node in the cycle storage chain according to the write instruction, wherein the environmental context parameters include location data, transportation mode, energy composition, and real-time carbon emission factor. The evolution analysis module performs carbon footprint evolution analysis based on the environmental context parameters and the carbon emission data, and establishes node update data. The tracking management module writes the node update data into the mapped storage space after associating the node update data with data of the previous chain node, and performs carbon footprint tracking management according to the two-dimensional code identification and the updated cycle storage chain.

[0008] The one or more technical solutions provided in the present application have at least the following technical effects or advantages: Firstly, the full life cycle of the target product is acquired, and a cycle storage chain is created according to the full life cycle, wherein a storage space one-to-one mapped with the full life cycle is configured in the cycle storage chain, and the storage space is a one-time write space; then, when the target product is in the manufacturing process, a unique two-dimensional code identifier of the target product is generated, and the two-dimensional code identifier is bound with the cycle storage chain; further, in any life cycle, if a first authority subject triggers the two-dimensional code identifier, a write instruction is generated, and then the carbon emission data of a previous chain node in the cycle storage chain is called according to the write instruction, and then the environmental context parameters of a scanning node are read, the environmental context parameters including position data, transportation mode, energy composition and real-time carbon emission factor; then, based on the environmental context parameters and the carbon emission data, carbon footprint evolution analysis is performed to establish node update data; finally, after the node update data is associated with the data of the previous chain node, the data is written into the mapped storage space, and carbon footprint tracking management is performed according to the two-dimensional code identifier and the updated cycle storage chain. The technical problems of inaccurate carbon emission accounting and low tracking efficiency caused by data fragmentation, dynamic update lag and fuzzy boundary definition in the traditional carbon footprint calculation method are solved, and through the combination of the two-dimensional code identifier binding the cycle storage chain and the real-time collection of the environmental context parameters, a carbon footprint dynamic evolution mechanism is achieved, which achieves the technical effects of improving the real-time, accuracy and traceability of carbon footprint accounting data. BRIEF DESCRIPTION OF DRAWINGS

[0009] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0010] Figure 1 The flowchart of the product carbon footprint tracking method assisted by two-dimensional code traceability provided by the embodiments of the present application.

[0011] Figure 2 The structure diagram of the product carbon footprint tracking system assisted by two-dimensional code traceability provided by the embodiments of the present application.

[0012] Legend: chain creation module 11, identifier binding module 12, identifier triggering module 13, data reading module 14, evolution analysis module 15, tracking management module 16. DETAILED DESCRIPTION

[0013] This application addresses the technical problems of inaccurate carbon emission accounting and low tracking efficiency caused by traditional carbon footprint calculation methods due to data fragmentation, delayed dynamic updates, and ambiguous boundary definitions by providing a product carbon footprint tracking method, system, and equipment assisted by QR code traceability.

[0014] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0015] It should be noted that the terms "comprising" and "having" are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or modules that are not explicitly listed or that are inherent to these processes, methods, products, or devices.

[0016] Example 1, as Figure 1 As shown, this application provides a product carbon footprint tracking method assisted by QR code traceability, wherein the method includes: Obtain the entire lifecycle of the target product, and create a lifecycle storage chain based on the entire lifecycle. The lifecycle storage chain is configured with storage spaces that are mapped one-to-one with the entire lifecycle, and the storage spaces are one-time write spaces.

[0017] In one embodiment, the entire lifecycle information of the target product is first acquired, covering all stages from raw material acquisition, production and processing, transportation and distribution, use and maintenance to end-of-life recycling. Then, based on the acquired lifecycle information, a corresponding cycle storage chain is established. This cycle storage chain is logically divided into multiple contiguous storage spaces, each corresponding one-to-one with a stage in the entire lifecycle, thus achieving hierarchical data management for different lifecycle stages. To ensure data authenticity and immutability, each storage space is designed as a one-time write space; that is, after data is written at the corresponding lifecycle node, the space is locked and can no longer be overwritten or modified, only appended reading is allowed. This design ensures that carbon emission activity data at each stage becomes a fixed record after being written, preventing human or systemic tampering and guaranteeing the integrity and reliability of the tracking data. Through this cycle storage chain, carbon emission data at each stage of the product lifecycle can be clearly linked together, forming a dynamically updated and traceable carbon footprint record chain, providing a solid foundation for subsequent QR code-based triggering, data retrieval, and tracking management.

