Agroecological detection data sharing method, terminal and storage medium

Abstract

The invention discloses an agro-ecology detection data sharing method, which comprises the following steps: S1, receiving agro-ecology detection data, and preprocessing the agro-ecology detection data to obtain agro-ecology detection first-level data; s2, carrying out correlation analysis, network topology reconstruction and unique identification coding processing on the basis of the agricultural ecology detection first-level data to obtain agricultural ecology detection second-level data; s3, predicting the scientificity of the agricultural production link based on the agro-ecology detection secondary data, and verifying to obtain agro-ecology detection tertiary data; and S4, obtaining account information of a data sharing request end, determining an authority level of the data sharing request end, and sending data information to the data sharing end based on the authority level of the data sharing request end and a data sharing demand. The management efficiency of the agro-ecological detection data is improved, the efficiency, accuracy and practicability of data sharing are improved, and the data sharing requirements of different types of data sharing request ends are met.

Description

Technical Field

[0001] This invention relates to the field of agricultural data management and sharing, specifically to a method, terminal, and storage medium for sharing agricultural ecological monitoring data. Background Technology

[0002] With the continuous advancement of information technology, agricultural informatization and scientific planting have become the cornerstone of improving the quality and efficiency of modern agriculture, and big data sharing is a crucial driving force for the rapid development of modern agricultural science. However, my country lags behind other countries in agricultural big data resource sharing. Currently, the development and utilization rate of various ecological monitoring data in agricultural production is low, and the data sources are different and the data standards are not uniform, making data sharing difficult and creating data silos and information blockages, which restricts the efficient management and high-quality development of modern agricultural production. At the same time, different institutions and units have different needs for sharing agricultural big data. Some institutions and units only need raw agricultural ecological monitoring data, while others need agricultural ecological monitoring data that has undergone in-depth analysis and processing to meet their specific needs. Providing different types of shared data on demand is also key to improving the efficiency and accuracy of agricultural big data sharing. Summary of the Invention

[0003] To address the above problems, this invention provides a method, terminal, and storage medium for sharing agricultural ecological monitoring data.

[0004] The objective of this invention is achieved through the following technical solution: This invention provides a method for sharing agricultural ecological monitoring data, comprising the following steps: S1. Receive agricultural ecological monitoring data, preprocess the agricultural ecological monitoring data to obtain primary agricultural ecological monitoring data, classify and store the primary agricultural ecological monitoring data to obtain a primary agricultural ecological monitoring data sharing set; S2. Retrieve target primary agricultural ecological monitoring data from the primary agricultural ecological monitoring data sharing set, perform correlation analysis on the target primary agricultural ecological monitoring data to generate intermediate data, perform network topology reconstruction on the intermediate data, and perform unique identifier encoding processing on the intermediate data after network topology reconstruction to obtain secondary agricultural ecological monitoring data, store the secondary agricultural ecological monitoring data, and obtain a secondary agricultural ecological monitoring data sharing set. S3. Retrieve target agricultural ecological monitoring secondary data from the secondary agricultural ecological monitoring data sharing set. Based on the target agricultural ecological monitoring secondary data, predict the scientific nature of agricultural production processes and generate agricultural ecological monitoring tertiary data. The agricultural ecological monitoring tertiary data is the result of scientific prediction indicators. Validate the agricultural ecological monitoring tertiary data and store the validated agricultural ecological monitoring tertiary data to obtain the tertiary agricultural ecological monitoring data sharing set. S4. Obtain the account and password information of the data sharing requester, determine the permission level of the data sharing requester, and send data information to the data sharing client based on the permission level and data sharing needs. The permission levels include no permission, level 1 permission, level 2 permission, and level 3 permission. The data sharing requester with no permission cannot receive data information from the level 1 agricultural ecological monitoring data sharing set, the level 2 agricultural ecological monitoring data sharing set, and the level 3 agricultural ecological monitoring data sharing set. The data sharing requester with level 1 permission can only receive data information from the level 1 agricultural ecological monitoring data sharing set. The data sharing requester with level 2 permission can only receive data information from the level 1 agricultural ecological monitoring data sharing set and the level 2 agricultural ecological monitoring data sharing set. The data sharing requester with level 3 permission can receive data information from the level 1 agricultural ecological monitoring data sharing set, the level 2 agricultural ecological monitoring data sharing set, and the level 3 agricultural ecological monitoring data sharing set.

