CN117993923A - Agricultural product tracing method and system - Google Patents
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Abstract
The invention relates to the technical field of information, and discloses an agricultural product tracing method and system, wherein the method comprises the following steps: real-time monitoring is carried out on links of production, packaging, transportation and sales of agricultural products through an industrial Internet platform, and data of each link acquired by a data acquisition module are acquired; distributing industrial Internet identifiers to the data of each link to obtain the data of each link after the identifiers; verifying the data of each link after identification through a preset node of a block chain in a data storage module; after passing the verification, recording the data of each link after the identification on a block chain; searching the identification from the blockchain to obtain the tracing information of the agricultural product. The invention successfully solves the defects of the existing agricultural product traceability system in terms of data processing efficiency, safety, instantaneity and prediction capability through integrating the industrial Internet and a blockchain technology.
Description
Technical Field
The invention relates to the technical field of information, in particular to an agricultural product tracing method and system.
Background
The existing product tracing system has the safety problems that a quality safety tracing system is not easy to manage, various tracing codes are easy to copy and forge and the like. The requirements of wide consumers on product safety are difficult to meet, and products with quality safety problems can only be destroyed regionally because accurate tracing cannot be achieved, so that the loss is brought to factories. For a wide consumer group, products which are expected to be purchased by the consumer group are safe and have guaranteed quality; for product suppliers and origin owners, they want to know the circulation condition of own products and the quality condition of own products by establishing a traceability platform; merchants hope to show the whole flow of the sold products from production to circulation, quality inspection and sales to wide consumers; meanwhile, the government supervision department can also carry out more efficient supervision on the product sales market and the quality safety through a high-quality traceability platform.
Besides, the existing traceability system has the following problems, mainly including insufficient data real-time performance, limited prediction capability, data security and transparency problems, lack of effective cross-platform integration, poor user interface and interaction experience, and deficiencies in terms of resource efficiency and environmental impact. These systems often rely on non-real-time data updates, lack real-time monitoring capabilities, and limit immediate response to the state of the agricultural product. Furthermore, they often cannot predict product shelf life and quality changes due to the lack of advanced data analysis tools. In terms of data security, conventional systems are vulnerable to data tampering and unauthorized access, while insufficient data transparency makes it difficult to verify data authenticity. These systems also often lack efficient integration with other systems (e.g., supply chain management, logistics tracking), limiting information sharing. In addition, many systems perform poorly in terms of user friendliness, are complex to operate, and lack intuitive interface designs. Finally, current systems are also significantly inadequate in terms of improving resource efficiency and reducing environmental impact. These drawbacks highlight the need for a more efficient, safe, transparent, and user-friendly agricultural product traceability and shelf-life prediction system.
The foregoing is provided merely for the purpose of facilitating understanding of the technical solutions of the present invention and is not intended to represent an admission that the foregoing is prior art.
Disclosure of Invention
The invention mainly aims to provide an agricultural product tracing method and system, and aims to solve the technical problems of insufficient data processing efficiency and safety of the existing agricultural product tracing system.
In order to achieve the above object, the present invention provides an agricultural product tracing method, which is applied to an agricultural product tracing system, the agricultural product tracing system includes a data acquisition module managed through an industrial internet platform and a data storage module managed through a blockchain, the agricultural product tracing method includes:
Real-time monitoring is carried out on links of production, packaging, transportation and sales of agricultural products through the industrial Internet platform, and data of all links acquired by the data acquisition module are acquired;
Distributing industrial Internet identifiers to the data of each link to obtain the data of each link after the identifiers;
verifying the data of each link after the identification through a preset node of a block chain in the data storage module;
After passing the verification, recording the data of each link after the identification on a block chain;
and searching the identification from the blockchain to obtain the traceability information of the agricultural product.
Optionally, the monitoring the links of the agricultural products in production, packaging, transportation and sales through the industrial internet platform in real time and acquiring the data of each link includes:
Acquiring data of temperature, humidity, product position, transportation condition and crop growth state acquired by a data acquisition module arranged in the process of producing, packaging, transporting and selling agricultural products;
the temperature, the humidity, the product position, the transportation condition and the crop growth state are monitored in real time through the industrial Internet platform, and the change of the data is obtained in real time;
and integrating the data of the temperature, the humidity, the product position, the transportation condition and the crop growth state with the monitored data to obtain a data pool containing the data of each link.