[0018] When the target product is in the manufacturing process, a unique two-dimensional code identifier of the target product is generated, and the two-dimensional code identifier is bound to the cycle storage chain.

[0019] In one embodiment, when the target product enters the manufacturing process, a unique digital identity is first generated for the target product in the form of a two-dimensional code. This two-dimensional code identifier can be attached or embedded to the target product in the form of a printed label, laser etching, or electronic coding, so that it always accompanies the product throughout its life cycle. In addition, the generated two-dimensional code identifier is bound to the cycle storage chain, i.e., a mapping relationship between the two-dimensional code identifier and the cycle storage chain is established, so that whenever the two-dimensional code is scanned or triggered, the corresponding cycle storage chain of the product can be automatically located, and data writing or reading operations can be performed in the storage space corresponding to the life cycle. Through this binding mechanism, the carbon emission data of each product can be guaranteed to correspond one-to-one with its two-dimensional code identifier, avoiding confusion of different product data.

[0020] In any life cycle, if the first authority triggers the two-dimensional code identifier, a write instruction is generated.

[0021] In one embodiment, the target product can trigger carbon emission data update at any life cycle node. When the subject with write permission, i.e., the first authority, scans or activates the unique two-dimensional code identifier of the product, the two-dimensional code is automatically recognized, and the legality and effectiveness of its authority identity are verified. If the verification is passed, a write instruction is generated, which contains the trigger time, trigger subject identity information, and node identifier of the current life cycle, and is used to indicate subsequent data collection and storage operations. After the write instruction is generated, the cycle storage chain of the target product is automatically associated, and the one-time storage space corresponding to the current life cycle node is located, the data interface for the environmental context parameters and carbon emission activity data to be written is reserved, the integrity and continuity of the whole life cycle carbon footprint information are guaranteed, and the problem of data loss or delayed update is avoided.

[0022] Further, the generation of a write instruction if the first authority triggers the two-dimensional code identifier in any life cycle further includes: determining whether the life cycle is a product quality detection cycle; if the life cycle is a product quality detection cycle, generating a cycle verification instruction; performing target product quality verification of the current node according to the cycle verification instruction; if the quality verification result is a pass result, retaining the cycle storage chain and continuing to update the carbon emission data according to the write instruction.

[0023] Preferably, during the life cycle of the target product, each stage is tracked and determined in real time according to the stage of the life cycle. When the target product is in the quality detection stage, the cycle is automatically identified as a product quality detection cycle. Once it is determined that the current life cycle stage is a product quality detection cycle, a cycle verification instruction is automatically generated, which is designed to start the quality detection process and confirm whether the product meets the quality standards at this stage. When the automated detection equipment receives the cycle verification instruction, it will verify the quality of the current batch of target products from the aspects of product appearance inspection, performance test, etc., and feed back the quality verification result to the system according to the verification result. Subsequently, the feedback quality verification result is analyzed, and if the quality verification result shows that the verification is passed, it is determined that the batch of target products meets the quality requirements, the verification process is passed, and the data in the cycle storage chain will continue to remain unchanged, and the carbon emission data will continue to be updated according to the previous write instruction, ensuring the quality of the product and the accuracy of the carbon emission data.

[0024] Further, the target product quality verification of the current node according to the cycle verification instruction comprises: If the quality verification result is a failure result, a chain reset instruction of the cycle storage chain is generated; the cycle storage chain is reset to a scrap storage chain according to the chain reset instruction; and the carbon emission data is updated according to the scrap storage chain.

[0025] Optionally, if the quality verification result shows that the verification is not passed, a chain reset instruction is automatically generated, which carries the unique two-dimensional code identification of the target product, the detection result state and the reset type field, and is used to trigger the system to reset the cycle storage chain. When executing the chain reset instruction, the system marks the original cycle storage chain bound to the product as invalid and resets it to a scrap storage chain. The scrap storage chain is consistent in structure with the normal cycle storage chain, but the life cycle node attributes are uniformly defined as scrap state, which is used to record the carbon emission data generated during the scrap processing of the product. At the same time, all subsequent write instructions can only be executed on the scrap storage chain, avoiding invalid products from continuing to accumulate data in the normal chain. After the target product enters the scrap stage, the system updates the carbon emission data according to the scrap storage chain. The updated data includes parameters such as disassembly energy consumption, transportation mode, waste treatment mode and recycling rate generated during the scrap process. By writing these data into the one-time storage space of the scrap storage chain, a complete carbon footprint record of the product at the end of the life cycle can be formed. These records will also be synchronized to the cloud platform to improve the full life cycle carbon footprint report of the target product.

