Inventory carbon footprint real-time tracking and early warning system based on dynamic weighing

Abstract

This invention belongs to the field of intelligent management technology and discloses a real-time inventory carbon footprint tracking and early warning system based on dynamic weighing. It includes: a dynamic weighing module: collecting raw weight signals and ambient temperature and analyzing them to obtain real-time weight values; determining the start and end of weighing events; an identification management module: assigning material object identifiers; a fingerprint establishment module: generating corresponding carbon fingerprints by combining real-time weight values ​​and material information; a perception triggering module: calculating the net weight change of each weighing event, confirming the event type based on business scenarios and net weight changes, and performing batch association based on carbon fingerprints; a footprint analysis module: tracking carbon footprints based on weighing events, net weight changes, and carbon fingerprints to obtain the current total inventory carbon footprint and carbon footprint log; and a tracking and early warning module: performing footprint analysis based on the carbon footprint log and providing tiered early warnings based on the analysis results. This invention achieves accurate quantification of carbon emissions throughout the entire lifecycle of each batch of materials.

Description

Technical Field

[0001] This invention relates to the field of intelligent management technology, and more specifically, to a real-time tracking and early warning system for inventory carbon footprint based on dynamic weighing. Background Technology

[0002] In existing inventory carbon footprint management, the lack of a unified and resolvable IoT identification system for entities such as materials, batches, and equipment makes it difficult to efficiently connect and exchange carbon footprint data with upstream and downstream supply chains, IoT devices, and external carbon accounting platforms, thus restricting the interconnectivity and end-to-end traceability of carbon footprint data. Carbon footprint data accounting generally relies on a fixed average emission factor, which is often set based on industry-standard data or historical statistics, failing to consider the inherent differences in raw material composition, production processes, supplier capacity, and transportation methods across the entire lifecycle of different batches of materials. This results in all batches of the same type of material being calculated using the same emission factor, failing to reflect the differences in carbon emission levels between batches. Furthermore, existing solutions lack a precise correlation mechanism between material batches and carbon emission data. Records of events throughout the entire lifecycle of materials, such as warehousing, storage, and losses, are disconnected from carbon emission accounting data, making it impossible to accurately match specific carbon emission values ​​to individual material batches. The aforementioned issues directly result in inventory carbon footprint data remaining at a coarse level at the material type level, making it difficult to refine to the batch level. Consequently, it is impossible to accurately capture the actual carbon emission characteristics of each batch of materials throughout the entire process from warehousing and storage to outbound delivery, and it is impossible to provide enterprises with accurate data support for the carbon emissions of a single batch of materials, thus restricting the accuracy and effectiveness of carbon footprint management.

[0003] In view of this, the present invention proposes a real-time inventory carbon footprint tracking and early warning system based on dynamic weighing to solve the above problems. Summary of the Invention

[0004] To overcome the aforementioned deficiencies of the prior art and to achieve the above objectives, the present invention provides the following technical solution: a real-time inventory carbon footprint tracking and early warning system based on dynamic weighing, comprising:

[0005] Dynamic weighing module: Collects raw weight signal and ambient temperature, corrects the raw weight signal based on ambient temperature to obtain real-time weight value; calculates instantaneous weight change rate based on real-time weight value, and determines the start and end of weighing event based on instantaneous weight change rate;

[0006] The identification management module assigns a material object identifier that conforms to the unified item coding standard for the Internet of Things to each type of stored material;

[0007] Fingerprint generation module: Generates a carbon fingerprint for each stored material based on the material object identifier, combined with real-time weight value and material information;

[0008] The perception trigger module calculates the net weight change for each weighing event, confirms the event type by combining the business scenario and the net weight change, and performs batch association based on the event type and carbon fingerprint.

[0009] Footprint Analysis Module: Based on weighing events and their corresponding net weight changes, as well as carbon fingerprints, carbon footprint is tracked to obtain the current total carbon footprint and carbon footprint transaction log.

[0010] Tracking and Early Warning Module: Performs footprint analysis based on carbon footprint logs and issues tiered early warnings based on the analysis results.

[0011] Furthermore, methods for assigning material object identifiers conforming to the IoT unified item coding standard to each type of stored material include:

[0012] When materials are received into the warehouse, the corresponding additional information is obtained. The additional information includes material type, batch number, warehouse receipt time, supplier name, country of origin, transportation method and transportation distance. A unique identification code that conforms to the unified item coding standard of the Internet of Things is assigned to the material as a material object identifier. A supplier ID based on the object identifier system is assigned to the supplier.

[0013] Methods for generating carbon fingerprints for each type of storage material include:

[0014] The carbon emission factor is calculated based on the real-time weight value;

[0015] Combine the material object identifier, batch number, warehousing time, carbon emission factor, supplier ID, country of origin, transportation method and transportation distance to obtain the carbon fingerprint corresponding to the material;

[0016] The generated carbon fingerprint is associated with the corresponding material batch number and stored in the batch inventory table; when a weighing event is detected, the batch inventory table is updated.

[0017] Furthermore, methods for obtaining carbon emission factors include:

[0018] A carbon accounting unit is set up to collect the real-time weight value of a single carbon-containing raw material, as well as the volume or mass data of non-solid raw materials, energy consumption data, the real-time weight value of qualified exported products, the real-time weight value of solid waste, and the dry basis volume fraction of carbon dioxide and flue gas flow rate; among which, the energy consumption data includes electricity consumption, natural gas consumption and steam consumption.

[0019] Based on the collected data, the total input material weight, cumulative energy consumption, cumulative weight of qualified products, waste weight, and carbon dioxide mass in flue gas are calculated. The total input material weight, cumulative weight of qualified products, and waste weight are verified. If the verification is successful, the dynamic carbon emission factor is calculated based on the verified data; otherwise, the equipment is recalibrated.

[0020] The mean and standard deviation of dynamic carbon emission factors are statistically analyzed. Using statistical process control methods, the upper and lower control limits of dynamic carbon emission factors are set as the sum and difference of the mean and three times the standard deviation of the dynamic carbon emission factors, respectively. Dynamic carbon emission factors that exceed the upper and lower control limits are eliminated to obtain effective carbon emission factors.

[0021] The carbon emission factor is obtained by averaging the effective carbon emission factors over N consecutive periods.

[0022] Furthermore, the verification methods based on the total input material weight, the cumulative weight of qualified products, and the waste weight include:

[0023] The real-time weight values ​​of a single carbon-containing raw material after calibration are periodically integrated and accumulated to obtain the cumulative input amount of the single raw material. Then, the cumulative input amount of the single raw material is accumulated by the raw material integral to obtain the total input material weight.

[0024] The real-time weight values ​​of the calibrated products and solid waste are periodically integrated and accumulated to obtain the cumulative weight of qualified products and the weight of waste.

[0025] The mass of carbon dioxide in the flue gas is obtained by calculating the dry volume fraction of carbon dioxide and the flue gas flow rate, and by periodically integrating and summing the results.

[0026] Verify that the total weight of input materials is the sum of the cumulative weight of qualified products, the weight of waste, and the amount of process loss. If yes, the material balance is determined and the verification is passed. If no, the equipment is recalibrated.

