Risk management system and method based on food supply chain

Abstract

This invention discloses a risk management system and method based on the food supply chain, relating to the field of food supply chain risk management technology. The food supply chain-based risk management system includes: a food transfer and delay monitoring module; a food waste risk assessment module; and a carbon footprint information update accuracy monitoring module. This invention monitors food transfer and delays using acquired food transfer delay parameters and determines whether to optimize food transfer delays. If not, it assesses the food waste risk level. Finally, it monitors the accuracy of carbon footprint information updates using acquired carbon footprint information update parameters and determines whether to optimize food carbon footprint information updates. This improves the accuracy of risk management in the food supply chain based on carbon footprint detection, solving the problem of low data accuracy in existing carbon footprint-based food supply chain risk management technologies.

Description

Technical Field

[0001] This invention relates to the field of food supply chain risk management technology, and in particular to a risk management system and method based on the food supply chain. Background Technology

[0002] Food supply chain risk management refers to the systematic identification, assessment, control, and mitigation of potential risks in the food supply chain to ensure food safety, supply stability, and sustainability. With increasing global focus on carbon reduction, carbon footprint management in the food supply chain has become a crucial issue. Optimizing food supply chain risk management can reduce environmental impact and lower carbon emissions. Carbon footprint is a key consideration in food supply chain risk management. Reducing the carbon footprint can mitigate environmental risks and improve supply chain sustainability.

[0003] Existing systems primarily rely on blockchain to ensure the transparency and immutability of carbon emission data throughout the food supply chain. Carbon emission information at each stage can be recorded on the blockchain, allowing for traceability of carbon emissions at each step in the event of transportation delays or other problems. Sidechain technology is used to migrate some data from the main chain for processing, thus reducing the burden on the main chain.

[0004] For example, the invention patent announcement CN113592338B discloses a food quality management safety risk pre-screening model, which includes: (1) text data acquisition and preprocessing; the text data is online comment text; (2) preprocessed text data encoding vectorization; (3) judging the degree of food safety hazard through the attention scoring mechanism in supervised deep learning; a new food text mining technology based on the association attention mechanism uses the mutual information of each word and the unsafety tag in consumer comments to calculate the association score between each word and food safety hazard, and then combines the attention score in supervised deep learning to further explore the potential interaction between consumers and dangerous food.

[0005] For example, the invention patent application with publication number CN119443491A discloses a product lifecycle carbon emission tracking method, which includes: S1. Formulating product definition boundaries and cutoff standards based on carbon emission calculation formulas; S2. Completing data acquisition and calculation according to local conditions, and conducting real-time monitoring and data collection for each stage of the product production process.

[0006] However, in the process of implementing the inventive technical solution in the embodiments of this application, it was found that the above-mentioned technology has at least the following technical problems:

[0007] In existing technologies, material waste and carbon emissions are often closely related in the food supply chain. During transportation, food may indirectly increase carbon emissions due to transportation losses. For foods that are transported multiple times (such as fresh food), the risk of material waste can be assessed by detecting carbon footprints. However, due to transportation delays during multiple transportation processes, the tracking and updating of carbon emission information may not be timely, resulting in low accuracy of risk management data for food supply chains based on carbon footprint detection. Summary of the Invention

[0008] This application provides a risk management system and method based on the food supply chain, which solves the problem of low accuracy of risk management data in the prior art based on carbon footprint detection for food supply chains, and improves the accuracy of risk management in the food supply chain based on carbon footprint detection.

[0009] This application provides a risk management system based on the food supply chain, including a food transportation and delay monitoring module, a food waste risk assessment module, and a carbon footprint information update accuracy monitoring module. The food transportation and delay monitoring module monitors food transportation and delays based on acquired food transportation delay parameters and determines whether to optimize food transportation delays. The food waste risk assessment module assesses the food waste risk level if food transportation delay optimization is not performed. The carbon footprint information update accuracy monitoring module monitors the accuracy of carbon footprint information updates based on acquired carbon footprint information update parameters and determines whether to optimize food carbon footprint information updates.

[0010] This application provides a risk management method based on the food supply chain, including the following steps: S1, monitoring food transportation and delays based on the acquired food transportation delay parameters, and determining whether to optimize food transportation delays; S2, if food transportation delays are not optimized, then assessing the risk level of food waste; S3, monitoring the accuracy of carbon footprint information updates based on the acquired carbon footprint information update parameters, and determining whether to optimize food carbon footprint information updates.

[0011] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages:

[0012] 1. By acquiring food transfer delay parameters, food transfer and delay monitoring is conducted, and it is determined whether food transfer delay optimization should be performed. If food transfer delay optimization is not performed, a food waste risk level assessment is conducted. Finally, by acquiring carbon footprint information update parameters, the accuracy of carbon footprint information updates is monitored, and it is determined whether food carbon footprint information updates should be optimized. This improves the accuracy of food waste risk level assessment and carbon footprint information updates, thereby improving the accuracy of risk management in the food supply chain based on carbon footprint detection. This effectively solves the problem of low data accuracy in risk management of the food supply chain based on carbon footprint detection in existing technologies.

[0013] 2. By monitoring the food spoilage rate within a preset time period, the food information corresponding to the food spoilage rate exceeding the preset food spoilage rate is classified as Level 1 food waste risk. Finally, the carbon footprint information of food information within the Level 1 food waste risk is monitored for accuracy, thereby improving the effectiveness of food waste risk level assessment and, consequently, improving the effectiveness of carbon footprint information update capability assessment.

