A real-time design interaction system

Abstract

The present invention relates to the field of data analysis technology, and in particular to a real-time design interaction system, including a multi-source data management module, a data interaction middle platform, and a dynamic maintenance scheduling module; by classifying and processing the original data set of the target area, obtaining the data set, creating a data table, using a database for storage, and establishing an index, it is beneficial to convert the original data into a high-quality data set that can be used for subsequent analysis, and speed up data retrieval; by integrating data from the multi-source data management module through the data interaction middle platform, and performing integration processing, data exchange is performed between data of different categories; by performing quantitative analysis based on the data exchange results, the conditions for crop growth are dynamically adjusted, and the strategy can be quickly responded and adjusted to improve agricultural production efficiency. The present invention is used to solve the technical problems of insufficient data integration and real-time regulation capabilities in current agricultural production management.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to a real-time design interaction system. Background Art

[0002] Data analysis technology refers to the process of collecting, processing, analyzing and interpreting data to extract valuable information and insights. It helps businesses and individuals make fact-based decisions, optimize operational strategies, and predict future trends.

[0003] With the continuous advancement of technology and the continuous expansion of application fields, the field of smart agriculture is also developing steadily. However, in the production management of smart agriculture, the following problems still exist: agricultural data management is chaotic and inefficient. A large amount of raw data will be generated in agricultural production. These data come from different devices and sensors, including environmental data, crop growth data, equipment efficiency data, etc. If these data are not effectively classified and managed, it will lead to data confusion, which is difficult to find and use, and traditional data management methods often rely on manual sorting, which is inefficient and prone to errors; data islands and information are not shared, and various systems and equipment in agricultural production often act independently. Data is difficult to circulate and share between different systems, forming data islands, which not only limits the utilization value of data, but also increases the complexity and cost of data processing; agricultural production control lacks real-time and accuracy. Traditional agricultural production decisions often rely on experience and regular data collection, which is difficult to achieve real-time and accuracy. The agricultural production environment is complex and changeable, requiring rapid response and adjustment, and traditional control methods cannot meet this demand. To this end, the present invention proposes a real-time design interaction system. Summary of the invention

[0004] The purpose of the present invention is to solve the problems in the background technology and to propose a real-time design interaction system.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] A real-time design interaction system, comprising: a multi-source data management module, a data interaction middle platform and a dynamic maintenance scheduling module;

[0007] The multi-source data management module is used to classify and manage the original agricultural data sets in the target area, obtain the environmental comprehensive monitoring set, crop growth status set, equipment efficiency evaluation set and farmland space information set through data processing, and create a data table for each category of data set, use the database for data storage, and establish an index at the same time; the multi-source data management module includes a classification management unit, a fusion processing unit, a data table design unit, a data storage unit and an index establishment unit;

[0008] The data interaction platform is used to integrate data from multi-source data management modules, integrate and process the data resources within the modules, and form a centralized data interaction platform to enable data exchange between different categories;

[0009] The dynamic maintenance scheduling module is used to conduct quantitative analysis based on real-time data exchange results and dynamically adjust crop growth conditions.

[0010] It should be noted that the application object of a real-time design interaction system in the embodiment of the present invention can be agricultural production management in the field of smart agriculture, and can be used to monitor the farmland environment, crop growth status, equipment efficiency, farmland spatial layout and other aspects. Specifically, it can be through data analysis technology to collect environmental data, crop growth data, equipment efficiency data and farmland spatial information data for comprehensive analysis and accurate evaluation, so as to achieve dynamic grasp and precise regulation of agricultural production conditions. Through data integration of the data interaction middle platform, quantitative analysis and dynamic adjustment of the dynamic maintenance scheduling module, and data processing and storage of the multi-source data management module, a complete intelligent management system is formed, so that the system can significantly improve the operation efficiency and resource utilization efficiency of agricultural production, and ensure the optimization of the crop growth environment and the increase of yield; at the same time, the system also promotes the transparency and traceability of agricultural production information, meets the needs of efficient utilization of agricultural resources and sustainable development, and through the application of the real-time design interaction system, agricultural production management becomes more intelligent, refined and scientific, providing strong technical support for the development of smart agriculture.

[0011] Furthermore, the classification management unit is used for the classification management of the agricultural original data set of the target area, and the process includes:

[0012] Identify and access all data sources to obtain raw data sets, including weather stations, soil monitoring stations, crop growth monitoring systems, equipment monitoring systems, and GIS systems;

[0013] Define the weather station data as X m , the data of soil monitoring station is X s , the data of the crop growth monitoring system is X c , the data of the equipment monitoring system is X e And the data of GIS system is X g ;

[0014] Classify the original data set according to the source of the data and the type of information it represents:

[0015] D en =b en (X m ,X s )

[0016] D cr =b cr (X c )

[0017] D eq =b eq (X e )

[0018] D ge =b ge (X g )

[0019] Where D en , D cr , D eq , D ge Respectively represent environmental information, crop growth status, equipment operation status and geographic space information; b en 、b cr 、b eq 、b ge They represent the environmental information conversion function, the crop growth state conversion function, the equipment operation status conversion function and the geographic space information conversion function respectively;

