Food safety tracing method and system based on multi-source monitoring

Abstract

The invention discloses a food safety tracing method and system based on multi-source monitoring, and relates to the technical field of data management, and the method comprises the steps: carrying out the full-period monitoring of target food, and obtaining target multi-source data; obtaining a first target data preprocessing result of the first link; a target monitoring data chain established based on the first corresponding relation is stored in the target digital middle station; traversing in a food safety database to obtain a first suspicious link set; performing data analysis to obtain a first analysis result set; screening according to a predetermined screening strategy to obtain a target abnormal result; and tracing and rectifying the target abnormal link. The technical problems that existing food safety tracing is limited to a single data source and processing means, full-cycle monitoring of food is difficult, and then accuracy and efficiency of food safety tracing are poor are solved, centralized management and convenient query of food full-cycle data are achieved, and the food safety tracing efficiency is improved. The technical effect of improving the accuracy and efficiency of food safety tracing is achieved.

Description

Technical Field

[0001] This application relates to the technical field of data management, and particularly to a food safety traceability method and system based on multi-source monitoring. Background Art

[0002] Today, with the increasing globalization, the complexity and diversification of the food supply chain and consumers' high attention to food safety have made food safety traceability a crucial issue. With the rapid development of technologies such as the Internet of Things, big data, and cloud computing, multi-source monitoring devices have been widely used, making it possible to monitor the entire life cycle of food, collect data in real time at all links such as food production, processing, transportation, and sales, and form target multi-source data, providing a rich data basis for food safety traceability. However, traditional food safety traceability often relies on a single monitoring method and data source, unable to achieve full-cycle monitoring, and the processing of a large amount of data by a single data center may lead to low processing efficiency, making it difficult to quickly locate food safety problems and conduct analysis, which greatly limits the accuracy and efficiency of food safety traceability.

[0003] Therefore, in the current technologies related to food safety traceability, there are technical problems such as being limited to a single data source and processing method, being difficult to conduct full-cycle monitoring of food, and thus resulting in poor accuracy and efficiency of food safety traceability. Summary of the Invention

[0004] This application provides a food safety traceability method and system based on multi-source monitoring. By adopting technical means such as full-cycle monitoring, establishing a data chain, and data preprocessing, it solves the technical problems existing in the existing food safety traceability, such as being limited to a single data source and processing method, being difficult to conduct full-cycle monitoring of food, and thus resulting in poor accuracy and efficiency of food safety traceability, realizes the centralized management and convenient query of food full-cycle data, and achieves the technical effect of improving the accuracy and efficiency of food safety traceability.

[0005] This application provides a food safety traceability method based on multi-source monitoring. The method includes: performing full-cycle monitoring on a target food through multi-source monitoring devices to obtain target multi-source data; traversing and matching a distributed data center and activating a first edge data center to process and analyze first target data in the target multi-source data, obtaining a preprocessing result of the first target data in the first link, where the first target data corresponds to the first link in the full cycle; obtaining a first correspondence between the first link and the preprocessing result of the first target data, and storing a target monitoring data chain formed based on the first correspondence in a target digital middle platform; obtaining a first food safety problem of the target food, and traversing in a food safety database to obtain a first set of suspicious links; combining the target digital middle platform to perform data analysis on the first set of suspicious links to obtain a first analysis result set; reading a predetermined screening policy, and screening the first analysis result set according to the predetermined screening policy to obtain a target abnormal result; and tracing and rectifying a target abnormal link corresponding to the matched target abnormal result.

[0006] In a possible implementation, traversing and matching a distributed data center and activating a first edge data center to process and analyze first target data in the target multi-source data, obtaining a preprocessing result of the first target data in the first link, further performs the following processing: matching a first monitoring device of the first target data in the multi-source monitoring device; reading a predetermined environmental dimension, and collecting the environment of the first link based on the predetermined environmental dimension to obtain first environmental information; introducing a monitoring loss analysis function to analyze the first environmental information and the first monitoring device to obtain the preprocessing result of the first target data, where the expression of the monitoring loss analysis function is as follows: ; Where refers to the first target data of the preprocessing result of the first target data, refers to the ideal monitoring accuracy of the first monitoring device, refers to the total influence coefficient of the first environmental information on the ideal monitoring accuracy of the first monitoring device, refers to the th environmental feature among environmental features in the first environmental information, refers to the th environmental feature and the th correlation coefficient of the accuracy of the first monitoring device, refers to the th weight coefficient of the correlation coefficient, and .

[0007] In a possible implementation, traverse and match the distributed data centers and activate the first edge data center to process and analyze the first target data in the target multi-source data, and obtain the preprocessing result of the first target data in the first link, and perform the following processing: The environmental features at least include environmental temperature, environmental humidity, environmental network coverage rate, and environmental network stability.