[0014] 3. By coupling the updated food carbon footprint information data and combining it with the preset carbon emission delay weights, the update delay values ​​of food and carbon emissions are obtained through weighted calculation. This enables an accurate assessment of the food carbon footprint information update capability and improves the reliability of the assessment. Attached Figure Description

[0015] Figure 1 A schematic diagram of the structure of a risk management system based on the food supply chain provided in this application embodiment;

[0016] Figure 2 A flowchart of a risk management method based on the food supply chain provided in this application embodiment. Detailed Implementation

[0017] This application provides a risk management system and method based on the food supply chain, which solves the problem of low accuracy of risk management data in the prior art based on carbon footprint detection. It monitors food transportation and delays by acquiring food transportation delay parameters. When the assessed value of the impact of food transportation delays is greater than a preset threshold, food transportation delay optimization is performed; when the assessed value is not greater than the preset threshold, no optimization is performed. If no optimization is performed, a food waste risk level assessment is conducted. Finally, the accuracy of carbon footprint information updates is monitored using acquired carbon footprint information update parameters, and a decision is made on whether to optimize food carbon footprint information updates. This improves the accuracy of risk management in the food supply chain based on carbon footprint detection.

[0018] The technical solution in this application aims to address the problem of low accuracy in risk management data for food supply chains based on carbon footprint detection. The overall approach is as follows:

[0019] By acquiring food transit delay parameters, we monitor food transit and delays, and determine whether to optimize food transit delays. If not, we conduct a food waste risk level assessment. Finally, by acquiring carbon footprint information update parameters, we monitor the accuracy of carbon footprint information updates and determine whether to optimize food carbon footprint information updates. This achieves the effect of improving the accuracy of risk management of the food supply chain based on carbon footprint detection.

[0020] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0021] like Figure 1 The diagram shows the structure of a risk management system based on a food supply chain provided in this application embodiment. It includes a food transfer and delay monitoring module, a food waste risk assessment module, and a carbon footprint information update accuracy monitoring module. The food transfer and delay monitoring module monitors food transfer and delays based on acquired food transfer delay parameters and determines whether to optimize food transfer delays. The food waste risk assessment module assesses the food waste risk level if food transfer delays are not optimized. The carbon footprint information update accuracy monitoring module monitors the accuracy of carbon footprint information updates based on acquired carbon footprint information update parameters and determines whether to optimize food carbon footprint information updates.

[0022] In this embodiment, a food transportation delay monitoring module monitors food transportation delay parameters to obtain an assessment value of the impact of food transportation delays. When the assessment value exceeds a preset threshold, food transportation delay optimization is performed. When the assessment value is not greater than the preset threshold, a food waste risk assessment module assesses the risk level of food waste. By monitoring food spoilage rates, food information with spoilage rates exceeding a preset threshold is classified as Level 1 food waste risk. A carbon footprint information update accuracy monitoring module monitors the accuracy of carbon footprint information updates. When the monitored food and carbon emission update delay values ​​exceed a preset carbon emission update delay threshold, food carbon footprint information updates are optimized; otherwise, the corresponding food information is updated to a preset data center. The food transportation delay monitoring module, the food waste risk assessment module, and the carbon footprint information update accuracy monitoring module collaborate and influence each other, helping to improve the accuracy of food waste risk level assessment and carbon footprint information updates, thereby improving the accuracy of risk management in the food supply chain based on carbon footprint detection.

[0023] For foods that undergo multiple transfers (such as fresh produce), accurate tracking and timely updates of carbon footprint information are crucial for assessing material waste risks and developing emission reduction strategies. By having modules for monitoring food transfer and delays, assessing food waste risks, and monitoring the accuracy of carbon footprint updates work together across the food supply chain, the accuracy of carbon footprint updates and the precision of food waste risk assessments can be improved, thus supporting risk management within the food supply chain.

[0024] Furthermore, the food transfer delay parameters include average transfer delay time at transport points, number of food transfers, average food transport duration, average distance between transport points, and food shelf life. These parameters, along with preset food transfer delay parameters obtained from the database, jointly affect the food transfer delay data. The average transfer delay time at transport points is represented by the difference between the average food transport duration between adjacent transport stations within a preset time period and the preset average food transport duration. The preset food transfer delay parameters include preset average transfer delay time, preset number of food transfers, preset average food transport duration, preset average distance between transport points, preset food shelf life, preset comprehensive delay impact weight, and preset food delay and impact weight recombination. The preset food delay and impact weight recombination reflects the degree of influence of the food transfer delay parameters on the food transfer delay data, specifically including a preset first transfer delay impact weight, a preset second transfer delay impact weight, a preset third transfer delay impact weight, and a preset fourth transfer delay impact weight. The preset comprehensive delay impact weight reflects the degree of influence of the food transfer delay data on the food transfer delay impact assessment value.

[0025] Among these methods, the average transfer delay time at each transport point is calculated by using a timer to monitor the difference between the average food transport time between adjacent transport stations within a preset time period and the preset average food transport time; the number of food transfers within a preset time period is monitored by a counter to calculate the number of food transfers; the average transport time to the transport point is monitored by a timer to calculate the average food transport time; the average distance between transport points within a preset time period is monitored by GIS (Geographic Information System) technology to calculate the average distance between transport points; and the shelf life on the food packaging is used as the food shelf life.

[0026] The units for average transfer delay time and preset average transfer delay time at transportation points are both seconds; the units for average food transportation time and preset average food transportation time are both hours; the units for food transfer frequency and preset food transfer frequency are both times; the units for average distance between transportation points and preset average distance between transportation points are both kilometers; the units for food shelf life and preset food shelf life are both months (if the unit is not months, the unit needs to be converted).

