Method and system for determining carbon footprint of product, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a method and system for determining a product carbon footprint (PCF), electronic equipment and a storage medium. The method comprises the following steps: receiving a PCF query request containing description information of a product; comparing the description information with an index of a PCF stored in a PCF database; when the comparison result is that the description information is matched with the PCF database, inquiring the PCF in the PCF database based on the description information; when the comparison result is that the PCF query request is not matched with the description information, the PCF query request is sent to a calculation engine, and the calculation engine calculates the PCF based on the description information. According to the embodiment of the invention, the PCF is uniformly obtained in various modes. When the PCF is directly obtained based on retrieval of the PCF database, the response speed can be increased; when the PCF is calculated based on the calculation engine, the defect that the data volume of the PCF database is insufficient can be overcome. The user does not need to pay attention to where the details of the PCF are obtained, and the difficulty of determining the PCF by the user is reduced.

Description

Method, system, electronic device and storage medium for determining product carbon footprint Technical Field

[0001] The present invention relates to the technical field of Product Carbon Footprint (PCF), and in particular to a method, system, electronic device, and storage medium for determining PCF. Background Art

[0002] PCF refers to the greenhouse gas emissions generated throughout a product's life cycle, from raw material extraction, manufacturing, transportation, distribution, use, to final disposal. PCF has become increasingly important due to growing concerns about global climate change.

[0003] Currently, obtaining the PCF for a specific product is often difficult. One reason is that the PCF calculation process is complex and requires covering the entire product lifecycle, from raw material production to end-of-life. Another reason is that raw materials, processing methods, shapes and volumes, and suppliers often vary significantly between products, resulting in a unique PCF for each product.

[0004] Summary of the Invention

[0005] The embodiments of the present invention provide a method, system, electronic device and storage medium for determining PCF.

[0006] In a first aspect, a method for determining a PCF is provided, comprising:

[0007] Receive a PCF query request containing product description information;

[0008] Comparing the description information with the index of the PCF stored in the PCF database;

[0009] When the comparison result is a match, the PCF is queried in the PCF database based on the description information; when the comparison result is a mismatch, the PCF query request is sent to a calculation engine, where the calculation engine calculates the PCF based on the description information.

[0010] In a second aspect, a system for determining a PCF is provided, comprising:

[0011] An application programming interface (API) configured to receive a PCF query request including product description information;

[0012] a comparison module configured to compare the description information with an index of a PCF stored in a PCF database;

[0013] a calculation engine configured to provide a PCF calculated based on the description information when the comparison result is a mismatch;

[0014] The PCF database is configured to provide a PCF queried based on the description information when the comparison result is a match.

[0015] According to a third aspect, an electronic device is provided, including:

[0016] processor;

[0017] a memory for storing executable instructions of the processor;

[0018] The processor is configured to read the executable instructions from the memory and execute the executable instructions to implement the above method for determining the PCF.

[0019] In a fourth aspect, a computer-readable storage medium is provided, on which computer instructions are stored. When the computer instructions are executed by a processor, the method for determining the PCF as described above is implemented.

[0020] In a fifth aspect, a computer program product is provided, comprising a computer program, which implements the above method for determining PCF when executed by a processor.

[0021] As can be seen, the embodiments of the present invention uniformly acquire PCFs in multiple ways. Directly acquiring PCFs by searching a PCF database improves response speed. Calculating PCFs using a computational engine overcomes the limited data available in PCF databases. Furthermore, users do not need to worry about the details of where to obtain PCFs, reducing the difficulty of determining PCFs. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings, so that those skilled in the art will understand the above and other features and advantages of the present invention more clearly. In the accompanying drawings:

[0023] FIG1 is an exemplary flow chart of a method for determining a PCF according to an embodiment of the present invention.

[0024] FIG2 is an exemplary structural diagram of a system for determining PCF according to an embodiment of the present invention.

[0025] FIG3 is an exemplary schematic diagram of an API according to an embodiment of the present invention.

[0026] FIG. 4 is an exemplary diagram of a comparison module processing procedure according to an embodiment of the present invention.

[0027] FIG5 is an exemplary schematic diagram of a server according to an embodiment of the present invention.

[0028] FIG6 is an exemplary structural diagram of an electronic device according to an embodiment of the present invention.