[0008] In a possible implementation, obtain the first safety problem of the target food, traverse the food safety database to obtain the first set of suspicious links, and also perform the following processing: obtain the historical safety traceability records of the same kind of food of the target food, and the historical safety traceability records include multiple historical records; obtain any safety problem, and traverse and screen the any safety problem in the multiple historical records to obtain the any safety problem record set; perform a union operation on the first abnormal link in the first record to obtain the any safety problem suspicious link set, where the first record refers to any record in the any safety problem record set; construct the food safety database according to the mapping relationship between the any safety problem and the any safety problem suspicious link set.

[0009] In a possible implementation, read the predetermined screening strategy, and screen the first analysis result set according to the predetermined screening strategy to obtain the target abnormal result, and also perform the following processing: traverse the target monitoring data chain in the target digital middle platform based on the first set of suspicious links to obtain the first set of suspicious link data; extract the first link data in the first set of suspicious link data, and compare the first link data with the first predetermined link data to obtain the first link data difference; sort the first set of suspicious links in descending order based on the first link data difference to obtain the first set of suspicious link sequences; screen the first set of suspicious link sequences in combination with the predetermined screening ratio in the predetermined screening strategy to obtain the target set of abnormal links; use the target set of abnormal links as the target abnormal result.

[0010] In a possible implementation, trace and rectify the target abnormal link corresponding to the matched target abnormal result, and also perform the following processing: obtain the first abnormal link in the target set of abnormal links; if the first data difference corresponding to the first abnormal link does not reach the first data difference limit value, issue a full trace command; perform a full-cycle safety trace of the target food based on the full trace command.

[0011] In a possible implementation, trace and rectify the target abnormal link corresponding to the matched target abnormal result, and also perform the following processing: The first data difference limit value is determined by analyzing the first data interval of the first abnormal link.

[0012] The present application also provides a food safety traceability system based on multi-source monitoring, including: a target multi-source data acquisition module, which is used to perform full-cycle monitoring on target foods through multi-source monitoring devices to obtain target multi-source data; a data preprocessing result acquisition module, which is used to traverse and match a distributed data center and activate a first edge data center to process and analyze the first target data in the target multi-source data to obtain a first target data preprocessing result for the first link, where the first target data corresponds to the first link in the full cycle; a target monitoring data chain construction module, which is used to obtain a first correspondence between the first link and the first target data preprocessing result, and store the target monitoring data chain constructed based on the first correspondence in a target digital middleware; a first suspicious link set acquisition module, which is used to obtain a first food safety problem of the target food and traverse in a food safety database to obtain a first suspicious link set; a first analysis result set acquisition module, which is used to perform data analysis on the first suspicious link set in combination with the target digital middleware to obtain a first analysis result set; a target abnormal result acquisition module, which is used to read a predetermined screening strategy and screen the first analysis result set according to the predetermined screening strategy to obtain a target abnormal result; a target abnormal link traceability and rectification module, which is used to trace and rectify the target abnormal link corresponding to the matched target abnormal result.

[0013] It is intended to solve the technical problems existing in the existing food safety traceability, such as being limited to a single data source and processing means and being difficult to perform full-cycle monitoring on foods, which in turn leads to poor accuracy and efficiency of food safety traceability, by means of the food safety traceability method and system based on multi-source monitoring proposed in the present application. It realizes the centralized management and convenient query of full-cycle data of foods, and achieves the technical effect of improving the accuracy and efficiency of food safety traceability. Brief Description of the Drawings

[0014] To more clearly illustrate the technical solutions of the embodiments of the present disclosure, the accompanying drawings of the embodiments of the present disclosure will be briefly introduced below. Flowcharts are used in this application to illustrate the operations performed by the systems according to the embodiments of this application. It should be understood that the operations above or below do not necessarily need to be executed precisely in sequence. On the contrary, as needed, various steps can be processed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or several operations can be removed from these processes.

[0015] Figure 1 It is a schematic flowchart of the food safety traceability method based on multi-source monitoring provided by the embodiments of this application; Figure 2 It is a schematic structural diagram of the food safety traceability system based on multi-source monitoring provided by the embodiments of this application.

[0016] Description of the reference numerals: Target multi-source data acquisition module 10, data preprocessing result acquisition module 20, target monitoring data chain formation module 30, first set of suspicious links acquisition module 40, first set of analysis results acquisition module 50, target abnormal result acquisition module 60, target abnormal link traceability and rectification module 70. Detailed Embodiments

[0017] The above description is only an overview of the technical solutions of this application. In order to be able to understand the technical means of this application more clearly, it can be implemented in accordance with the content of the specification. And in order to make the above and other purposes, features and advantages of this application more obvious and understandable, the following specifically illustrates the detailed embodiments of this application.

[0018] In order to make the purpose, technical solutions and advantages of this application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limitations of the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of this application.