[0020] It can be understood that environmental information includes temperature and humidity, precipitation, wind speed, wind direction, and sunshine duration data from meteorological stations, as well as soil pH and temperature and humidity data from soil monitoring stations. Crop growth status covers crop growth stages, health conditions, and yield forecast data from crop growth monitoring systems. Equipment operating conditions refer to agricultural machinery working conditions and energy consumption monitoring data obtained through equipment monitoring systems. Geospatial information involves land division and terrain information in GIS systems. Environmental information mainly covers natural environmental factors that affect crop growth and agricultural activities. Crop growth status focuses on the growth process and condition of crops. Equipment operating conditions focus on the operating status and efficiency of various equipment used in agricultural activities. Geospatial information covers information related to the geographical location and spatial characteristics of agricultural areas.

[0021] Furthermore, the process of the fusion processing unit for obtaining the comprehensive environmental monitoring set, the crop growth situation set, the equipment performance evaluation set and the farmland spatial information set through data processing includes:

[0022] After integrating environmental information, crop growth status, equipment operation status and geographic space information, we can obtain the comprehensive environmental monitoring set, crop growth status set, equipment efficiency evaluation set and farmland space information set:

[0023]

[0024] Where D' en , D' cr , D'eq , D' ge They represent the integrated environmental monitoring set, crop growth status set, equipment efficiency evaluation set and farmland spatial information set after fusion processing respectively; F en 、F cr 、F eq 、F ge Respectively represent the fusion functions of environmental information, crop growth status, equipment operation status and geographic space information; d en ,d cr ,d eq ,d ge The data points represent environmental information, crop growth status, equipment operation status and geographic space information respectively; en Indicates D en Environmental impact weight factor; α cr , β eq , γ ge Respectively represent D cr Growth contribution coefficient, D eq The efficiency weight coefficient and D ge The spatial correlation coefficient.

[0025] Furthermore, the process of the data table design unit for creating a corresponding data table for each category of data set includes:

[0026] For comprehensive environmental monitoring data table T en :

[0027] Field Collection E en ={f1,f2,...,fn},

[0028] Wherein, fi represents the i-th field, and i=1,2,...,n;

[0029] Record set R en , each record r en ∈R en Indicates a en Mapping to data values ​​in the environmental comprehensive monitoring set;

[0030] For the crop growth status data table T cr :

[0031] Field Collection E cr ={f1 (1) ,f2 (1) ,...,fn (1)},

[0032] Among them, (1) Indicates the i (1) fields, and i (1) =1,2,...,n(1) ;

[0033] Record set R cr , each record r cr ∈R cr Indicates a cr Mapping to data values ​​in a crop growth status set;

[0034] Data sheet T for equipment effectiveness evaluation eq :

[0035] Field Collection E eq ={f1 (2) ,f2 (2) ,...,fn (2)},

[0036] Among them, (2) Indicates the i (2) fields, and i (2) =1,2,...,n (2) ;

[0037] Record set R eq , each record r eq ∈R eq Indicates a eq Mapping to data values ​​in a crop growth status set;

[0038] For farmland space information data table T ge :

[0039] Field Collection E ge ={f1 (3) ,f2 (3) ,...,fn (3)},

[0040] Among them, (3) Indicates the i (3) fields, and i (3) =1,2,...,n (3) ;

[0041] Record set R ge , each record r ge ∈R ge Indicates a ge A mapping to data values ​​in the crop growth status set.

[0042] Furthermore, the process of the data storage unit using the database to store the data set includes:

[0043] Each record in the fused data set is stored in the corresponding database according to the structure of its corresponding data table:

[0044] For each data set D(D' en , D' cr , D' eq , D' ge ) and the corresponding data table T(T en 、T cr 、T eq 、T ge ), the stored procedure is formalized as:

[0045]

[0046] In the formula, Store(D,T) represents the storage result of the data set and the corresponding data table; E(E en 、E cr 、E eq 、E ge ) is the data table T(T en 、T cr 、T eq 、T ge ) field set; r(ι) represents each record r(r en 、r cr 、r eq 、r ge ) in the field ι(fi,fi (1) 、fi (2) 、fi (3) ) value; r'(ι) represents the data table T(T en 、T cr 、T eq 、T ge ) in the newly created record r' in the field ι(fi, fi (1) 、fi (2) 、fi (3) ) on the .

[0047] Furthermore, the index building unit is used to build an index according to the created data table, and the process includes:

[0048] Based on the created data table T(T en 、T cr 、T eq 、T ge ), create indexes for key fields of various data sets, using I(I en ,I cr ,I eq ,I ge ) represents an index set; each element τ∈I is a en 、E cr 、E eq 、E ge ) to index types;

[0049] For each data table and its index set, the index creation process is formalized as follows:

[0050]

[0051] In the formula, CI(T,I) represents the output result of the created data table and the corresponding index set; τ.key represents the field on which the index is based; τ.type represents the type of index.