[0026] After the carbon emission data of the preceding chain node in the period storage chain is called according to the write instruction, the environmental context parameters of the scanning node are read, including location data, transportation mode, energy composition and real-time carbon emission factor.

[0027] In one embodiment, after the write instruction is generated, the system updates the data of the current life cycle node according to the write instruction, at this time, the carbon emission data of the preceding chain node written in the period storage chain is called to ensure the continuity and integrity of the data. Subsequently, the scanning node is activated, and the Internet of Things device bound to the node is synchronously called according to the write instruction to capture the context information of the environment where the target product is located, including location data, transportation mode, energy composition and real-time carbon emission factor. The location data records the geographical position of the current link; the transportation mode records the transportation mode of the target product at the node, such as road transportation, railway transportation, air transportation or sea transportation, etc.; the energy composition describes the types and proportions of energy used in this link, usually including electricity, fuel, natural gas, etc.; the real-time carbon emission factor reflects the carbon emission factor at the current time, which measures the carbon emission amount per unit of energy or material consumption. Then, the collected environmental context parameters are combined with the carbon emission data of the preceding chain node as input data for subsequent carbon footprint evolution analysis, ensuring that the carbon emission data of each life cycle node not only reflects the historical cumulative value, but also reflects the immediate state and actual impact of the node, thereby improving the accuracy and timeliness of carbon footprint tracking.

[0028] Further, the environmental context parameters of the scanning node include: According to the write instruction, the Internet of Things device is activated, the environmental context parameters are collected using the Internet of Things device, and the collection results are established; the edge computing node is activated, and the data preprocessing of the collection results is performed according to the edge computing node; and the collection results after data preprocessing are uploaded to the storage space under the current scanning node as environmental context parameters.

[0029] Preferably, an activation signal is first sent to the Internet of Things (IoT) device configured to the current node according to the write instruction, including but not limited to smart meters, temperature and humidity sensors, energy consumption monitoring terminals, GPS positioning devices or transportation trackers, etc. Subsequently, the activated IoT device is used to collect real-time environmental context data related to the product life cycle, such as geographic location, transportation method, energy consumption type and quantity, and carbon emission factor provided by external database or real-time interface, and a collection result is formed by summarizing and storing the collected data. Then, the collection result is transmitted to the edge computing node, which is usually deployed in the production workshop gateway, logistics relay station or local server, and is used to preprocess the raw collected data, such as removing outliers and duplicate data, filling missing values, and standardizing data, etc. The removal of outliers can be performed by statistical methods (such as Z-score and box plot method); the removal of duplicate data can be performed by comparison based on primary key or timestamp; the missing value filling can be performed by mean / median interpolation; and the data standardization can be performed by converting data from different sources into a unified unit. Through the processing of the edge computing node, the data transmission efficiency can be significantly improved, and the delay can be reduced. Then, the edge computing node returns the preprocessed collection result, and the system uploads the received return data as environmental context parameters to the one-time storage space corresponding to the current scanning node in the periodic storage chain, and controls the writing process by the write instruction, to ensure that the data corresponds to the life cycle node one by one and cannot be modified. In this way, each node retains verified context information, which can be directly called to combine with the carbon emission data of the previous node for carbon footprint evolution analysis, to ensure the integrity and credibility of the carbon footprint data chain.

[0030] Based on the environmental context parameters and the carbon emission data, carbon footprint evolution analysis is performed to establish node update data.

[0031] In one embodiment, after obtaining the environmental context parameters of the scanning node and the carbon emission data of the previous chain node, the environmental context parameters and the accumulated carbon emission data of the previous node are sent to the carbon footprint dynamic evolution network for fusion processing. The quantitative indicators in the environmental context are converted into calculable carbon footprint evolution operators, and the calculated carbon footprint evolution operators are combined with the carbon emission data for dynamic transformation processing, i.e., the carbon emission data is corrected according to the real-time carbon footprint evolution operator, so as to reflect the influence of energy structure change on cumulative carbon emission. Finally, the update data of the current node is established according to the calculation result, and is associated with the data of the previous chain node to form a complete and continuous carbon footprint evolution chain, providing a solid data foundation for subsequent tracking and authentication.