[0019] In the following description, "some embodiments" are involved, which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict. The terms "first / second" involved are only used to distinguish similar objects and do not represent a specific order for the objects. The terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or server that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application.

[0020] An embodiment of this application provides a food safety traceability method based on multi-source monitoring, as Figure 1 shown, the method includes: Step S100, perform full-cycle monitoring on the target food through multi-source monitoring devices to obtain target multi-source data. Use various monitoring devices and means from different sources to conduct all-round and multi-angle real-time monitoring and data collection on the target food from various links such as production, processing, transportation to sales. The monitoring devices include but are not limited to Internet of Things sensors, cameras, detection instruments, etc., which can obtain and record key data such as the status, environmental parameters, and quality indicators of the food at each stage in real time. Specifically, the full-cycle monitoring of food may include the following stages: production stage, processing stage, transportation stage, sales stage, etc. For example, use sensors to monitor conditions such as temperature, humidity, and light in the production environment to ensure that the food is produced in a suitable environment, use cameras to monitor the production site and record the production process to ensure standard operations and avoid contamination, and use detection instruments to detect raw materials to ensure that the raw material quality meets the standards; use sensors to monitor key parameters such as temperature, pressure, and time during the processing process to ensure that the processing technology meets the requirements, monitor the operating status of the processing equipment to ensure normal operation of the equipment and avoid faults affecting food quality, and detect semi-finished products during the processing process, such as microbial detection, additive detection, etc., to ensure that the food is not contaminated or damaged during the processing process; use GPS and sensor technologies to monitor information such as the location, speed, and temperature of transportation vehicles in real time to ensure that the food is in a suitable environmental condition during transportation, monitor abnormal conditions such as vibration and impact during transportation, and discover and handle potential risks in a timely manner; install cameras and sensors at the sales point to monitor the storage environment, sales situation, etc. of the food in real time, and conduct quality inspections on the food to be sold to ensure that the food meets the quality standards before sale. These monitoring data are the target multi-source data, which provide rich information support for food safety traceability and help to discover and handle food safety problems in a timely manner.

[0021] Step S200: Traverse and match the distributed data centers and activate the first edge data center to process and analyze the first target data in the target multi-source data, obtaining the preprocessing result of the first target data in the first stage, where the first target data corresponds to the first stage in the whole cycle. Among the target multi-source data obtained from the whole food cycle monitoring, select the data (i.e., the first target data) related to a specific stage (i.e., the first stage), and use the first edge data center in the distributed data center to efficiently and quickly process and analyze this data to obtain the preprocessing result at this stage. Specifically, the target multi-source data refers to various data collected by multi-source monitoring devices during the whole food cycle (including production, processing, transportation, sales, etc.), from different sensors, cameras, detection instruments, etc., and covers various environmental parameters and quality indicators in the whole food cycle. The first stage refers to any stage in the whole food cycle, such as the production stage or the processing stage, etc. The first target data refers to the part of the data extracted from the target multi-source data related to the first stage, reflecting the state and quality of the food at this stage. The distributed data center is a network composed of multiple data centers for storing, processing, and analyzing a large amount of data. Data can be backed up and load-balanced among multiple data centers, ensuring the efficient processing and high availability of data. The first edge data center is a data center close to the food data source in the distributed data center network, which can respond to data requests faster and reduce the data transmission delay. The first edge data center is responsible for processing and analyzing the real-time food monitoring data in the first stage. The preprocessing result of the first target data is the result obtained by the first edge data center processing and analyzing the first target data, which may include data cleaning, format conversion, feature extraction, etc., for facilitating subsequent data analysis and visualization.

[0022] In a possible implementation, step S200 further includes step S210: Match the first monitoring device of the first target data in the multi-source monitoring device. The multi-source monitoring device refers to various monitoring devices of different sources and types for collecting data in food safety traceability, including sensors, detectors, measuring instruments, etc., used to capture various data related to food safety, quality control, or other monitoring objectives. In the multi-source monitoring device, match the first monitoring device of the first target data, that is, find the specific monitoring device used to collect or generate the first target data. For example, determine which monitoring point or which stage the first target data comes from, and according to the characteristics of the first target data, find the monitoring device with the corresponding function. For example, if the first target data is temperature data, then a monitoring device for measuring temperature needs to be found to ensure that the first monitoring device can communicate with the system effectively to transmit the collected data to the subsequent processing stage.

[0023] Step S200 further includes step S220, which reads the predetermined environmental dimensions and collects the environment of the first link based on the predetermined environmental dimensions to obtain the first environmental information. The predetermined environmental dimensions refer to the environmental parameters or characteristics that have been set in advance and need to be concerned about or measured before monitoring or data collection, such as temperature, humidity, light, air pressure, air quality, etc. Reading the predetermined environmental dimensions means determining the specific parameters or characteristics to be measured, that is, clarifying the environmental dimensions to be monitored, and then collecting the environment of the first link based on the predetermined environmental dimensions, that is, using corresponding monitoring devices (such as sensors, detectors, etc.) to collect the environmental information of the first link, including measurement data of each dimension, which is the environmental information of the first link corresponding to the predetermined environmental dimensions, such as temperature values, humidity values, light intensities, air pressure values and other related data.

