Agricultural information management system and method based on big data

Abstract

The invention discloses an agricultural information management system and method based on big data, relates to the technical field of intelligent management and control of water supply, and solves the problems that water supply is not accurate and the water consumption of plants in a region is neglected due to the fact that water supply is performed only according to the land water storage amount in agricultural water supply. And the technical problem that the water supply pressure is relieved by adaptively utilizing natural rainfall is neglected. According to the method, the water evaporation capacity of each time period is obtained according to the basic data, the plant available water amount of the regulation and control area is obtained according to the water evaporation capacity and the target data, and the pre-water-supply time is obtained through analysis based on the plant available water amount; analyzing the pre-water-supply time to obtain an operation instruction, and controlling water supply of the regulation and control area based on the operation instruction; according to the device, water can be supplied to plants when the plants are most needed or the absorption effect is the best, the absorption efficiency of the plants is improved, and waste of water resources is reduced.

Description

Technical Field

[0001] The present invention belongs to the field of smart agriculture and relates to intelligent water supply control technology, specifically an agricultural information management system and method based on big data. Background Art

[0002] In traditional agriculture, agricultural producers mainly rely on experience or weather forecasts to obtain information and carry out agricultural production based on the information obtained. This will result in inaccurate information or the information obtained is for a large area, making it difficult to provide accurate data support for the production work of small precision farms, which in turn leads to certain restrictions on the development of smart agriculture. With the continuous development of big data, its application in various fields is becoming more and more extensive. In the agricultural field, big data technology can help farmers better understand the water demand of plants, predict weather changes, optimize water supply plans, etc., thereby improving agricultural production efficiency and reducing production costs, while also improving the quality and safety of agricultural products.

[0003] At present, most agricultural information management systems based on big data only supply water according to the water storage capacity of the land, and ignore the analysis of the available water amount of plants in the region, resulting in inaccurate water supply, which may further affect crops by water shortage or water excess, interfere with crop growth and development, and even lead to reduced yields; at the same time, most agricultural information management systems based on big data ignore the adaptive use of natural rainfall to alleviate water supply pressure, and cannot automatically adjust the subsequent water supply time and water supply according to the rainfall conditions, resulting in a waste of water resources.

[0004] Therefore, the present invention discloses an agricultural information management system and method based on big data, which are used to solve the above technical problems. Summary of the invention

[0005] The present invention aims to solve at least one of the technical problems existing in the prior art; to this end, the present invention proposes an agricultural information management system and method based on big data, which is used to solve the technical problems that water is only supplied according to the water storage capacity of the land in agricultural water supply, and the analysis of the available water capacity of plants in the region is ignored, resulting in inaccurate water supply, and the adaptive use of natural rainfall to alleviate the water supply pressure is ignored. The present invention obtains the water evaporation in each time period according to basic data, obtains the available water capacity of plants in the control area according to the water evaporation and target data, and obtains the pre-water supply time based on the available water capacity of the plants; the pre-water supply time is analyzed to obtain operation instructions, and the water supply of the control area is controlled based on the operation instructions to solve the above problems.

[0006] To achieve the above-mentioned purpose, the first aspect of the present invention provides an agricultural information management system based on big data, comprising: an information analysis module, and a data collection module, a management control module and a database connected thereto;

[0007] The data collection module is used to obtain basic data, target data and weather conditions in the control area; wherein the basic data includes characteristic values ​​of temperature, light intensity and wind speed in each time period; the target data includes water supply time and water supply amount; the weather conditions include rainfall time and rainfall amount of effective rainfall, and each time period is obtained by manual setting; when the rainfall is greater than the rainfall threshold, it is effective rainfall, and the rainfall threshold is obtained by manual setting;

[0008] The information analysis module is used to obtain the water evaporation amount in each time period according to the basic data, obtain the available water amount of plants in the control area according to the water evaporation amount and the target data, and obtain the pre-water supply time based on the analysis of the available water amount of plants;

[0009] The management control module is used to analyze the pre-water supply time to obtain operation instructions, and control the water supply of the control area based on the operation instructions.