[0027] Furthermore, methods for calculating dynamic carbon emission factors based on validated data include:

[0028] The fixed carbon emissions of the product are calculated based on the cumulative weight of qualified products, the carbon content of the product, and the molecular weight ratio of carbon dioxide to carbon. The carbon emissions of the input materials are calculated based on the cumulative input of a single raw material, the carbon content of the raw material, the molecular weight ratio of carbon dioxide to carbon, the fixed carbon emissions of the product, and the carbon dioxide equivalent of the carbon transferred to the by-product.

[0029] The calibrated energy consumption data is integrated and accumulated over a periodic period to obtain the cumulative energy consumption. The carbon emissions from energy consumption are then calculated based on the cumulative energy consumption, electricity emission factor, natural gas emission factor, and steam emission factor. The cumulative energy consumption includes cumulative electricity consumption, cumulative natural gas consumption, and cumulative steam consumption.

[0030] The total carbon emissions of the carbon accounting unit are obtained by summing the carbon emissions from input materials and energy consumption.

[0031] The dynamic carbon emission factor is calculated based on the carbon emissions from input materials and the carbon emissions from energy consumption.

[0032] Furthermore, methods for batch association based on event type and carbon fingerprinting include:

[0033] The net weight change of the event is calculated based on the weighing weight corresponding to the end time and start time of the weighing event. The event type is determined by combining the business scenario and the sign of the net weight change. The event types include inbound events and outbound events.

[0034] For weighing events with the event type of outbound event, the associated batches that meet the conditions are selected from the batch inventory table in combination with the preset inventory management rules;

[0035] Calculate the weight deducted from each associated batch until the total weight deducted from each associated batch equals the total outbound weight, and record the associated batch ID and its corresponding deducted weight.

[0036] For weighing events with the event type "inbound event", create a new batch record and assign it a new batch ID. Record the new batch ID and record the corresponding net weight change as the inbound weight.

[0037] Update the batch inventory table based on the updated data corresponding to outbound and inbound events.

[0038] Furthermore, methods for obtaining the current total carbon footprint and carbon footprint log include:

[0039] Calculate the product of the net weight change and the carbon emission factor for the event type of inbound event to obtain the carbon emission corresponding to the event type of inbound event. Include the carbon emission of the event type of inbound event in the inventory carbon assets and calculate the total carbon emission of inbound event.

[0040] Calculate the product of the net weight change and the carbon emission factor for events of the outbound type to obtain the carbon emission corresponding to the outbound event. Deduct the carbon emission of the outbound event from the inventory carbon assets and include it in the outbound carbon footprint to calculate the total outbound carbon emission.

[0041] Calculate the total energy emissions for a single cycle, and combine this with the ratio of the current inventory weight of a single batch to the total inventory weight of all batches in stock during the same period to obtain the carbon emissions for a single batch of energy; calculate the mass of carbon dioxide in the flue gas for a single cycle, and combine this with the ratio of the current inventory weight of a single batch to the total inventory weight of all batches in stock during the same period to obtain the carbon emissions for a single batch of warehousing flue gas; include the carbon emissions for a single batch of energy and the carbon emissions for a single batch of warehousing flue gas of all related batches in the cumulative value of derived carbon emissions;

[0042] The carbon emissions of a single batch of waste are obtained by multiplying the weight of a single batch of waste by the corresponding carbon emission factor. The total carbon emission change of the waste event is obtained by calculating the carbon emissions of single batches of waste for all related batches.

[0043] When it is detected that the carbon accounting unit updates the carbon emission factor, or the supplier updates the carbon emission factor in the carbon fingerprint, or the regional energy carbon emission factor is adjusted, all in-stock batches and batches that have been shipped out but not settled in the past K months are matched by material object identifier and supplier ID, and all data related to the carbon emission factor are updated to obtain the carbon footprint difference of the factor adjustment.

[0044] The current total inventory carbon footprint is dynamically updated based on the previous period's total inventory carbon footprint, total inbound carbon emissions, total outbound carbon emissions, cumulative derived carbon emissions, total carbon emissions changes from scrapping events, and factor-adjusted carbon footprint differences, and corresponding updated carbon footprint transaction records are generated.

[0045] Furthermore, methods for obtaining real-time weight values ​​include:

[0046] The original weight signal is acquired, and the original weight signal is smoothed based on the Kalman filter algorithm to obtain the filtered weight signal.

[0047] The filtered weight signal is temperature drift corrected based on the temperature compensation coefficient, ambient temperature, and reference temperature to obtain the corrected weight value.

[0048] The corrected weight value is calibrated based on the zero-point offset value of the weighing equipment to obtain the real-time weight value.

[0049] Furthermore, methods for determining the start and end of a weighing event based on the instantaneous rate of change of weight include:

[0050] The instantaneous weight change rate is calculated based on the real-time weight value using the finite difference method.

[0051] When the instantaneous rate of change of weight exceeds the rate of change of weight threshold for a period of time that reaches the duration threshold, a weighing event is determined to have started, and the start time of the weighing event is recorded.

[0052] After the weighing event begins, when the instantaneous rate of change of weight falls below the rate of change of weight threshold and remains stable for a period of time until it reaches the stable time threshold, the weighing event is considered to have ended, and the end time of the weighing event is recorded.

[0053] Furthermore, methods for tiered early warning based on analysis results include:

[0054] Regularly extract updated total carbon footprint and carbon footprint log from the database;

[0055] Calculate the inbound and outbound carbon emissions for the target period based on the carbon footprint log.

[0056] Based on a preset set of warning thresholds, hierarchical warning management is implemented;

[0057] According to the preset notification rules, send early warning notifications and corresponding early warning information.

[0058] The technical effects and advantages of this invention, a real-time inventory carbon footprint tracking and early warning system based on dynamic weighing, are as follows:

[0059] This invention constructs a carbon fingerprint generation mechanism, integrating key information throughout the entire lifecycle of each batch of materials and assigning unique IDs to both materials and suppliers. It also divides individual equipment, production lines, or independent processes into carbon accounting units, collecting multi-dimensional measured data within each unit to calculate dynamic carbon emission factors, replacing the traditional fixed average carbon emission factor. This achieves precise binding of carbon emission factors to individual batches of materials, addressing the issue of coarse data granularity caused by fixed factors at the accounting level. By combining net weight changes from weighing events with business scenarios such as inbound and outbound points, it accurately determines event types, creating unique batch records for inbound materials and associating them with carbon fingerprints. For outbound materials, it filters associated batches according to preset rules such as first-in-first-out and accurately allocates outbound weights, achieving real-time and accurate association between inbound / outbound behavior and specific material batches. This solves the problem of batch and carbon emission information being disconnected in traditional management. Furthermore, it establishes batch ID generation rules. This invention ensures a unique mapping between the full lifecycle information, dynamic carbon emission factors, and batch identifiers of each batch of materials, providing identity traceability support for accurate batch-level accounting. Based on the dynamic carbon emission factors associated with the batch ID and the net weight upon entry and exit from the warehouse, the carbon emissions of each batch of materials are accurately calculated and allocated to the corresponding batch, generating a carbon footprint log containing full-dimensional information such as batch ID, carbon emission factors, and carbon emission changes. This achieves accurate quantification of the full lifecycle carbon emissions of each batch of materials, solving the core problem that traditional solutions cannot reflect the actual carbon emission level of a single batch of materials. This invention adopts a dual-path cross-validation mechanism of material balance and online monitoring. By establishing a real-time verification relationship between process emissions and online flue gas measurement data, it ensures that the dynamic carbon emission factors, which are the cornerstone of accounting, have extremely high data quality and anti-interference capabilities, thereby improving the accuracy and reliability of batch-level carbon footprint tracking from the source. Attached Figure Description

[0060] Figure 1 This is a schematic diagram of the real-time inventory carbon footprint tracking and early warning system based on dynamic weighing according to the present invention.