[0029] The accompanying drawings are numerals as follows:

[0030]

[0031] DETAILED DESCRIPTION

[0032] In order to make the purpose, technical solutions and advantages of the present invention more clear, the present invention is further described in detail with reference to the following examples.

[0033] For the sake of brevity and intuitiveness in description, the solution of the present invention is explained below by describing several representative implementations. A large number of details in the implementations are only used to help understand the solution of the present invention. However, it is obvious that the technical solution of the present invention may not be limited to these details when implemented. In order to avoid unnecessarily obscuring the solution of the present invention, some implementations are not described in detail, but only a framework is given. Hereinafter, "including" means "including but not limited to", and "according to..." means "at least according to..., but not limited to only according to...". Due to the language habits of Chinese, when the number of a component is not specifically specified below, it means that the component can be one or more, or can be understood as at least one.

[0034] The applicant has found that in the prior art, there are currently two types of PCF databases, including:

[0035] (1) High-level databases: These can also be called ready-to-use databases, which are used to store collections of calculated PCFs. Typical examples of high-level databases include: IPCC Emission Factor Database (https: / / www.ipcc-nggip.iges.or.jp / EFDB / main.php); UK Conversion Factors (https: / / www.gov.uk / government / publications / greenhouse-gas-reporting-conversion-factors-2021); CEADs Database (https: / / www.ceads.net / ), etc. These high-level databases provide a large number of calculated PCFs, making it easy for users to quickly query PCFs. However, compared with the products actually used, the number of PCFs that these high-level databases can provide is still small.

[0036] (2) Low-level databases: They do not provide ready-made PCFs, but serve as building blocks for calculating PCFs. Typical examples of low-level databases include: GaBi database (https: / / gabi.sphera.com / databases / gabi-databases / ); Ecoinvent database (https: / / ecoinvent.org / the-ecoinvent-database / ), etc. Low-level databases can be imported into life cycle assessment (LCA) modeling tools and then used as metadata for PCF calculations. These low-level databases have an overwhelming advantage in the amount of data input because the data granularity is finer than that of the final product. However, calculating PCFs usually takes time, so the response speed of low-level databases is slower than that of high-level databases.

[0037] In the embodiment of the present invention, a technical solution is provided that can uniformly access the above two types of PCF databases, which can not only provide a large number of PCFs but also improve the response speed.

[0038] FIG1 is an exemplary flow chart of a method for determining a PCF according to an embodiment of the present invention.

[0039] As shown in FIG1 , the method includes:

[0040] Step 101: Receive a PCF query request containing product description information.

[0041] Here, a PCF query request triggered by a user can be received via a human-computer interaction interface. The PCF query request contains description information of the product. The description information can be the shape description information of the product (such as: block, plate, pile, etc.), component description information (such as copper, iron, aluminum, etc.) or structure description information (such as the engine of a car, the chassis of a car, the body of a car, etc.). Moreover, the description information can also include the processing process of the product, such as the material mining process, the manufacturing process, the transportation process, the distribution process, the use process or the disposal process, etc. For example, the description information of the product can be: "Aluminum Block Production in Shandong, China", "Eraser Production in Fujian, China" or "Pencil Case Transportation in Henan, China", etc.

[0042] Step 102: Compare the description information with the index of the PCF stored in the PCF database; when the comparison result is a match (corresponding to the "Y branch"), execute step 103; when the comparison result is a mismatch (corresponding to the "N branch"), execute step 104.

[0043] An index is a storage structure that sorts the stored PCFs in the PCF database. For example, the index can be implemented as the key of a key-value pair in the PCF database. The description information can be sent to the PCF database, and the description information can be compared with the index of the stored PCF in the PCF database. In another embodiment, the index of the stored PCF in the PCF database can be synchronously saved to a third party (for example, a high-level application of the PCF database), and the comparison process of the description information and the index is performed in the third party. The comparison process can adopt an exact matching method or a simulated matching method. Regardless of the matching method, when the comparison result of the description information and the index is a match, step 103 is executed; when the comparison result of the description information and the index is a mismatch, step 104 is executed.