[0010] Preferably, the obtaining of basic data, target data and weather conditions of the control area includes:

[0011] A day is divided into several time periods according to manual planning, several temperatures in each time period are obtained through a temperature sensor, several light intensities in each time period are obtained through a light intensity sensor, several wind speeds in each time period are obtained through a wind speed sensor, and characteristic values ​​of several temperatures, several light intensities and several wind speeds are obtained;

[0012] The last water supply time and water supply amount of the control area are extracted from the database; the last and next effective rainfall time and rainfall amount of the control area are obtained from the computer.

[0013] Preferably, the obtaining of characteristic values ​​of a plurality of temperatures, a plurality of light intensities and a plurality of wind speeds includes:

[0014] Integrate several temperatures into group A1, several light intensities into group A2, and several wind speeds into group A3, and obtain the maximum value ZDi, minimum value ZXi, and mode ZSi of each group in turn;

[0015] The characteristic value TZi of the group is obtained based on the formula TZi=(B1i×ZDi+B2i×ZXi+ZSi) / 2; wherein i represents the serial number of each group; B1i and B2i are both proportional adjustment coefficients greater than 0, and B1i+B2i=1, B1i>B2i.

[0016] It is worth noting that the present invention performs comprehensive calculations of the maximum, minimum and mode of the temperature, light intensity and wind speed in the control area, and obtains a characteristic value that can express the standard conditions of each group of data, providing data support for subsequent analysis and calculation.

[0017] Preferably, obtaining the water evaporation amount in each time period according to the basic data includes:

[0018] The characteristic value TZ1 of temperature, the characteristic value TZ2 of light intensity, and the characteristic value TZ3 of wind speed are extracted for each time period; the water evaporation amount SZL of each time period is obtained based on the formula SZL=BSZL+(α1×exp((TZ1-BTZ1) / BTZ1-1)+α2×exp((TZ2-BTZ2) / BTZ2-1)+α3×exp((TZ3-BTZ3) / BTZ3-1))×BSZL; wherein α1, α2 and α3 are all proportional adjustment coefficients greater than 0, and α1+α2+α3=1, α2>α1>α3; BTZ1 is the standard characteristic value of the artificially set temperature, BTZ2 is the standard characteristic value of the artificially set light intensity, BTZ3 is the standard characteristic value of the artificially set wind speed; BSZL is the artificially set standard water evaporation amount.

[0019] It is worth noting that water evaporation is not only related to temperature and light intensity but also to the wind speed in the current area. The present invention obtains a numerical value that can express the water evaporation in the regulated area in each time period by analyzing the characteristic values ​​of temperature, light intensity and wind speed in each time period. This can more accurately understand and predict the water evaporation in the regulated area, provide data support for the subsequent calculation of the available water volume in the regulated area after removing water evaporation, and help to achieve optimal utilization of water resources and sustainable development.

[0020] Preferably, obtaining the amount of water available for plants in the regulated area according to the amount of water evaporation and the target data includes:

[0021] Extract the water supply time GST and water supply volume SL of the last water supply in the control area; extract the rainfall time and rainfall volume of the last effective rainfall in the control area, and determine whether the rainfall time is after the water supply time GST of the last water supply; if yes, use the rainfall time and rainfall volume to update the data of the water supply time GST and water supply volume SL; if no, do nothing;

[0022] Obtain the current time, calculate the time difference between the water supply time GST and the current time to obtain the time difference, and mark the time difference as the duration of no water supply;

[0023] The water evaporation amount SZL of the incomplete time period during the period without water supply is proportionally calculated to obtain the incomplete evaporation amount ZL, and the water evaporation amount SZLj of the complete time period during the period without water supply is extracted; the plant available water amount ZCL is obtained based on the formula ZCL=β×(δ×SL-(∑(SZLj)+ZL)); wherein j is the number of the complete time period, the value range is [0,n], and n is the number of complete time periods during the period without water supply; ∑ is the summation symbol, and the summation range is [0,n]; β is the plant water storage coefficient greater than 0, and δ is the proportional adjustment coefficient greater than 0.

[0024] It is worth noting that the present invention performs a step of judging the rainfall time of the last effective rainfall before using the water supply time GST and the water supply amount SL to calculate the available water volume ZCL for plants. When there is effective rainfall after the last water supply, the rainfall time and rainfall amount of the effective rainfall are used to update the water supply time GST and the water supply amount SL. This can ensure that the plants get the right amount of water when needed, thereby improving irrigation efficiency and avoiding the waste of water resources due to excessive water supply and adverse effects on plant growth.