[0061] Figure 2 This is a schematic diagram of the method for obtaining carbon emission factors according to the present invention;

[0062] Figure 3 This is a schematic diagram of the method for batch association based on event type and carbon fingerprint according to the present invention;

[0063] Figure 4 This is a schematic diagram of the method for obtaining the current total carbon footprint and carbon footprint log of the present invention. Detailed Implementation

[0064] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0065] Example 1:

[0066] Please see Figure 1 As shown, this embodiment provides a real-time inventory carbon footprint tracking and early warning system based on dynamic weighing, including:

[0067] Dynamic weighing module: Collects raw weight signal and ambient temperature, corrects the raw weight signal based on ambient temperature to obtain real-time weight value; calculates instantaneous weight change rate based on real-time weight value, and determines the start and end of weighing event based on instantaneous weight change rate; raw weight signal is the core basic data for calculating the weight of a single batch of materials, and ambient temperature is a key correlation variable to ensure the accuracy of weight measurement. The synchronous collection of both provides complete raw data support for subsequent accurate batch-level weight measurement, avoiding batch weight calculation deviation due to missing basic data.

[0068] Methods for obtaining real-time weight values ​​include:

[0069] The raw weight signal is acquired and smoothed using a Kalman filter algorithm to obtain a filtered weight signal. By filtering out random noise in the raw weight signal, the stability and consistency of the weight data are effectively improved, and batch weight data fluctuations caused by noise interference are avoided. This provides reliable filtered data for accurately defining the actual weight range of a single batch of materials.

[0070] Temperature drift correction is performed on the filtered weight signal based on the temperature compensation coefficient, ambient temperature, and reference temperature to obtain the corrected weight value. The temperature compensation coefficient is obtained based on equipment calibration experiments. Correcting the filtered weight signal based on the temperature compensation coefficient, ambient temperature, and reference temperature eliminates measurement deviations of the weighing equipment under different ambient temperatures, ensuring the comparability of weight data of the same or different batches of materials collected at different times and under different temperature environments, thus removing environmental interference obstacles for accurate batch-level weight calculation.

[0071] The corrected weight value is calibrated based on the zero-point offset value of the weighing equipment to obtain the real-time weight value. The zero-point offset value is obtained through periodic calibration. By correcting the inherent zero-point error of the weighing equipment, the absolute accuracy of the weight data is further improved, avoiding systematic deviations in batch weight caused by zero-point drift of the equipment. This ensures that the real-time weight value of each batch of materials can truly reflect its actual weight, providing an accurate weight base for calculating the carbon emissions of a single batch of materials.

[0072] Methods for determining the start and end of a weighing event based on the instantaneous rate of change of weight include:

[0073] Based on real-time weight values, the instantaneous weight change rate is calculated using the differential method. By dynamically calculating the instantaneous weight change rate based on real-time weight values, the dynamic fluctuation characteristics of material weight can be captured in real time. This provides a quantitative basis for accurately defining the time nodes and weight change ranges of each batch of materials entering and leaving the warehouse, and is the core technical support for achieving accurate correlation between weighing events and batch materials.

[0074] When the instantaneous weight change rate exceeds the weight change rate threshold for a duration threshold, a weighing event is determined to have started, and the start time of the weighing event is recorded. Through the dual determination logic of the instantaneous weight change rate exceeding the weight change rate threshold and reaching the duration threshold, the misjudgment of weighing events caused by instantaneous interference is effectively avoided, the starting point of each batch of materials entering the warehouse is accurately identified, and the weight statistics of a single batch of materials are accurately matched from the initial stage, avoiding the misrecording of batch weight due to misjudgment of the starting point.

[0075] After a weighing event begins, the event is considered to have ended when the instantaneous weight change rate falls below the weight change rate threshold and remains stable for a specified time. The end time of the weighing event is then recorded. The event is only considered to have ended when the instantaneous weight change rate falls below the weight change rate threshold and remains stable for a specified time. This precise definition of the complete time cycle for each batch of materials entering and leaving the warehouse ensures that the weight data of a single batch of materials can fully cover its actual entry and exit process, avoiding omissions in batch weight recording due to misjudgment of the end point.

[0076] The identification management module assigns a material object identifier that conforms to the unified item coding standard for the Internet of Things to each type of stored material;

[0077] Methods for assigning material object identifiers conforming to the IoT unified item coding standard to each type of stored material include:

[0078] When materials are received into the warehouse, corresponding additional information is obtained. This information includes material type, batch number, receipt time, supplier name, country of origin, mode of transport, and transport distance. A unique identifier code conforming to the unified IoT item coding standard is assigned to each material as its object identifier. A supplier ID based on the object identifier system is assigned to the supplier. The material object identifier is assigned using a combination of a 3-digit prefix, a 4-digit material classification code, a 6-digit material feature code, a 5-digit serial number, and a 2-digit check code. The prefix is ​​a fixed three-digit identifier, distinguishing it from the supplier ID and batch ID. The batch ID is a unique and structured internal identifier dynamically generated by the system for each receipt event. The batch ID serves as the core index for tracking the inventory and carbon footprint of that batch of materials in the system and is linked to the material's... The original batch number is stored in association. The material classification code is classified according to the enterprise's production attributes or industry standards. The first two digits are the primary classification, such as 01 for raw materials, 02 for semi-finished products, and 03 for finished products. The last two digits are the secondary classification, such as 0101 for solid raw materials, 0102 for liquid raw materials, and 0201 for injection-molded semi-finished products. This adapts to the need for carbon footprint accounting based on material type. The material feature code embeds key attributes to improve readability and relevance. The first three digits are the composition code, and the last three digits are the morphology code, which facilitates quick location of the material's core attributes and association with the corresponding carbon fingerprint template. The serial number increases sequentially according to the order in which materials are added to ensure the uniqueness of the same category. The check code is calculated based on the first 18 characters using the Mod11-2 algorithm to verify the accuracy of the material object identifier input and avoid errors caused by manual input or system transmission. Through a structured design of prefixes, classification codes, feature codes, serial numbers, and check codes, the uniqueness, readability, and traceability of material object identifiers are ensured. This adapts to the needs of carbon footprint accounting by material type, avoids confusion in batch carbon emission accounting caused by chaotic material identification, and enhances the accuracy of batch-level association.