[0044] In one embodiment, comparing the description information with an index of PCFs stored in the PCF database includes: extracting at least one keyword from the description information; assigning a weight to the at least one keyword; and comparing the at least one keyword and its weight with an index of PCFs stored in the PCF database using a fuzzy matching method. This weighted fuzzy matching method enables intelligent search.

[0045] Fuzzy matching can be implemented using an elastic fuzzy matching engine (e.g., https: / / www.elastic.co / ). The search strategy can employ prioritizing clauses based on multiple queries. For example, assuming the search information includes "aluminum production in China," different weights can be assigned to different keywords in the search information. For example, "aluminum" has a weight of 3; "production" has a weight of 2; and "China" has a weight of 1. Therefore, "aluminum" has a greater impact on the search results than "production" and "China," and "production" has a greater impact on the search results than "China." Based on the fuzzy matching results, a match result is generated with the index, and a confidence score normalized to the range (0, 1) is generated for each match result. A threshold value for the confidence score can be set (e.g., 0.6). When the confidence score of an index is greater than or equal to the threshold value, the index is considered a match with the search information. When the confidence score of an index is less than the threshold value, the index is considered a mismatch. Otherwise, the PCF is calculated using the calculation engine.

[0046] Step 103: Query the PCF in the PCF database based on the description information and exit this process.

[0047] Here, it has been determined in step 102 that a matching index exists, so the corresponding PCF is directly retrieved from the PCF database.

[0048] In one embodiment, the PCF database is a key-value database, and querying the PCF in the PCF database based on the description information includes: using the description information as a key, querying the PCF database for a value corresponding to the key; and determining the value as the PCF.

[0049] Step 104: Send the PCF query request to the calculation engine, where the calculation engine calculates the PCF based on the description information and exits this process.

[0050] Here, it has been determined in step 102 that there is no matching index in the PCF database, so the calculation engine is called to calculate the PCF based on the description information.

[0051] In one embodiment, the PCF query request further includes authentication information; the method further includes: authenticating the PCF query request based on the authentication information.

[0052] Authentication is the credential that determines whether to execute a PCF query request. Various methods can be used to implement authentication. For example, authentication methods may include: Basic authentication based on the Hypertext Transfer Protocol (HTTP); token authentication; combined session and cookie authentication; OAuth authentication, and so on.

[0053] Let's take OAuth authentication as an example. You can choose OAuth2 (https: / / oauth.net / 2 / ) to handle authentication and authorization specifications. A user registers for a service using a username and corresponding password. After successful registration, the user is provided with a random access token (for example, "2YotnFZFEjr1zCsicMWpAA"), which can be appended to the query URL as a suffix and used as a credential for headless API calls (with batch processing).

[0054] The above exemplary description is of a typical embodiment of authenticating a PCF query request. Those skilled in the art will appreciate that this description is merely exemplary and is not intended to limit the scope of protection of the embodiments of the present invention.

[0055] As can be seen, the embodiments of the present invention uniformly acquire PCFs in multiple ways. Directly acquiring PCFs by searching a PCF database improves response speed. Calculating PCFs using a computational engine overcomes the limited data available in PCF databases. Furthermore, users do not need to worry about the details of where to obtain PCFs, reducing the difficulty of determining PCFs.

[0056] In one embodiment, before comparing the description information with the index of the PCF stored in the PCF database, the method further includes: sorting information fields in the historical description information that have the same information field attributes; determining recommended information fields for each information field attribute based on the sorting results; and, if the description information does not contain the information field attribute, supplementing the description information with the recommended information field for the information field attribute. Therefore, supplementing the description information with historical description information can enrich the content of the description information and facilitate rapid and accurate PCF determination.

[0057] For example, assume that the description information contains four information field attributes by default, namely material, process, location, and shape. By querying the historical records of PCF query requests, all historical description information is obtained. The information fields of each information field attribute in all historical description information are sorted (for example, sorted by the number of occurrences or frequency of occurrence, etc.) to determine the recommended information fields. For example: (1) for material attributes, the most frequently occurring information field is "aluminum"; (2) for process attributes, the most frequently occurring information field is "production"; (3) for location attributes, the most frequently occurring information field is "Shandong, China"; (4) for shape attributes, the most frequently occurring information field is "block". Therefore, "aluminum" can be determined as the recommended information field for material attributes, "casting" can be determined as the recommended information field for process attributes, "Shandong, China" can be determined as the recommended information field for location attributes, and "block" can be determined as the recommended information field for shape attributes.