[0005] Preferably, the agricultural ecological monitoring data includes at least two of the following: soil monitoring data, meteorological monitoring data, water and fertilizer application monitoring data, and pesticide monitoring data.

[0006] Preferably, the preprocessing of the agricultural ecological monitoring data includes: data cleaning, format conversion and standardization of the agricultural ecological monitoring data.

[0007] Preferably, the classification and storage involves storing the primary agricultural ecological monitoring data according to four categories: soil testing, meteorological testing, water and fertilizer application testing, and pesticide testing, generating corresponding primary agricultural ecological monitoring data subsets, and configuring and integrating the primary agricultural ecological monitoring data subsets into a primary agricultural ecological monitoring data sharing set.

[0008] Preferably, the correlation analysis includes a first correlation analysis, a second correlation analysis, and a third correlation analysis; the first correlation analysis is used for digital data, and includes performing at least one of correlation verification, causal verification, or regression verification on the digital data; the second correlation analysis is used for text data, and includes performing at least one of word segmentation, vectorization learning, text similarity analysis, or frame analysis on the text data; the third correlation analysis is used for digital text data, and includes performing at least one of cross-modal data fusion, semantic analysis feature mining, or collaborative correlation analysis on the digital data and text data; the corresponding first correlation analysis, second correlation analysis, or third correlation analysis is performed according to the type of the target agricultural ecological monitoring primary data retrieved.

[0009] Preferably, the prediction of the scientific nature of agricultural production processes includes: constructing a stage-dependent causal graph model based on the temporal logic of agricultural production processes; mapping the node codes in the target agricultural ecological monitoring secondary data to the corresponding stage nodes of the dependent causal graph model; extracting the correlation strength and environmental constraint parameters between nodes; and obtaining the scientific nature prediction index results of the agricultural production processes through a pre-trained TCN model. The scientific nature prediction index includes at least one of the following: scientific nature of plant selection, scientific nature of nutrient resource planning, and scientific nature of pest and disease prevention. The scientific nature of plant selection is related to the matching degree between crop varieties and soil physicochemical properties and climatic conditions; the scientific nature of nutrient resource planning is related to the deviation rate between actual water and fertilizer application values ​​and standard water and fertilizer application values; and the scientific nature of pest and disease prevention is related to the deviation rate between actual pesticide application values ​​and standard pesticide application values.

[0010] Preferably, the verification of the agricultural ecological monitoring three-level data includes integrity verification and practicality verification.

[0011] Preferably, obtaining the account and password information of the data sharing requester and determining the permission level of the data sharing requester includes: searching the account and password information in the account database; the account database stores registered account and password information in categories, including a primary member account database, an intermediate member account database, and a senior member account database; if the account and password information cannot be found in the account database, the data sharing requester is determined to have no permission; otherwise, the data sharing requester is determined to have level one, level two, or level three permission; if the account and password information is found in the primary member account database, the data sharing requester is determined to have level one permission; if the account and password information is found in the intermediate member account database, the data sharing requester is determined to have level two permission; if the account and password information is found in the senior member account database, the data sharing requester is determined to have level three permission.

[0012] Furthermore, the present invention also provides a terminal for agricultural ecological monitoring data, the terminal comprising: a memory, a processor, and an agricultural ecological monitoring data sharing program stored in the memory and executable on the processor, wherein the agricultural ecological monitoring data sharing program, when executed by the processor, implements the steps of the agricultural ecological monitoring data sharing method described above.

[0013] Furthermore, the present invention also provides a storage medium for agricultural ecological monitoring data, wherein the storage medium stores the agricultural ecological monitoring data sharing program, and when the agricultural ecological monitoring data sharing program is executed by a processor, it implements the steps of the agricultural ecological monitoring data sharing program method described above.