[0032] Further, the carbon footprint evolution analysis based on the environmental context parameters and the carbon emission data, and the establishment of node update data, include: The environmental context parameters and the carbon emission data are synchronously sent to a carbon footprint dynamic evolution network; a data conversion of the environmental context parameters is performed by a preprocessing layer of the carbon footprint dynamic evolution network, a carbon footprint evolution operator is established, the carbon footprint evolution operator includes a space migration operator, a circulation operator, an energy mixture operator, and a time sequence disturbance operator; the carbon footprint evolution operator and the carbon emission data are sent to a calculation layer to perform a dynamic transformation processing of the carbon emission data, and node update data is established according to a dynamic transformation processing result.

[0033] Optionally, the collected environmental context parameters and the carbon emission data of the front chain nodes are synchronously sent to a pre-constructed carbon footprint dynamic evolution network, the carbon footprint dynamic evolution network serves as an integrated data analysis platform, can centrally process and real-time analyze the carbon emission data from different nodes, and ensures real-time and accuracy of the carbon emission data. In the carbon footprint dynamic evolution network, the preprocessing layer receives the environmental context parameters, uses the Euclidean distance to calculate a geographical distance between geographical coordinates of the front chain nodes and geographical coordinates of a current scanning node, and takes the distance as the space migration operator; for the received transportation mode, the transportation mode is compared with a transportation emission table to obtain a unit transportation emission coefficient of the transportation mode, and the unit transportation emission coefficient is taken as the circulation operator; for the received energy composition, the energy composition of the current scanning node is sorted into a proportion set, such as: E={(e1, p1), (e2, p2),..., (en, pn)}, where en represents an n-th energy type, and pn represents a proportion of the n-th energy type in total energy consumption, and p1, p2,..., pn are all greater than or equal to 0 and less than or equal to 1, and the energy composition is taken as the energy mixture operator; for the received time sequence, a time sequence disturbance operator is established according to a time sequence disturbance table. n n n n n ​​​​The carbon emission factors of various types of energy are labeled to form an energy mixing operator; for the received real-time carbon emission factor, the real-time carbon emission factor is divided by the historical average carbon emission factor to obtain a time sequence disturbance operator. The calculated spatial migration operator, flow operator, energy mixing operator and time sequence disturbance operator are summarized and stored to form a carbon footprint evolution operator, which will be used as a key tool for analyzing carbon footprint changes. Then, the carbon footprint evolution operator and carbon emission data are sent to the calculation layer by the preprocessing layer, and the calculation layer operates and corrects the carbon emission data according to the carbon footprint evolution operator to generate a final dynamic transformation result, which reflects the real-time changes of carbon emissions and comprehensively considers spatial, transportation, energy and time factors. Finally, a node update data is established through the dynamic transformation result, which includes the carbon emission value adjusted according to the evolution operator and possible new carbon emission sources, and is used to supplement and correct the carbon footprint data chain in the product life cycle to ensure more accurate and reasonable calculation of carbon emissions.

[0034] Further, the carbon footprint evolution operator and the carbon emission data are sent to the calculation layer, and the dynamic transformation processing of the carbon emission data is performed, including: The spatial processing sub-layer in the calculation layer iteratively operates the carbon emission data and the spatial migration operator corresponding to the location parameter to establish a first dynamic correction value; the transportation processing sub-layer in the calculation layer processes the first dynamic correction value and the flow operator corresponding to the transportation mode to establish a second dynamic correction value; the energy mixing sub-layer in the calculation layer processes the second dynamic correction value and the energy mixing operator corresponding to the energy composition to establish a third dynamic correction value; the confidence calculation layer in the calculation layer calculates the credibility of the data source according to the time sequence disturbance operator, and weights the third dynamic correction value according to the credibility to establish a dynamic transformation result.

[0035] Optionally, the calculation layer in the carbon footprint dynamic evolution network includes a space processing sub-layer, a transportation processing sub-layer, an energy mix sub-layer, and a confidence calculation layer. In the space processing sub-layer, the spatial migration operator corresponding to the location parameter is multiplied by the carbon intensity of the region at the current time, and then added to the current carbon emission data. This process is iterated, and each time the location changes, the spatial migration operator is recalculated, and the carbon emission data is corrected according to the new spatial migration operator, thereby obtaining a first dynamic correction value. In the transportation processing sub-layer, the flow operator corresponding to the transportation mode is multiplied by the transportation quality and the transportation distance, and then the calculated product is superimposed with the first dynamic correction value to obtain a second dynamic correction value. In the energy mix sub-layer, the proportion of each energy type in the energy mix operator corresponding to the energy composition is multiplied by the carbon emission factor of that energy type, and then the products are added to obtain an energy mix correction value. By adding the energy mix correction value to 1 and then multiplying the sum with the second dynamic correction value, a third dynamic correction value is obtained. In the confidence calculation layer, the time series disturbance operator is quantified according to the Sigmoid function or the linear function to determine the confidence weight of the data source. By weighting the third dynamic correction value with this confidence weight, a dynamic transformation result is obtained, which contains the carbon emission value corrected in the four dimensions of space, transportation, energy, and confidence, thereby providing high-precision data support for carbon footprint tracking in the whole life cycle of a product.

