System, method, device, and medium for hybrid carbon footprint data collection and calculation
The hybrid carbon footprint data collection and calculation model addresses the lack of unified data management by integrating automated and manual processes, improving accuracy and efficiency in carbon footprint measurement.
Patent Information
- Authority / Receiving Office
- WO · WO
- Patent Type
- Applications
- Current Assignee / Owner
- SIEMENS AG
- Filing Date
- 2025-01-27
- Publication Date
- 2026-07-30
AI Technical Summary
Traditional carbon footprint calculation systems lack a unified model to manage both automated and manual data collection and calculation, leading to inefficiencies and inaccuracies.
A hybrid model integrating automated and manual data collection and calculation processes through a system comprising a data source, collector, aggregator, validator, and server, ensuring seamless integration and improved accuracy and efficiency.
The hybrid model provides a unified framework for managing both types of data, enhancing the accuracy and efficiency of carbon footprint measurement.
Smart Images

Figure CN2025075479_30072026_PF_FP_ABST
Abstract
Description
System, Method, Device, and Medium for Hybrid Carbon Footprint Data Collection and CalculationTECHNICAL FIELD
[0001] The present disclosure relates to the technical field of environmental sustainability, in particular to a system, method, device, and medium for a hybrid carbon footprint data collection and calculation model.BACKGROUND
[0002] Traditional carbon footprint calculation systems rely on either manual input data or automated collected data. However, in most cases, the data sources are mixed with both types, and there is no unified model to manage the collection and calculation of these two types of data. This invention aims to address this limitation by providing a hybrid model that integrates both automated and manual data collection and calculation processes.SUMMARY
[0003] Embodiments of the present disclosure propose a system, method, device, and medium for a hybrid carbon footprint data collection and calculation model. The system comprises a data source, a collector, an aggregator, a validator, a calculator, and a server. The data source stores business data acquired through automation or manual operations. The collector collects data from the data source or manual input. The aggregator aggregates the collected data, the validator validates the aggregated data, and the calculator calculates emission data based on the validated data. The server generates the carbon footprint based on the calculated emission data or manual input. This invention provides a unified model for managing both automated and manual data collection and calculation, improving the accuracy and efficiency of carbon footprint measurement.BRIEF DESCRIPTION OF THE DRAWINGS
[0004] To make technical solutions of examples of the present disclosure clearer, accompanying drawings to be used in description of the examples will be simply introduced hereinafter. Obviously, the accompanying drawings to be described hereinafter are only some examples of the present disclosure. Those skilled in the art may obtain other drawings according to these accompanying drawings without creative labor.
[0005] Fig. 1: An exemplary schematic diagram of a system for hybrid carbon footprint data collection and calculation according to an embodiment of the present disclosure.
[0006] Fig. 2: An exemplary flowchart of a method for hybrid carbon footprint data collection and calculationaccording to an embodiment of the present disclosure.
[0007] Fig. 3: An exemplary structural diagram of an electronic device according to an embodiment of the present disclosure.
[0008] List of reference numbers: DETAILED DESCRIPTION
[0009] To make the purpose, technical scheme, and advantages of the disclosure clearer, the following examples are given to further explain the disclosure in detail. Nouns and pronouns related to people in this patent application are not limited to specific gender.
[0010] To be concise and intuitive in description, the scheme of the disclosure is described below by describing several representative embodiments. Many details in the embodiments are only used to help understand the scheme of the disclosure. However, it is obvious that the technical scheme of the disclosure can be realized without being limited to these details. To avoid unnecessarily blurring the scheme of the disclosure, some embodiments are not described in detail, but only the framework is given. Hereinafter, "including" refers to "including but not limited to" , "according to... " refers to "at least according to..., but not limited to... " . When the number of an element is not specifically indicated below, it means that the element can be one or more or can be understood as at least one. The terms "a" or "an" in this disclosure should not be understood as one, but as at least one.