[0027] The carbon footprint information update parameters include average carbon emission update delay time, average carbon emission increase rate, average transit delay time at transport points, and food spoilage rate. These parameters, along with preset carbon footprint information update parameters obtained from the database, jointly affect the food carbon footprint information update data. The average carbon emission update delay time is represented by the difference between the food carbon footprint information update time corresponding to the transport station within the qualified preset time period and the preset food carbon footprint information update time. The average carbon emission increase rate is represented by the average ratio of the carbon emission increment to the carbon emission duration corresponding to the transport station within the qualified preset time period. The preset carbon footprint information update parameters include preset average carbon emission update delay time, preset average carbon emission increase rate, preset average transit delay time, preset food spoilage rate, preset carbon emission delay weight, and preset carbon emission delay weight reassembly. The preset carbon emission delay weight reassembly includes preset first carbon emission delay weight, preset second carbon emission delay weight, and preset third carbon emission delay weight, used to reflect the degree of influence of the qualified preset time period carbon footprint information update parameters on the food carbon footprint information update data. The preset carbon emission delay weight is used to reflect the degree of influence of the qualified preset time period food carbon footprint information update data on the food and carbon emission update delay values.

[0028] Among them, the difference between the update time of food carbon footprint information corresponding to the qualified preset time period and the preset food carbon footprint information update time is used as the average carbon emission update delay time; the average value of the ratio of carbon emission increment to carbon emission duration of the qualified preset time period is used as the average carbon emission increase rate; and the ratio of the number of spoiled foods to the total number of foods in the qualified preset time period is used as the food spoilage rate.

[0029] The units for both the average carbon emission update delay and the preset average carbon emission update delay are seconds; the units for both the average carbon emission increase rate and the preset average carbon emission increase rate are kilograms of carbon dioxide per hour; and the units for both the food spoilage rate and the preset food spoilage rate are not specified.

[0030] In this embodiment, the aforementioned database is the database used by the food supply chain-based risk management system provided in this application embodiment to store various set data. The database includes, but is not limited to, preset average transfer delay time, preset number of food transfers, preset average food transportation time, etc., and the various values ​​therein are directly set by technical personnel; for example, preset food supply risk parameters are represented by the average value of food supply risk parameters for the corresponding historical time period in the database; preset food supply risk parameters include preset average transfer delay time, preset number of food transfers, preset average food transportation time, preset average distance to transportation points, preset food shelf life, preset average carbon emissions, etc. The new delay duration, preset average carbon emission increase rate, and preset food spoilage rate; food supply risk parameters include average transit delay time at transport points, number of food transits, average food transport time, average transport point distance, food shelf life, average carbon emission update delay duration, average carbon emission increase rate, and food spoilage rate; food transit delay data and food carbon footprint information update data are all greater than 0; by monitoring food transit delay parameters and carbon footprint information update parameters, the accuracy of assessing the ability to update food transport delay data and food carbon footprint information has been improved, thereby improving the accuracy of risk management of the food supply chain based on carbon footprint detection.

[0031] It should be added that two mapping sets containing mapping sets are obtained from the database. These mapping sets are used to reflect the mapping relationship between food transportation delay parameters and the corresponding preset food delay and impact weight sets, as well as the mapping relationship between food transportation delay data and the corresponding preset comprehensive delay impact weights. The mapping relationship in the mapping sets can be one-to-one or many-to-one. By inputting real-time food transportation delay parameters and food transportation delay data into the corresponding mapping sets, the corresponding preset food delay and impact weight sets and preset comprehensive delay impact weights can be obtained. For example, the weight values ​​range from 0 to 1.

[0032] Two mapping sets are obtained from the database, each containing a mapping set. These mapping sets reflect the mapping relationship between carbon footprint information update parameters and corresponding preset carbon emission delay weights, as well as the mapping relationship between food carbon footprint information update data and corresponding preset carbon emission delay weights. The mapping relationships in the mapping sets can be one-to-one or many-to-one. By inputting real-time carbon footprint information update parameters and food carbon footprint information update data into the corresponding mapping sets, the corresponding preset carbon emission delay weights and preset carbon emission delay weights can be obtained. For example, the weight values ​​range from 0 to 1.

[0033] Furthermore, the specific process for monitoring food transfer and delays based on the acquired food transfer delay parameters is as follows: Food transfer delay data is obtained by processing the food transfer delay parameters and preset food transfer delay parameters obtained from the database; it is then determined whether the average transfer delay time at the transport point is greater than 0. If the average transfer delay time at the transport point is not greater than 0, food transfer and delay monitoring is not performed, and the corresponding food information (such as food shelf life, food name, etc.) is updated to the preset data center; if the average transfer delay time at the transport point is greater than 0, the monitoring is performed by combining the preset comprehensive delay impact weight and the proportion of the average transfer delay time at the transport point to the preset average transfer delay time. The analysis results, after coupling processing, involve superimposing and weighting the food transport delay data to obtain the food transport delay impact assessment value. Food transport delay data processing includes food delay and transport processing, food delay and transport time processing, food delay and transport distance processing, and food delay and food shelf life processing. Food delay and transport processing involves analyzing the proportion of food transport frequency and preset food transport frequency, and then combining this with a preset first transport delay impact weight to obtain the food delay and transport processing value. This value reflects the effect of food transport frequency on the update capability of food transport delay data (such as transport delay duration and transport delay frequency). The transportation time processing method analyzes the proportion of average food transportation time and preset average food transportation time, and then performs weighted calculations based on a preset second transshipment delay impact weight to obtain the food delay and transportation time processing value. This value reflects the effect of average food transportation time on the ability to update food transportation delay data. Similarly, the food delay and transportation distance processing method analyzes the proportion of average transportation point distance and preset average transportation point distance, and then performs weighted calculations based on a preset third transshipment delay impact weight to obtain the food delay and transportation distance processing value. This value reflects the effect of average transportation point distance on the ability to update food transportation delay data. The "Food Delay and Food Shelf Life Handling" values ​​are derived by analyzing the proportion of preset food shelf life and food shelf life duration, and then weighting them with a preset fourth transit delay impact weight. These values ​​reflect the impact of food shelf life duration on the ability to update food transportation delay data. Food transit delay data includes the values ​​for food delay and transit handling, food delay and transportation time handling, food delay and transportation distance handling, and food delay and food shelf life handling. The "Food Transit Delay Impact Assessment Value" reflects the combined effect of preset time period food transit delay parameters and preset food transit delay parameters on the ability to update food transportation delay data.