Optionally, after the real-time monitoring is performed on the links of production, packaging, transportation and sales of the agricultural products through the industrial internet platform and the data of each link are obtained, the method further includes:
processing and analyzing the data of each link through a machine learning algorithm and an artificial intelligence algorithm, and constructing a data analysis and prediction model;
Predicting shelf life and quality changes of the agricultural product by the data analysis and prediction model.
Optionally, the method further comprises:
Performing cross-validation and parameter adjustment on the data analysis and prediction model to improve generalization capability and performance of the data analysis and prediction model;
The data analysis and prediction model is trained and fine-tuned by data periodically monitored by an industrial internet platform, and performance indicators of the data analysis and prediction model are continuously monitored.
Optionally, the predicting, by the data analysis and prediction model, the shelf life and quality change of the agricultural product includes:
Acquiring historical data and real-time data of the agricultural products;
predicting a future shelf life of the agricultural product by analyzing historical performances of the agricultural product under different conditions and by the data analysis and prediction model;
And analyzing the influence of environmental factors on the quality of the product through a machine learning algorithm, and predicting the change trend of the quality of the agricultural product through the data analysis and prediction model.
Optionally, the verifying the data of each link after the identification through a preset node in the blockchain network includes:
Storing the data of each link after the identification into a database of an agricultural product tracing system;
uploading the data of each identified link to a blockchain network through a database request;
verifying the data of each link after the identification through a preset node in the blockchain network, and judging whether the data of each link after the identification is correct or not;
when the verification result is correct, the data of each link after the identification is successfully uploaded to the block chain, wherein each data block on the block chain comprises a time stamp and encryption hash of the previous data block;
and when the verification result is wrong, judging that the uploading fails.
In addition, in order to achieve the above purpose, the invention also provides an agricultural product tracing system, which comprises a physical layer, a data layer, a business layer and a representation layer;
The physical layer is used for interacting with actual physical equipment and sensors and collecting real-time data of the agricultural products in each link;
the data layer is used for transmitting the data acquired by the sensor to an industrial Internet identification analysis secondary node management system for identification, and transmitting the identified data to a distributed network;
The service layer is used for encapsulating the data in the distributed network by adopting an open source tool and software in the block chain field, and storing the encapsulated data in the block chain network;
The representation layer is used for providing a user interface and displaying the traceability information and the state of the agricultural products.
Optionally, the presentation layer is configured to provide a user interface, and display traceability information and status of the agricultural product, and includes:
responding to registration and registration requests of a system administrator through the user interface, and registering a company and registering a user account;
data isolation is carried out on data of different companies, and corresponding operation authorities are granted to each user;
performing authority verification on the user, and allowing the user conforming to the agricultural product information management authority to add and inquire the agricultural product information;
And allowing the user conforming to the traceability data management authority to select and add the traceability record and the quality inspection operation information of the agricultural products of the enterprise to which the user belongs.
Optionally, the database of the agricultural product tracing system includes: agricultural product information table, product link table, data table on block chain, company user table and company information table;
the agricultural product information table is used for storing basic information of agricultural products;
the product link table is used for recording the production process of agricultural products;
The data table on the blockchain is used for storing data to be recorded on the blockchain;
the company user table is used for storing the information of the company user;
the company information table is used for recording related data of agricultural product production enterprises.
Optionally, the agricultural product traceability system comprises a front end part of a technical stack, a user interface, a main development language, a development environment and package management tool, an integrated development environment and a back end framework;
The front end part of the technical stack is developed by JavaScript, HTML and CSS;
The user interface is designed using the Vue2 framework and elementUI;
NodeJs and npm are used as development environments and package administration tools;
the rear end part of the technical stack of the agricultural product tracing system adopts Java8 as a main development language;
and use IntelliJ IDEA 2023.1.2 as an integrated development environment;
The back end frame is composed of Spring Boot, mybatis-plus and Maven.