[0079] Supplier IDs are assigned using a combination of a 3-digit prefix, a 2-digit region code, a 2-digit supplier type code, a 9-digit serial number, and a 2-digit check digit. The prefix is ​​a fixed 3-digit identifier, distinguishing it from material object identifiers and batch IDs. The region code is obtained according to the ISO 3166-1 alpha-2 standard, such as CN for China, US for the United States, and DE for Germany, facilitating the traceability of regional carbon emissions in the supply chain. The supplier type code distinguishes the supplier's core business, starting from 01 and incrementing sequentially according to the supplier's core business, such as 01 for raw material suppliers, 02 for transportation service providers, and 03 for energy suppliers, to meet the needs of multi-source carbon footprint accounting. The serial number increments sequentially according to the order in which suppliers are added to ensure global uniqueness. The check digit is calculated using the Mod11-2 algorithm based on the first 16 characters to verify the accuracy of ID entry and avoid errors from manual entry or system transmission. The structured coding based on regional and type codes enables globally unique identification of suppliers and rapid traceability of supply chain regions and business types. This provides a foundation for accurately calculating the carbon emission differences of materials from different suppliers and regions, and makes up for the shortcomings of traditional solutions that cannot distinguish the source of carbon emissions in the supply chain.

[0080] The identifier management module can also connect to the identifier resolution service module to receive query requests based on the material object identifier, and return the corresponding material carbon footprint information according to the carbon fingerprint and carbon footprint log associated with the material object identifier.

[0081] Fingerprint creation module: Combines real-time weight value and material information to generate a carbon fingerprint corresponding to each stored material; with real-time weight value as the core association basis, it creates a unique file for each material and generates a carbon fingerprint, breaking the traditional disconnect between material information and carbon emission data, giving each batch of materials a unique data carrier for carbon emission accounting, and laying the foundation for accurate batch-level association.

[0082] Methods for generating carbon fingerprints for each type of storage material include:

[0083] By comprehensively collecting key information throughout the entire lifecycle of materials and generating unique material object identifiers and supplier IDs through standardized coding rules, we can not only achieve unique identification of materials, suppliers and batches, but also quickly associate the core attributes required for carbon accounting through the classification and feature information embedded in the IDs, thus solving the problem of ambiguous association between batches and supply chains and material attributes in traditional management.

[0084] The carbon emission factor is calculated based on the real-time weight value;

[0085] By combining material object identifiers, batch numbers, warehousing time, carbon emission factors, supplier IDs, country of origin, transportation methods, and transportation distances, a carbon fingerprint corresponding to each material is obtained. As an extended IoT identification object, the carbon fingerprint's identification code supports querying and verification through an identifier resolution service. By integrating core data such as material object identifiers, carbon emission factors, and supply chain information into a carbon fingerprint and storing it in a batch inventory table in association with the batch number, a precise mapping of one fingerprint per batch is achieved. This makes the carbon emission information of each batch of materials traceable and accountable throughout its entire life cycle, directly solving the core problem of lacking precise batch-level association.

[0086] The generated carbon fingerprint is associated with the corresponding material batch number and stored in the batch inventory table; when a weighing event is detected, the batch inventory table is updated. A real-time linkage mechanism between carbon fingerprints and inventory data has been established to ensure that carbon fingerprint information is updated synchronously when batch inventory changes, avoiding a disconnect between carbon emission data and inventory status, and ensuring the real-time performance and accuracy of batch-level carbon emission accounting.

[0087] Reference Figure 2 Methods for obtaining carbon emission factors include:

[0088] Carbon accounting units are established, which can be single equipment, production lines, or independent processes, depending on the specific circumstances. The division of carbon accounting units must meet the following principles: continuous material conversion, equipment functional association, energy consumption attribution, delimitable boundaries, and minimum measurability. The continuous material conversion principle means that materials within a unit must form a closed loop of input, conversion, and output, with no disordered cross-unit intersections; that is, materials entering a unit should not mix with materials from other units until they are output. The equipment functional association principle means that equipment within a unit must work collaboratively to achieve the same technological objective, with no isolated equipment independent of the technological objective. The energy consumption attribution principle means that energy consumption within a unit must be independently measurable. The principle of clearly delineating boundaries indicates that the physical or logical boundaries of a unit can be clearly defined. Physical boundaries include equipment enclosures and pipe interfaces, while logical boundaries include production batches and process periods. The principle of minimum measurability indicates the degree to which further subdivision would make it impossible to independently collect material or energy data, thus avoiding excessive subdivision that would render accounting infeasible. The principle of refining accounting units to individual equipment / production lines / processes according to the multi-dimensional principle ensures independent measurement and no overlap or omission of material and energy consumption data, providing a scientific accounting framework for the accurate calculation of dynamic carbon emission factors and avoiding the distortion of carbon emission factors caused by traditional extensive accounting.

[0089] The system collects real-time weight values ​​of individual carbon-containing raw materials in the carbon accounting unit, as well as volume or mass data of non-solid raw materials, energy consumption data, real-time weight values ​​of qualified exported products, real-time weight values ​​of solid waste, and dry-basis volume fraction of carbon dioxide and flue gas flow rate. Among these, energy consumption data includes electricity consumption, natural gas consumption, and steam consumption.

[0090] Based on the collected data, the total input material weight, cumulative energy consumption, cumulative weight of qualified products, waste weight, and carbon dioxide mass in flue gas are calculated. The total input material weight, cumulative weight of qualified products, and waste weight are verified. If the verification is successful, the dynamic carbon emission factor is calculated based on the verified data; otherwise, the equipment is recalibrated.

[0091] Verification methods based on the total weight of input materials, the cumulative weight of qualified products, and the weight of waste include:

[0092] The real-time weight values ​​of a single carbon-containing raw material after calibration are periodically integrated and accumulated to obtain the cumulative input amount of the single raw material. Then, the cumulative input amount of the single raw material is accumulated by the raw material integral to obtain the total input material weight.

[0093] The real-time weight values ​​of the calibrated products and solid waste are periodically integrated and accumulated to obtain the cumulative weight of qualified products and the weight of waste.

[0094] The mass of carbon dioxide in the flue gas is obtained by calculating the dry basis volume fraction of carbon dioxide and the flue gas flow rate, and then integrating and summing over a periodic period; for example, the mass of carbon dioxide in the flue gas... ,in, for Carbon dioxide volume fraction on a dry basis at any given time; for The calibrated flue gas flow rate under standard conditions at any given time; This is the density of pure carbon dioxide under standard conditions;

[0095] The process verifies whether the total input material weight is the sum of the cumulative weight of qualified products, waste, and process losses. If yes, the material balance is determined, and the verification is passed. If not, the equipment must be recalibrated. Process losses can be obtained through statistical calculation of historical production data. It is unclear whether the statistical period is consistent with the carbon accounting unit's accounting period. If historical production data is unavailable, industry standards or data from similar companies can be used as a basis, combined with the user's own process, for statistical correction. Through the balance verification of total input material weight with qualified products, waste, and process losses, and the data calibration process, the accuracy of the basic carbon accounting data is ensured, providing reliable data support for dynamic carbon emission factor calculation and avoiding batch carbon emission accounting errors due to data deviations.

[0096] Methods for calculating dynamic carbon emission factors based on validated data include:

[0097] The product's fixed carbon emissions are calculated based on the cumulative weight of qualified products, the product's carbon content, and the molecular weight ratio of carbon dioxide to carbon. (The final sentence appears to be incomplete and requires further context.) ,in, The cumulative weight of qualified products; The carbon content of the product, i.e., its mass fraction, is calculated based on the cumulative input amount of each raw material, the carbon content of the raw materials, the molecular weight ratio of carbon dioxide to carbon, the fixed carbon emissions of the product, and the carbon dioxide equivalent of the carbon transferred to by-products. For example, the carbon emissions of the input materials... ,in, For a single raw material Cumulative investment; as raw materials Carbon content, i.e., mass fraction; This represents the molecular weight ratio of carbon dioxide to carbon, specifically... ; as raw materials The carbon oxidation rate is determined by the process; for example, it is 1 for complete combustion, but may be less than 1 for a specific chemical reaction. This represents the carbon dioxide equivalent of the carbon transferred into the byproducts.