[0034] The assessment value for the impact of food transport delays was obtained using the following method:

[0035] ;

[0036] In the formula, This represents the assessed value of the food transport delay impact during the Zth preset time period. Z represents the preset time period number, and P represents the total number of preset time periods. This represents the average transfer delay time at the transport point during the Z-th preset time period. This represents the food delay and transfer processing value for the Zth preset time period. This represents the processing value for food delays and transportation time in the Zth preset time period. This represents the food delay and transportation distance handling value for the Zth preset time period. This represents the food delay and food preservation processing value for the Zth preset time period. This indicates the preset average transit delay time. This indicates the pre-set weight of the overall delay impact.

[0037] Specifically, In the formula This indicates the preset weight of the first transit delay. This represents the number of food transfers during the Zth preset time period. This indicates the preset number of food transfers.

[0038] In the formula This indicates the preset weight of the second transit delay. This represents the average food transportation time during the Zth preset time period. This indicates the preset average food transportation time.

[0039] In the formula This indicates the weight of the preset third transit delay. This represents the average distance between transport points during the Zth preset time period. This indicates the preset average distance to the transport point.

[0040] In the formula This indicates the shelf life of food during the Zth preset time period. This indicates the preset weight of the fourth transit delay effect. This indicates the preset shelf life of food.

[0041] In this embodiment, the impact assessment value of food transportation delay is obtained by combining food transportation delay data analysis. A larger food delay and transportation processing value indicates a stronger effect of the number of food transportation trips on the ability to update food transportation delay data, resulting in a larger impact assessment value. Similarly, a larger food delay and transportation time processing value indicates a stronger effect of the average food transportation time on the ability to update food transportation delay data, leading to a larger impact assessment value. Likewise, a larger food delay and transportation distance processing value indicates a stronger effect of the average transportation point distance on the ability to update food transportation delay data, leading to a larger impact assessment value. Finally, a larger food delay and food shelf-life processing value indicates a stronger effect of the food shelf-life on the ability to update food transportation delay data, leading to a larger impact assessment value. In summary, there is a positive correlation between food transportation delay data and the impact assessment value of food transportation delay.

[0042] In this embodiment, the food transit delay parameters are not independent but interrelated and require comprehensive analysis. More transit trips mean the food needs to pass through more transit points during transportation, increasing the likelihood of delays and potentially increasing the average transit delay time. Increased transit trips may also lengthen transportation routes, leading to a longer average food transportation time. Shorter food shelf life requires faster transportation to minimize delays, potentially reducing the average food transportation time. Larger average transit point distances require more time and resources to complete transits, potentially increasing both the average food transportation time and the number of transit trips. By analyzing the combined effects of these parameters, a precise assessment of the food transit delay data update capability is achieved, thereby improving the accuracy of risk management in the food supply chain based on carbon footprint detection.

[0043] Furthermore, the specific process for determining whether to optimize food transport delays is as follows: The impact assessment value of the food transport delay is compared with the preset impact threshold for transport delays obtained from the database. When the impact assessment value is greater than the preset impact threshold, the corresponding food information is marked as delayed food information, and food transport delay optimization is performed. When the impact assessment value is not greater than the preset impact threshold, food transport delay optimization is not performed, and a food waste risk level assessment is conducted. The specific steps for optimizing food transport delays are as follows: First, a delayed food information transfer notification is sent, indicating that a preset person is being notified. The process involves three steps: First, the system uses a sidechain method to transfer delayed food information from the main chain to a first sidechain. This first sidechain is used to process the food transportation delay data corresponding to the delayed food information. Second, the system sets the number of nodes on the first sidechain, which represents the number of backup computing nodes on the first sidechain at a preset ratio. Third, the system sets the update frequency of the first sidechain. When the monitored food transportation delay impact assessment value is not greater than the preset transportation delay impact threshold, the operation stops. This setting represents the update frequency of delayed food information on the first sidechain at a preset ratio. Food transportation delay optimization is used to improve the update capability of food transportation delay data within a preset time period.