According to the invention, the real-time data acquisition function of the industrial Internet is combined with the data safety and transparency of the blockchain, so that the accuracy and timeliness of the data are improved, and the credibility and transparency of the whole traceability process are increased; real-time monitoring of agricultural products in various links such as production, processing and transportation is realized through an industrial internet technology; advanced machine learning algorithm is adopted to conduct deep analysis and prediction on the collected data, so that the tracing efficiency is improved, and powerful data support is provided for food safety and quality control; by using the blockchain technology, the data records in the system are non-tamper-resistant, so that the safety and the integrity of the data are greatly improved; the whole supply chain from agricultural product production to final consumption is covered, the information tracing of the whole process is ensured, and more comprehensive food safety guarantee is provided for consumers.
Drawings
FIG. 1 is a block diagram of a first embodiment of an agricultural product traceability system of the present invention;
FIG. 2 is a core business flow diagram of the agricultural product traceability system of the present invention;
FIG. 3 is a database table E-R diagram of the agricultural product traceability system of the present invention;
FIG. 4 is a schematic flow chart of a first embodiment of the agricultural product tracing method of the present invention;
Fig. 5 is a flowchart of tracing information records of a first embodiment of the agricultural product tracing method of the present invention;
fig. 6 is a schematic flow chart of a second embodiment of the agricultural product tracing method of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the invention provides an agricultural product tracing system, and referring to fig. 1, fig. 1 is a structural block diagram of a first embodiment of the agricultural product tracing system.
In this embodiment, the agricultural product tracing system includes a physical layer, a data layer, a service layer, and a presentation layer;
in this embodiment, the physical layer is configured to interact with actual physical devices and sensors, and collect real-time data of agricultural products in each link;
It can be understood that the information of agricultural products is collected mainly through RFID radio frequency identification, bar codes and two-dimensional codes.
In the specific implementation, the physical layer is responsible for interacting with actual physical equipment and sensors, and collecting real-time data of agricultural products in various links such as production, processing, transportation and the like.
In this embodiment, the data layer is configured to transmit data collected by the sensor to the industrial internet identifier analysis secondary node management system for identification, and transmit the identified data to the distributed network;
It should be noted that, the data layer applies a database, a blockchain and is provided with an industrial internet platform, and the type of the database adopted by the system is a relational database for storing the traceability information of the farm products of the main users.
In a specific implementation, data acquired by the sensor are transmitted to an industrial Internet identification analysis secondary node management system. These data are then transmitted into a distributed network for further processing.
In this embodiment, the service layer is configured to package data in a distributed network by using an open source tool and software in the blockchain field, and store the packaged data in the blockchain network;
It should be noted that, the service layer encapsulates the data by using an open source tool and software in the blockchain field, which is to ensure the security and integrity of the data. The encapsulated data is stored in a blockchain network to take advantage of the non-tamper and transparency of the blockchain.
In a specific implementation, the business layer is mainly used for managing agricultural product data, including agricultural product enterprise management, user management, agricultural product management, traceability record management and data synchronization management.
In this embodiment, the presentation layer is configured to provide a user interface, and display traceability information and status of the agricultural product.
It should be noted that, the presentation layer performs presentation of agricultural product data through a PC browser or H5, and H5 is the latest version of a standard for constructing and presenting contents on the internet. It includes many new semantical elements, graphic and multimedia elements, form controls and enhances support for mobile devices.
In a specific implementation, the presentation layer is a user interface provided by the system externally, and displays the traceability information and the state of the product, so that users such as farmers, logistics companies, retailers and consumers can inquire about the product information in real time. The layer is also responsible for displaying the circulation record of the data, and the transparency of the system and the trust feeling of the user are enhanced.
Further, responding to registration and registration requests of a system administrator through the user interface, and registering a company and registering a user account; data isolation is carried out on data of different companies, and corresponding operation authorities are granted to each user; performing authority verification on the user, and allowing the user conforming to the agricultural product information management authority to add and inquire the agricultural product information; and allowing the user conforming to the traceability data management authority to select and add the traceability record and the quality inspection operation information of the agricultural products of the enterprise to which the user belongs.