[0011] Fig. 1 is an exemplary schematic diagram of a system for hybrid carbon footprint data collection and calculation according to an embodiment of the present disclosure. As shown in Figure 1, the system 100 includes a data source 101, a collector 102, an aggregator 103, a validator 104, a calculator 105, and a server 106. The data source stores business data acquired through automation or manual operations. The collector collects data from the data source or manual input. The aggregator aggregates the collected data, the validator validates the aggregated data, and the calculator calculates emission data based on the validated data. The server generates the carbon footprint based on the calculated emission data or manual input. This unified model ensures that both automated and manual data are seamlessly integrated into the carbon footprint calculation process, improving accuracy and efficiency.
[0012] In one embodiment, the data source 101 stores the business data generated by the business components or provided through user input. Receives business data from business components or user input. Provides necessary data to other system components on demand.
[0013] In one embodiment, the collector 102 collects carbon footprint-related data, such as production data and energy consumption data. Receives data from the data source or user input. Provides collected data, including production data, energy consumption data, and other carbon footprint-related data.
[0014] In one embodiment, the aggregator 103 performs basic aggregation on the collected data to prepare it for carbon footprint calculation. Receives data from the collector or user input. Provides aggregated data for further processing.
[0015] In one embodiment, the validator 104 validates the aggregated data to ensure its accuracy and reliability. Receives aggregated data from the aggregator or user input. Provides validated data for carbon footprint calculation.
[0016] In one embodiment, the calculator 105 calculates the carbon footprint based on the validated data. Receives validated data from the validator or user input. Provides emission values, which are used to determine the carbon footprint.
[0017] In one embodiment, the server 106 generates the final carbon footprint report based on the calculated emission values. Receives emission values from the calculator or user input values / offsets. Provides the carbon footprint report.
[0018] In one embodiment, the manual input allows users to supply raw business data, manually collected data, manually normalized data, manually aggregated data, manually validated data, manually calculated emission data or emission offsets, such as production data and energy consumption data.
[0019] Fig. 2 is an exemplary flowchart of a method for hybrid carbon footprint data collection and calculation according to an embodiment of the present disclosure. As shown in Figure 2, the method 200 involves the following steps.
[0020] Step 201, storing business data acquired through automation or manual operations in a data source.
[0021] In one embodiment, storing production data and energy consumption data in the data source. The data source stores business data acquired through automated processes or manual operations.
[0022] Step 202, collecting data from the data source or manual input using a collector.
[0023] In one embodiment, collecting production data and energy consumption data from the data source or manual input using the collector.
[0024] Step 203, aggregating the collected data using an aggregator.
[0025] In one embodiment, performing basic aggregation on the collected data to calculate carbon footprint using the aggregator.
[0026] Step 204, validating the aggregated data using a validator.
[0027] In one embodiment, validating the aggregated data to ensure data accuracy using the validator.
[0028] Step 205, calculating emission data based on the validated data using a calculator.
[0029] In one embodiment, calculating emission values based on the validated data using the calculator.
[0030] Step 206, generating the carbon footprint based on the calculated emission data or manual input using a server.
[0031] In one embodiment, generating the carbon footprint based on the calculated emission values or manual input values using the server.
[0032] In one embodiment, the unified data flow and calculation process, which integrates data collection, aggregation, validation, and calculation into a single, cohesive system. This algorithm ensures that data is processed consistently and accurately, leading to reliable carbon footprint assessments.
[0033] Embodiments of the present disclosure also propose an electronic device with a processor memory architecture. Fig. 3 is an exemplary structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in Figure 3, electronic device 300 includes a processor 310, a memory 320, and a computer program stored on memory 320 that can run on processor 310. When the computer program is executed by processor 310, the method as described in either of the above is implemented. Among them, memory 320 can be implemented as various storage media such as electrically erasable programmable read-only memory (EEPROM) , flash memory, programmable program read-only memory (PROM) , etc. Processor 310 can be implemented to include one or more central processors or one or more field programmable gate arrays, wherein the field programmable gate array integrates one or more central processor cores. Specifically, the central processing unit or core can be implemented as a CPU, MCU, DSP, and so on.