[0014] This invention includes hierarchical processing of agricultural ecological monitoring data and determination of data sharing permissions. Regarding hierarchical processing, agricultural ecological monitoring data from different sources is first received and preprocessed, including data cleaning, format conversion, and standardization, to obtain primary agricultural ecological monitoring data, which is stored in a primary agricultural ecological monitoring data sharing set. Then, based on the primary agricultural ecological monitoring data, correlation analysis, network topology reconstruction, and unique identifier encoding are performed to obtain secondary agricultural ecological monitoring data, which is stored in a secondary agricultural ecological monitoring data sharing set. Next, based on the secondary agricultural ecological monitoring data, scientific predictions are made about agricultural production processes to obtain tertiary agricultural ecological monitoring data, which is stored in a tertiary agricultural ecological monitoring data sharing set. Regarding the determination of data sharing permissions, the permission level of the data sharing requester is determined based on the account and password information provided by the requesting party. Data information is then sent to the data sharing party according to the permission level and data sharing requirements of the requesting party.

[0015] This invention performs hierarchical processing of agricultural ecological monitoring data and determines the permissions of data sharing requesters. Data information is sent according to the permissions of the data sharing requesters, thereby achieving standardized and unified management of agricultural ecological monitoring data from different data sources. It completes the analysis, overall planning and coordination of agricultural ecological monitoring data, improves the management efficiency of agricultural ecological monitoring data, enhances the efficiency, accuracy and practicality of data sharing, and meets the data sharing needs of different types of data sharing requesters. Attached Figure Description

[0016] The present invention will be further described with reference to the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present invention. For those skilled in the art, other drawings can be obtained based on the following drawings without creative effort.

[0017] Figure 1 This is a flowchart of Embodiment 1 of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] This invention provides a method for sharing agricultural ecological monitoring data, comprising the following steps: S1. Receive agricultural ecological monitoring data, preprocess the agricultural ecological monitoring data to obtain primary agricultural ecological monitoring data, classify and store the primary agricultural ecological monitoring data, and obtain a primary agricultural ecological monitoring data sharing set.

[0020] In this step, the agricultural ecological monitoring data comes from different data acquisition devices or data storage platforms. The agricultural ecological monitoring data includes at least two of the following: soil monitoring data, meteorological monitoring data, water and fertilizer application monitoring data, and pesticide monitoring data. The classification and storage in this step involves storing the primary agricultural ecological monitoring data according to four categories: soil monitoring, meteorological monitoring, water and fertilizer application monitoring, and pesticide monitoring, generating corresponding primary agricultural ecological monitoring data subsets, namely, soil monitoring data subsets, meteorological monitoring data subsets, water and fertilizer application monitoring data subsets, and pesticide monitoring data subsets. These primary agricultural ecological monitoring data subsets are configured and integrated into a primary agricultural ecological monitoring data sharing set. The preprocessing in this step includes data cleaning, format conversion, and standardization. During data cleaning, outlier detection and correction are performed, missing values ​​are filled, and duplicate values ​​are removed. During format conversion, multi-source heterogeneous data are unified and spatiotemporal benchmark alignment is performed. During standardization, dimensional normalization and semantic normalization are performed, and metadata is annotated.

[0021] S2. Retrieve the target agricultural ecological monitoring first-level data from the first-level agricultural ecological monitoring data sharing set, perform correlation analysis on the target agricultural ecological monitoring first-level data, generate intermediate data, perform network topology reconstruction on the intermediate data, and perform unique identifier encoding processing on the intermediate data after network topology reconstruction to obtain agricultural ecological monitoring second-level data, store the agricultural ecological monitoring second-level data, and obtain the second-level agricultural ecological monitoring data sharing set.

[0022] In this step, the correlation analysis includes a first correlation analysis, a second correlation analysis, and a third correlation analysis. The first correlation analysis is used for digital data and includes performing at least one of correlation verification, causal verification, or regression verification on the digital data. The second correlation analysis is used for text data and includes performing at least one of word segmentation, vectorization learning, text similarity analysis, or frame analysis on the text data. The third correlation analysis is used for digital text data and includes performing at least one of cross-modal data fusion, semantic analysis feature mining, or collaborative correlation analysis on the digital and text data. Depending on the type of the target agricultural ecological monitoring primary data retrieved, the corresponding first, second, or third correlation analysis is performed.