In the agricultural products of the enterprise, users with different roles can select to add information such as tracing records of the agricultural products, quality inspection operation and the like. This helps to record the production and circulation information of the product, thereby enabling traceability of the product. The user with corresponding authority can perform the operations, so that the safety and the accuracy of the data are ensured;
To ensure security of the system, user registration is not through foreground registration, but company registration and user account registration are performed by a system administrator. This includes enterprise registration, account management between multiple users, and operations on the user's agricultural products, agricultural product traceability operations, and quality inspection operations. In the aspect of user management, data isolation is a key strategy, data of different enterprises are strictly isolated, and different roles are authorized to have different operation rights, so that the safety and controllability of user management are ensured;
the user with corresponding authority can add and inquire agricultural product information including basic information, place of production, date of production, etc. This is very important for product management and traceability.
As shown in fig. 2, fig. 2 is a core business flow chart of the agricultural product tracing system of the present invention. The enterprise management system comprises an administrator, an enterprise administrator and a user, wherein the administrator is responsible for registering the enterprise and registering the user administrator, authorization data and service to which the enterprise belongs; after being registered, the enterprise manager can log in an interface of the enterprise manager to manage agricultural products, including traceability record management and agricultural product information management; the user has the authority of inquiring the traceability information of the product.
Further, the database of the agricultural product tracing system includes: agricultural product information table, product link table, data table on block chain, company user table and company information table; the agricultural product information table is used for storing basic information of agricultural products; the product link table is used for recording the production process of agricultural products; the data table on the blockchain is used for storing data to be recorded on the blockchain; the company user table is used for storing the information of the company user; the company information table is used for recording relevant data of agricultural product production enterprises.
It should be noted that, the agricultural product information table stores basic information of agricultural products, such as names, production batches and places of production, and these data are input through the internet of things equipment or manually and are associated with the subsequent tracing records; the product link table records various activities in the agricultural product production process, such as planting, harvesting and processing, and each record is related to a specific batch so as to realize the whole-course tracing; the block chain uplink data table is used for storing data to be recorded on the block chain, so that the non-tamper property and transparency of the data are ensured; the corporate user table stores corporate user information including definitions of different roles and rights; and the company information table records related data of agricultural product production enterprises.
As shown in FIG. 3, FIG. 3 is a database table E-R diagram of the agricultural product traceability system of the present invention. Firstly registering manager information, including manager id, manager password, manager phone and manager mailbox; managing n company administrators and n users by an administrator, n representing a preset number; a company administrator manages m company user tables including a primary key id, a user id, a company id, and a creation time; each company user table is provided with a company information table and n traceable agricultural products, wherein the company information table comprises a company id, a company contact person, a contact person mobile phone number, a company address and a company profile, and the traceable agricultural products comprise a product id, a company id, a product name and a product description; the traceable agricultural products comprise n blockchain uplink data tables and n operation record tables, the blockchain uplink data tables comprise a primary key id, uplink product information, a company id, a hash address and a two-dimensional code address, and the operation record tables comprise an operation name, operation time, operation description, a product id and a company id.
Further, the agricultural product traceability system comprises a front end part of a technical stack, a user interface, a main development language, a development environment and package management tool, an integrated development environment and a back end framework; the front end part of the technical stack is developed by JavaScript, HTML and CSS; the user interface is designed using the Vue2 framework and elementUI; nodeJs and npm are used as development environments and package administration tools; java8 is used as the main development language; intelliJ IDEA 2023.1.2 is used as an integrated development environment; the back end frame is composed of Spring Boot, mybatis-plus and Maven.
It should be noted that mysql5.7 is used as database software to support the storage and management of large amounts of data.
The architecture and logic of the agricultural product traceability system based on the industrial Internet and the blockchain are divided into four main layers, so that efficient operation of the system and safety and traceability of data are ensured, and user experience is focused on by user interface design. Through the concise and visual interface design and the functional layout easy to operate, various users can easily access and use the system, so that the participation of the users is improved, and the trust feeling of the system is enhanced.