[0025] Preferably, the method of proportionally calculating the water evaporation amount SZL in the incomplete time period within the water supply non-time period to obtain the incomplete evaporation amount ZL includes:

[0026] Extract the water evaporation amount SZL of each incomplete time period during the water non-supply period, obtain the duration SC of the incomplete time period during the water non-supply period in turn, obtain the water evaporation amount of the current incomplete time period during the water non-supply period based on the formula = SZL × SC / WSC, add the water evaporation amount of each incomplete time period during the water non-supply period to obtain the incomplete evaporation amount ZL; wherein WSC is the duration of the complete time period.

[0027] It is worth noting that the present invention performs a refined calculation of the water evaporation SZL in the incomplete time period to obtain the proportional value of the corresponding time period within the non-water supply period, which can reduce the error of the calculated plant available water ZCL and improve the accuracy of the system calculation results.

[0028] Preferably, the pre-watering time is obtained by analyzing the available water amount of the plant, comprising:

[0029] Extract the historical plant available water from the database, the characteristic values ​​of temperature, light intensity and wind speed in the next r time periods corresponding to the historical plant available water, and the pre-watering time corresponding to the historical plant available water;

[0030] Integrate the historical available water volume for plants, characteristic values ​​of temperature, light intensity and wind speed in r time periods, and pre-watering time into several groups of training data and test data; use the training data to train the artificial intelligence model; use the test data to test the trained artificial intelligence model, and adjust the artificial intelligence model according to the test results; finally obtain a time evaluation model with inputs of the available water volume for plants ZCL, characteristic values ​​of temperature, light intensity and wind speed in the next r time periods, and output of the pre-watering time; wherein the artificial intelligence model includes a BP neural network model or an RBF neural network model, and r is obtained by manual setting;

[0031] The temperature, light intensity and wind speed for the next r time periods are obtained by computer, and the temperature, light intensity and wind speed are input into the time evaluation model as characteristic values. At the same time, the available water volume ZCL of the plant analyzed this time is input into the time evaluation model to obtain the pre-watering time.

[0032] Specifically, the characteristic values ​​of the available water for plants and the temperature, light intensity and wind speed for r time periods in the test data are input into the trained artificial intelligence model to obtain the corresponding pre-water supply time, and the pre-water supply time is compared with the corresponding pre-water supply time in the test data. When the difference between the two is within a threshold value, which is obtained based on experience, no parameter adjustment is required, and the next set of test data is tested; if not within the threshold value, the corresponding parameters are adjusted until the difference between the two is within the threshold value, and then the next set of test data is tested. When the number of test data with pre-water supply times within the threshold value obtained from all test data accounts for 90% or more of the total amount of test data, the input is the characteristic values ​​of the available water for plants ZCL, the temperature, light intensity and wind speed for the next r time periods, and the output is a time evaluation model for the pre-water supply time.

[0033] Preferably, the analyzing the pre-water supply time to obtain the operation instruction includes:

[0034] C1: Extract the pre-water supply time, and determine whether the time difference between the pre-water supply time and the last water supply time GST is greater than the protection time; if yes, jump to C2; if no, do not issue an operation instruction; wherein the protection time is obtained through experience;

[0035] C2: Determine whether there is effective rainfall between the pre-water supply time and the current time; if yes, do not issue an operation instruction; if no, jump to C3;

[0036] C3: Determine whether there is a water supply target time point between the pre-water supply time and the current time; if yes, jump to C4; if no, issue operation instruction 1; wherein the water supply target time point is a time point within the manually set recommended water supply time range;

[0037] C4: Mark the minimum time among the water supply target time points as the target time, mark the time difference between the current time and the pre-water supply time as duration one SH1, and mark the time difference between the current time and the target time as duration two SH2; obtain the control ratio TB based on the formula TB=SH1 / SH2, and issue operation instruction two; wherein the operation instructions include operation instruction one and operation instruction two.

[0038] It is worth noting that because the pre-water supply time is obtained by analyzing the evaporation situation, the result time obtained will not be fixed to a certain time point. It may be at noon when the water evaporates faster. If water is supplied to the control area at this time, it will lead to reduced utilization of water resources and bring economic losses; at the same time, the time range when plants absorb water best in a day is fixed. Therefore, the present invention does not fix the pre-water supply time as the final water supply time, but analyzes the water supply time. When there is no water supply target time point between the pre-water supply time and the current time, a fixed amount of water is supplied according to the pre-water supply time; when there is a water supply target time point between the pre-water supply time and the current time, water is supplied according to the water supply target time point, and the water supply is reduced to obtain a dynamic water supply; this can ensure that plants are supplied with water when they are most needed or when the absorption effect is best, which improves the absorption efficiency of plants and reduces the waste of water resources.