[0023] S3. Retrieve the target agricultural ecological monitoring secondary data from the secondary agricultural ecological monitoring data sharing set. Based on the target agricultural ecological monitoring secondary data, predict the scientific nature of agricultural production processes and generate agricultural ecological monitoring tertiary data. The agricultural ecological monitoring tertiary data is the result of scientific prediction indicators. Validate the agricultural ecological monitoring tertiary data and store the validated agricultural ecological monitoring tertiary data to obtain the tertiary agricultural ecological monitoring data sharing set.

[0024] In this step, the prediction of the scientific validity of agricultural production processes includes: constructing a stage-dependent causal graph model based on the temporal logic of agricultural production processes; mapping the node codes in the target agricultural ecological monitoring secondary data to the corresponding stage nodes in the causal graph model; extracting the correlation strength and environmental constraint parameters between nodes; and obtaining the scientific validity prediction index results of agricultural production processes through a pre-trained TCN model. The scientific validity prediction index includes at least one of the following: scientific validity of plant selection, scientific validity of nutrient resource planning, and scientific validity of pest and disease prevention. Scientific validity of plant selection is related to the matching degree between crop varieties and soil physicochemical properties and climatic conditions; scientific validity of nutrient resource planning is related to the deviation rate between actual water and fertilizer application values ​​and standard water and fertilizer application values; and scientific validity of pest and disease prevention is related to the deviation rate between actual pesticide application values ​​and standard pesticide application values. In this step, the verification of the agricultural ecological monitoring tertiary data includes completeness verification and practicality verification.

[0025] S4. Obtain the account and password information of the data sharing requester, determine the permission level of the data sharing requester, and send data information to the data sharing client based on the permission level and data sharing needs. The permission levels include no permission, level 1 permission, level 2 permission, and level 3 permission. A data sharing requester with no permission cannot receive data information from level 1, level 2, and level 3 agricultural ecological monitoring data sharing sets. A data sharing requester with level 1 permission can only receive data information from level 1 agricultural ecological monitoring data sharing sets. A data sharing requester with level 2 permission can only receive data information from level 1 and level 2 agricultural ecological monitoring data sharing sets. A data sharing requester with level 3 permission can receive data information from level 1, level 2, and level 3 agricultural ecological monitoring data sharing sets.

[0026] In this step, the specific method for determining the permission level of the data sharing requester is as follows: The account database is searched for account and password information. The account database stores registered account and password information in three categories: basic member account database, intermediate member account database, and advanced member account database. The basic member account database stores registered account and password information for those who have not paid membership fees, the intermediate member account database stores registered account and password information for those who have paid limited-term membership fees, and the advanced member account database stores registered account and password information for those who have paid lifetime membership fees. Account and password information is not shared between the basic, intermediate, and advanced member account databases. If account and password information cannot be found in the account database, the data sharing requester is deemed to have no permission; otherwise, the data sharing requester is deemed to have level one, level two, or level three permission. If account and password information is found in the basic member account database, the data sharing requester is deemed to have level one permission; if account and password information is found in the intermediate member account database, the data sharing requester is deemed to have level two permission; and if account and password information is found in the advanced member account database, the data sharing requester is deemed to have level three permission.

[0027] A terminal for agricultural ecological monitoring data includes: a memory, a processor, and an agricultural ecological monitoring data sharing program stored in the memory and executable on the processor. When the agricultural ecological monitoring data sharing program is executed by the processor, it implements the steps of the agricultural ecological monitoring data sharing method described above.

[0028] A storage medium for agricultural ecological monitoring data, wherein the storage medium stores an agricultural ecological monitoring data sharing program, and when the agricultural ecological monitoring data sharing program is executed by a processor, the steps of the agricultural ecological monitoring data sharing program method described above are implemented.

[0029] Example 1 A method for sharing agricultural ecological monitoring data includes the following steps: S1. Receive agricultural ecological monitoring data, preprocess the agricultural ecological monitoring data to obtain primary agricultural ecological monitoring data, classify and store the primary agricultural ecological monitoring data, and obtain a primary agricultural ecological monitoring data sharing set.