The embodiment of the invention provides an agricultural product tracing method, and referring to fig. 4, fig. 4 is a schematic flow chart of a first embodiment of the agricultural product tracing method.
In this embodiment, the agricultural product tracing method includes the following steps:
Step S10: real-time monitoring is carried out on links of production, packaging, transportation and sales of agricultural products through an industrial Internet platform, and data of all links acquired by the data acquisition module are acquired.
It should be noted that, the execution body of the method of this embodiment may be a terminal device with functions of data processing and program running, for example, a computer, a central server, etc., or may be an electronic device with the same or similar functions, for example, the above-mentioned agricultural product tracing device. The present embodiment and the following embodiments will be described below with reference to an agricultural product tracing apparatus as an example.
It can be appreciated that the industrial internet platform plays an important role as a data acquisition center as a core component of the present invention. The system is responsible for collecting key data in real time from production to sales of agricultural products, and provides data support and analysis basis for the whole system.
It should be understood that the data collected includes monitoring temperature changes, humidity data of the product during production, storage and transportation, tracking the geographic location of the product in real time, transportation conditions including transportation mode, environmental conditions, etc., and for source farm products, monitoring the growth status of the crop, such as growth cycle, health status, etc.
Further, acquiring data of temperature, humidity, product position, transportation condition and crop growth state acquired by a data acquisition module arranged in the process of production, packaging, transportation and sales of agricultural products; the temperature, the humidity, the product position, the transportation condition and the crop growth state are monitored in real time through an industrial internet platform, and the change of the data is obtained in real time; and integrating the data of the temperature, the humidity, the product position, the transportation condition and the crop growth state with the monitored data to obtain a data pool containing the data of each link.
It should be noted that, the industrial internet platform can perform real-time monitoring and data integration, through the real-time monitoring of the data, any key change can be ensured to be captured in time, when an abnormality or a key data deviation is detected, the system can send out a warning, allow timely response and intervention, and the industrial internet platform has data accessibility, so that other components in the system can be ensured to conveniently access and utilize the data.
It can be understood that the system realizes real-time monitoring of various links of agricultural products such as production, processing, transportation and the like through an industrial internet technology. The real-time data acquisition and monitoring mechanism ensures the timely update of information and improves the accuracy and the real-time performance of the traceability information.
Step S20: and distributing industrial Internet identifiers to the data of each link to obtain the data of each link after the identifiers.
It should be noted that the identifier is used as an identity mark of the product in its life cycle, and is used for tracking and recording related information.
It will be appreciated that at various stages of production, packaging, transportation and sales of the product, relevant data such as temperature, humidity, geographical location and time stamp are collected in real time and associated with the product identity.
Step S30: and verifying the data of each link after the identification through a preset node of the block chain in the data storage module.
It should be noted that, each new data block in the agricultural product traceability system can be added into the blockchain only after passing the verification of a plurality of nodes in the blockchain network, so that the authenticity and consistency of the data are ensured.
Further, storing the data of each link after identification into a database of an agricultural product traceability system; uploading the data of each identified link to a block chain network through a database request; verifying the data of each link after the identification through a preset node in the block chain network, and judging whether the data of each link after the identification is correct or not; when the verification result is correct, successfully uploading the data of each identified link to a block chain, wherein each data block on the block chain comprises a time stamp and encryption hash of the previous data block; and when the verification result is wrong, judging that the uploading fails.
The verification method can be hash value verification, digital signature and multiparty participation verification, and the multiparty participation verification is adopted by the method, so that a plurality of nodes independently verify the validity of a new block. Only blocks that are verified by multiple parties can be added to the blockchain.
Fig. 5 shows a flowchart of tracing information records of the first embodiment of the tracing method for agricultural products according to the present invention. And starting an agricultural product tracing system, distributing industrial Internet identification for each agricultural product, storing the identified information into a system database, uploading data to a blockchain network, verifying the data, and if the verification result is Y, the uploading is successful, and if the verification result is N, the uploading is failed.