[0034] It should be noted that not all steps and modules in the above processes and structural diagrams are necessary, and some steps or modules can be ignored according to actual needs. The execution sequence of each step is not fixed and can be adjusted as needed. The division of each module is only for the convenience of describing the functional division used. In actual implementation, a module can be divided into multiple modules, and the functions of multiple modules can also be implemented by the same module. These modules can be in the same device or different devices.
[0035] The hardware modules in each implementation can be implemented mechanically or electronically. For example, a hardware module may include specially designed permanent circuits or logic devices (such as dedicated processors, such as FPGA or ASIC) to complete specific operations. Hardware modules can also include programmable logic devices or circuits temporarily configured by software (such as general-purpose processors or other programmable processors) for performing specific operations. As for the specific use of mechanical methods, either dedicated permanent circuits or temporarily configured circuits (such as software configuration) to implement hardware modules, it can be determined based on cost and time considerations.
[0036] The above is only a preferred embodiment of the present disclosure and is not intended to limit the scope of protection of the present disclosure. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of this disclosure shall be included within the scope of protection of this disclosure.
Claims
1.A system (100) for hybrid carbon footprint data collection and calculation, comprising:a data source (101) , configured to store business data acquired through automation or manual operations;a collector (102) , configured to collect data from the data source or manual input;an aggregator (103) , configured to aggregate the collected data;a validator (104) , configured to validate the aggregated data;a calculator (105) , configured to calculate emission data based on the validated data; anda server (106) , configured to generate the carbon footprint based on the calculated emission data or manual input.2.The system according to claim 1, wherein the data source is further configured to store production data and energy consumption data.3.The system according to claim 1, wherein the collector is further configured to collect production data and energy consumption data from the data source or manual input.4.The system according to claim 1, wherein the aggregator is further configured to perform basic aggregation on the collected data to calculate carbon footprint.5.The system according to claim 1, wherein the validator is further configured to validate the aggregated data to ensure data accuracy.6.The system according to claim 1, wherein the calculator is further configured to calculate emission values based on the validated data.7.The system according to claim 1, wherein the server is further configured to generate the carbon footprint based on the calculated emission values or manual input values.8.A method (200) for hybrid carbon footprint data collection and calculation, the method comprising:storing (S201) business data acquired through automation or manual operations in a data source;collecting (S202) data from the data source or manual input using a collector;aggregating (S203) the collected data using an aggregator;validating (S204) the aggregated data using a validator;calculating (S205) emission data based on the validated data using a calculator; andgenerating (S206) the carbon footprint based on the calculated emission data or manual input using a server.9.The method according to claim 8, further comprising storing production data and energy consumption data in the data source.10.The method according to claim 8, further comprising collecting production data and energy consumption data from the data source or manual input using the collector.11.The method according to claim 8, further comprising performing basic aggregation on the collected data to calculate carbon footprint using the aggregator.12.The method according to claim 8, further comprising validating the aggregated data to ensure data accuracy using the validator.13.The method according to claim 8, further comprising calculating emission values based on the validated data using the calculator.14.The method according to claim 8, further comprising generating the carbon footprint based on the calculated emission values or manual input values using the server.15.An electronic device, comprising a processor and a memory, wherein an application program executable by the processor is stored in the memory for causing the processor to execute a method for hybrid carbon footprint data collection and calculation according to any one of claims 8-14.16.A computer-readable medium comprising computer-readable instructions stored thereon, wherein the computer-readable instructions for executing a method for hybrid carbon footprint data collection and calculation according to any one of claims 8-14.17.A computer program product comprising a computer program, upon the computer program is executed by a processor for executing a method for hybrid carbon footprint data collection and calculation according to any one of claims 8-14.