[0039] Preferably, the controlling of the water supply to the control area based on the operation instruction includes:

[0040] Extract the operation instruction and determine whether the operation instruction is operation instruction one; if yes, supply water to the control area according to the fixed water supply volume GSL when the pre-water supply time is reached; if no, extract the control ratio TB corresponding to the operation instruction two, obtain the dynamic water supply volume DSL based on the formula DSL=TB×GSL, and supply water to the control area according to the dynamic water supply volume DSL when the target time is reached; wherein, the fixed water supply volume GSL is obtained by manual setting.

[0041] A second aspect of the present invention provides an agricultural information management method based on big data, comprising the following steps:

[0042] S1: Obtain basic data, target data and weather conditions of the control area;

[0043] S2: The amount of water evaporation in each time period is obtained based on the basic data, the amount of water available for plants in the control area is obtained based on the amount of water evaporation and the target data, and the pre-water supply time is obtained based on the analysis of the amount of water available for plants;

[0044] S3: Analyze the pre-water supply time to obtain an operation instruction, and control the water supply of the control area based on the operation instruction.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] 1. The present invention obtains the amount of water evaporation in each time period according to basic data, obtains the amount of water available for plants in the control area according to the amount of water evaporation and target data, and obtains the pre-water supply time based on the amount of water available for plants; the pre-water supply time is analyzed to obtain an operation instruction, and the water supply of the control area is controlled based on the operation instruction, thereby solving the technical problems of only supplying water according to the amount of water stored in the land in agricultural water supply, ignoring the analysis of the amount of water available for plants in the region, resulting in inaccurate water supply, and ignoring the adaptive use of natural rainfall to alleviate water supply pressure; the present invention can determine the required amount of water more accurately, avoid waste, and ensure that plants get enough water, thereby improving the efficiency of agricultural production.

[0047] 2. Because the pre-water supply time is obtained by analyzing the evaporation situation, the result time obtained will not be fixed to a certain time point. It may be at noon when the water evaporates faster. If water is supplied to the control area at this time, it will lead to reduced utilization of water resources and bring economic losses; at the same time, the time range in a day when plants absorb water best is fixed. Therefore, the present invention does not fix the pre-water supply time as the final water supply time, but analyzes the water supply time. When there is no water supply target time point between the pre-water supply time and the current time, a fixed amount of water is supplied according to the pre-water supply time; when there is a water supply target time point between the pre-water supply time and the current time, water is supplied according to the water supply target time point, and the water supply is reduced to obtain a dynamic water supply; this can ensure that plants are supplied with water when they are most needed or when the absorption effect is best, thereby improving the absorption efficiency of plants and reducing the waste of water resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0049] Figure 1 It is a schematic diagram of the operation steps of the present invention;

[0050] Figure 2 It is a schematic diagram of the system module of the present invention;

[0051] Figure 3 A schematic diagram of the operation steps for obtaining the amount of water available to plants according to the present invention;

[0052] Figure 4 The figure is a schematic diagram of the operation steps for obtaining the operation instruction of the present invention. DETAILED DESCRIPTION

[0053] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than 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.

[0054] See also Figure 1-Figure 2 , the first aspect of the present invention provides an agricultural information management system based on big data, including: an information analysis module, and a data collection module, a management control module and a database connected thereto;

[0055] Data collection module: used to obtain basic data, target data and weather conditions in the control area; among them, basic data include characteristic values ​​of temperature, light intensity and wind speed in each time period; target data include water supply time and water supply amount; weather conditions include rainfall time and rainfall amount of effective rainfall, and each time period is obtained by manual setting; when the rainfall is greater than the rainfall threshold, it is effective rainfall, and the rainfall threshold is obtained by manual setting;

[0056] Information analysis module: used to obtain the water evaporation in each time period based on the basic data, obtain the available water for plants in the control area based on the water evaporation and target data, and obtain the pre-water supply time based on the analysis of the available water for plants;

[0057] Management and control module: used to analyze the pre-water supply time to obtain operation instructions, and control the water supply in the control area based on the operation instructions.