[0036] After associating the node update data with the data of the preceding chain node, write it into the mapped storage space, and perform carbon footprint tracking management according to the two-dimensional code identifier and the updated periodic storage chain.

[0037] In one embodiment, when the node update data is obtained, the node update data is associated with the data of the preceding chain node and written into the corresponding mapped storage space in the periodic storage chain. After writing is completed, it is automatically locked to prevent subsequent modification, thereby ensuring the non-tamperability and authenticity of the data. After writing is completed, the system binds the updated periodic storage chain to the target product using the two-dimensional code identifier as an access portal. At this time, any authority subject can real-time retrieve the latest carbon footprint data of the product by scanning the two-dimensional code, ensuring the completeness and immediacy of carbon footprint tracking management. Through the above carbon footprint tracking management, not only can the accurate traceability of a product in each life cycle stage be achieved, but also an international standard-compliant carbon footprint archive can be established at the whole-chain level, which can be used for subsequent carbon certification, green supply chain management, etc.

[0038] Further, the carbon footprint tracking management according to the two-dimensional code identifier and the updated periodic storage chain includes: If the second authority triggers the two-dimensional code identifier, a read-only instruction is generated; after the periodic storage chain is packaged according to the read-only instruction, the carbon footprint visualization expression is performed.

[0039] Preferably, when the second authority (such as a supervisor, a third-party certification agency or a user) scans the two-dimensional code identifier of the target product, the identity of the authority is verified to ensure that it has read-only access. After verification, a read-only instruction is generated, which contains the two-dimensional code identifier, product information, read timestamp and user identity information, etc. Subsequently, the system encapsulates the periodic storage chain corresponding to the target product according to the read-only instruction, that is, extracts all relevant carbon footprint data from the periodic storage chain and stores it separately, ensuring that all carbon emission data related to the product life cycle can be extracted at once through the read-only instruction. During the encapsulation process, the data in the chain is encrypted to ensure the security of data transmission and prevent unauthorized access or tampering. After encapsulation, the extracted carbon footprint data is visualized, usually in the form of charts, dashboards or other visualizations to display the full life cycle carbon emissions of the product, including carbon emissions, energy structure, transportation mode contribution, etc. at each stage (such as production, transportation, use, disposal, etc.), thereby improving user awareness of product carbon emissions and providing transparent and verifiable basis for third-party certification and international green trade.

[0040] Further, the generation of the write instruction includes: According to the write instruction, a cloud platform synchronization instruction is generated; based on the cloud platform synchronization instruction, the storage data in the periodic storage chain is uploaded to the cloud platform, and a carbon footprint report is constructed on the cloud platform; according to the carbon footprint report of the cloud platform, the target product carbon footprint tracking management is performed.

[0041] Preferably, a cloud platform synchronization instruction is first generated according to the content of the write instruction, which contains all the carbon emission data in the periodic storage chain, the upload timestamp of the data, the data source identification, and the unique two-dimensional code identification of the target product, to ensure that the data in the periodic storage chain can be accurately and timely uploaded to the cloud platform. Subsequently, all the carbon emission data in the periodic storage chain is uploaded to the cloud platform through a secure data transmission protocol according to the cloud platform synchronization instruction. During the uploading process, the data is packaged and encrypted according to the predetermined format to ensure the security during the transmission. Once the data is successfully uploaded, the cloud platform will automatically generate a carbon footprint report based on the uploaded data. The carbon footprint report calculates the overall carbon footprint based on the carbon emission data of the product throughout its life cycle, and provides detailed carbon emission distribution, carbon emission amount of each life cycle stage, etc. The carbon footprint report generated by the cloud platform will be used for carbon footprint tracking management, including continuous monitoring and analysis of carbon emissions during the product life cycle, to track the carbon emission dynamics of the product in different life cycle stages in real time, and help enterprises, regulatory agencies or consumers understand the green performance of the product and achieve the goal of sustainable development.