[0024] Step S200 further includes step S230, which introduces a monitoring loss analysis function to analyze the first environmental information and the first monitoring device to obtain the first target data preprocessing result. The monitoring loss analysis function is used to analyze the relationship between the first environmental information and the first monitoring device and quantify the loss or error in this relationship. By introducing the monitoring loss analysis function, the accuracy and reliability of the first environmental information and the performance of the first monitoring device can be evaluated. Specifically, the first environmental information and the output data of the first monitoring device are integrated to form environmental information obtained from multiple sources (i.e., different monitoring devices). The monitoring loss analysis function is used to calculate the difference or loss between the actual measurement value (i.e., the first environmental information) and the output value of the monitoring device and generate a loss value or loss index. According to the result of the loss analysis, the accuracy of the first environmental information and the performance of the first monitoring device can be judged. If the loss value is small, it indicates that the first environmental information is relatively accurate and the monitoring device has good performance; otherwise, there may be errors or problems. Based on the result of the monitoring loss analysis, preprocessing is performed to obtain the first target data and the processing result.

[0025] The expression of the monitoring loss analysis function is as follows: ; where refers to the first target data of the first target data preprocessing result, refers to the ideal monitoring accuracy of the first monitoring device, refers to the total influence coefficient of the first environmental information on the ideal monitoring accuracy of the first monitoring device, refers to the th environmental feature among the environmental features in the first environmental information, refers to the The correlation coefficient between an environmental feature and the accuracy of the first monitoring device , refers to the weight coefficient of the th correlation coefficient, and .

[0026] In a possible implementation manner, the environmental features in step S230 at least include environmental temperature, environmental humidity, environmental network coverage rate, and environmental network stability. Among them, the environmental network coverage rate refers to the area or range covered by network devices (such as base stations, routers, etc.) within a specific area, which directly affects the reliability and efficiency of communication between wireless communication and Internet of Things devices. The higher the network coverage rate, the smoother the communication between devices. Otherwise, problems such as communication interruption or delay may occur. The environmental network stability refers to the persistence and reliability of the network connection. In a stable network environment, the communication between devices can be continuous, and the data transmission delay and packet loss rate are both low. If the network environment is unstable, the communication between devices may be interfered with or interrupted, resulting in data transmission errors or delays. Maintaining network stability is crucial for ensuring the normal operation of devices and accurate data transmission.

[0027] Step S300: Obtain the first correspondence between the first link and the first target data preprocessing result, and store the target monitoring data chain formed based on the first correspondence in the target digital middle platform. In the full-cycle monitoring of food, each link (such as the first link) corresponds to a specific set of target multi-source data (i.e., the first target data). After the first edge data center processes and analyzes the first target data, the first target data preprocessing result under this link will be obtained. Establishing and obtaining the correspondence between the first link and the first target data preprocessing result, that is, clarifying which data of which link has been processed to obtain which results. The target monitoring data chain is a logically interconnected data set that contains the data and processing results of each link in the food full cycle. Specifically, based on the first correspondence between the first link and the first target data preprocessing result, these data and processing results are organized according to their chronological order and logical association in the food full cycle to form a complete data chain, which not only records the status and changes of food in each link but also includes the data flow and dependency relationships between links. Among them, the target digital middle platform is used to store and manage the data and results of food full-cycle monitoring, providing data storage, query, and analysis processing. The system stores the formed target monitoring data chain in the target digital middle platform for subsequent data analysis and traceability, realizing the organization and storage from the original monitoring data to the processing results, ensuring the integrity and traceability of the data, and providing reliable data support for food safety traceability.

[0028] Step S400: Obtain the first food safety issue of the target food and traverse the food safety database to obtain the first set of suspicious links. The first food safety issue of the target food may include microbial contamination, chemical residue, expiration, etc., which can be obtained by conducting quality inspections on the target food, user feedback, etc. The food safety database is a database that stores information such as data on each link in the food safety cycle, test results, and problem records. After determining the first food safety issue of the target food, traverse this food safety database, search for all records and data related to this safety issue, and then identify all links related to the first food safety issue. These links may be the key points that cause the safety issue or the links affected by the safety issue. After identifying the links related to the problem, form a set of these links, that is, the first set of suspicious links, which contains all links that may be related to the first food safety issue and is the key object for subsequent analysis and traceability.