[0052] Furthermore, the data interaction platform integrates data from multi-source data management modules, integrates and processes the data resources within the modules, and performs data exchange processes including:

[0053] Get the data sets of the multi-source data management module and define the basic structure for each data set, that is, assume that each data set Θ p (aj,vj) contains several attributes:

[0054] Θ p (aj,vj)={(a1,v1),(a2,v2),...,(ao,vo)}

[0055] In the formula, p represents the index subscript of en, cr, eq, ge; aj represents the attribute name; vj represents the corresponding attribute value; j represents the data set Θ p The attribute name and attribute value number in (aj,vj), where j = 1, 2, ..., o; o represents the data set Θ p The total number of attribute names and attribute values ​​in (aj,vj);

[0056] Use the mapping function y pq Represents the dataset Θ p (aj,vj) to Θ q The mapping relationship of (aj',vj') is:

[0057] y pq :Θ p (aj,vj)→Θ q (aj',vj'); where Θ q (aj',vj') represents the mapped data set;

[0058] This is achieved by defining a set of transformation rules Z, where each rule z∈Z is used to determine the transformation from one data set to another data set or an intermediate format;

[0059] A data exchange protocol is set, wherein the set data exchange protocol is a message-based protocol, and each message M includes a message type L, a data set identifier J, and data content N, that is, an exchange triplet M = (L, J, N);

[0060] It can be understood that in the exchange triplet, the message types include request, response, notification, etc., the dataset identifier indicates the dataset involved in the message, and the data content refers to the actual data; wherein, the data interaction process is: 1. The data request unit initiates a data request, 2. The target unit processes the data according to the request and generates a response message containing the required data, 3. The data request unit receives the data and performs further integration processing as needed.

[0061] Furthermore, the dynamic maintenance scheduling module conducts quantitative analysis based on the real-time data exchange results, and the process of dynamically adjusting crop growth conditions includes:

[0062] Let G k ={G1,G2,...,G h} represents the parameter set of crop growth conditions in the current target area; where G k is the current value of the kth parameter of the crop growth condition of the current target area; k represents the parameter number of the crop growth condition of the current target area, and k=1, 2, ..., h; h represents the total number of parameters of the crop growth condition of the current target area;

[0063] Then G id = {G id,1 ,G id,2 ,...,G id,h} is the parameter set under ideal conditions; where G id,k is the ideal value of the kth parameter under ideal conditions;

[0064] Comprehensive assessment of each crop growth condition parameter:

[0065]

[0066] In the formula, δ k Represents the comprehensive evaluation score; |G k -G id,k | indicates the deviation between the calculated current value and the ideal value; U k The weight of the kth parameter representing the crop growth condition reflects the importance of this parameter to crop growth;

[0067] Determine whether crop growth conditions need to be adjusted based on the evaluation score and calculate the adjustment amount △G k :

[0068] △G k =Y k ·δ k

[0069] Where Y kThe adjustment coefficient of the kth parameter representing the crop growth condition depends on the adjustment capacity of the system and the urgency of the current deviation;

[0070] After obtaining the adjustment amount of each parameter of crop growth conditions, the overall adjustment plan △G is formed k ={△G1,△G2,...,△G h};

[0071] Combined with the adjustment scheme, an adjustment function Q is created. The adjustment function Q receives the current crop growth conditions and the adjustment amount as input, and outputs the adjusted crop growth conditions G k+1 :

[0072] G k+1 =Q(G k ,△G k );

[0073] Once adjustments are made, the system will respond according to the new crop growing conditions;

[0074] Understandably, this may include changing irrigation amounts, adjusting greenhouse temperatures, etc., and these responses will directly affect the growth environment of crops; Understandably, the entire dynamic adjustment process is iterative, and after each adjustment, the system will re-collect data, analyze, and possibly adjust again, ensuring that the system can continuously optimize crop growth conditions.

[0075] Compared with the existing technology, the present invention provides a real-time design interaction system and method with the advantages of:

[0076] 1. The present invention classifies and manages the original agricultural data set of the target area, and the original agricultural data is orderly classified, making the data use more efficient; through data processing, the comprehensive environmental monitoring set, the crop growth situation set, the equipment efficiency evaluation set and the farmland spatial information set are obtained, so that the data from different sources can be matched and integrated with each other, providing a more complete and rich data set for subsequent analysis and application;

[0077] 2. The present invention can reduce data redundancy and waste of storage space and improve the storage efficiency of the database by creating a data table for each category of data set; by using the database for data storage and establishing indexes at the same time, the long-term preservation and reliability of the data are ensured, the risk of data loss is avoided, data retrieval is faster and more efficient, and the query time can be significantly reduced;

[0078] 3. The present invention integrates data from multi-source data management modules through a data interaction middle platform, integrates and processes the data resources within the module, and enables data exchange between different categories of data; by performing quantitative analysis based on real-time data exchange results and dynamically adjusting crop growth conditions, it is able to respond and adjust strategies quickly, thereby enhancing the adaptability and resilience of agricultural production and improving crop yield and quality.