Step S40: and after passing the verification, recording the data of each link after the identification on the blockchain.
It should be noted that once the data is added, it will be synchronized among all nodes in the entire network, guaranteeing the uniformity and transparency of the data.
It should be appreciated that all transactions and data changes are recorded on the blockchain, which ensures the integrity and security of the data. A key feature of the blockchain is that once recorded, the data cannot be changed or deleted, and the tamper-resistant characteristic greatly enhances the reliability of data recording and provides a firm trust basis for the whole system. Each data block contains a time stamp and a cryptographic hash of the preceding block, in a manner that makes the entire chain a continuous, irreversible recording system.
Step S50: searching the identification from the blockchain to obtain the tracing information of the agricultural product.
It should be noted that all participants in the supply chain, including producers, logistics companies, retailers, and consumers, can access the data on the blockchain through the system to track the complete history of the product.
It should be appreciated that due to the distributed nature of the blockchain, all parties can access and verify the data on the chain, but cannot unilaterally tamper with the data. The transparent and unchangeable data recording mode obviously improves the overall transparency of the system and enhances the trust of all stakeholders to the whole traceability system. In supply chain management, this means that every link from producer to consumer can be assured that the data contacted is accurate and untampered.
The system of the embodiment creatively combines the real-time data acquisition function of the industrial Internet with the data safety and transparency of the blockchain. The integration not only improves the accuracy and timeliness of the data, but also increases the credibility and transparency of the whole tracing process; the real-time data acquisition capability of the industrial Internet platform is utilized to effectively capture key information of each link from production to sales of agricultural products, such as temperature, humidity, geographical position and the like. The real-time data acquisition not only ensures the timeliness and accuracy of information, but also improves the response speed and dynamic monitoring capability of the whole tracing process, and by recording all key data on a block chain, the system ensures the non-tamper property and permanence of the data, and the safety and transparency of the data; the system covers the whole supply chain from agricultural product production to final consumption, ensures the information tracing of the whole process, and provides more comprehensive food safety guarantee for consumers.
Referring to fig. 6, fig. 6 is a schematic flow chart of a second embodiment of the agricultural product tracing method of the present invention.
Based on the first embodiment, in this embodiment, after step S20, for the sake of-, the method further includes:
Step S201: the data of each link is processed and analyzed through a machine learning algorithm and an artificial intelligence algorithm, and a data analysis and prediction model is constructed.
It should be noted that, in constructing the data analysis and prediction model, it is important to select an appropriate algorithm and perform optimization. Different machine learning algorithms, such as regression analysis, classification algorithms, cluster analysis, etc., are each adapted for a particular type of data processing, thereby ensuring that the model is able to effectively cope with complex agricultural product data. For example, regression analysis is suitable for predicting numeric target variables, while classification and clustering algorithms are more suitable for identifying different data categories or patterns. Furthermore, the complexity of modern agricultural product data often requires that the model be able to process high dimensional data and reveal nonlinear relationships, thus selecting algorithms such as neural networks that can capture these complexities.
Further, cross-validation and parameter adjustment are carried out on the data analysis and prediction model, so that the generalization capability and performance of the data analysis and prediction model are improved; the data analysis and prediction model is trained and fine-tuned by data periodically monitored by the industrial internet platform, and performance indexes of the data analysis and prediction model are continuously monitored.
In a specific implementation, in the optimization process, the generalization capability and performance of the model are continuously improved through methods such as cross-validation, parameter adjustment and the like, for example, grid search is used for determining optimal model parameters. In particular, continuous learning and adaptation of the model is critical to ensure long term effectiveness, which includes training and fine tuning the model with new data periodically, and continuously monitoring the performance metrics of the model to ensure its stable operation. The method ensures that the model not only has good performance in the initial stage, but also can adapt to new trend and mode which appear along with time, thereby providing accurate and reliable prediction in practical application and providing powerful data support for decision-making.
Step S202: shelf life and quality changes of agricultural products are predicted by data analysis and prediction models.