[0030] In this embodiment, the agricultural ecological monitoring data comes from soil monitoring sensors, temperature monitoring sensors, and humidity monitoring sensors. The agricultural ecological monitoring data includes soil monitoring data and meteorological monitoring data. The classification and storage in this step involves storing the primary agricultural ecological monitoring data according to four categories: soil monitoring, meteorological monitoring, water and fertilizer application monitoring, and pesticide monitoring, generating subsets of soil monitoring data, meteorological monitoring data, water and fertilizer application monitoring data, and pesticide monitoring data, where the water and fertilizer application monitoring data subset and the pesticide monitoring data subset are empty sets. These primary agricultural ecological monitoring data subsets are configured and integrated into a shared primary agricultural ecological monitoring data set. The preprocessing in this step includes data cleaning, format conversion, and standardization. During data cleaning, outlier detection and correction are performed, missing values ​​are filled in, and duplicate values ​​are removed. During format conversion, multi-source heterogeneous data is unified, and spatiotemporal benchmark alignment is performed. During standardization, dimensional normalization and semantic normalization are performed, and metadata is annotated.

[0031] S2. Retrieve the target agricultural ecological monitoring first-level data from the first-level agricultural ecological monitoring data sharing set, perform correlation analysis on the target agricultural ecological monitoring first-level data, generate intermediate data, perform network topology reconstruction on the intermediate data, and perform unique identifier encoding processing on the intermediate data after network topology reconstruction to obtain agricultural ecological monitoring second-level data, store the agricultural ecological monitoring second-level data, and obtain the second-level agricultural ecological monitoring data sharing set.

[0032] In this embodiment, the target agricultural ecological monitoring primary data type is digital data, and a first correlation analysis is performed. Correlation and regression verifications are then performed on the target agricultural ecological monitoring primary data.

[0033] S3. Retrieve the target agricultural ecological monitoring secondary data from the secondary agricultural ecological monitoring data sharing set. Based on the target agricultural ecological monitoring secondary data, predict the scientific nature of agricultural production processes and generate agricultural ecological monitoring tertiary data. The agricultural ecological monitoring tertiary data is the result of scientific prediction indicators. Perform integrity and practicality checks on the agricultural ecological monitoring tertiary data, store the verified agricultural ecological monitoring tertiary data, and obtain the tertiary agricultural ecological monitoring data sharing set.

[0034] In this embodiment, predicting the scientific nature of agricultural production processes includes: constructing a stage-dependent causal graph model based on the temporal logic of agricultural production processes; mapping the node codes in the target agricultural ecological monitoring secondary data to the corresponding stage nodes in the dependent causal graph model; extracting the correlation strength and environmental constraint parameters between nodes; and obtaining the scientific nature prediction index results of agricultural production processes through a pre-trained TCN model. The scientific nature prediction index includes the scientific nature of plant selection; the scientific nature of plant selection is related to the matching degree between crop varieties and soil physicochemical properties and climatic conditions.

[0035] In the integrity verification of this embodiment, the integrity of the agricultural ecological monitoring level 3 data is verified by hash value comparison to ensure that the prediction result fields are free from missing or tampered with. Furthermore, based on the agricultural production stages, time windows are divided to check the integrity of the timestamp coverage of the prediction indicator results. In the practicality verification of this embodiment, residual analysis and confidence level assessment are performed.

[0036] S4. Obtain the account and password information of the data sharing requester, determine the permission level of the data sharing requester, and send data information to the data sharing client based on the permission level and data sharing needs. The permission levels include no permission, level 1 permission, level 2 permission, and level 3 permission. A data sharing requester with no permission cannot receive data information from level 1, level 2, and level 3 agricultural ecological monitoring data sharing sets. A data sharing requester with level 1 permission can only receive data information from level 1 agricultural ecological monitoring data sharing sets. A data sharing requester with level 2 permission can only receive data information from level 1 and level 2 agricultural ecological monitoring data sharing sets. A data sharing requester with level 3 permission can receive data information from level 1, level 2, and level 3 agricultural ecological monitoring data sharing sets.