[0058] For example, if the description information received in step 101 is "aluminum sheet casting," after parsing the description information, it is found that the location attribute is missing. The recommended information field "Shandong, China" for the location attribute is added to "aluminum sheet casting" to form a new description information: "Aluminum sheet casting, Shandong, China." The new description information can then be used to perform subsequent operations.

[0059] For example, if the description information received in step 101 is "copper," it is found that the process attribute, location attribute, and shape attribute are missing. The recommended information field "production" for the process attribute, "Shandong, China" for the location attribute, and "block" for the shape attribute are added to "copper" to form a new description information: "Copper Block Production, Shandong, China." Subsequent operations can then be performed using this new description information.

[0060] The above description is made by taking the example of the description information including four information field attributes. In fact, the number and types of information field attributes can be adjusted, and the embodiments of the present invention have no limitation on this.

[0061] In one embodiment, the method further includes: receiving first configuration information, where the first configuration information is used to configure a display mode of the PCF; and displaying the PCF based on the display mode.

[0062] For example, input information provided by the user can be received on the human-computer interaction interface. The input information includes description information and first configuration information. Exemplarily, the input information includes the following information items:

[0063] (1) Description: This field must be filled in to indicate the product the user is looking for. In practice, it can be a raw material (such as aluminum) or a product (such as an inductor).

[0064] (2) Only field: optional, data type is Boolean, default value is true, indicating whether the PCF corresponding to the description information contains only one item.

[0065] (3) Upstream emissions: optional, data type is Boolean, default value is true, indicating whether to return the upstream emission value of the product.

[0066] (4) Downstream emissions: optional, data type is Boolean, default value is false, indicating whether to return the downstream emission value of the product.

[0067] (5) Emission Process: Optional, data type is Boolean, default value is false, indicating whether to return the detailed emission process that constitutes upstream emissions or downstream emissions.

[0068] (6)GHG percentage: optional, data type is Boolean value, default value is false, indicating whether to return detailed values ​​of greenhouse gas emissions.

[0069] (7) Year: Optional, data type is Boolean, default value is false, indicating the timestamp of data input.

[0070] (8) Uncertainty: Optional, data type is Boolean, default value is false, indicating uncertainty assessment of data input.

[0071] (9) Data source: optional, data type is Boolean value, default value is false, indicating the data source.

[0072] Based on the above information items (2) to (9), it is possible to configure whether to display the corresponding information in the PCF, thereby achieving a personalized configurable display effect.

[0073] The above exemplary descriptions are typical examples of the first configuration information. Those skilled in the art will appreciate that such descriptions are merely exemplary and are not intended to limit the scope of protection of the embodiments of the present invention.

[0074] In one embodiment, step 104 includes: using the descriptive information as a search term, searching the life cycle inventory database for a corresponding life cycle inventory; and, based on the life cycle inventory, invoking a life cycle assessment modeling tool to calculate the PCF. The life cycle inventory includes a rich set of attributes related to the search term, such as time, location, energy type (e.g., wind power vs. thermal power), and processing attributes (e.g., submerged arc welding vs. free-gas welding). The life cycle inventory also includes product input data (e.g., the number and type of raw materials required to produce the product) and product output data (e.g., the type and number of products).

[0075] Preferably, it also includes: receiving second configuration information, the second configuration information is used to configure the PCF calculation method in the life cycle assessment modeling tool; based on the life cycle inventory, calling the life cycle assessment modeling tool to calculate PCF includes: configuring the PCF calculation method in the life cycle assessment modeling tool based on the second configuration information; based on the life cycle inventory, calling the configured life cycle assessment modeling tool to calculate PCF.

[0076] In one embodiment, the PCF calculation method includes a calculation specification and / or a calculation type. For example, the calculation specification may include: IPCC 2013 no LT, IPCC 2013, CML V4.8 2016 no LT, CML V4.8 2016, ReCiPe Midpoint(i), ReCiPe Endpoint(E,A), etc. The calculation type may include at least one of the following: simple calculation; contribution calculation; upstream analysis calculation; regionalized calculation; Monte Carlo simulation, etc. Preferably, the PCF calculation method may also include geographic location information. When the description information does not include the geographic location, the geographic location information is automatically filled into the description information, thereby enriching the description information in terms of geographic latitude. For example, the geographic location information has a default value: China. When the description information does not include the geographic location, "China" is automatically filled into the description information.