[0029] In a possible implementation, step S400 further includes step S410: Obtain the historical safety traceability records of the same-type foods of the target food, and the historical safety traceability records include multiple historical records. The same-type foods refer to foods that are similar to the target food in terms of type, ingredients, production process, etc., such as belonging to the same category, the same brand, or the same production line. The historical safety traceability records include multiple historical records, and each record corresponds to a specific production batch or sales batch. Each record may include basic information, raw material information, processing information, transportation and sales information, inspection information, etc., and is arranged in chronological order to form a complete traceability chain.

[0030] Step S400 also includes step S420: Obtain any food safety issue, and traverse and filter the any food safety issue in the multiple historical records to obtain an any food safety issue record set. The historical record set refers to multiple historical safety traceability records of the same-type foods collected previously, which contains detailed information on each link from the production to the sales of the food. Specifically, first clarify a specific food safety issue, such as microbial contamination, excessive food additives, damaged packaging, etc., and conduct a detailed inspection and analysis of each historical record to find the records related to the any food safety issue. Extract all historical records related to the any food safety issue to form a new set, that is, the food safety issue record set.

[0031] Step S400 further includes step S430 of performing a union operation on the first abnormal links in the first record to obtain a set of any suspicious links for safety issues, where the first record refers to any one record in the set of any safety issue records. The first record refers to any one record selected from the set of any safety issue records and contains historical traceability information related to a specific safety issue, which may be detailed information about a certain production batch, sales batch or specific link. Specifically, in the first record, there may be one or more abnormal links, which are production, processing, transportation or sales links that cause or may be related to safety issues, such as unqualified raw material sources, illegal processing technologies, inappropriate storage conditions, etc. The union operation is used to combine all elements in two or more sets into a new set. When traversing multiple records (not just the first record), the links identified as abnormal links in all records are combined to form a set containing all possible abnormal links, and the resulting set is the set of any suspicious links for safety issues.

[0032] Step S400 further includes step S440 of constructing the food safety database according to the mapping relationship between the any safety issue and the set of any suspicious links for safety issues. Associating the any safety issue with the set of any suspicious links for safety issues to establish a mapping relationship, which clarifies which suspicious links are related to each safety issue. Based on the above mapping relationship, a food safety database is constructed. The food safety database specifically includes safety issue information, suspicious link information, mapping relationship information, etc. Specifically, the safety issue information records basic information such as the detailed description, source, time, etc. of each safety issue; the suspicious link information details the specific situation of each suspicious link, including the link name, location, products or batches involved, abnormal manifestations, etc.; the mapping relationship information clarifies which suspicious links are related to each safety issue, forming a clear corresponding relationship.

[0033] Step S500, performing data analysis on the first set of suspicious links in combination with the target digital data platform to obtain a first analysis result set. When the first set of suspicious links is obtained, the target digital data platform will call all data related to these links, including raw data, processing results, historical records, etc., clean and preprocess the called data to ensure the quality and accuracy of the data, and then conduct in-depth data analysis according to the nature of the food safety issue and the characteristics of the first set of suspicious links, which may include but are not limited to comparing data differences between different links, analyzing data change trends, detecting outliers or patterns, mining data correlations, etc. During the data analysis process, the computing power and storage capacity of the target digital data platform will be fully utilized to ensure the efficiency and accuracy of the analysis. The results of the data analysis are summarized to form a first analysis result set, such as the identified key problem links, the causes or mechanisms of the problems, potential risk factors, possible solutions or suggestions, etc.

[0034] Step S600: Read a predetermined screening strategy and screen the first analysis result set according to the predetermined screening strategy to obtain target abnormal results. The predetermined screening strategy is a predefined set of rules or conditions used to screen specific types or information that meet specific conditions from a large amount of data. In food safety traceability, the predetermined screening strategy may include specific indicators, thresholds, patterns, etc. for food safety issues, as well as specific screening ratios. Specifically, each piece of data in the first analysis result set is compared and matched with the predetermined screening strategy. According to the rules or conditions in the screening strategy, results that meet or exceed the threshold, conform to a specific pattern or indicator are screened out. The screened results do not conform to the predetermined safety standards or expectations, may pose food safety risks or problems, and are considered target abnormal results, including all data and information identified as abnormal or potentially risky in the first analysis result set.

[0035] In a possible implementation, step S600 further includes step S610: Traverse the target monitoring data chain in the target digital platform based on the first set of suspicious links to obtain a first set of suspicious link data. Based on the first set of suspicious links, a comparative analysis is performed on each node and each data flow segment on the target monitoring data chain in the target digital platform to screen out data related to these suspicious links, including real-time monitoring data, historical data, log information, etc. related to the suspicious links, forming a first set of suspicious link data.

[0036] Step S600 also includes step S620: Extract the first link data from the first set of suspicious link data and compare the first link data with the first predetermined link data to obtain a first link data difference. The first link data refers to the data of any link in the first set of suspicious link data, and the first predetermined link data refers to the expected or standard data related to the first link, which may be derived from industry specifications, enterprise internal standards, historical normal data, etc. Compare the extracted first link data with the first predetermined link data, including comparing the numerical values, change trends, fluctuation ranges, etc. of the data, and find the differences and abnormalities between the first link data and the first predetermined link data. These differences and abnormalities are called the first link data difference, which may be manifested as numerical deviations, inconsistent change trends, exceeding the normal fluctuation range, etc.