[0037] In this embodiment, the specific method for determining the permission level of the data sharing requester is as follows: The account database is searched for account and password information. The account database stores registered account and password information in three categories: basic member account database, intermediate member account database, and advanced member account database. The basic member account database stores registered account and password information for those who have not paid membership fees, the intermediate member account database stores registered account and password information for those who have paid limited-term membership fees, and the advanced member account database stores registered account and password information for those who have paid lifetime membership fees. Account and password information is not shared between the basic, intermediate, and advanced member account databases. If account and password information cannot be found in the account database, the data sharing requester is determined to have no permission; otherwise, the data sharing requester is determined to have level one, level two, or level three permission. If account and password information is found in the basic member account database, the data sharing requester has level one permission; if account and password information is found in the intermediate member account database, the data sharing requester has level two permission; and if account and password information is found in the advanced member account database, the data sharing requester has level three permission. If the data sharing request from the second-level permission data sharing client only requires second-level agricultural ecological monitoring data, then only the data information of the second-level agricultural ecological monitoring data sharing set will be sent. If the data sharing request requires both first-level and second-level agricultural ecological monitoring data, then the data information of both first-level and second-level agricultural ecological monitoring data sharing sets will be sent. The same applies to the third-level permission data sharing client.

[0038] The foregoing description and accompanying drawings fully illustrate embodiments of this disclosure to enable those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, procedural, and other changes. The embodiments represent only possible variations. Individual components and functions are optional unless explicitly required, and the order of operations may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terminology used in this application is for describing embodiments only and is not intended to limit the claims. As used in the description of embodiments and claims, the singular forms “a,” “an,” and “the” are intended to equally include the plural forms unless the context clearly indicates otherwise. Similarly, the term “and / or” as used in this application means including one or more of the associated listed items and all possible combinations thereof. Additionally, when used in this application, the term "comprise" and its variations "comprises" and / or "comprising" refer to the presence of stated features, integrals, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or groups thereof. Without further limitations, an element defined by the phrase "comprises a..." does not exclude the presence of other identical elements in the process, method, or apparatus that includes said element. In this document, each embodiment may focus on the differences from other embodiments, and similar or identical parts between embodiments can be referred to mutually. For methods, products, etc., disclosed in the embodiments, if they correspond to the method section disclosed in the embodiments, the relevant parts can be referred to the description of the method section.

[0039] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented using electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods for each specific application to achieve the described functions, but such implementation should not be considered beyond the scope of the embodiments of this disclosure. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the described devices, apparatuses, and units can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0040] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, function, and operation of possible implementations of apparatus, methods, and computer program products according to embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than those disclosed in the description; sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based device that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

Claims

1. A method for sharing agricultural ecological monitoring data, characterized in that, Includes the following steps: S1. Receive agricultural ecological monitoring data, preprocess the agricultural ecological monitoring data to obtain primary agricultural ecological monitoring data, classify and store the primary agricultural ecological monitoring data to obtain a primary agricultural ecological monitoring data sharing set; S2. Retrieve target primary agricultural ecological monitoring data from the primary agricultural ecological monitoring data sharing set, perform correlation analysis on the target primary agricultural ecological monitoring data to generate intermediate data, perform network topology reconstruction on the intermediate data, and perform unique identifier encoding processing on the intermediate data after network topology reconstruction to obtain secondary agricultural ecological monitoring data, store the secondary agricultural ecological monitoring data, and obtain a secondary agricultural ecological monitoring data sharing set. S3. Retrieve target agricultural ecological monitoring secondary data from the secondary agricultural ecological monitoring data sharing set. Based on the target agricultural ecological monitoring secondary data, predict the scientific nature of agricultural production processes and generate agricultural ecological monitoring tertiary data. The agricultural ecological monitoring tertiary data is the result of scientific prediction indicators. Validate the agricultural ecological monitoring tertiary data and store the validated agricultural ecological monitoring tertiary data to obtain the tertiary agricultural ecological monitoring data sharing set. S4. Obtain the account and password information of the data sharing requesting end, determine the permission level of the data sharing requesting end, and send data information to the data sharing end based on the permission level of the data sharing requesting end and the data sharing requirements; the permission level includes no permission, level 1 permission, level 2 permission, and level 3 permission; The data sharing request client without authorization cannot receive data from the Level 1 agricultural ecological monitoring data sharing set, the Level 2 agricultural ecological monitoring data sharing set, and the Level 3 agricultural ecological monitoring data sharing set; the data sharing request client with Level 1 authorization can only receive data from the Level 1 agricultural ecological monitoring data sharing set. The secondary-level permission data sharing request terminal can only receive data information from the primary-level agricultural ecological monitoring data sharing set and the secondary-level agricultural ecological monitoring data sharing set; the tertiary-level permission data sharing request terminal can receive data information from the primary-level agricultural ecological monitoring data sharing set, the secondary-level agricultural ecological monitoring data sharing set, and the tertiary-level agricultural ecological monitoring data sharing set.