[0058] This application obtains basic data, target data and weather conditions of the regulated area, including:

[0059] A day is divided into several time periods according to manual planning, several temperatures in each time period are obtained through a temperature sensor, several light intensities in each time period are obtained through a light intensity sensor, several wind speeds in each time period are obtained through a wind speed sensor, and characteristic values ​​of several temperatures, several light intensities and several wind speeds are obtained;

[0060] The last water supply time and water supply amount of the control area are extracted from the database; the last and next effective rainfall time and rainfall amount of the control area are obtained from the computer.

[0061] It should be noted that the several temperatures, several light intensities and several wind speeds are data acquired by the corresponding several sensors at different positions and at different times within the control area.

[0062] It should be noted that the time and amount of the next effective rainfall are estimated values ​​obtained through weather forecast.

[0063] In this application, characteristic values ​​of several temperatures, several light intensities and several wind speeds are obtained, including:

[0064] Integrate several temperatures into group A1, several light intensities into group A2, and several wind speeds into group A3, and obtain the maximum value ZDi, minimum value ZXi, and mode ZSi of each group in turn;

[0065] The characteristic value TZi of the group is obtained based on the formula TZi=(B1i×ZDi+B2i×ZXi+ZSi) / 2; wherein i represents the serial number of each group; B1i and B2i are both proportional adjustment coefficients greater than 0, and B1i+B2i=1, B1i>B2i.

[0066] It should be noted that when i is 1, it represents the data of group A1, when i is 2, it represents the data of group A2, and when i is 3, it represents the data of group A3.

[0067] It should be noted that the proportional adjustment coefficients corresponding to each group are set by the staff based on experience, and the set values ​​are not necessarily the same; for example: B11=0.8, B21=0.2 of group A1; B12=0.6, B22=0.4 of group A2; B13=0.62, B23=0.38 of group A3.

[0068] It should be noted that, if more than one mode is found in a group of data when obtaining the mode, the average of these modes is calculated to obtain a mode average, and this mode average is used as the mode of the group of data for subsequent calculations.

[0069] In this application, the water evaporation in each time period is obtained based on basic data, including:

[0070] The characteristic value TZ1 of temperature, the characteristic value TZ2 of light intensity, and the characteristic value TZ3 of wind speed are extracted for each time period; the water evaporation amount SZL of each time period is obtained based on the formula SZL=BSZL+(α1×exp((TZ1-BTZ1) / BTZ1-1)+α2×exp((TZ2-BTZ2) / BTZ2-1)+α3×exp((TZ3-BTZ3) / BTZ3-1))×BSZL; wherein α1, α2 and α3 are all proportional adjustment coefficients greater than 0, and α1+α2+α3=1, α2>α1>α3; BTZ1 is the standard characteristic value of the artificially set temperature, BTZ2 is the standard characteristic value of the artificially set light intensity, BTZ3 is the standard characteristic value of the artificially set wind speed; BSZL is the artificially set standard water evaporation amount.

[0071] See also Figure 3 In this application, the available water for plants in the control area is obtained based on the water evaporation and target data, including:

[0072] Extract the last water supply time GST and water supply volume SL of the control area; extract the rainfall time and rainfall volume of the last effective rainfall in the control area, and determine whether the rainfall time is after the last water supply time GST; if yes, use the rainfall time and rainfall volume to update the data of the water supply time GST and water supply volume SL; if no, do nothing;

[0073] Get the current time, calculate the time difference between the water supply time GST and the current time to get the time difference, and mark the time difference as the duration of no water supply;

[0074] The water evaporation amount SZL of the incomplete time period during the period without water supply is proportionally calculated to obtain the incomplete evaporation amount ZL, and the water evaporation amount SZLj of the complete time period during the period without water supply is extracted; the plant available water amount ZCL is obtained based on the formula ZCL=β×(δ×SL-(∑(SZLj)+ZL)); wherein j is the number of the complete time period, the value range is [0,n], and n is the number of complete time periods during the period without water supply; ∑ is the summation symbol, and the summation range is [0,n]; β is the plant water storage coefficient greater than 0, and δ is the proportional adjustment coefficient greater than 0.