[0077] For example, the second configuration information may be provided by the user on the human-computer interaction interface. The second configuration information may include:

[0078] (1) Process: This parameter is optional and has a string data type. It indicates the processing method of the product, such as raw material production, die casting, or injection molding. The reason for setting it as optional is that users may not know the detailed process in the product life cycle. If the user leaves it blank, the most likely process can be automatically filled in for this parameter.

[0079] (2) Shape: Similar to process parameters, it indicates the shape of the product, such as plate, rod, ingot, etc.

[0080] (3) Location: Optional, the data type is enumeration, which means that the user can only set the parameter to a limited number of candidate objects, such as China, Europe, the United States, and other regions.

[0081] (4) Calculation Specification: Optional, enumeration data type. The calculation specification parameter makes the calculation engine API more flexible than the previous product API. It provides the underlying calculation engine with many calculation methods to call to calculate PCF, such as IPCC or CML, etc. Therefore, the engine can return different PCF values ​​based on the settings here.

[0082] (5) Calculation type: Optional, data type is enumeration. It indicates the type of calculation to be performed by the calculation engine. The default selection is simple calculation, but it provides the freedom to perform complex calculations, such as Monte Carlo simulations.

[0083] (6) Quantity: Optional, data type is floating point number. It represents the target quantity for calculation. In most cases, only the unit is calculated, that is, the carbon emissions of 1 kg of product are calculated. However, this parameter provides the freedom to set other target values.

[0084] The above exemplary descriptions are typical examples of the second configuration information. Those skilled in the art will appreciate that such descriptions are merely exemplary and are not intended to limit the scope of protection of the embodiments of the present invention.

[0085] The process shown in Figure 1 can be implemented as a complete API service. The API service combines different types of databases and has at least the following advantages: (1) PCF can be accessed from a single API call, eliminating the need for multiple searches. (2) The API service is powerful. When calculating PCF based on the calculation engine, it can overcome the shortcomings of insufficient data in the PCF database. When directly obtaining PCF based on searching the PCF database, it can improve response speed. Moreover, users do not need to worry about the details of where to obtain PCF, which reduces the difficulty of determining PCF. (3) The API service can be seamlessly integrated into third-party platforms or software with multiple data resources.

[0086] FIG2 is a diagram showing a system structure for determining PCF according to an embodiment of the present invention. As shown in FIG2 , the system includes:

[0087] API 21 is configured to receive a PCF query request containing product description information from user 20;

[0088] a comparison module 22 configured to compare the description information with an index of a PCF stored in a PCF database;

[0089] The server 23 includes a PCF database 231 and a calculation engine 232. The server 23 is configured to query the PCF in the PCF database 231 based on the description information when the comparison result of the comparison module 22 is a match, and send a PCF query request to the calculation engine 232 when the comparison result is a mismatch, wherein the calculation engine 232 calculates the PCF based on the description information.

[0090] The calculation engine 232 is configured to provide a PCF calculated based on the description information when the comparison result is a mismatch; the PCF database 231 is configured to provide a PCF queried based on the description information when the comparison result is a match.

[0091] In one embodiment, the calculation engine 232 includes: a life cycle inventory database configured to provide a life cycle inventory corresponding to the description information; and a life cycle assessment modeling tool configured to calculate the PCF based on the life cycle inventory.

[0092] For example, if the description is "aluminum sheet production in Shandong, China," the life cycle inventory represents the production process of aluminum sheet in Shandong, China. Based on this production process, the life cycle assessment modeling tool can create a virtual model of aluminum sheet production in Shandong, China, and output the PCF for aluminum sheet production in Shandong, China based on the virtual model.

[0093] FIG3 is an exemplary schematic diagram of an API according to an embodiment of the present invention. As shown in FIG3 , API 21 has an authentication process 211 and a RESTful interaction process 212. Whether to execute a PCF query request is determined based on the authentication process 211. In the RESTful interaction process 212, the following interaction processes can be executed: (1) obtaining a product catalog 30 from the PCF database; (2) obtaining a PCF 31 from the PCF database; (3) obtaining a product catalog 32 from the calculation engine; (4) obtaining product introduction information 33 from the calculation engine; (4) obtaining the PCF calculated by the calculation engine.