[0079] To sum up, the present invention performs comprehensive data analysis and precise monitoring through data processing and storage management of multi-source data management modules, data integration of data interaction middle platform, and quantitative analysis and dynamic adjustment of dynamic maintenance scheduling modules. The various modules in the invention cooperate and work together to promote the intelligent, efficient and sustainable development of agricultural production, which not only helps to improve the automation level of agricultural production, but also provides strong support for the sustainable development of agriculture, ensuring the efficient and stable operation of a subsequent real-time design interaction system. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] Figure 1 This is a module diagram of a real-time design interaction system proposed by the present invention. DETAILED DESCRIPTION

[0081] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the implementation regulations described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0082] Reference Figure 1 , a real-time design interaction system, the system includes a multi-source data management module, a data interaction middle platform and a dynamic maintenance scheduling module;

[0083] The multi-source data management module is used to classify and manage the original agricultural data sets in the target area, obtain the environmental comprehensive monitoring set, crop growth status set, equipment efficiency evaluation set and farmland space information set through data processing, and create a data table for each category of data set, use the database for data storage, and establish an index at the same time; the multi-source data management module includes a classification management unit, a fusion processing unit, a data table design unit, a data storage unit and an index establishment unit;

[0084] The data interaction platform is used to integrate data from multi-source data management modules, integrate and process the data resources within the modules, and form a centralized data interaction platform to enable data exchange between different categories;

[0085] The dynamic maintenance scheduling module is used to conduct quantitative analysis based on real-time data exchange results and dynamically adjust crop growth conditions.

[0086] It should be noted that the application object of a real-time design interaction system in the embodiment of the present invention can be agricultural production management in the field of smart agriculture, and can be used to monitor the farmland environment, crop growth status, equipment efficiency, farmland spatial layout and other aspects. Specifically, it can be through data analysis technology to collect environmental data, crop growth data, equipment efficiency data and farmland spatial information data for comprehensive analysis and accurate evaluation, so as to achieve dynamic grasp and precise regulation of agricultural production conditions. Through data integration of the data interaction middle platform, quantitative analysis and dynamic adjustment of the dynamic maintenance scheduling module, and data processing and storage of the multi-source data management module, a complete intelligent management system is formed, so that the system can significantly improve the operation efficiency and resource utilization efficiency of agricultural production, and ensure the optimization of the crop growth environment and the increase of yield; at the same time, the system also promotes the transparency and traceability of agricultural production information, meets the needs of efficient utilization of agricultural resources and sustainable development, and through the application of the real-time design interaction system, agricultural production management becomes more intelligent, refined and scientific, providing strong technical support for the development of smart agriculture.

[0087] The multi-source data management module classifies and manages the original agricultural data sets in the target area, obtains the environmental comprehensive monitoring set, crop growth status set, equipment efficiency evaluation set and farmland space information set through data processing, and creates a data table for each category of data set, uses a database for data storage, and the steps of establishing an index include:

[0088] Step 101, identifying and accessing all data sources to obtain original data sets, including weather stations, soil monitoring stations, crop growth monitoring systems, equipment monitoring systems, and GIS systems;

[0089] Step 102: define the weather station data as X m , the data of soil monitoring station is X s , the data of the crop growth monitoring system is X c , the data of the equipment monitoring system is X e And the data of GIS system is X g ;

[0090] Step 103: Classify and divide the original data set according to the data source and the type of information represented:

[0091] D en =b en (X m ,X s )

[0092] Dcr =b cr (X c )

[0093] D eq =b eq (X e )

[0094] D ge =b ge (X g )

[0095] Where D en , D cr , D eq , D ge Respectively represent environmental information, crop growth status, equipment operation status and geographic space information; b en 、b cr 、b eq 、b ge They represent the environmental information conversion function, the crop growth state conversion function, the equipment operation status conversion function and the geographic space information conversion function respectively;

[0096] In step 103, the environmental information includes the temperature and humidity, precipitation, wind speed, wind direction, and sunshine duration data of the meteorological station, and the soil pH value and temperature and humidity data of the soil monitoring station. The crop growth status covers the crop growth stage, health status, and yield prediction data of the crop growth monitoring system. The equipment operation status refers to the working status and energy consumption monitoring data of the agricultural machinery obtained through the equipment monitoring system. The geographic spatial information involves the plot division and terrain information in the GIS system. The environmental information mainly covers the natural environmental factors that affect the growth of crops and agricultural activities. The crop growth status focuses on the growth process and status of crops. The equipment operation status focuses on the operation status and efficiency of various equipment used in agricultural activities. The geographic spatial information covers information related to the geographical location and spatial characteristics of the agricultural area.

[0097] Step 104: After fusing the environmental information, crop growth status, equipment operation status and geographic space information, a comprehensive environmental monitoring set, a crop growth status set, an equipment efficiency evaluation set and a farmland space information set are obtained:

[0098]

[0099]

[0100] Where D' en , D' cr , D' eq , D' geThey represent the integrated environmental monitoring set, crop growth status set, equipment efficiency evaluation set and farmland spatial information set after fusion processing respectively; F en 、F cr 、F eq 、F ge Respectively represent the fusion functions of environmental information, crop growth status, equipment operation status and geographic space information; d en d cr d eq d ge The data points represent environmental information, crop growth status, equipment operation status and geographic space information respectively; en Indicates D en Environmental impact weight factor; α cr , β eq , γ ge Respectively represent D cr Growth contribution coefficient, D eq The efficiency weight coefficient and D ge The spatial correlation coefficient of