[0098] The calibrated energy consumption data is integrated and accumulated over a periodic period to obtain the cumulative energy consumption, which includes cumulative electricity consumption, cumulative natural gas consumption, and cumulative steam consumption. The carbon emissions from energy consumption are then calculated based on the cumulative energy consumption, electricity emission factor, natural gas emission factor, and steam emission factor. (The last sentence appears to be incomplete and possibly refers to a different topic.) ,in, This represents the cumulative power consumption. This is an electricity emission factor, which can be obtained through historical data statistics; This represents the cumulative natural gas consumption. This is a natural gas emission factor, which can be obtained through historical data statistics; Cumulative steam consumption; The steam emission factor can be obtained through historical data statistics;

[0099] The total carbon emissions of the carbon accounting unit are obtained by summing the carbon emissions from input materials and energy consumption; for example, the total carbon emissions of the carbon accounting unit... If the absolute value of the difference between the carbon emissions of the input material and the mass of carbon dioxide in the flue gas, and the ratio of the maximum value between the carbon emissions of the input material and the mass of carbon dioxide in the flue gas, are not higher than the preset error threshold, which is obtained based on historical data statistics and is preferably 5%-10%, then the quality of the process emission accounting data for this period is deemed to be qualified; otherwise, the operator is prompted to check the carbon content or energy metering accuracy.

[0100] Dynamic carbon emission factors are calculated based on the carbon emissions from input materials and energy consumption; such as dynamic carbon emission factors. It integrates multi-dimensional measured data such as raw materials, energy, products, and flue gas, and calculates the total carbon emissions of the carbon accounting unit through a quantitative formula, thereby obtaining a dynamic carbon emission factor, which replaces the traditional fixed average emission factor. This allows the carbon emission factor to reflect the actual situation of production processes, raw material characteristics, etc. in real time, solving the core pain point of coarse data granularity.

[0101] The mean and standard deviation of dynamic carbon emission factors are statistically analyzed. A statistical process control method is employed, setting the upper and lower control limits for dynamic carbon emission factors as the sum and difference of the mean and three times the standard deviation, respectively. Dynamic carbon emission factors exceeding the upper and lower control limits are eliminated to obtain effective carbon emission factors. By eliminating outliers and using continuous periodic averages through statistical process control, the stability and reliability of dynamic carbon emission factors are improved, ensuring that batch-level carbon emission accounting is both accurate and consistent, and avoiding distortion of carbon emission results caused by fluctuations in single-period measured data.

[0102] The carbon emission factor is obtained by averaging the effective carbon emission factors over N consecutive periods. N is designed based on the number of production batches or the number of natural months, and the number of consecutive periods N meets the minimum statistical sample size requirement, such as N≥30 effective accounting periods, to ensure the statistical stability of the mean.

[0103] The perception trigger module calculates the net weight change for each weighing event, confirms the event type by combining the business scenario and the net weight change, and performs batch association based on the event type and carbon fingerprint.

[0104] Reference Figure 3 Methods for batch association based on event type and carbon fingerprint include:

[0105] The net weight change of the weighing event is calculated based on the weighing weight corresponding to the end time and start time of the weighing event. The event type is determined by combining the business scenario and the sign of the net weight change. Event types include inbound and outbound events. The business scenario is analyzed based on the actual situation, such as weighing events at the inbound and outbound ports, overlapping warehouse transfers (transferring goods between different areas within the same warehouse), and returns (goods returned after being shipped). Generally, when the net weight change at the inbound port is positive, it is determined as an inbound event; when the net weight change at the outbound port is negative, it is determined as an outbound event. Warehouse transfers may be misjudged as inbound or outbound due to incorrect weighing location, and returns may be misjudged because the direction of weight change is opposite to that of regular outbound shipments, causing event identification errors. The net weight change of a weighing event is calculated by measuring the weight difference between the start and end of the event. The event type is determined by combining the business scenario and the positive or negative weight change. This avoids the omission of special scenarios in traditional event identification and ensures the accurate positioning of inbound and outbound events and related events. It provides an accurate event trigger basis for the carbon emission correlation of each batch of materials and avoids confusion in batch carbon emission accounting due to event misjudgment.

[0106] For weighing events with the event type "outbound event," the system uses preset inventory management rules to filter out relevant batches that meet certain conditions from the batch inventory table. This can be done by prioritizing the earliest received batch with a current inventory level greater than 0, or by filtering out all eligible batches at once and issuing each batch according to its inventory ratio, or by prioritizing the latest received batch with a current inventory level greater than 0. By filtering out relevant batches corresponding to outbound shipments based on preset inventory management rules, the system achieves precise binding between outbound weight and specific material batches. This solves the problem of ambiguous correspondence between outbound weight and batches in traditional management, allowing carbon emissions from the outbound process to be accurately allocated to the corresponding batches, thus ensuring the accuracy of batch-level carbon emission accounting.

[0107] The system calculates the weight deducted from each associated batch until the accumulated weight deducted from all associated batches equals the total outbound weight. It records the associated batch ID and its corresponding deducted weight. If the sum of the total weight of raw materials in all associated batches is insufficient to reach the total outbound weight, the highest-level alert is triggered. Outbound weight is allocated and recorded sequentially by associated batch to ensure a perfect match between the outbound weight and the batch deduction amount. Simultaneously, the system triggers the highest-level alert for insufficient inventory scenarios, avoiding carbon emission accounting deviations caused by weight allocation errors or negative batch inventory, thus strengthening the rigor of batch-level correlation.