[0075] It should be noted that the plant water storage coefficient β set in the present invention is a proportional value indicating that the plant can absorb the surrounding water into its body.

[0076] It should be noted that the amount of water available to plants includes the amount of water in the plants, in the soil and in the air.

[0077] It should be noted that the value of the proportional adjustment coefficient δ changes with the change of the water supply SL. For example, when the value of the water supply SL is greater than or equal to the fixed water supply GSL, the proportional adjustment coefficient δ takes a value of 1; when the value of the water supply SL is less than the fixed water supply GSL, the control ratio TB of the last water supply is extracted, and the proportional adjustment coefficient δ is obtained based on the formula δ=D / TB; wherein the value of D is obtained through manual setting.

[0078] It should be noted that the possible situations where the value of the water supply SL is greater than the fixed water supply GSL include: data of the water supply SL is updated using rainfall.

[0079] It should be noted that the specific steps for updating the data of water supply time GST and water supply volume SL using rainfall time and rainfall volume are as follows:

[0080] If the rainfall time is September 20, 2024, the rainfall is 10mm / day; the water supply time GST is September 18, 2024, and the water supply SL is 5mm / day;

[0081] The current time is September 21, 2024, so the water supply time GST is updated to September 20, 2024, and the water supply volume SL is updated to 10mm / day.

[0082] It should be noted that when a certain time period is entirely within the period of no water supply, the time period will be marked as a complete time period.

[0083] It should be noted that an incomplete time period refers to a time period that is not entirely within the duration of no water supply. For example, if the water supply time GST is 14:00 on September 20, 2024, and the current time is 14:00 on September 21, 2024, then the duration of no water supply is from 14:00 on September 20, 2024 to 14:00 on September 21, 2024. If a time period is 13:00-15:00 every day, then this time period is an incomplete time period.

[0084] In this application, the water evaporation amount SZL of the incomplete time period during the water supply period is proportionally calculated to obtain the incomplete evaporation amount ZL, including:

[0085] Extract the water evaporation amount SZL of each incomplete time period during the water non-supply period, obtain the duration SC of the incomplete time period during the water non-supply period in turn, obtain the water evaporation amount of the current incomplete time period during the water non-supply period based on the formula = SZL × SC / WSC, add the water evaporation amount of each incomplete time period during the water non-supply period to obtain the incomplete evaporation amount ZL; wherein WSC is the duration of the complete time period.

[0086] In this application, the pre-watering time is obtained based on the analysis of the available water for plants, including:

[0087] Extract the historical plant available water from the database, the characteristic values ​​of temperature, light intensity and wind speed in the next r time periods corresponding to the historical plant available water, and the pre-watering time corresponding to the historical plant available water;

[0088] Integrate the historical available water volume for plants, characteristic values ​​of temperature, light intensity and wind speed in r time periods, and pre-watering time into several groups of training data and test data; use the training data to train the artificial intelligence model; use the test data to test the trained artificial intelligence model, and adjust the artificial intelligence model according to the test results; finally obtain a time evaluation model with inputs of the available water volume for plants ZCL, characteristic values ​​of temperature, light intensity and wind speed in the next r time periods, and output of the pre-watering time; wherein the artificial intelligence model includes a BP neural network model or an RBF neural network model, and r is obtained by manual setting;

[0089] The temperature, light intensity and wind speed in the next r time periods are obtained by computer, and the temperature, light intensity and wind speed are input into the time assessment model as characteristic values. At the same time, the available water volume ZCL of the plant analyzed this time is input into the time assessment model to obtain the pre-watering time.

[0090] Specifically, the characteristic values ​​of the available water for plants and the temperature, light intensity and wind speed for r time periods in the test data are input into the trained artificial intelligence model to obtain the corresponding pre-water supply time, and the pre-water supply time is compared with the corresponding pre-water supply time in the test data. When the difference between the two is within the threshold, which is obtained based on experience, there is no need to adjust the parameters and the next set of test data is tested; if not within the threshold, the corresponding parameters are adjusted until the difference between the two is within the threshold, and then the next set of test data is tested. When the number of test data with pre-water supply times within the threshold obtained from all test data accounts for 90% or more of the total amount of test data, the input is the characteristic values ​​of the available water for plants ZCL, the temperature, light intensity and wind speed for the next r time periods, and the output is a time evaluation model for the pre-water supply time.