[0101] Step 105: For the comprehensive environmental monitoring data table T en :

[0102] Field Collection E en ={f1,f2,...,fn},

[0103] Wherein, fi represents the i-th field, and i=1,2,...,n;

[0104] Record set R en , each record r en ∈R en Indicates a en Mapping to data values ​​in the environmental comprehensive monitoring set;

[0105] Step 106: For the crop growth status data table T cr :

[0106] Field Collection E cr ={f1 (1) ,f2 (1) ,...,fn (1)},

[0107] Among them, (1) Indicates the i (1) fields, and i (1) =1,2,...,n (1) ;

[0108] Record set R cr , each record r cr ∈Rcr Indicates a cr Mapping to data values ​​in a crop growth status set;

[0109] Step 107: Equipment performance evaluation data table T eq :

[0110] Field Collection E eq ={f1 (2) ,f2 (2) ,...,fn (2)},

[0111] Among them, (2) Indicates the i (2) fields, and i (2) =1,2,...,n (2) ;

[0112] Record set R eq , each record r eq ∈R eq Indicates a eq Mapping to data values ​​in a crop growth status set;

[0113] Step 108: For the farmland spatial information data table T ge :

[0114] Field Collection E ge ={f1 (3) ,f2 (3) ,...,fn (3)},

[0115] Among them, (3) Indicates the i (3) fields, and i (3) =1,2,...,n (3) ;

[0116] Record set R ge , each record r ge ∈R ge Indicates a ge Mapping to data values ​​in a crop growth status set;

[0117] Step 109: Store each record in the fused data set in the corresponding database according to the structure of its corresponding data table:

[0118] For each data set D(D' en , D' cr , D' eq , D' ge ) and the corresponding data table T(T en 、Tcr 、T eq 、T ge ), the stored procedure is formalized as:

[0119]

[0120] In the formula, Store(D,T) represents the storage result of the data set and the corresponding data table; E(E en 、E cr 、E eq 、E ge ) is the data table T(T en 、T cr 、T eq 、T ge ) field set; r(ι) represents each record r(r en 、r cr 、r eq 、r ge ) in the field ι(fi,fi (1) 、fi (2) 、fi (3) ) value; r'(ι) represents the data table T(T en 、T cr 、T eq 、T ge ) in the newly created record r' in the field ι(fi, fi (1) 、fi (2) 、fi (3) ) on the value;

[0121] Step 110: Based on the created data table T(T en 、T cr 、T eq 、T ge ), create indexes for key fields of various data sets, using I(I en ,I cr ,I eq ,I ge ) represents an index set; each element τ∈I is a en 、E cr 、E eq 、E ge ) to index types;

[0122] Step 111: For each data table and its index set, the index creation process is formalized as follows:

[0123]

[0124] In the formula, CI(T,I) represents the output result of the created data table and the corresponding index set; τ.key represents the field on which the index is based; τ.type represents the type of index;

[0125] For example, suppose the environmental comprehensive monitoring set D' en Often you need to query data based on date and time. en Create an index based on a datetime field:

[0126] Index Set I en ={τ};

[0127] Execute CI(T en ,I en ) is T en Create indexes;

[0128] Among them, for the data table T of the comprehensive environmental monitoring set en , index set I en It may contain the following elements: τ1, a B-tree index based on the date and time field; τ2, a hash index based on the location field; τ3, a composite B-tree index based on the combination of the date and time field and the location field, used for efficient query based on both time and location;

[0129] It should be noted that hash index is implemented based on hash table, which converts index key into hash value through hash function and stores the hash value in the index; B-tree index is a balanced search tree, which keeps data in order and stores all values ​​in a certain order;

[0130] When choosing between hash index and B-tree index, you need to weigh them according to the specific application scenario and requirements. If the application scenario is mainly based on equal value query and has extremely high requirements for query speed, you can choose hash index. If the application scenario needs to support range query, dynamic data update or sequential access, B-tree index is more suitable. In the comprehensive environmental monitoring center, you can choose the appropriate index type according to the characteristics of the monitoring data and query requirements to improve the efficiency of query, data management and subsequent data interaction.

[0131] In step 101 to step 111, the original agricultural data set of the target area is automatically classified to ensure the orderliness and manageability of the data; the original data is converted into a high-quality data set that can be used for subsequent analysis through data processing; a reasonable data table structure is designed according to the type and purpose of the data set to provide a basis for data storage and query; the processed data is stored using database technology to ensure the persistence and accessibility of the data; and indexes are established for key fields to improve data retrieval efficiency.