[0037] Step S600 further includes step S630 of descending the first set of suspicious links based on the first link data difference to obtain a first sequence of suspicious links. Each first link data difference is associated with its corresponding suspicious link to obtain a data difference quantization value corresponding to each suspicious link. According to the magnitude of the data difference quantization value, the first set of suspicious links is sorted in descending order. The greater the data difference quantization value of a suspicious link, the greater its likelihood of being related to the problem, and it is ranked at the front of the sequence, finally obtaining a first sequence of suspicious links. It further includes step S640 of screening the first sequence of suspicious links in combination with a predetermined screening ratio in the predetermined screening strategy to obtain a set of target abnormal links. According to the screening ratio in the predetermined screening strategy, the first sequence of suspicious links is screened. For example, if the screening ratio is set to the first 20%, the first 20% of the links in the sequence are taken as the set of target abnormal links. After screening, a set of target abnormal links is obtained. It further includes step S650 of taking the set of target abnormal links as the target abnormal result.

[0038] Step S700: Trace and rectify the target abnormal links corresponding to the obtained target abnormal result. Compare the obtained target abnormal result with each link in the entire food cycle to determine the corresponding target abnormal links, and then trace the target abnormal links. Specifically, apply the data traceability method to review the entire working process of the food cycle, collect and analyze all data related to the target abnormal links, including raw data, processing results, historical records, etc. By comparing and analyzing the relationships between different data, gradually trace to the target abnormal links, find out the specific events and links that led to the abnormality, identify the causes and underlying roots of the problem, and then rectify the target abnormal links. For example, conduct a comprehensive review and improvement of the work process of the target abnormal links, look for links and methods that can be optimized, reduce duplicate and cumbersome links in the work, improve work efficiency, establish a corresponding supervision mechanism for the target abnormal links, supervise and inspect the work process and results to ensure the timely discovery and resolution of food safety issues and safeguard the health and safety of consumers.

[0039] In a possible implementation, step S700 further includes step S710 of obtaining a first abnormal link from the set of target abnormal links. The first abnormal link refers to any link in the set of target abnormal links. It further includes step S720 of issuing a comprehensive traceability instruction if the first abnormal link data difference corresponding to the first abnormal link does not reach the first data difference limit value. The first data difference limit value is a preset threshold for determining whether the data difference of the abnormal link has reached the level where further actions need to be taken. The first abnormal link data difference refers to the degree of difference between the actual data of the first abnormal link and the predetermined standard. If the first abnormal link data difference does not reach the first data difference limit value, it means that although this abnormal link has attracted attention, its data difference has not reached the level where immediate emergency measures need to be taken. To ensure food safety and prevent potential risks, the system issues a comprehensive traceability instruction, requiring full-cycle traceability of all production, processing, transportation, sales and other links related to the first abnormal link that may affect food safety. It further includes step S730 of performing full-cycle safety traceability on the target food based on the comprehensive traceability instruction.

[0040] In a possible implementation, step S720 further includes that the first data difference limit value is determined by analyzing the first data interval of the first abnormal link. For the first abnormal link, historical data, real-time monitoring data, etc. related to this link are obtained to form a data interval, which may include statistical quantities such as the maximum value, minimum value, average value, standard deviation, etc. of the data of this link. By analyzing this data interval, information such as the distribution range, fluctuation situation, change trend, etc. of the data of this link is understood, and then the first data difference limit value is set according to the statistical quantities of the data interval (such as standard deviation, percentage of the average value, etc.). For example, the first data difference limit value is set to ±2 standard deviations of the average value of the data of this link, or a certain percentage of the maximum difference value in the historical data.

[0041] In the above, reference is made to Figure 1 The food safety traceability method based on multi-source monitoring according to the embodiments of the present invention has been described in detail. Next, reference will be made to Figure 2 Describe the food safety traceability system based on multi-source monitoring according to the embodiments of the present invention.

[0042] The food safety traceability system based on multi-source monitoring according to an embodiment of the present invention is used to solve the technical problems existing in the existing food safety traceability, such as being limited to a single data source and processing means, and being difficult to monitor the whole life cycle of food, thereby resulting in poor accuracy and efficiency of food safety traceability. It realizes the centralized management and convenient query of the whole life cycle data of food, and achieves the technical effect of improving the accuracy and efficiency of food safety traceability. The food safety traceability system based on multi-source monitoring includes: a target multi-source data acquisition module 10, a data preprocessing result acquisition module 20, a target monitoring data chain construction module 30, a first set of suspicious links acquisition module 40, a first analysis result set acquisition module 50, a target abnormal result acquisition module 60, and a target abnormal link traceability and rectification module 70.