[0091] It should be noted that the pre-watering time used in the training model and the test model is calculated by the historical plant available water and the characteristic values ​​of temperature, light intensity and wind speed in the next r time periods. The specific calculation steps are:

[0092] Extract the temperature characteristic value TZ1, the light intensity characteristic value TZ2 and the wind speed characteristic value TZ3 of the next r time periods corresponding to the time of historical plant available water, and obtain the water evaporation SZL of the next h-th time period in chronological order based on the formula SZL=BSZL+(α1×exp((TZ1-BTZ1) / BTZ1-1)+α2×exp((TZ2-BTZ2) / BTZ2-1)+α3×exp((TZ3-BTZ3) / BTZ3-1))×BSZL; where the value range of h is [0, r]; α1, α2 and α3 are all proportional adjustment coefficients greater than 0, and α1+α2+α3=1, α2>α1>α3; BTZ1 is the standard characteristic value of the artificially set temperature, BTZ2 is the standard characteristic value of the artificially set light intensity, and BTZ3 is the standard characteristic value of the artificially set wind speed; BSZL is the artificially set standard water evaporation;

[0093] The plant available water volume ZCL for the next h-th time period is obtained based on the formula ZCL = β × (δ × SLh - SZL); where SLh is the historical plant available water volume corresponding to the beginning of the h-th time period, β is the plant water storage coefficient greater than 0, and δ is the proportional adjustment coefficient greater than 0;

[0094] Determine whether the plant available water volume ZCL in the hth time period is greater than the available water volume threshold; if yes, calculate and determine the plant available water volume ZCL in the next time period; if no, mark the start time of the hth time period as the pre-water supply time; wherein the available water volume threshold is obtained through experience.

[0095] See also Figure 4 In this application, the pre-water supply time is analyzed to obtain operation instructions, including:

[0096] C1: Extract the pre-water supply time and determine whether the time difference between the pre-water supply time and the last water supply time GST is greater than the protection time; if yes, jump to C2; if no, do not issue an operation instruction; the protection time is obtained through experience;

[0097] C2: Determine whether there is effective rainfall between the pre-water supply time and the current time; if yes, do not issue an operation instruction; if no, jump to C3;

[0098] C3: Determine whether there is a water supply target time point between the estimated water supply time and the current time; if yes, jump to C4; if no, issue operation instruction 1; wherein the water supply target time point is a time point within the manually set recommended water supply time range;

[0099] C4: Mark the minimum time among the water supply target time points as the target time, mark the time difference between the current time and the pre-water supply time as duration one SH1, and mark the time difference between the current time and the target time as duration two SH2; obtain the control ratio TB based on the formula TB=SH1 / SH2, and issue operation instruction two; wherein the operation instructions include operation instruction one and operation instruction two.

[0100] It should be noted that step C1 is used to determine whether the pre-water supply time is too close to the previous water supply time, so as to avoid water resource waste and economic losses caused by plant root rot caused by multiple water supplies in a short period of time.

[0101] It should be noted that step C2 is to make full use of natural rainfall and avoid supplying water when there is effective rainfall in a short period of time, thereby reducing the waste of water resources.

[0102] It should be noted that the most effective water supply time in different seasons for agricultural water supply is also different. Therefore, the present invention manually sets the recommended water supply time range for each day or week in the current season, and marks the time point within the recommended water supply time range as the water supply target time point.

[0103] In this application, the water supply to the control area is controlled based on the operation instructions, including:

[0104] Extract the operation instruction and determine whether the operation instruction is operation instruction one; if yes, supply water to the control area according to the fixed water supply GSL when the pre-water supply time is reached; if no, extract the control ratio TB corresponding to operation instruction two, obtain the dynamic water supply DSL based on the formula DSL=TB×GSL, and supply water to the control area according to the dynamic water supply DSL when the target time is reached; wherein, the fixed water supply GSL is obtained by manual setting.

[0105] A second aspect of the present invention provides an agricultural information management method based on big data, comprising the following steps:

[0106] S1: Obtain basic data, target data and weather conditions of the control area;

[0107] S2: The amount of water evaporation in each time period is obtained based on the basic data, the amount of water available for plants in the control area is obtained based on the amount of water evaporation and the target data, and the pre-water supply time is obtained based on the analysis of the amount of water available for plants;

[0108] S3: Analyze the pre-water supply time to obtain an operation instruction, and control the water supply of the control area based on the operation instruction.