[0094] FIG4 is an exemplary schematic diagram of the comparison module processing process according to an embodiment of the present invention. The comparison module processing process specifically includes:

[0095] Step 40: Receive a PCF query request containing product description information.

[0096] Step 41: Compare the description information with the index of the stored PCF in the PCF database. Here, the index of the stored PCF in the PCF database can be stored locally in the comparison module, thereby enabling the comparison of the description information with the index in the comparison module. Alternatively, the comparison module can send the description information to the PCF database via an interface with the PCF database, thereby enabling the comparison of the description information with the index in the PCF database.

[0097] Step 42: Score the comparison results.

[0098] Here, a matching result with the index is generated, and a confidence score normalized to the range (0, 1) is generated for the matching result.

[0099] Step 43: Determine whether the score exceeds a preset threshold value. If yes (corresponding to “Y branch”), execute step 44; if no (corresponding to “N branch”), execute step 45.

[0100] Step 44: Routing the PCF query request to the PCF database in the server 23, thereby querying the PCF in the PCF database based on the description information in the PCF query request, and ending this process.

[0101] Step 45: Routing the PCF query request to the calculation engine in the server 23, so that the calculation engine calculates the PCF based on the description information in the PCF query request, and ending this process.

[0102] Figure 5 is an exemplary schematic diagram of a server according to an embodiment of the present invention. In Figure 5, server 23 includes a PCF database 231 and a computing engine 232. Computing engine 232 includes a life cycle inventory database 51 and a life cycle assessment modeling tool 52. For example, life cycle inventory database 51 can be implemented as the Ecoinvent database (https: / / ecoinvent.org / the-ecoinvent-database / ); life cycle assessment modeling tool 52 can be implemented as OpenLCA (https: / / www.openlca.org / ) or Brightway2 (https: / / brightway.dev / ), etc.

[0103] When the PCF database 231 receives the PCF query request, it uses the description information in the PCF query request as a key to query the value corresponding to the key in the PCF database 231, and the value is PCF70.

[0104] When calculation engine 232 receives a PCF query request, it executes PCF calculation process 50. In PCF calculation process 50, the following steps are performed: First, the life cycle inventory (LCI) corresponding to the search term (e.g., a product's process) is searched in LCI database 51, using the descriptive information as the search term. Then, the life cycle assessment modeling tool 52 creates a virtual model corresponding to the LCI based on the LCI and runs the virtual model to calculate PCF 70.

[0105] The embodiment of the present invention further provides an electronic device having a processor-memory architecture. FIG6 is an exemplary structural diagram of an electronic device having a processor-memory architecture according to an embodiment of the present invention.

[0106] As shown in Figure 6, the electronic device 600 includes a processor 601, a memory 602, and a computer program stored in the memory 602 and executable on the processor 601. When the computer program is executed by the processor 601, any of the above methods for determining the PCF is implemented. Among them, the memory 602 can be specifically implemented as a variety of storage media such as an electrically erasable programmable read-only memory (EEPROM), a flash memory (Flash memory), and a programmable read-only memory (PROM). The processor 601 can be implemented to include one or more central processing units or one or more field programmable gate arrays, wherein the field programmable gate array integrates one or more central processing unit cores. Specifically, the central processing unit or the central processing unit core can be implemented as a CPU, an MCU, or a DSP, etc.

[0107] It should be noted that not all steps and modules in the above processes and structure diagrams are required, and certain steps or modules can be omitted based on actual needs. The execution order of the steps is not fixed and can be adjusted as needed. The division of the modules is merely for the convenience of describing the functional division adopted. In actual implementation, a module can be implemented by multiple modules, and the functions of multiple modules can be implemented by the same module. These modules can be located in the same device or in different devices.

[0108] The hardware modules in each embodiment can be implemented mechanically or electronically. For example, a hardware module may include a specially designed permanent circuit or logic device (such as a dedicated processor, such as an FPGA or ASIC) for performing a specific operation. The hardware module may also include a programmable logic device or circuit (such as a general-purpose processor or other programmable processor) temporarily configured by software to perform a specific operation. As for whether to implement the hardware module mechanically, or using a dedicated permanent circuit, or using a temporarily configured circuit (such as configured by software), it can be decided based on cost and time considerations.