[0108] For weighing events with the event type "inbound event", create a new batch record and assign it a new batch ID. Record the new batch ID and the corresponding net weight change as the inbound weight. A new batch ID is assigned by combining a 20-digit material object identifier prefix, an 8-digit inbound date code, a 3-digit daily batch number, and a 1-digit check digit. The material object identifier prefix directly reuses the complete code of the material object identifier, achieving a strong binding between the batch ID and the material object identifier. This eliminates the need for additional association queries to determine the material attributes corresponding to the batch, adapting to the requirement of carbon footprint accounting by material type. The inbound date code clearly indicates the inbound time of the batch, facilitating the statistical analysis of batch carbon footprints by time dimension, while also resolving the issue of distinguishing batches of the same material inbound on different dates. The daily batch number increments sequentially according to the batches of the same material inbound on the same day, ensuring the uniqueness of batches of the same material under the same inbound date. If the number of inbound batches of the same material exceeds 999 in a single day, the system automatically triggers an alert, requiring manual verification to determine if it is an abnormal batch inbound, in order to avoid serial number overflow. The check digit is calculated using the modulo-10 check method, which is based on the sum of the ASCII codes of the first 31 characters and then modulo 10, used to quickly verify ID entry or transmission errors, improving data accuracy. When returned materials are re-entered into the warehouse, if the original batch is still in stock, the original batch ID is used, and only the current inventory weight and current inventory carbon footprint in the batch inventory table are updated. If the original batch has been completely shipped out, a new batch ID is generated based on the new inbound event. In this new batch, the material object identifier remains unchanged, the inbound date code is the date of return, and the sequence number is assigned according to the order of the day. Simultaneously, the original batch ID corresponding to the returned inbound item is noted in the batch inventory table to ensure uninterrupted carbon footprint traceability. If the inbound event spans midnight, the inbound date code is based on the date of the weighing event's end, avoiding splitting the same inbound event into two batches with different dates. If an inbound batch is split into multiple sub-batches due to quality issues, the sub-batch ID is based on the original batch ID, with one sub-batch number appended to the current batch sequence number, and is also associated with the original batch ID, ensuring traceability of carbon footprint data before and after the split. Standardized batch IDs containing material object identifiers, warehousing dates, and serial numbers are generated for incoming materials. This achieves a strong binding between batch IDs and material object identifiers, ensuring unique batch identification and facilitating rapid association of material attributes and carbon fingerprints. It solves the problem of difficult carbon emission traceability caused by the chaotic batch identification of traditional batches, laying the foundation for accurate batch-level accounting. New batch IDs can be flexibly reused or generated based on the original batch inventory status and associated with the original batch ID, ensuring uninterrupted carbon emission traceability for returned materials. This avoids the disconnect between batch and carbon emission data caused by returns and ensures the integrity of carbon emission data throughout the entire lifecycle, meeting the core requirement of accurate batch-level association. For cross-day warehousing, the event end date is used as the basis, batches are split, serial numbers are added, and associated with the original batch ID. This avoids carbon emission accounting errors caused by splitting the same event or confusing batches, ensuring the uniqueness and continuity of batch division, allowing the carbon emission data of each batch of materials to accurately correspond to its actual flow process.

[0109] The batch inventory table is updated based on the corresponding data from outbound and inbound events. This dynamic updating of core data in the batch inventory table based on outbound and inbound events enables real-time linkage between batch inventory weight, carbon footprint, and events. This avoids disconnection between batch information, inventory status, and carbon emission data, ensuring the real-time nature and accuracy of batch-level carbon emission accounting, and allowing the carbon emission status of each batch of materials to be updated synchronously with inventory changes.

[0110] In scenarios where bulk, powder, or liquid materials are stored together in the same warehouse, the original batches of outbound materials may not be physically distinguishable at the molecular level. The batch-level carbon footprint tracking achieved by the above steps is a solution based on the principle of quality balance accounting under this physical reality. The system, according to preset and clearly defined inventory management rules, such as first-in, first-out (FIFO) and allocation based on inventory ratios, fairly and traceably allocates outbound carbon emissions to the corresponding accounting batches. This step complies with the requirements of international standards such as ISO 14067 for carbon footprint accounting in complex supply chains and can be clearly explained in the carbon footprint report, ensuring the interpretability and audit compliance of the accounting results.

[0111] Footprint Analysis Module: Based on weighing events and their corresponding net weight changes, as well as carbon fingerprints, carbon footprint is tracked to obtain the current total carbon footprint and carbon footprint transaction log.

[0112] Reference Figure 4 Methods for obtaining the current total carbon footprint and carbon footprint log include:

[0113] Calculate the product of the net weight change and the carbon emission factor for the event type of inbound event to obtain the carbon emission corresponding to the event type of inbound event. Include the carbon emission of the event type of inbound event in the inventory carbon assets and calculate the total carbon emission of inbound event.

[0114] The system calculates the product of the net weight change and the carbon emission factor for events of the outbound type to obtain the carbon emission corresponding to the outbound event. The carbon emission of the outbound event is then deducted from the inventory carbon assets and included in the outbound carbon footprint to calculate the total outbound carbon emission. The system also calculates the inbound and outbound carbon emission by multiplying the net weight change of the event with the carbon emission factor in the carbon fingerprint. This achieves a direct link between single-batch inbound and outbound behavior and precise carbon emission, replacing the traditional coarse accounting model of fixed average carbon emission factor. This fundamentally solves the problem of coarse granularity in batch-level carbon emission data.

[0115] The system calculates the total energy emissions in a single cycle and uses the ratio of the current inventory weight of a single batch to the total inventory weight of all batches in storage during the same period to calculate the carbon emissions of a single batch. It also calculates the carbon dioxide mass in the flue gas during a single cycle and uses the ratio of the current inventory weight of a single batch to the total inventory weight of all batches in storage during the same period to calculate the carbon emissions of a single batch of warehousing flue gas. The system includes the carbon emissions of single batches and warehousing flue gas from all related batches in the cumulative value of derived carbon emissions. Finally, it allocates the energy emissions and warehousing flue gas emissions of a single cycle to related batches according to their weight percentage and includes them in the cumulative value of derived carbon emissions. This fills the gap in traditional solutions that omit carbon emissions from the storage stage, ensuring that the carbon footprint of each batch of materials covers both warehousing and storage, accurately reflecting the actual carbon emission level throughout the entire life cycle of the batch.

[0116] The carbon emissions of a single batch of waste are obtained by multiplying the weight of a single batch of waste with the corresponding carbon emission factor. The total carbon emission change of the waste event is obtained by calculating the carbon emissions of a single batch of waste across all related batches. By calculating the carbon emissions of a single batch of waste through the product of the weight of a single batch of waste with the corresponding carbon emission factor, the carbon emissions of waste at the batch level are accurately calculated. This avoids the problem in traditional extensive management where waste carbon emissions cannot be associated with specific batches and are included in the total emissions in a general way, thus strengthening the integrity of batch-level association.

[0117] When the carbon accounting unit updates the carbon emission factor, the supplier updates the carbon emission factor in the carbon fingerprint, or the regional energy carbon emission factor is adjusted, all in-stock batches and batches that have been shipped but not settled in the past K months are matched by material object identifier and supplier ID. All data related to the carbon emission factor are updated to obtain the carbon footprint difference of the factor adjustment. Among them, the K value is set based on the enterprise settlement cycle or industry practice. When the carbon emission factor is adjusted, the in-stock batches and batches that have not been settled in the past K months are matched by material object identifier and supplier ID, and the data is updated and the difference is calculated. This solves the defect that the traditional fixed carbon emission factor cannot adapt to changes in processes, raw materials, etc., and ensures that batch-level carbon emission data is dynamically calibrated with the carbon emission factor and always maintains accuracy.

[0118] The current total inventory carbon footprint is dynamically updated based on the previous period's total inventory carbon footprint, total inbound carbon emissions, total outbound carbon emissions, cumulative derived carbon emissions, changes in total carbon emissions from scrapping events, and factor-adjusted carbon footprint differences. A corresponding carbon footprint log record is generated, including the log number, event type, event occurrence time, associated batch, event net weight change, carbon emission factor, corresponding batch carbon emission change, total event carbon emission change, the total inventory carbon footprint before the update, and the total inventory carbon footprint after the update. A 2-digit... The serial number is obtained by using a prefix, a 2-digit event type code, an 8-digit date code, a 10-digit batch ID prefix, a 5-digit daily sequence number, and a 3-digit checksum. The prefix is ​​a fixed two-digit identifier that clearly defines the serial number type. The event type code is assigned according to the event type. The date code is taken from the date the event occurred. The batch ID prefix is ​​extracted from the first 10 digits of the batch ID to associate it with the specific batch. The daily sequence number increments according to the same event type on that day to ensure uniqueness. The checksum is based on the first 27 characters of the ASCII code, calculated using the Mod10-3 algorithm to sum and modulo the results, and checks for errors. This generates a serial number containing comprehensive information such as associated batches, carbon emission factors, and carbon emission changes. By associating the batch ID with the structured serial number, a full-chain traceability of event, batch, and carbon emission data is constructed, solving the traceability difficulties caused by the lack of precise batch-level association and providing a reliable basis for auditing.