[0044] In this embodiment, the preset transit delay impact threshold is represented by the average value of the food transit delay impact assessment value over a historical time period. When food information is marked as delayed food information, the delayed food information is transferred from the main chain to a first side chain (such as a consortium chain) using side chain technology. Based on the ratio between the food transit delay impact assessment value and the preset transit delay impact threshold, the number of backup computing nodes on the first side chain is increased step by step according to a corresponding preset ratio, and the update frequency of delayed food information on the first side chain is increased step by step according to a corresponding preset ratio. For example, the real-time location, temperature, and humidity data of fresh food transportation are stored independently through the side chain, which ensures data integrity and reduces the computational pressure on the main chain. The independent processing of food transportation delay data corresponding to delayed food information by the first side chain helps to reduce the computational pressure on the main chain, thereby improving the update capability of food transportation delay data, and thus achieving the effect of improving the accuracy of risk management of the food supply chain based on carbon footprint detection.

[0045] Furthermore, the specific process for assessing the risk level of food waste is as follows: The food spoilage rate is monitored within a preset time period, obtained by analyzing the proportion of spoiled food to the total amount of transported food during that period; the food spoilage rate is compared with a preset food spoilage rate obtained from the database; when the monitored food spoilage rate is greater than the preset rate, the corresponding food information is classified as Level 1 food waste risk; the accuracy of carbon footprint information updates is monitored for food information within the Level 1 risk range; when the monitored food spoilage rate is not greater than the preset rate, the corresponding food information is classified as Level 2 food waste risk, and no carbon footprint information update accuracy monitoring is performed.

[0046] The specific process for monitoring the accuracy of carbon footprint information updates based on the acquired carbon footprint information update parameters is as follows: First, determine if the average carbon emission update delay is greater than 0. If the average carbon emission update delay is not greater than 0, no carbon footprint information update accuracy monitoring is performed, and the corresponding food information is updated to the preset data center. If the average carbon emission update delay is greater than 0, the carbon emission update delay impact value is obtained by analyzing the proportion of the average carbon emission update delay and the preset average carbon emission update delay. Second, after analyzing the proportion of the average carbon emission increase rate and the preset average carbon emission increase rate, a weighted calculation is performed using the preset first carbon emission delay weight and the carbon emission update delay impact value to obtain the carbon emission delay-increase rate analysis value. This value reflects the comprehensive impact of the average carbon emission update delay and the average carbon emission increase rate on the ability to update food carbon footprint information (e.g., total greenhouse gas emissions, food transportation time, etc.) within the qualified preset time period. Third, after analyzing the proportion of the average transfer delay time at transportation points within the qualified preset time period and the preset average transfer delay time, a weighted calculation is performed using the preset second carbon emission delay weight and the carbon emission update delay impact value to obtain the carbon emission delay-increase rate analysis value. The carbon emission delay-transfer delay analysis value reflects the combined impact of the average carbon emission update delay duration and the average transfer delay time at transport points on the ability to update food carbon footprint information within a qualified preset time period. After analyzing the proportion of food spoilage rate and preset food spoilage rate, a weighted calculation is performed using preset third carbon emission delay weights and the impact value of carbon emission update delay to obtain the carbon emission delay-increased food spoilage analysis value, which reflects the combined impact of the average carbon emission update delay duration and food spoilage rate on the ability to update food carbon footprint information within a qualified preset time period. After coupling food carbon footprint information update data, a weighted calculation is performed using preset carbon emission delay weights to obtain the food and carbon emission update delay value. The food and carbon emission update delay value reflects the combined effect of the qualified preset time period carbon footprint information update parameters and preset carbon footprint information update parameters on the ability to update food carbon footprint information. Food carbon footprint information update data includes the carbon emission delay-increase rate analysis value, the carbon emission delay-transfer delay analysis value, and the carbon emission delay-increased food spoilage analysis value. A qualified preset time period indicates a preset time period corresponding to a food transfer delay impact assessment value that is not greater than the preset transfer delay impact threshold.

[0047] The updated delay values ​​for food and carbon emissions were obtained using the following methods:

[0048] ;

[0049] In the formula, This represents the update delay value for food and carbon emissions in the Yth qualified preset time period. Y represents the number of the qualified preset time period, and H represents the total number of qualified preset time periods. This represents the carbon emission delay-increase rate analysis value for the Yth qualified preset time period. This represents the carbon emission delay-transportation delay analysis value for the Yth qualified preset time period. This represents the carbon emission delay-increase food spoilage analysis value for the Yth qualified preset time period. This represents the average carbon emission update delay time for the Yth qualified preset time period. This indicates the preset carbon emission delay weight.

[0050] Specifically, In the formula This indicates the preset first carbon emission delay weight. This represents the average rate of increase in carbon emissions during the Yth qualified preset time period. This indicates the preset average rate of increase in carbon emissions.

[0051] In the formula This indicates a preset second carbon emission delay weight. This represents the average transfer delay time at the transport point for the Yth qualified preset time period. This indicates the preset average transit delay time.

[0052] In the formula This indicates a preset third carbon emission delay weight. This represents the food spoilage rate during the Yth qualified preset time period. This indicates the preset food spoilage rate.

[0053] In the formula This represents the impact value of the carbon emission update delay for the Yth qualified preset time period. This indicates the preset average carbon emission update delay time.

[0054] In this embodiment, food information with a spoilage rate greater than a preset spoilage rate is classified as Level 1 food waste risk, and the accuracy of carbon footprint information updates is monitored. Level 1 food waste risk may have a greater impact on the ability to update food carbon footprint information, which helps to more accurately track the carbon footprint of food and effectively identify and manage food waste risks.