[0132] The data exchange platform integrates data from multi-source data management modules, integrates and processes the data resources within the modules, and performs data exchange steps including:

[0133] Step 201: Obtain the data sets of the multi-source data management module and define the basic structure for each data set. That is, assume that each data set Θ p (aj,vj) contains several attributes:

[0134] Θ p (aj,vj)={(a1,v1),(a2,v2),...,(ao,vo)}

[0135] In the formula, p represents the index subscript of en, cr, eq, ge; aj represents the attribute name; vj represents the corresponding attribute value; j represents the data set Θ p The attribute name and attribute value number in (aj,vj), where j = 1, 2, ..., o; o represents the data set Θ p The total number of attribute names and attribute values ​​in (aj,vj);

[0136] Step 202: Use mapping function y pq Represents the dataset Θ p (aj,vj) to Θ q The mapping relationship of (aj',vj') is:

[0137] y pq :Θ p (aj,vj)→Θ q (aj',vj'); where Θ q (aj',vj') represents the mapped data set;

[0138] Step 203, implemented by defining a conversion rule set Z, wherein each rule z∈Z is used to determine conversion from one data set to another data set or an intermediate format;

[0139] For example, rule z en →z cr It defines how to extract parameters such as temperature and humidity from comprehensive environmental monitoring data to predict certain indicators in crop growth status data;

[0140] Step 204: Set a data exchange protocol, wherein the set data exchange protocol is a message-based protocol, and each message M includes a message type L, a data set identifier J, and data content N, that is, an exchange triplet M = (L, J, N);

[0141] In step 204, the message type of the exchange triplet includes request, response, notification, etc., the data set identifier indicates the data set involved in the message, and the data content refers to the actual data;

[0142] The data interaction process is as follows: 1. The data request unit initiates a data request; 2. The target unit processes the data according to the request and generates a response message containing the required data; 3. The data request unit receives the data and further integrates and processes it as needed;

[0143] For example, extracting temperature data H from the comprehensive environmental monitoring system en , used to update the temperature dependence index H in the crop growth situation set cr , the data exchange process is simplified to:

[0144] y en→cr (M,H en )→H cr ;

[0145] In step 201 to step 204, data is collected from the multi-source data management module, and necessary integration and conversion are performed, while providing a centralized data interaction platform to support real-time exchange and sharing of different categories of data.

[0146] The dynamic maintenance scheduling module conducts quantitative analysis based on the real-time data exchange results. The steps of dynamically adjusting crop growth conditions include:

[0147] Step 301: Set G k ={G1,G2,...,G h} represents the parameter set of crop growth conditions in the current target area; where G k is the current value of the kth parameter of the crop growth condition of the current target area; k represents the parameter number of the crop growth condition of the current target area, and k=1, 2, ..., h; h represents the total number of parameters of the crop growth condition of the current target area;

[0148] Step 302: G id = {G id,1 ,G id,2 ,...,G id,h} is the parameter set under ideal conditions; where G id,k is the ideal value of the kth parameter under ideal conditions;

[0149] Step 303: Comprehensively evaluate the parameters of each crop growth condition:

[0150]

[0151] In the formula, δ k Represents the comprehensive evaluation score; |G k -G id,k | indicates the deviation between the calculated current value and the ideal value; U kThe weight of the kth parameter representing the crop growth condition reflects the importance of this parameter to crop growth;

[0152] Step 304: Determine whether to adjust the crop growth conditions based on the evaluation score and calculate the adjustment amount ΔG k :

[0153] △G k =Y k ·δ k

[0154] Where Y k The adjustment coefficient of the kth parameter representing the crop growth condition depends on the adjustment capacity of the system and the urgency of the current deviation;

[0155] Step 305: After obtaining the adjustment amount of each parameter of the crop growth condition, a total adjustment plan △G is formed comprehensively. k ={△G1,△G2,...,△G h};

[0156] Step 306: Create an adjustment function Q in combination with the adjustment scheme. The adjustment function Q receives the current crop growth condition and the adjustment amount as input and outputs the adjusted crop growth condition G. k+1 :

[0157] G k+1 =Q(G k ,△G k );

[0158] Step 307, after the adjustment is performed, the system will respond according to the new crop growth conditions;

[0159] In step 307, this may include changing the irrigation amount, adjusting the greenhouse temperature, etc., which will directly affect the growing environment of the crops; it is understandable that the entire dynamic adjustment process is iterative, and after each adjustment, the system will re-collect data, analyze, and possibly adjust again, ensuring that the system can continuously optimize the growing conditions of the crops;

[0160] In steps 301 to 307, the real-time exchanged data is quantitatively analyzed to achieve precise control of the crop growth environment. According to preset rules, it is determined whether the current crop growth conditions meet the requirements, and through real-time adjustments, waste of resources such as excessive irrigation and fertilization is avoided. According to the analysis results, adjustment measures such as irrigation, fertilization, and environmental regulation are automatically or manually triggered to quickly respond to environmental changes, adjust crop growth conditions in time, and improve agricultural production efficiency.