It should be noted that, the product state analysis is a key link, and it involves three main aspects of real-time monitoring, anomaly detection and trend analysis. The real-time monitoring function focuses on continuously tracking and analyzing critical data, such as temperature and humidity, which are critical to assessing the stability of the product during storage and transportation. By monitoring these parameters in real time, the model can ensure that the product is in an optimal state and timely responds to any adverse environmental changes. The anomaly detection function is to discover potential problems in time by identifying anomaly patterns in the data. This includes using statistical methods and machine learning algorithms to identify outliers in the data, such as temperatures or humidities suddenly exceeding a preset safety range. Such timely anomaly identification and alert mechanisms are critical to preventing product damage and ensuring quality control. Trend analysis reveals the trend of changes in product status through in-depth analysis of long-term data, which is critical to predicting future status changes, identifying risk, and capturing opportunities.
In particular implementations, by analyzing past temperature and humidity data, the model may be able to predict potential changes in product quality over a particular season or under particular storage conditions.
Further, acquiring historical data and real-time data of agricultural products; predicting future shelf life of the agricultural product by analyzing historical performances of the agricultural product under different conditions and using a data analysis and prediction model; and analyzing the influence of environmental factors on the quality of the product through a machine learning algorithm, and predicting the change trend of the quality of the agricultural product through a data analysis and prediction model.
It should be noted that the shelf life prediction uses a combination of historical data and real-time data, and the model can predict the future shelf life by analyzing the historical performance of the product under different conditions. This is not only critical to food safety, but also plays a critical role in inventory management and reduction of expiration risk. The quality change prediction function is then focused on evaluating quality changes of the product under specific environmental conditions, such as the maturity of vegetables or the freshness of meat. The influence of environmental factors such as temperature, humidity and storage time on the quality of the product is analyzed by using a machine learning algorithm, and the model can predict the variation trend of the quality and provide a basis for timely quality control. Finally, these predictions provide scientific basis for various aspects of supply chain management, helping businesses to formulate more rational and efficient production, storage, and logistics plans. For example, inventory levels can be optimized, reducing waste, by accurately predicting product shelf life; meanwhile, the prediction of quality change is helpful to adjust the production strategy, and the optimal state of the product when the product reaches the hand of a consumer is ensured.
The present embodiment uses advanced machine learning algorithms to conduct in-depth analysis and prediction of the collected data, particularly in predicting the shelf life of agricultural products. The system not only improves the tracing efficiency, but also provides powerful data support for food safety and quality control, and by providing accurate data analysis and prediction, the system provides more scientific decision support for enterprises in a supply chain. This includes optimizing inventory management, improving logistics planning, and improving food safety standards.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. read-only memory/random-access memory, magnetic disk, optical disk), comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
Claims (10)
1. The agricultural product tracing method is characterized by being applied to an agricultural product tracing system, the agricultural product tracing system comprises a data acquisition module managed through an industrial Internet platform and a data storage module managed through a blockchain, and the agricultural product tracing method comprises the following steps:
Real-time monitoring is carried out on links of production, packaging, transportation and sales of agricultural products through the industrial Internet platform, and data of all links acquired by the data acquisition module are acquired;
Distributing industrial Internet identifiers to the data of each link to obtain the data of each link after the identifiers;
verifying the data of each link after the identification through a preset node of a block chain in the data storage module;
After passing the verification, recording the data of each link after the identification on a block chain;
and searching the identification from the blockchain to obtain the traceability information of the agricultural product.
2. The agricultural product tracing method of claim 1, wherein said real-time monitoring and obtaining data of each link of production, packaging, transportation and sales of said agricultural product through said industrial internet platform comprises:
Acquiring data of temperature, humidity, product position, transportation condition and crop growth state acquired by a data acquisition module arranged in the process of producing, packaging, transporting and selling agricultural products;
the temperature, the humidity, the product position, the transportation condition and the crop growth state are monitored in real time through the industrial Internet platform, and the change of the data is obtained in real time;
and integrating the data of the temperature, the humidity, the product position, the transportation condition and the crop growth state with the monitored data to obtain a data pool containing the data of each link.