[0055] This embodiment analyzes food carbon footprint information update data to determine the impact value of carbon emission update delay. A larger carbon emission delay-rate of increase analysis value indicates a stronger combined impact of the average carbon emission update delay duration and the average rate of increase in carbon emissions on the ability to update food carbon footprint information, resulting in a larger impact value for carbon emission update delay. Similarly, a larger carbon emission delay-transfer delay analysis value indicates a stronger combined impact of the average carbon emission update delay duration and the average transfer delay time at transport points on the ability to update food carbon footprint information, resulting in a larger impact value for carbon emission update delay. Likewise, a larger carbon emission delay-food spoilage analysis value indicates a stronger combined impact of the average carbon emission update delay duration and the food spoilage rate on the ability to update food carbon footprint information, resulting in a larger impact value for carbon emission update delay. In summary, food carbon footprint information update data and the impact value of carbon emission update delay are directly proportional.

[0056] In this embodiment, the carbon footprint information update parameters are not independent but interrelated, requiring comprehensive analysis. The average rate of increase in carbon emissions necessitates more frequent updates to maintain accuracy and timeliness. However, frequent updates may increase the average carbon emission update delay, failing to reflect actual changes in carbon emissions in a timely manner. A longer average transit delay at transport points likely means longer food stays during transport, increasing carbon emissions and potentially leading to a higher average rate of increase in carbon emissions. Food spoilage rate reflects quality loss during transport and storage; a higher spoilage rate suggests food is more prone to deterioration during transport, increasing carbon emissions and consequently increasing both average transit delay at transport points and average carbon emission update delay. By analyzing the combined effects of these parameters, a precise assessment of food transport delay data update capabilities is achieved, thereby improving the accuracy of risk management in the food supply chain based on carbon footprint detection.

[0057] Furthermore, the specific process for determining whether to update and optimize food carbon footprint information is as follows: The food carbon emission update delay value is compared with a preset carbon emission update delay threshold obtained from the database; when the food carbon emission update delay value is greater than the preset carbon emission update delay threshold, the food carbon footprint information is updated and optimized, and the corresponding food information is marked as food information to be optimized; when the food carbon emission update delay value is not greater than the preset carbon emission update delay threshold, the food carbon footprint information is not updated and optimized, and the corresponding food information is updated to the preset data center; the food carbon footprint information update optimization is used to improve the ability to update food carbon footprint information within a qualified preset time period.

[0058] It should be added that the specific process for updating and optimizing food carbon footprint information is as follows: Monitor the carbon emission increment deviation within a qualified preset time period and determine whether the carbon emission increment deviation meets the increment qualification condition; when the carbon emission increment deviation meets the increment qualification condition, update the corresponding food information to the preset data center; when the carbon emission increment deviation does not meet the increment qualification condition, perform second sidechain transfer optimization; the second sidechain transfer optimization is used to improve the updating capability of food transportation delay data corresponding to the food information to be optimized on the second sidechain; the increment qualification condition means that the carbon emission increment deviation is not greater than 0; the carbon emission increment deviation is obtained by calculating the difference between the carbon emission increase amount within the qualified preset time period and the preset increase threshold.

[0059] In this embodiment, the preset carbon emission update delay threshold is represented by the average value of food and carbon emission update delay values ​​over a historical time period, and the preset increase threshold is represented by the average value of carbon emission increase over a historical time period. When the food and carbon emission update delay values ​​are greater than the preset carbon emission update delay threshold, the corresponding food information is marked as food information to be optimized and the food carbon footprint information is updated and optimized. By transferring the food transportation delay data corresponding to food information whose carbon emission increment deviation does not meet the increment qualification conditions to the second side chain, the updating capability of food transportation delay data on the second side chain is improved, while reducing the burden of main chain data processing. This helps the system to respond quickly and update food information to ensure the accuracy and timeliness of carbon footprint data, thereby improving the accuracy of risk management of the food supply chain based on carbon footprint detection.

[0060] Furthermore, the specific process for optimizing the second sidechain is as follows: W1, send a prompt to transfer the food information to be optimized, indicating that the preset personnel are prompted to transfer the food information to be optimized from the main chain to the second sidechain using the sidechain method; W2, set the number of nodes in the second sidechain, indicating that the number of backup computing nodes on the second sidechain is set according to a preset ratio; W3, set the update frequency of the second sidechain, stopping the operation when the monitored food and carbon emission update delay values ​​are not greater than the preset carbon emission update delay threshold, indicating that the update frequency of the food information to be optimized on the second sidechain is set according to a preset ratio; the second sidechain is used to process the food transportation delay data corresponding to the food information to be optimized.

[0061] like Figure 2The diagram shows a flowchart of a risk management method based on a food supply chain provided in this application embodiment. This application embodiment provides a risk management method based on a food supply chain, including the following steps: S1, Food transfer and delay monitoring: Based on the acquired food transfer delay parameters, food transfer and delay monitoring is performed, and it is determined whether food transfer delay optimization should be carried out; S2, Food waste risk assessment: If food transfer delay optimization is not performed, a food waste risk level assessment is performed; S3, Carbon footprint information update accuracy monitoring: Based on the acquired carbon footprint information update parameters, the accuracy of carbon footprint information updates is monitored, and it is determined whether food carbon footprint information update optimization should be carried out.

[0062] In this embodiment, when a second sidechain transfer optimization prompt is received, the number of backup computing nodes on the second sidechain is gradually increased by a corresponding preset ratio by monitoring the ratio between the increase in carbon emissions and a preset increase threshold. Similarly, the update frequency of the food information to be optimized on the second sidechain is gradually increased by monitoring the ratio between the food and carbon emission update delay values ​​and a preset carbon emission update delay threshold. The second sidechain is specifically used to process food transportation delay data corresponding to the food information to be optimized, which helps to separate food transportation delay data from the main chain, ensuring the stability and efficiency of the main chain. By increasing the number of nodes and adjusting the update frequency, the timeliness and accuracy of the food information to be optimized can be ensured, thereby improving the accuracy of risk management in the food supply chain based on carbon footprint detection.