[0161] In the embodiment of the present invention, by classifying agricultural raw data sets, such as environmental data, crop growth data, equipment efficiency data, farmland space data, etc., the standardization and efficiency of data management are improved, which is convenient for subsequent data analysis and utilization; by using data fusion technology, data from different sources are integrated into a consistent, high-quality data set to ensure the accuracy and consistency of the data and reduce erroneous decisions caused by data quality problems; by designing a reasonable data table structure according to data type and purpose, the integrity, consistency and efficient access of the data are ensured; by persistently storing data according to the designed data table structure, and establishing indexes for key fields in the data table, the data retrieval speed is accelerated and the query efficiency is improved; by merging data from multiple sources, Extract data from the data management module, break the data island, realize centralized management and sharing of data, and improve data utilization; by defining standardized data exchange protocols, realize data interaction and sharing between different modules, and reduce the complexity and cost of data use; by quantitatively analyzing the data exchanged in real time, realize precise control of the crop growth environment and improve crop yield and quality; by judging whether the current crop growth conditions meet the requirements based on the analysis results and combined with preset rules, thereby reducing human intervention and misjudgment and reducing agricultural production costs; by triggering corresponding adjustment measures based on the judgment results, to optimize crop growth conditions, improve the intelligence and automation level of agricultural production, and enhance the sustainability and competitiveness of agricultural production. In summary, the examples of the present invention solve the problem of insufficient data integration and real-time control capabilities in current agricultural production management. In actual situations, more data and contextual information may be needed to make specific decisions and optimization plans.

[0162] In addition, the formulas involved in the above are all calculated by removing dimensions and taking their numerical values. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The proportional coefficient in the formula and the various preset thresholds in the analysis process are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data; the size of the proportional coefficient is to quantify each parameter to obtain a specific value for subsequent comparison. The size of the proportional coefficient depends on the amount of sample data and the preliminary setting of the corresponding processing coefficient for each group of sample data by technical personnel in this field; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0163] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device embodiment, since it is basically based on the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0164] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0165] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0166] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0167] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0168] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0169] Secondly: In the drawings of the embodiments disclosed in the present invention, only the structures related to the embodiments disclosed in the present invention are involved, and other structures can refer to the general design. In the absence of conflict, the same embodiment and different embodiments of the present invention can be combined with each other;

[0170] Finally: The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A real-time design interaction system, characterized in that: Includes multi-source data management module, data interaction platform and dynamic maintenance scheduling module; The multi-source data management module is used to classify and manage the original agricultural data sets in the target area, obtain the environmental comprehensive monitoring set, crop growth status set, equipment efficiency evaluation set and farmland space information set through data processing, and create a data table for each category of data set, use the database for data storage, and establish an index at the same time; the multi-source data management module includes a classification management unit, a fusion processing unit, a data table design unit, a data storage unit and an index establishment unit; The data interaction platform is used to integrate data from multi-source data management modules, integrate and process the data resources within the modules, and form a centralized data interaction platform to enable data exchange between different categories; The dynamic maintenance scheduling module is used to conduct quantitative analysis based on real-time data exchange results and dynamically adjust crop growth conditions; The data interaction platform integrates data from multi-source data management modules, integrates and processes data resources within the modules, and performs data exchange, including: Get the data sets of the multi-source data management module and define the basic structure for each data set, that is, assume that each data set Θ p (aj,vj) contains several attributes: Θ p (aj,vj)={(a1,v1),(a2,v2),...,(ao,vo)} In the formula, p represents the index subscript of en, cr, eq, ge; aj represents the attribute name; vj represents the corresponding attribute value; j represents the data set Θ p The attribute name and attribute value number in (aj,vj), where j = 1, 2, ..., o; o represents the data set Θ p The total number of attribute names and attribute values ​​in (aj,vj); Use the mapping function y pq Represents the dataset Θ p (aj,vj) to Θ q The mapping relationship of (aj',vj') is: y pq :Θ p (aj,vj)→Θ q (aj',vj'); where Θ q (aj',vj') represents the mapped data set; This is achieved by defining a set of transformation rules Z, where each rule z∈Z is used to determine the transformation from one data set to another data set or an intermediate format; A data exchange protocol is set, wherein the set data exchange protocol is a message-based protocol, and each message M includes a message type L, a data set identifier J, and data content N, that is, an exchange triplet M=(L, J, N).

2. A real-time design interaction system according to claim 1, characterized in that: The classification management unit is used to classify and manage the original agricultural data set of the target area, including: Identify and access all data sources to obtain raw data sets, including weather stations, soil monitoring stations, crop growth monitoring systems, equipment monitoring systems, and GIS systems; Define the weather station data as X m , the data of soil monitoring station is X s , the data of the crop growth monitoring system is X c , the data of the equipment monitoring system is X e And the data of GIS system is X g ; Classify the original data set according to the source of the data and the type of information it represents: D en =b en (X m ,X s ) D cr =b cr (X c ) D eq =b eq (X e ) D ge =b ge (X g ) Where D en , D cr , D eq , D ge Respectively represent environmental information, crop growth status, equipment operation status and geographic space information; b en 、b cr 、b eq 、b ge They represent the environmental information conversion function, the crop growth status conversion function, the equipment operation status conversion function and the geographic space information conversion function respectively.