[0042] In summary, the embodiments of the present application have at least the following technical effects: First, the full life cycle of the target product is obtained, and a periodic storage chain is created according to the full life cycle, wherein the periodic storage chain is configured with a storage space that is one-to-one mapped with the full life cycle, and the storage space is a one-time write space. Then, when the target product is in the manufacturing process, a unique two-dimensional code identification of the target product is generated, and the two-dimensional code identification is bound to the periodic storage chain. Further, in any life cycle, if a first principal triggers the two-dimensional code identification, a write instruction is generated, and then the carbon emission data of the previous chain node in the periodic storage chain is called according to the write instruction, the environmental context parameters of the scanning node are read, the environmental context parameters include location data, transportation mode, energy composition and real-time carbon emission factor. Then, based on the environmental context parameters and the carbon emission data, carbon footprint evolution analysis is performed to establish node update data. Finally, the node update data is associated with the data of the previous chain node, and then written into the mapped storage space. According to the two-dimensional code identification and the updated periodic storage chain, carbon footprint tracking management is performed. The technical problems of inaccurate carbon emission accounting and low tracking efficiency caused by data fragmentation, dynamic update lag and fuzzy boundary definition in the traditional carbon footprint calculation method are solved. Through the combination of two-dimensional code identification binding periodic storage chain and real-time collection of environmental context parameters, a carbon footprint dynamic evolution mechanism is achieved, which improves the real-time, accuracy and traceability of carbon footprint accounting data.

[0043] Embodiment two, based on the same inventive concept as the product carbon footprint tracking method assisted by the two-dimensional code traceability in the preceding embodiments, as shown in Figure 2 The present application provides a product carbon footprint tracking system assisted by two-dimensional code traceability, wherein the system comprises: Chain creation module 11: obtain the full life cycle of the target product, and create a cycle storage chain according to the full life cycle, wherein the cycle storage chain is configured with a storage space one-to-one mapped with the full life cycle, and the storage space is a one-time write space; identification binding module 12: when the target product is in the manufacturing process, generate a unique two-dimensional code identification of the target product, and bind the two-dimensional code identification with the cycle storage chain; identification triggering module 13: in any life cycle, if a first authority triggers the two-dimensional code identification, a write instruction is generated; data reading module 14: after calling the carbon emission data of the previous chain node in the cycle storage chain according to the write instruction, reading the environmental context parameters of the scanning node, the environmental context parameters including location data, transportation mode, energy composition and real-time carbon emission factor; evolution analysis module 15: based on the environmental context parameters and the carbon emission data, carbon footprint evolution analysis is performed to establish node update data; tracking management module 16: after associating the node update data with the data of the previous chain node, writing into the mapped storage space, and according to the two-dimensional code identification and the updated cycle storage chain, carbon footprint tracking management is performed.

[0044] In some embodiments, the identification triggering module 13 comprises: determining whether the life cycle is a product quality detection cycle; if the life cycle is a product quality detection cycle, a cycle verification instruction is generated; according to the cycle verification instruction, the target product quality of the current node is verified; if the quality verification result is a pass result, the cycle storage chain is retained, and the carbon emission data update is continued according to the write instruction.

[0045] In some embodiments, the identification triggering module 13 comprises: If the quality verification result is a fail result, a chain reset instruction of the cycle storage chain is generated; according to the chain reset instruction, the cycle storage chain is reset to a scrap storage chain; according to the scrap storage chain, the carbon emission data is updated.

[0046] In some embodiments, the data reading module 14 comprises: activating the Internet of Things device according to the write instruction, collecting the environmental context parameters by using the Internet of Things device, and establishing the collection result; activating the edge computing node, and performing data preprocessing of the collection result according to the edge computing node; uploading the collection result after data preprocessing as the environmental context parameters to the storage space under the current scanning node.

[0047] In some embodiments, the evolution analysis module 15 includes: Synchronously sending the environmental context parameters and the carbon emission data to a carbon footprint dynamic evolution network; performing data conversion of the environmental context parameters through a preprocessing layer of the carbon footprint dynamic evolution network, establishing a carbon footprint evolution operator, the carbon footprint evolution operator including a spatial migration operator, a circulation operator, an energy mixture operator, and a time series disturbance operator; sending the carbon footprint evolution operator and the carbon emission data to a computing layer, performing dynamic transformation processing of the carbon emission data, and establishing node update data according to a dynamic transformation processing result.