3. The agricultural product tracing method of claim 1, wherein after the links of production, packaging, transportation and sales of the agricultural product are monitored in real time and data of each link are obtained through the industrial internet platform, the method further comprises:
processing and analyzing the data of each link through a machine learning algorithm and an artificial intelligence algorithm, and constructing a data analysis and prediction model;
Predicting shelf life and quality changes of the agricultural product by the data analysis and prediction model.
4. The agricultural product tracing method of claim 3, further comprising:
Performing cross-validation and parameter adjustment on the data analysis and prediction model to improve generalization capability and performance of the data analysis and prediction model;
The data analysis and prediction model is trained and fine-tuned by data periodically monitored by an industrial internet platform, and performance indicators of the data analysis and prediction model are continuously monitored.
5. A method of tracing agricultural products according to claim 3, wherein said predicting said variations in shelf life and quality of said agricultural products by said data analysis and prediction model comprises:
Acquiring historical data and real-time data of the agricultural products;
predicting a future shelf life of the agricultural product by analyzing historical performances of the agricultural product under different conditions and by the data analysis and prediction model;
And analyzing the influence of environmental factors on the quality of the product through a machine learning algorithm, and predicting the change trend of the quality of the agricultural product through the data analysis and prediction model.
6. The agricultural product tracing method of claim 1, wherein said verifying the data of each link after said identifying by a preset node in a blockchain network comprises:
Storing the data of each link after the identification into a database of an agricultural product tracing system;
uploading the data of each identified link to a blockchain network through a database request;
verifying the data of each link after the identification through a preset node in the blockchain network, and judging whether the data of each link after the identification is correct or not;
when the verification result is correct, the data of each link after the identification is successfully uploaded to the block chain, wherein each data block on the block chain comprises a time stamp and encryption hash of the previous data block;
and when the verification result is wrong, judging that the uploading fails.
7. The agricultural product tracing system is characterized by comprising a physical layer, a data layer, a business layer and a representation layer;
The physical layer is used for interacting with actual physical equipment and sensors and collecting real-time data of the agricultural products in each link;
the data layer is used for transmitting the data acquired by the sensor to an industrial Internet identification analysis secondary node management system for identification, and transmitting the identified data to a distributed network;
The service layer is used for encapsulating the data in the distributed network by adopting an open source tool and software in the block chain field, and storing the encapsulated data in the block chain network;
The representation layer is used for providing a user interface and displaying the traceability information and the state of the agricultural products.
8. The agricultural product tracing system of claim 7, wherein said presentation layer for providing a user interface for presenting tracing information and status of said agricultural product comprises:
responding to registration and registration requests of a system administrator through the user interface, and registering a company and registering a user account;
data isolation is carried out on data of different companies, and corresponding operation authorities are granted to each user;
performing authority verification on the user, and allowing the user conforming to the agricultural product information management authority to add and inquire the agricultural product information;
And allowing the user conforming to the traceability data management authority to select and add the traceability record and the quality inspection operation information of the agricultural products of the enterprise to which the user belongs.
9. The agricultural product tracing system of claim 7, wherein said database of said agricultural product tracing system comprises: agricultural product information table, product link table, data table on block chain, company user table and company information table;
the agricultural product information table is used for storing basic information of agricultural products;
the product link table is used for recording the production process of agricultural products;
The data table on the blockchain is used for storing data to be recorded on the blockchain;
the company user table is used for storing the information of the company user;
the company information table is used for recording related data of agricultural product production enterprises.
10. The agricultural product tracing system of claim 7, wherein said agricultural product tracing system comprises a front-end portion of a technical stack, a user interface, a main development language, a development environment and package management tool, an integrated development environment, and a back-end framework;
The front end part of the technical stack is developed by JavaScript, HTML and CSS;
The user interface is designed using the Vue2 framework and elementUI;
NodeJs and npm are used as development environments and package administration tools;
Java8 is used as the main development language;
IntelliJ IDEA 2023.1.2 is used as an integrated development environment;
The back end frame is composed of Spring Boot, mybatis-plus and Maven.
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