[0043] The target multi-source data acquisition module 10 is configured to perform whole life cycle monitoring on the target food through multi-source monitoring devices to obtain target multi-source data; The data preprocessing result acquisition module 20 is configured to traverse and match the distributed data center and activate the first edge data center to process and analyze the first target data in the target multi-source data, so as to obtain the first target data preprocessing result of the first link, wherein the first target data corresponds to the first link in the whole life cycle; The target monitoring data chain construction module 30 is configured to obtain the first correspondence between the first link and the first target data preprocessing result, and store the target monitoring data chain formed based on the first correspondence in the target digital middle platform; The first set of suspicious links acquisition module 40 is configured to obtain the first food safety problem of the target food, and traverse in the food safety database to obtain the first set of suspicious links; The first analysis result set acquisition module 50 is configured to perform data analysis on the first set of suspicious links in combination with the target digital middle platform to obtain the first analysis result set; The target abnormal result acquisition module 60 is configured to read a predetermined screening strategy, and screen the first analysis result set according to the predetermined screening strategy to obtain the target abnormal result; The target abnormal link traceability and rectification module 70 is configured to trace and rectify the target abnormal link corresponding to the matched target abnormal result.

[0044] Next, the specific configuration of the target monitoring data link formation module 30 will be described in detail. The target monitoring data link formation module 30 further includes: a first monitoring device that matches the first target data in the multi-source monitoring devices; reads a predetermined environmental dimension, and collects the environment of the first link based on the predetermined environmental dimension to obtain first environmental information; introduces a monitoring loss analysis function to analyze the first environmental information and the first monitoring device to obtain a preprocessing result of the first target data, where the expression of the monitoring loss analysis function is as follows: ; wherein, refers to the first target data of the preprocessing result of the first target data, refers to the ideal monitoring accuracy of the first monitoring device, refers to the total influence coefficient of the first environmental information on the ideal monitoring accuracy of the first monitoring device, refers to the th environmental feature among the environmental features in the first environmental information, refers to the th correlation coefficient between the th environmental feature and the accuracy of the first monitoring device, and refers to the weight coefficient of the th correlation coefficient, and .

[0045] Next, the specific configuration of the target monitoring data link formation module 30 will be continued to be described in detail. The target monitoring data link formation module 30 may further include: the environmental features at least include environmental temperature, environmental humidity, environmental network coverage rate, and environmental network stability.

[0046] Next, the specific configuration of the first suspicious link set obtaining module 40 will be described in detail. The first suspicious link set obtaining module 40 may further include: obtaining historical safety traceability records of the same type of food of the target food, where the historical safety traceability records include multiple historical records; obtaining any safety problem, and traversing and screening the any safety problem in the multiple historical records to obtain an any safety problem record set; performing a union operation on the first abnormal link in the first record to obtain an any safety problem suspicious link set, where the first record refers to any one record in the any safety problem record set; constructing the food safety database according to the mapping relationship between the any safety problem and the any safety problem suspicious link set.

[0047] Next, the specific configuration of the target abnormal result obtaining module 60 will be described in detail. The target abnormal result obtaining module 60 further includes: traversing the target monitoring data chain in the target digital middle platform based on the first set of suspicious links to obtain a first set of suspicious link data; extracting the first link data in the first set of suspicious link data, and comparing the first link data with the first predetermined link data to obtain a first link data difference; sorting the first set of suspicious links in descending order based on the first link data difference to obtain a first sequence of suspicious links; screening the first sequence of suspicious links in combination with the predetermined screening ratio in the predetermined screening strategy to obtain a set of target abnormal links; and using the set of target abnormal links as the target abnormal result.

[0048] Next, the specific configuration of the target abnormal link traceability and rectification module 70 will be described in detail. The target abnormal link traceability and rectification module 70 further includes: obtaining a first abnormal link in the set of target abnormal links; if the first abnormal link data difference corresponding to the first abnormal link does not reach the first data difference limit value, issuing a comprehensive traceability instruction; and performing full-cycle safety traceability on the target food based on the comprehensive traceability instruction.

[0049] Next, the specific configuration of the target abnormal link traceability and rectification module 70 will be further described in detail. The target abnormal link traceability and rectification module 70 may further include: the first data difference limit value is determined by analyzing the first data interval of the first abnormal link.

[0050] The food safety traceability system based on multi-source monitoring provided by the embodiments of the present invention can execute the food safety traceability method based on multi-source monitoring provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0051] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, however, any number of different modules can be used and run on the user terminal and / or the server. The included various units and modules are only divided according to the functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the present invention.