[0063] In summary, by acquiring food transportation delay parameters, monitoring food transportation and delays is conducted, and it is determined whether food transportation delay optimization should be implemented. If food transportation delay optimization is not implemented, a food waste risk level assessment is performed. Finally, by acquiring carbon footprint information update parameters, the accuracy of carbon footprint information updates is monitored, and it is determined whether food carbon footprint information updates should be optimized. This improves the accuracy of food waste risk level assessment and carbon footprint information updates, thereby enhancing the accuracy of risk management in the food supply chain based on carbon footprint detection. This effectively solves the problem of low data accuracy in risk management of the food supply chain based on carbon footprint detection in existing technologies.

[0064] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0065] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0066] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0067] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0068] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0069] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A risk management system based on the food supply chain, characterized in that, This includes modules for monitoring food transportation and delays, assessing food waste risks, and monitoring the accuracy of carbon footprint information updates. The food transfer and delay monitoring module is used to monitor food transfer and delay based on the acquired food transfer delay parameters, and to determine whether to optimize food transfer delay. The food waste risk assessment module is used to assess the food waste risk level if food transportation delays are not optimized. The carbon footprint information update accuracy monitoring module is used to monitor the accuracy of carbon footprint information updates based on the acquired carbon footprint information update parameters, and to determine whether to optimize the update of food carbon footprint information. The food transfer delay parameters include average transfer delay time at transport points, number of food transfers, average food transport time, average distance to transport points, and food shelf life. The food transport delay parameter is used in conjunction with a preset food transport delay parameter obtained from the database to jointly affect the food transport delay data; The carbon footprint information update parameters include average carbon emission update delay time, average carbon emission increase rate, average transit delay time at transport points, and food spoilage rate. The carbon footprint information update parameters are used in conjunction with preset carbon footprint information update parameters obtained from the database to jointly affect the food carbon footprint information update data; The specific process for monitoring food transportation and delays based on the acquired food transportation delay parameters is as follows: Food transport delay data is obtained by processing the food transport delay parameters and the preset food transport delay parameters obtained from the database. Determine whether the average transfer delay time at the transportation point is greater than 0. If the average transfer delay time at the transportation point is not greater than 0, do not monitor food transfer and delay, and update the corresponding food information to the preset data center. When the average transfer delay time at the transportation point is greater than 0, the food transfer delay impact assessment value is obtained by combining the preset comprehensive delay impact weight and the results of the proportion analysis of the average transfer delay time at the transportation point and the preset average transfer delay time, and by superimposing and weighting the coupled food transfer delay data. The food transport delay data processing includes food delay and transport processing, food delay and transport time processing, food delay and transport distance processing, and food delay and food shelf life processing. The food delay and transfer processing is used to analyze the proportion of food transfer times and preset food transfer times, and then perform weighted calculations based on the preset first transfer delay impact weight to obtain the food delay and transfer processing value. The food delay and transfer processing value is used to reflect the effect of food transfer times on the ability to update food transportation delay data. The food delay and transportation time processing is used to analyze the proportion of average food transportation time and preset average food transportation time, and then perform weighted calculations based on preset second transfer delay impact weights to obtain the food delay and transportation time processing value. The food delay and transportation time processing value is used to reflect the effect of average food transportation time on the ability to update food transportation delay data. The food delay and transportation distance processing is used to analyze the proportion of the average transportation point distance and the preset average transportation point distance, and then perform weighted calculations based on the preset third transfer delay impact weight to obtain the food delay and transportation distance processing value. The food delay and transportation distance processing value is used to reflect the effect of the average transportation point distance on the ability to update food transportation delay data. The food delay and food shelf life handling are used to analyze the proportion of preset food shelf life and food shelf life, and then perform weighted calculations based on the preset fourth transit delay impact weight to obtain the food delay and food shelf life handling values. The food delay and food shelf life handling values ​​are used to reflect the effect of food shelf life on the ability to update food transportation delay data. The food transport delay data includes food delay and transport processing values, food delay and transport time processing values, food delay and transport distance processing values, and food delay and food shelf-life processing values. The food transport delay impact assessment value is used to reflect the combined effect of the food transport delay parameter and the preset food transport delay parameter on the ability to update food transport delay data. The specific process for monitoring the accuracy of carbon footprint information updates based on the acquired carbon footprint information update parameters is as follows: Determine whether the average carbon emission update delay time is greater than 0. If the average carbon emission update delay time is not greater than 0, do not monitor the accuracy of carbon footprint information updates, and update the corresponding food information to the preset data center. When the average carbon emission update delay time is greater than 0, the impact value of carbon emission update delay is obtained by analyzing the proportion of the average carbon emission update delay time and the preset average carbon emission update delay time. After analyzing the proportion of the average increase rate of carbon emissions and the preset average increase rate of carbon emissions, a weighted calculation is performed by combining the preset first carbon emission delay weight and the carbon emission update delay impact value to obtain the carbon emission delay-increase rate analysis value, which is used to reflect the comprehensive impact of the average carbon emission update delay duration and the average increase rate of carbon emissions on the ability to update food carbon footprint information within the qualified preset time period. After analyzing the proportion of the average transfer delay time at transportation points during the qualified preset time period and the preset average transfer delay time, the carbon emission delay-transfer delay analysis value is obtained by weighting the preset second carbon emission delay weight and the carbon emission update delay impact value. This value is used to reflect the comprehensive impact of the average carbon emission update delay time and the average transfer delay time at transportation points on the ability to update food carbon footprint information. After analyzing the proportion of food spoilage rate and preset food spoilage rate, a weighted calculation is performed by combining the preset third carbon emission delay weight and the carbon emission update delay impact value to obtain the carbon emission delay-increase food spoilage analysis value, which is used to reflect the comprehensive impact of the average carbon emission update delay duration and food spoilage rate on the ability to update food carbon footprint information within the qualified preset time period. After coupling the updated food carbon footprint information data, the updated food and carbon emission delay values ​​are obtained by weighting the data with preset carbon emission delay weights. The food and carbon emission update delay value is used to reflect the combined effect of the qualified preset time period carbon footprint information update parameters and the preset carbon footprint information update parameters on the food carbon footprint information update capability. The updated food carbon footprint information includes carbon emission delay-increase rate analysis values, carbon emission delay-transfer delay analysis values, and carbon emission delay-increase food spoilage analysis values.