[0119] Tracking and Early Warning Module: Performs footprint analysis based on carbon footprint logs and issues tiered early warnings based on the analysis results.

[0120] Methods for issuing multi-level early warnings based on analysis results include:

[0121] The system regularly extracts updated total carbon footprint and carbon footprint log from the database; it also automatically extracts total carbon footprint and carbon footprint log with associated batch information, dynamic carbon emission factors, and full life cycle data, replacing the traditional manual data aggregation model. This ensures that the data source for early warning analysis has batch-level accuracy and timeliness, providing a reliable batch-level data foundation for subsequent targeted early warnings.

[0122] The carbon footprint data is used to calculate the carbon emissions of materials entering and leaving the warehouse during the target period. Based on the batch-level entry and exit data in the carbon footprint data, the carbon emissions of each batch of materials entering and leaving the warehouse during the target period are accurately broken down. This breaks away from the traditional extensive model of only counting the overall carbon emissions, and enables the early warning analysis to locate high-emission batches in specific periods, providing a detailed quantitative basis for accurate early warning.

[0123] A tiered early warning management system is implemented based on a pre-set set of early warning thresholds. This set includes thresholds for carbon budget early warning, carbon emission factor fluctuation, energy consumption, material loss, flue gas emissions, and carbon footprint adjustment difference. These thresholds can be adjusted according to actual needs. Specifically, the carbon budget early warning thresholds are adaptively adjusted based on carbon budget and management requirements, enabling tiered early warning management. For example, early warning lines, alarm lines, and limit lines can be set for monthly carbon budgets. An early warning state is triggered when the monthly carbon budget reaches the early warning line but not the alarm line; an alarm state is triggered when the monthly carbon budget reaches the alarm line but not the limit line; and a limit state is triggered when the monthly carbon budget reaches the limit line. A carbon budget growth rate threshold can also be set; an alarm state is triggered when the average daily growth rate of carbon emissions within a target period exceeds the carbon budget growth rate threshold. Finally, a carbon budget asset excess threshold can be set; an alarm state is triggered when the current total carbon footprint exceeds the carbon budget asset excess threshold.

[0124] An alarm is triggered when the carbon emission factor fluctuation of different batches of the same material exceeds the carbon emission factor fluctuation threshold.

[0125] When the energy consumption per unit weight of inventory exceeds the energy consumption threshold, an early warning state is triggered.

[0126] An alarm is triggered when the loss rate of a single batch of materials, i.e., the ratio of the current loss weight to the weight received into the warehouse, exceeds the material loss threshold.

[0127] When the cumulative daily carbon dioxide mass in the flue gas of the carbon accounting unit exceeds the flue gas emission threshold, a limit state is triggered.

[0128] When the carbon emission factor is updated, an alarm is triggered when the absolute value of the carbon footprint difference in a single batch exceeds the carbon footprint adjustment difference threshold. The system has a pre-set set of warning thresholds covering multiple dimensions such as carbon budget, carbon emission factor, and energy consumption. In particular, it incorporates indicators that are strongly correlated with batch-level data, such as carbon emission factor fluctuations and material loss, to replace the traditional single total warning mode. The hierarchical management can respond accurately according to the degree of risk, adapt to the needs of precise batch-level control, and solve the shortcomings of traditional warnings that cannot be linked to batches.

[0129] According to preset notification rules, early warning notifications and corresponding early warning information are sent to designated management personnel. The early warning information includes the early warning level, the current cumulative carbon emission value, the corresponding threshold, the extent of exceedance, and a brief link to potential key weighing events. The early warning information is linked to key weighing events, which are directly bound to the batch ID and carbon fingerprint. This enables end-to-end traceability of early warnings, batches, and raw data, solving the problem of traditional early warnings only indicating total abnormalities without pinpointing specific batches and root causes, thus strengthening the practical management value of batch-level correlation.

[0130] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

[0131] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A real-time inventory carbon footprint tracking and early warning system based on dynamic weighing, characterized in that, include: Dynamic weighing module: Collects raw weight signal and ambient temperature, corrects the raw weight signal based on ambient temperature, and obtains real-time weight value; The instantaneous weight change rate is calculated based on the real-time weight value, and the start and end of the weighing event are determined based on the instantaneous weight change rate. The identification management module assigns a material object identifier that conforms to the unified item coding standard for the Internet of Things to each type of stored material; Fingerprint generation module: Generates a carbon fingerprint for each stored material based on the material object identifier, combined with real-time weight value and material information; The perception trigger module calculates the net weight change for each weighing event, confirms the event type by combining the business scenario and the net weight change, and performs batch association based on the event type and carbon fingerprint. Footprint Analysis Module: Based on weighing events and their corresponding net weight changes, as well as carbon fingerprints, carbon footprint is tracked to obtain the current total carbon footprint and carbon footprint transaction log. Tracking and Early Warning Module: Performs footprint analysis based on carbon footprint logs and issues tiered early warnings based on the analysis results.

2. The real-time inventory carbon footprint tracking and early warning system based on dynamic weighing according to claim 1, characterized in that, Methods for assigning material object identifiers conforming to the IoT unified item coding standard to each type of stored material include: When materials are received into the warehouse, the corresponding additional information is obtained. The additional information includes material type, batch number, warehouse receipt time, supplier name, country of origin, transportation method and transportation distance. A unique identification code that conforms to the unified item coding standard of the Internet of Things is assigned to the material as a material object identifier. A supplier ID based on the object identifier system is assigned to the supplier. Methods for generating carbon fingerprints for each type of storage material include: The carbon emission factor is calculated based on the real-time weight value; Combine the material object identifier, batch number, warehousing time, carbon emission factor, supplier ID, country of origin, transportation method and transportation distance to obtain the carbon fingerprint corresponding to the material; The generated carbon fingerprint is associated with the corresponding material batch number and stored in the batch inventory table; when a weighing event is detected, the batch inventory table is updated.

3. The real-time inventory carbon footprint tracking and early warning system based on dynamic weighing according to claim 2, characterized in that, Methods for obtaining carbon emission factors include: A carbon accounting unit is set up to collect the real-time weight value of a single carbon-containing raw material, as well as the volume or mass data of non-solid raw materials, energy consumption data, the real-time weight value of qualified exported products, the real-time weight value of solid waste, and the dry basis volume fraction of carbon dioxide and flue gas flow rate; among which, the energy consumption data includes electricity consumption, natural gas consumption and steam consumption. Based on the collected data, the total input material weight, cumulative energy consumption, cumulative weight of qualified products, waste weight, and carbon dioxide mass in flue gas are calculated. The total input material weight, cumulative weight of qualified products, and waste weight are verified. If the verification is successful, the dynamic carbon emission factor is calculated based on the verified data; otherwise, the equipment is recalibrated. The mean and standard deviation of dynamic carbon emission factors are statistically analyzed. Using statistical process control methods, the upper and lower control limits of dynamic carbon emission factors are set as the sum and difference of the mean and three times the standard deviation of the dynamic carbon emission factors, respectively. Dynamic carbon emission factors that exceed the upper and lower control limits are eliminated to obtain effective carbon emission factors. The carbon emission factor is obtained by averaging the effective carbon emission factors over N consecutive periods.