[0109] The above description is only a preferred embodiment of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included in the scope of protection of the present invention.

Claims

1. A method for determining the PCF of a product, characterized in that: include: Receiving (101) a PCF query request containing product description information; Comparing the description information with the index of the stored PCF in the PCF database (102); When the comparison result is a match, the PCF is queried (103) in the PCF database based on the description information; when the comparison result is a mismatch, the PCF query request is sent (104) to a calculation engine, wherein the calculation engine calculates the PCF based on the description information.

2. The method according to claim 1, characterized in that Before comparing the description information with the index of the PCF stored in the PCF database (102), the method further includes: Obtain historical description information of the product included in the PCF historical query request; sorting the information fields having the same information field attributes in the historical description information; Based on the ranking results, determine the recommended information fields for each information field attribute; When the description information does not include the information field attribute, the recommended information field of the information field attribute is added to the description information.

3. The method according to claim 1, characterized in that Comparing the description information with the index of the PCF stored in the PCF database includes: Parsing at least one keyword from the description information; assigning a weight to the at least one keyword; Based on the at least one keyword and its weight, a comparison is made with an index of a PCF stored in a PCF database in a fuzzy matching manner.

4. The method according to claim 1, wherein The PCF database is a key-value database, and querying the PCF in the PCF database based on the description information includes: Using the description information as a key, query the PCF database for a value corresponding to the key; The value is determined as the PCF.

5. The method according to claim 1, wherein After querying the PCF in the PCF database based on the description information or the calculation engine calculating the PCF based on the description information, the method further includes: receiving first configuration information, where the first configuration information is used to configure a display mode of the PCF; Based on the display method, the PCF is displayed.

6. The method according to claim 1, wherein Calculating the PCF based on the description information includes: Using the description information as a search term, searching a life cycle inventory database for a life cycle inventory corresponding to the search term; Based on the life cycle inventory, a life cycle assessment modeling tool is called to calculate the PCF.

7. The method according to claim 6, characterized in that Before calling the life cycle assessment modeling tool to calculate the PCF, the method further includes: receiving second configuration information, where the second configuration information is used to configure a PCF calculation method in the life cycle assessment modeling tool; The calculating of the PCF by calling a life cycle assessment modeling tool based on the life cycle inventory includes: Based on the second configuration information, configure a PCF calculation method in the life cycle assessment modeling tool; Based on the life cycle inventory, the configured life cycle assessment modeling tool is called to calculate the PCF.

8. The method according to claim 7, characterized in that The PCF calculation method includes calculation specifications and / or calculation types; The calculation type includes at least one of the following: Simple calculation; contribution calculation; upstream analysis calculation; regionalized calculation; Monte Carlo simulation.

9. The method according to any one of claims 1 to 8, characterized in that The PCF query request further includes authentication information; the method further includes: The PCF query request is authenticated based on the authentication information.

10. A system for determining PCF, characterized in that include: An application program interface (21) configured to receive a PCF query request containing product description information; a comparison module (22) configured to compare the description information with an index of a PCF stored in a PCF database; A calculation engine (232) configured to provide a PCF calculated based on the description information when the comparison result is a mismatch; The PCF database (231) is configured to provide a PCF queried based on the description information when the comparison result is a match.

11. The system according to claim 10, wherein: The computing engine (232) includes: A life cycle inventory database (51) is configured to determine a life cycle inventory corresponding to the description information; A life cycle assessment modeling tool (52) is configured to calculate the PCF based on the life cycle inventory.

12. An electronic device, characterized in that: include: Processor (601); a memory (602) for storing executable instructions of the processor (601); The processor (601) is configured to read the executable instructions from the memory (602) and execute the executable instructions to implement the method for determining the PCF according to any one of claims 1 to 9.

13. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the computer instructions are executed by a processor, the method for determining PCF according to any one of claims 1 to 9 is implemented.

14. A computer program product, characterized in that The invention comprises a computer program, which, when executed by a processor, implements the method for determining PCF according to any one of claims 1 to 9.

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