2. The risk management system based on the food supply chain as described in claim 1, characterized in that, The specific process for determining whether to optimize food transport delays is as follows: When the assessment value of the impact of food transportation delay exceeds the preset threshold for the impact of transportation delay, the corresponding food information is marked as delayed food information, and food transportation delay optimization is performed. When the assessment value of the impact of food transportation delay is not greater than the preset threshold for the impact of transportation delay, no food transportation delay optimization will be performed, but a food waste risk level assessment will be conducted. The specific steps for optimizing food transport delays are as follows: The first step is to send a delayed food information transfer prompt, which indicates that a preset person is prompted to transfer the delayed food information from the main chain to the first side chain through a side chain method. The first side chain is used to process the food transportation delay data corresponding to the delayed food information. The second step is to set the number of nodes in the first sidechain. Setting the number of nodes in the first sidechain means setting the number of spare computing nodes on the first sidechain according to a preset ratio. The third step is to set the update frequency of the first side chain. When the monitored food transportation delay impact assessment value is not greater than the preset transportation delay impact threshold, the operation is stopped. The first side chain update frequency setting means setting the update frequency of delayed food information on the first side chain according to a preset ratio. The food transport delay optimization is used to improve the ability to update food transport delay data within a preset time period.

3. The risk management system based on the food supply chain as described in claim 1, characterized in that, The specific process for assessing the risk level of food waste is as follows: The food spoilage rate is monitored within a preset time period, and the food spoilage rate is obtained by analyzing the proportion of spoiled food to the total amount of transported food within the preset time period. When the monitored food spoilage rate exceeds the preset food spoilage rate, the corresponding food information will be classified as a Level 1 food waste risk. Monitor the accuracy of carbon footprint information updates for food products within the first-level risk range of food waste. When the monitored food spoilage rate is not greater than the preset food spoilage rate, the corresponding food information is classified as a level 2 risk of food waste, and no carbon footprint information update accuracy monitoring is performed.

4. The risk management system based on the food supply chain as described in claim 1, characterized in that, The specific process for determining whether to update and optimize food carbon footprint information is as follows: When the food carbon emission update delay value is greater than the preset carbon emission update delay threshold, the food carbon footprint information is updated and optimized, and the corresponding food information is marked as food information to be optimized. When the food and carbon emission update delay values ​​are not greater than the preset carbon emission update delay threshold, the food carbon footprint information will not be updated and optimized, and the corresponding food information will be updated to the preset data center. The optimization of food carbon footprint information updates is used to improve the ability to update food carbon footprint information within a qualified preset time period.

5. The risk management system based on the food supply chain as described in claim 1, characterized in that, The specific process for updating and optimizing food carbon footprint information is as follows: Monitor the carbon emission increment deviation within a pre-defined qualified time period and determine whether the carbon emission increment deviation meets the increment qualification conditions. When the deviation of carbon emission increment meets the increment qualification conditions, the corresponding food information will be updated to the preset data center; When the deviation of carbon emission increment does not meet the increment qualification conditions, second side chain transfer optimization is performed. The second sidechain transfer optimization is used to improve the update capability of food transportation delay data corresponding to the food information to be optimized on the second sidechain; The incremental qualification condition means that the deviation of carbon emission increment is not greater than 0.

6. The risk management system based on the food supply chain as described in claim 5, characterized in that, The specific process for optimizing the second sidechain transfer is as follows: W1, send a prompt to transfer food information to be optimized, the prompt indicating that a preset person is prompted to transfer the food information to be optimized from the main chain to the second side chain through the side chain method; W2, set the number of second sidechain nodes. The setting of the number of second sidechain nodes means setting the number of spare computing nodes on the second sidechain according to a preset ratio. W3, set the second side chain update frequency. When the monitored food and carbon emission update delay value is not greater than the preset carbon emission update delay threshold, stop the operation. The second side chain update frequency setting means setting the update frequency of the food information to be optimized on the second side chain according to a preset ratio. The second sidechain is used to process food transportation delay data corresponding to the food information to be optimized.

7. A risk management method based on the food supply chain, applied to the risk management system based on the food supply chain as described in any one of claims 1-6, characterized in that, Includes the following steps: S1, based on the acquired food transfer delay parameters, monitor food transfer and delay, and determine whether to optimize food transfer delay. S2, If food transfer delay optimization is not carried out, then a food waste risk level assessment is conducted; S3. Based on the acquired carbon footprint information update parameters, monitor the accuracy of carbon footprint information updates and determine whether to optimize the update of food carbon footprint information.

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