4. The real-time inventory carbon footprint tracking and early warning system based on dynamic weighing according to claim 3, characterized in that, Verification methods based on the total weight of input materials, the cumulative weight of qualified products, and the weight of waste include: The real-time weight values ​​of a single carbon-containing raw material after calibration are periodically integrated and accumulated to obtain the cumulative input amount of the single raw material. Then, the cumulative input amount of the single raw material is accumulated by the raw material integral to obtain the total input material weight. The real-time weight values ​​of the calibrated products and solid waste are periodically integrated and accumulated to obtain the cumulative weight of qualified products and the weight of waste. The mass of carbon dioxide in the flue gas is obtained by calculating the dry volume fraction of carbon dioxide and the flue gas flow rate, and by periodically integrating and summing the results. Verify that the total weight of input materials is the sum of the cumulative weight of qualified products, the weight of waste, and the amount of process loss. If yes, the material balance is determined and the verification is passed. If no, the equipment is recalibrated.

5. The real-time inventory carbon footprint tracking and early warning system based on dynamic weighing according to claim 3, characterized in that, Methods for calculating dynamic carbon emission factors based on validated data include: The fixed carbon emissions of the product are calculated based on the cumulative weight of qualified products, the carbon content of the product, and the molecular weight ratio of carbon dioxide to carbon. The carbon emissions of the input materials are calculated based on the cumulative input of a single raw material, the carbon content of the raw material, the molecular weight ratio of carbon dioxide to carbon, the fixed carbon emissions of the product, and the carbon dioxide equivalent of the carbon transferred to the by-product. The calibrated energy consumption data is integrated and accumulated over a periodic period to obtain the cumulative energy consumption. The carbon emissions from energy consumption are then calculated based on the cumulative energy consumption, electricity emission factor, natural gas emission factor, and steam emission factor. The cumulative energy consumption includes cumulative electricity consumption, cumulative natural gas consumption, and cumulative steam consumption. The total carbon emissions of the carbon accounting unit are obtained by summing the carbon emissions from input materials and energy consumption. The dynamic carbon emission factor is calculated based on the carbon emissions from input materials and the carbon emissions from energy consumption.

6. The real-time inventory carbon footprint tracking and early warning system based on dynamic weighing according to claim 1, characterized in that, Methods for batch association based on event type and carbon fingerprinting include: The net weight change of the event is calculated based on the weighing weight corresponding to the end time and start time of the weighing event. The event type is determined by combining the business scenario and the sign of the net weight change. The event types include inbound events and outbound events. For weighing events with the event type of outbound event, the associated batches that meet the conditions are selected from the batch inventory table in combination with the preset inventory management rules; Calculate the weight deducted from each associated batch until the total weight deducted from each associated batch equals the total outbound weight, and record the associated batch ID and its corresponding deducted weight. For weighing events with the event type "inbound event", create a new batch record and assign it a new batch ID. Record the new batch ID and record the corresponding net weight change as the inbound weight. Update the batch inventory table based on the updated data corresponding to outbound and inbound events.

7. The real-time inventory carbon footprint tracking and early warning system based on dynamic weighing according to claim 1, characterized in that, Methods for obtaining the current total carbon footprint and carbon footprint log include: Calculate the product of the net weight change and the carbon emission factor for the event type of inbound event to obtain the carbon emission corresponding to the event type of inbound event. Include the carbon emission of the event type of inbound event in the inventory carbon assets and calculate the total carbon emission of inbound event. Calculate the product of the net weight change and the carbon emission factor for events of the outbound type to obtain the carbon emission corresponding to the outbound event. Deduct the carbon emission of the outbound event from the inventory carbon assets and include it in the outbound carbon footprint to calculate the total outbound carbon emission. Calculate the total energy emissions for a single cycle, and combine this with the ratio of the current inventory weight of a single batch to the total inventory weight of all batches in stock during the same period to obtain the carbon emissions for a single batch of energy; calculate the mass of carbon dioxide in the flue gas for a single cycle, and combine this with the ratio of the current inventory weight of a single batch to the total inventory weight of all batches in stock during the same period to obtain the carbon emissions for a single batch of warehousing flue gas; include the carbon emissions for a single batch of energy and the carbon emissions for a single batch of warehousing flue gas of all related batches in the cumulative value of derived carbon emissions; The carbon emissions of a single batch of waste are obtained by multiplying the weight of a single batch of waste by the corresponding carbon emission factor. The total carbon emission change of the waste event is obtained by calculating the carbon emissions of single batches of waste for all related batches. When it is detected that the carbon accounting unit updates the carbon emission factor, or the supplier updates the carbon emission factor in the carbon fingerprint, or the regional energy carbon emission factor is adjusted, all in-stock batches and batches that have been shipped out but not settled in the past K months are matched by material object identifier and supplier ID, and all data related to the carbon emission factor are updated to obtain the carbon footprint difference of the factor adjustment. The current total inventory carbon footprint is dynamically updated based on the previous period's total inventory carbon footprint, total inbound carbon emissions, total outbound carbon emissions, cumulative derived carbon emissions, total carbon emissions changes from scrapping events, and factor-adjusted carbon footprint differences, and corresponding updated carbon footprint transaction records are generated.

8. The real-time inventory carbon footprint tracking and early warning system based on dynamic weighing according to claim 1, characterized in that, Methods for obtaining real-time weight values ​​include: The original weight signal is acquired, and the original weight signal is smoothed based on the Kalman filter algorithm to obtain the filtered weight signal. The filtered weight signal is temperature drift corrected based on the temperature compensation coefficient, ambient temperature, and reference temperature to obtain the corrected weight value. The corrected weight value is calibrated based on the zero-point offset value of the weighing equipment to obtain the real-time weight value.

9. The real-time inventory carbon footprint tracking and early warning system based on dynamic weighing according to claim 1, characterized in that, Methods for determining the start and end of a weighing event based on the instantaneous rate of change of weight include: The instantaneous weight change rate is calculated based on the real-time weight value using the finite difference method. When the instantaneous rate of change of weight exceeds the rate of change of weight threshold for a period of time that reaches the duration threshold, a weighing event is determined to have started, and the start time of the weighing event is recorded. After the weighing event begins, when the instantaneous rate of change of weight falls below the rate of change of weight threshold and remains stable for a period of time until it reaches the stable time threshold, the weighing event is considered to have ended, and the end time of the weighing event is recorded.

10. The real-time inventory carbon footprint tracking and early warning system based on dynamic weighing according to claim 1, characterized in that, Methods for issuing graded early warnings based on analysis results include: Regularly extract updated total carbon footprint and carbon footprint log from the database; Calculate the inbound and outbound carbon emissions for the target period based on the carbon footprint log. Based on a preset set of warning thresholds, hierarchical warning management is implemented; According to the preset notification rules, send early warning notifications and corresponding early warning information.

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