[0052] The above specific embodiments do not constitute a limitation to the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A food safety traceability method based on multi-source monitoring, characterized in that Including: Performing full-cycle monitoring on the target food through multi-source monitoring devices to obtain target multi-source data; Traversing and matching the distributed data center and activating the first edge data center to process and analyze the first target data in the target multi-source data, obtaining the preprocessing result of the first target data in the first link, where the first target data corresponds to the first link in the full cycle; Obtaining the first correspondence between the first link and the preprocessing result of the first target data, and storing the target monitoring data chain formed based on the first correspondence in the target digital middle platform; Obtaining the first food safety problem of the target food, and traversing in the food safety database to obtain the first set of suspicious links; Combining the target digital middle platform to perform data analysis on the first set of suspicious links to obtain the first analysis result set; Reading the predetermined screening strategy, and screening the first analysis result set according to the predetermined screening strategy to obtain the target abnormal result; Tracing and rectifying the target abnormal link corresponding to the matched target abnormal result.

2. The food safety traceability method based on multi-source monitoring according to claim 1, wherein Including: Matching the first monitoring device of the first target data in the multi-source monitoring device; Reading the predetermined environmental dimension, and collecting the environment of the first link based on the predetermined environmental dimension to obtain the first environmental information; Introducing a monitoring loss analysis function to analyze the first environmental information and the first monitoring device to obtain the preprocessing result of the first target data, where the expression of the monitoring loss analysis function is as follows: ； Among them, refers to the first target data preprocessing result of the first target data, refers to the ideal monitoring accuracy of the first monitoring device, refers to the total influence coefficient of the first environmental information on the ideal monitoring accuracy of the first monitoring device, refers to the th environmental feature among the environmental features in the first environmental information, refers to the th correlation coefficient between the th environmental feature and the accuracy of the first monitoring device, refers to the weight coefficient of the th correlation coefficient, and .

3. The food safety traceability method based on multi-source monitoring according to claim 2, wherein The environmental features at least include environmental temperature, environmental humidity, environmental network coverage rate, and environmental network stability.

4. The food safety traceability method based on multi-source monitoring according to claim 1, characterized in that, Including: Obtaining the historical safety traceability records of the same type of food of the target food, and the historical safety traceability records include multiple historical records; Obtaining any food safety problem, and traversing and screening the any food safety problem in the multiple historical records to obtain the any food safety problem record set; Performing a union operation on the first abnormal link in the first record to obtain the any food safety problem suspicious link set, where the first record refers to any record in the any food safety problem record set; Constructing the food safety database according to the mapping relationship between the any food safety problem and the any food safety problem suspicious link set.

5. The food safety traceability method based on multi-source monitoring according to claim 1, wherein Including: Traversing the target monitoring data chain in the target digital middle platform based on the first set of suspicious links to obtain the first set of suspicious link data; Extracting the first link data in the first set of suspicious link data, and comparing the first link data with the first predetermined link data to obtain the first link data difference; Sorting the first set of suspicious links in descending order based on the first link data difference to obtain the first set of suspicious link sequences; Combining the predetermined screening ratio in the predetermined screening strategy to screen the first set of suspicious link sequences to obtain the target abnormal link set; Taking the target abnormal link set as the target abnormal result.

6. The food safety traceability method based on multi-source monitoring according to claim 1, characterized in that Further including: Obtaining the first abnormal link in the target abnormal link set; If the first abnormal link data difference corresponding to the first abnormal link does not reach the first data difference limit value, issuing a full traceability instruction; Performing full-cycle safety traceability on the target food based on the full traceability instruction.

7. The food safety traceability method based on multi-source monitoring according to claim 6, characterized in that, The first data difference limit value is determined by analyzing the first data interval of the first abnormal link.

8. The food safety traceability system based on multi-source monitoring is characterized in that, The system is used to implement the food safety traceability method based on multi-source monitoring according to any one of claims 1-7. The system includes: A target multi-source data acquisition module, which is used to perform full-cycle monitoring on the target food through multi-source monitoring devices to obtain target multi-source data; A data preprocessing result acquisition module, which is used to traverse and match a distributed data center and activate a first edge data center to process and analyze the first target data in the target multi-source data to obtain a first target data preprocessing result of the first link, where the first target data corresponds to the first link in the full cycle; A target monitoring data chain construction module, which is used to obtain the first correspondence between the first link and the first target data preprocessing result, and store the target monitoring data chain constructed based on the first correspondence in a target digital middle platform; A first suspicious link set acquisition module, which is used to obtain the first food safety problem of the target food and traverse in a food safety database to obtain a first suspicious link set; A first analysis result set acquisition module, which is used to perform data analysis on the first suspicious link set in combination with the target digital middle platform to obtain a first analysis result set; A target abnormal result acquisition module, which is used to read a predetermined screening strategy and screen the first analysis result set according to the predetermined screening strategy to obtain a target abnormal result; A target abnormal link traceability and rectification module, which is used to trace and rectify the target abnormal link corresponding to the matched target abnormal result.

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