2. The method for sharing agricultural ecological monitoring data according to claim 1, characterized in that, The agricultural ecological monitoring data includes at least two of the following: soil monitoring data, meteorological monitoring data, water and fertilizer application monitoring data, and pesticide monitoring data.

3. The method for sharing agricultural ecological monitoring data according to claim 1, characterized in that, The preprocessing of the agricultural ecological monitoring data includes: data cleaning, format conversion, and standardization of the agricultural ecological monitoring data.

4. The method for sharing agricultural ecological monitoring data according to claim 1, characterized in that, The classification and storage involves storing the primary agricultural ecological monitoring data according to four categories: soil testing, meteorological testing, water and fertilizer application testing, and pesticide testing, generating corresponding primary agricultural ecological monitoring data subsets, and configuring and integrating these primary agricultural ecological monitoring data subsets into a primary agricultural ecological monitoring data sharing set.

5. The method for sharing agricultural ecological monitoring data according to claim 1, characterized in that, The correlation analysis includes a first correlation analysis, a second correlation analysis, and a third correlation analysis; the first correlation analysis is used for digital data, and includes performing at least one of correlation verification, causal verification, or regression verification on the digital data; the second correlation analysis is used for text data, and includes performing at least one of word segmentation, vectorization learning, text similarity analysis, or frame analysis on the text data; the third correlation analysis is used for digital text data, and includes performing at least one of cross-modal data fusion, semantic analysis feature mining, or collaborative correlation analysis on the digital data and text data; the corresponding first correlation analysis, second correlation analysis, or third correlation analysis is performed according to the type of the target agricultural ecological monitoring primary data retrieved.

6. The method for sharing agricultural ecological monitoring data according to claim 1, characterized in that, The prediction of the scientific nature of agricultural production processes includes: constructing a stage-dependent causal graph model based on the temporal logic of agricultural production processes; mapping the node codes in the target agricultural ecological monitoring secondary data to the corresponding stage nodes in the dependent causal graph model; extracting the correlation strength and environmental constraint parameters between nodes; and obtaining the scientific nature prediction index results of the agricultural production processes through a pre-trained TCN model. The scientific nature prediction index includes at least one of the following: scientific nature of plant selection, scientific nature of nutrient resource planning, and scientific nature of pest and disease prevention. The scientific nature of plant selection is related to the matching degree between crop varieties and soil physicochemical properties and climatic conditions; the scientific nature of nutrient resource planning is related to the deviation rate between actual water and fertilizer application values ​​and standard water and fertilizer application values; and the scientific nature of pest and disease prevention is related to the deviation rate between actual pesticide application values ​​and standard pesticide application values.

7. The method for sharing agricultural ecological monitoring data according to claim 1, characterized in that, The verification of the three-level agricultural ecological monitoring data includes integrity verification and practicality verification.

8. The method for sharing agricultural ecological monitoring data according to claim 1, characterized in that, The step of obtaining the account and password information of the data sharing requester and determining the permission level of the data sharing requester includes: searching the account and password information in the account database; the account database stores registered account and password information in categories, including a primary member account database, an intermediate member account database, and a senior member account database; if the account and password information cannot be found in the account database, the data sharing requester is determined to have no permission; otherwise, the data sharing requester is determined to have level one, level two, or level three permission; if the account and password information is found in the primary member account database, the data sharing requester is determined to have level one permission; if the account and password information is found in the intermediate member account database, the data sharing requester is determined to have level two permission; if the account and password information is found in the senior member account database, the data sharing requester is determined to have level three permission.

9. A terminal, characterized in that, The terminal includes: a memory, a processor, and an agricultural ecological monitoring data sharing program stored in the memory and executable on the processor. When the agricultural ecological monitoring data sharing program is executed by the processor, it implements the steps of the agricultural ecological monitoring data sharing method as described in any one of claims 1-8.

10. A storage medium, characterized in that, The storage medium stores the agricultural ecological monitoring data sharing program, which, when executed by a processor, implements the steps of the agricultural ecological monitoring data sharing program method as described in any one of claims 1-8.

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