3. A real-time design interaction system according to claim 1, characterized in that: The process of the fusion processing unit for obtaining the comprehensive environmental monitoring set, the crop growth status set, the equipment performance evaluation set and the farmland spatial information set through data processing includes: After integrating environmental information, crop growth status, equipment operation status and geographic space information, we can obtain the comprehensive environmental monitoring set, crop growth status set, equipment efficiency evaluation set and farmland space information set: Where D' en , D' cr , D' eq , D' ge They represent the integrated environmental monitoring set, crop growth status set, equipment efficiency evaluation set and farmland spatial information set after fusion processing respectively; F en 、F cr 、F eq 、F ge Respectively represent the fusion functions of environmental information, crop growth status, equipment operation status and geographic space information; d en ,d cr ,d eq ,d ge The data points represent environmental information, crop growth status, equipment operation status and geographic space information respectively; en Indicates D en Environmental impact weight factor; α cr , β eq , γ ge Respectively represent D cr Growth contribution coefficient, D eq The efficiency weight coefficient and D ge The spatial correlation coefficient.

4. A real-time design interaction system according to claim 1, characterized in that: The process used by the data table design unit to create a corresponding data table for each category of data set includes: For comprehensive environmental monitoring data table T en : Field Collection E en ={f1,f2,...,fn}, Wherein, fi represents the i-th field, and i=1,2,...,n; Record set R en , each record r en ∈R en Indicates a en Mapping to data values ​​in the environmental comprehensive monitoring set; For the crop growth status data table T cr : Field Collection E cr ={f1 (1) ,f2 (1) ,...,fn (1) }, Among them, (1) Indicates the i (1) fields, and i (1) =1,2,…,n (1) ; Record set R cr , each record r cr ∈R cr Indicates a cr Mapping to data values ​​in a crop growth status set; Data sheet T for equipment effectiveness evaluation eq : Field Collection E eq ={f1 (2) ,f2 (2) ,...,fn (2) }, Among them, (2) Indicates the i (2) fields, and i (2) =1,2,...,n (2) ; Record set R eq , each record r eq ∈R eq Indicates a eq Mapping to data values ​​in a crop growth status set; For farmland space information data table T ge : Field Collection E ge ={f1 (3) ,f2 (3) ,...,fn (3) }, Among them, (3) Indicates the i (3) fields, and i (3) =1,2,...,n (3) ; Record set R ge , each record r ge ∈R ge Indicates a ge A mapping to data values ​​in the crop growth status set.

5. A real-time design interaction system according to claim 1, characterized in that: The process used by the data storage unit to store data sets using a database includes: Each record in the fused data set is stored in the corresponding database according to the structure of its corresponding data table: For each data set D(D' en , D' cr , D' eq , D' ge ) and the corresponding data table T(T en , T cr , T eq , T ge ), the stored procedure is formalized as: In the formula, Store(D,T) represents the storage result of the data set and the corresponding data table; E(E en 、E cr 、E eq 、E ge ) is the data table T(T en 、T cr 、T eq 、T ge ) field set; r(ι) represents each record r(r en 、r cr 、r eq 、r ge ) in the field ι(fi,fi (1) 、fi (2) 、fi (3) ) value; r'(ι) represents the data table T(T en 、T cr 、T eq 、T ge ) in the newly created record r' in the field ι(fi, fi (1) 、fi (2) 、fi (3) ) on the .

6. A real-time design interaction system according to claim 1, characterized in that: The index building unit is used to build an index based on the created data table. The process includes: Based on the created data table T(T en , T cr , T eq , T ge ), create indexes for key fields of various data sets, using I(I en ,I cr ,I eq ,I ge ) represents an index set; each element τ∈I is a en 、E cr 、E eq 、E ge ) to index types; For each data table and its index set, the index creation process is formalized as follows: In the formula, CI(T,I) represents the output result of the created data table and the corresponding index set; τ.key represents the field on which the index is based; τ.type represents the type of index.

7. A real-time design interaction system according to claim 1, characterized in that: The dynamic maintenance scheduling module conducts quantitative analysis based on real-time data exchange results and dynamically adjusts the crop growth conditions. include: Let G k ={G1,G2,...,G h } represents the parameter set of crop growth conditions in the current target area; where G k is the current value of the kth parameter of the crop growth condition of the current target area; k represents the parameter number of the crop growth condition of the current target area, and k=1, 2, ..., h; h represents the total number of parameters of the crop growth condition of the current target area; Then G id = {G id,1 ,G id,2 ,…,G id,h } is the parameter set under ideal conditions; where G id,k is the ideal value of the kth parameter under ideal conditions; Comprehensive assessment of each crop growth condition parameter: In the formula, δ k Represents the comprehensive evaluation score; |G k -G id,k | indicates the deviation between the calculated current value and the ideal value; U k The weight of the kth parameter representing the crop growth condition reflects the importance of this parameter to crop growth; Determine whether crop growth conditions need to be adjusted based on the evaluation score and calculate the adjustment amount ΔG k : ΔG k =Y k ·d k Where Y k The adjustment coefficient of the kth parameter representing the crop growth condition depends on the adjustment capacity of the system and the urgency of the current deviation; After obtaining the adjustment amount of each parameter of crop growth conditions, the overall adjustment plan ΔG is formed k ={ΔG1, ΔG2,…, ΔG h }; Combined with the adjustment scheme, an adjustment function Q is created. The adjustment function Q receives the current crop growth conditions and the adjustment amount as input and outputs the adjusted crop growth conditions Gk +1 : G k+1 =Q(G k ,ΔG k ); Once adjustments are made, the system will respond according to the new crop growing conditions.

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