[0048] In some embodiments, the evolution analysis module 15 includes: Performing iterative operation of the carbon emission data and a spatial migration operator corresponding to the location parameter by using a spatial processing sub-layer in the computing layer, establishing a first dynamic correction value; processing the first dynamic correction value and a circulation operator corresponding to the transportation mode by using a transportation processing sub-layer in the computing layer, establishing a second dynamic correction value; processing the second dynamic correction value and an energy mixture operator corresponding to the energy composition by using an energy mixture sub-layer in the computing layer, establishing a third dynamic correction value; calculating the credibility of the data source according to a time series disturbance operator by using a confidence computing layer in the computing layer, and weighting the third dynamic correction value by using the credibility, to establish a dynamic transformation result.

[0049] In some embodiments, the tracking management module 16 includes: If the second principal triggers the two-dimensional code identifier, a read-only instruction is generated; after performing periodic storage chain encapsulation according to the read-only instruction, carbon footprint visual expression is performed.

[0050] In some embodiments, the tracking management module 16 includes: A cloud platform synchronization instruction is generated according to the write instruction; storage data in the periodic storage chain is uploaded to a cloud platform based on the cloud platform synchronization instruction, and a carbon footprint report is constructed on the cloud platform; target product carbon footprint tracking management is performed according to the carbon footprint report of the cloud platform.

[0051] Embodiment three, based on the same inventive concept as the product carbon footprint tracking method assisted by the two-dimensional code traceability in the foregoing embodiment one, the present application provides an electronic device, which can be a server, comprising a processor, a memory and a network interface connected through a system bus, wherein the processor of the electronic device is used to provide computing and control capability, the memory of the electronic device comprises a non-volatile storage medium and an internal memory, the non-volatile storage medium stores an operating system, a computer program and a database, the internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium, the database of the electronic device is used to store data, the network interface of the electronic device is used to communicate with the terminal outside through the network connection, and the computer program is executed by the processor to realize the product carbon footprint tracking method assisted by the two-dimensional code traceability.

[0052] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description, not representing the advantages and disadvantages of the embodiments. And the above-mentioned describes the specific embodiments of the present application. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multi-task processing and parallel processing are also possible or can be advantageous.

[0053] The above-mentioned is only the preferred embodiment of the present application, and does not limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

[0054] The present application and the drawings are only exemplary description of the present application, and should be considered to cover any and all modifications, changes, combinations or equivalents within the scope of the present application. Obviously, those skilled in the art can make various modifications and changes to the present application without departing from the scope of the present application. Thus, if these modifications and changes of the present application belong to the scope of the present application and its equivalent technology, the present application intends to include these modifications and changes.

Claims

1. A method for product carbon footprint tracking with the aid of QR code traceability, characterized in that, The method comprises: acquiring a full life cycle of a target product, and creating a cycle storage chain according to the full life cycle, wherein a storage space that is one-to-one mapped with the full life cycle is configured in the cycle storage chain, and the storage space is a one-time write space; generating a unique two-dimensional code identifier of the target product when the target product is in a manufacturing process, and binding the two-dimensional code identifier with the cycle storage chain; if a first authority triggers the two-dimensional code identifier in any life cycle, generating a write instruction; reading environmental context parameters of a scanning node after calling carbon emission data of a previous chain node in the cycle storage chain according to the write instruction, wherein the environmental context parameters include location data, transportation mode, energy composition, and real-time carbon emission factor; performing carbon footprint evolution analysis based on the environmental context parameters and the carbon emission data, and establishing node update data; associating the node update data with data of the previous chain node, writing the node update data into the mapped storage space, and performing carbon footprint tracking management according to the two-dimensional code identifier and the updated cycle storage chain.

2. The product carbon footprint tracking method with the aid of the two-dimensional code traceability as claimed in claim 1, wherein, The reading of the environmental context parameters of the scanning node comprises: activating an Internet of Things device according to the write instruction, collecting environmental context parameters by using the Internet of Things device, and establishing collection results; activating an edge computing node, and performing data preprocessing of the collection results according to the edge computing node; uploading the collection results after data preprocessing to a storage space under the current scanning node as the environmental context parameters.

3. The product carbon footprint tracking method with the aid of a two-dimensional code traceability as claimed in claim 2, wherein, The carbon footprint evolution analysis based on the environmental context parameters and the carbon emission data, and the establishment of node update data, comprise: synchronously sending the environmental context parameters and the carbon emission data to a carbon footprint dynamic evolution network; performing data conversion of the environmental context parameters by a preprocessing layer of the carbon footprint dynamic evolution network, establishing a carbon footprint evolution operator, and the carbon footprint evolution operator comprises a space migration operator, a flow operator, an energy mixing operator, and a time series disturbance operator; sending the carbon footprint evolution operator and the carbon emission data to a computing layer, performing dynamic transformation processing of the carbon emission data, and establishing node update data according to a dynamic transformation processing result.

4. The product carbon footprint tracking method with the aid of a two-dimensional code traceability as claimed in claim 3, wherein, The sending of the carbon footprint evolution operator and the carbon emission data to the computing layer, and the dynamic transformation processing of the carbon emission data, comprise: performing iterative operation of the carbon emission data and a space migration operator corresponding to the location parameter by using a space processing sub-layer in the computing layer, and establishing a first dynamic correction value; processing the first dynamic correction value and a flow operator corresponding to the transportation mode by using a transportation processing sub-layer in the computing layer, and establishing a second dynamic correction value; processing the second dynamic correction value and an energy mixing operator corresponding to the energy composition by using an energy mixing sub-layer in the computing layer, and establishing a third dynamic correction value; calculating the credibility of the data source according to the time series disturbance operator by using a confidence computing layer in the computing layer, weighting the third dynamic correction value by using the credibility, and establishing a dynamic transformation result.

5. The product carbon footprint tracking method with the aid of the two-dimensional code traceability as claimed in claim 1, wherein, The carbon footprint tracking management according to the two-dimensional code identifier and the updated cycle storage chain comprises: If the second authority triggers the two-dimensional code identifier, a read-only instruction is generated; After the period storage chain is packaged according to the read-only instruction, carbon footprint visualization expression is performed.

6. The product carbon footprint tracking method with the aid of the two-dimensional code traceability as claimed in claim 1, wherein, If the first authority triggers the two-dimensional code identifier in any life cycle, a write instruction is generated, and the method further comprises: determining whether the life cycle is a product quality detection cycle; if the life cycle is a product quality detection cycle, a period verification instruction is generated; performing target product quality verification of the current node according to the period verification instruction; if the quality verification result is a pass result, the period storage chain is retained, and carbon emission data updating is continued according to the write instruction.

7. The product carbon footprint tracking method with the aid of a two-dimensional code traceability as claimed in claim 6, wherein, The method further comprises: if the quality verification result is a fail result, a chain reset instruction of the period storage chain is generated; the period storage chain is reset to a scrap storage chain according to the chain reset instruction; carbon emission data updating is performed according to the scrap storage chain.

8. The product carbon footprint tracking method with the aid of the two-dimensional code traceability as claimed in claim 1, wherein, After the write instruction is generated, the method further comprises: a cloud platform synchronization instruction is generated according to the write instruction; storage data in the period storage chain is uploaded to a cloud platform based on the cloud platform synchronization instruction, and a carbon footprint report is constructed on the cloud platform; target product carbon footprint tracking management is performed according to the carbon footprint report of the cloud platform.

9. A product carbon footprint tracking system assisted by QR traceability, characterized by, The system for implementing the product carbon footprint tracking method assisted by the two-dimensional code traceability of any one of claims 1-8, the system comprises: a chain creation module: obtaining the full life cycle of the target product, and creating a period storage chain according to the full life cycle, wherein the period storage chain is configured with a storage space one-to-one mapped with the full life cycle, and the storage space is a one-time write space; an identifier binding module: generating a unique two-dimensional code identifier of the target product when the target product is in the manufacturing process, and binding the two-dimensional code identifier with the period storage chain; an identifier triggering module: if the first authority triggers the two-dimensional code identifier in any life cycle, a write instruction is generated; a data reading module: after the carbon emission data of the previous chain node in the period storage chain is called according to the write instruction, the environmental context parameters of the scanning node are read, the environmental context parameters including location data, transportation mode, energy composition and real-time carbon emission factor; an evolution analysis module: based on the environmental context parameters and the carbon emission data, carbon footprint evolution analysis is performed, and node update data is established; a tracking management module: after the node update data is associated with the data of the previous chain node, the data is written into the mapped storage space, and carbon footprint tracking management is performed according to the two-dimensional code identifier and the updated period storage chain.

10. An electronic device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor executes the computer program to implement the steps of the product carbon footprint tracking method assisted by the two-dimensional code traceability of any one of claims 1-8.

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