[0109] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0110] Working principle of the present invention:

[0111] The present invention first obtains basic data, target data and weather conditions in the control area, providing data support for subsequent analysis and calculation; then, the water evaporation in each time period is obtained according to the basic data, the available water for plants in the control area is obtained according to the water evaporation and the target data, and the pre-water supply time is obtained based on the analysis of the available water for plants; this step can ensure that the plants get the right amount of water when needed, thereby improving irrigation efficiency and avoiding the waste of water resources caused by excessive water supply and adverse effects on plant growth; finally, the pre-water supply time is analyzed to obtain operation instructions, and the water supply of the control area is controlled based on the operation instructions.

[0112] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An agricultural information management system based on big data, characterized in that: include: Information analysis module, and the data collection module, management control module and database connected thereto; The data collection module is used to obtain basic data, target data and weather conditions of the control area; wherein the basic data includes characteristic values ​​of temperature, light intensity and wind speed in each time period; The target data includes water supply time and water supply amount; the weather conditions include effective rainfall time and rainfall amount, and effective rainfall is when the rainfall amount is greater than the rainfall threshold; The information analysis module is used to obtain the water evaporation amount in each time period according to the basic data, obtain the available water amount of plants in the control area according to the water evaporation amount and the target data, and obtain the pre-water supply time based on the analysis of the available water amount of plants; The management control module is used to analyze the pre-water supply time to obtain operation instructions, and control the water supply of the control area based on the operation instructions.

2. The agricultural information management system based on big data according to claim 1, characterized in that: The basic data, target data and weather conditions of the control area are obtained, including: A day is divided into several time periods according to manual planning, several temperatures in each time period are obtained through a temperature sensor, several light intensities in each time period are obtained through a light intensity sensor, several wind speeds in each time period are obtained through a wind speed sensor, and characteristic values ​​of several temperatures, several light intensities and several wind speeds are obtained; The last water supply time and water supply amount of the control area are extracted from the database; the last and next effective rainfall time and rainfall amount of the control area are obtained from the computer.

3. The agricultural information management system based on big data according to claim 2 is characterized in that: The obtaining of characteristic values ​​of a plurality of temperatures, a plurality of light intensities and a plurality of wind speeds comprises: Integrate several temperatures into group A1, several light intensities into group A2, and several wind speeds into group A3, and obtain the maximum value ZDi, minimum value ZXi, and mode ZSi of each group in turn; The characteristic value TZi of the group is obtained based on the formula TZi=(B1i×ZDi+B2i×ZXi+ZSi) / 2; wherein i represents the serial number of each group; B1i and B2i are both proportional adjustment coefficients greater than 0, and B1i+B2i=1, B1i>B2i.

4. The agricultural information management system based on big data according to claim 1, characterized in that: The water evaporation amount in each time period is obtained according to the basic data, including: The characteristic value TZ1 of temperature, the characteristic value TZ2 of light intensity, and the characteristic value TZ3 of wind speed are extracted for each time period; the water evaporation amount SZL for each time period is obtained based on the formula SZL=BSZL+(α1×exp((TZ1-BTZ1) / BTZ1-1)+α2×exp((TZ2-BTZ2) / BTZ2-1)+α3×exp((TZ3-BTZ3) / BTZ3-1))×BSZL; wherein α1, α2 and α3 are all proportional adjustment coefficients greater than 0, and α1+α2+α3=1, α2>α1>α3; BTZ1 is the standard characteristic value of temperature, BTZ2 is the standard characteristic value of light intensity, BTZ3 is the standard characteristic value of wind speed; BSZL is the standard water evaporation amount.

5. The agricultural information management system based on big data according to claim 4 is characterized in that: The method of obtaining the available water for plants in the control area according to the water evaporation amount and the target data includes: Extract the water supply time GST and water supply volume SL of the last water supply in the control area; extract the rainfall time and rainfall volume of the last effective rainfall in the control area, and determine whether the rainfall time is after the water supply time GST of the last water supply; if yes, use the rainfall time and rainfall volume to update the data of the water supply time GST and water supply volume SL; if no, do nothing; Obtain the current time, calculate the time difference between the water supply time GST and the current time to obtain the time difference, and mark the time difference as the duration of no water supply; The water evaporation amount SZL of the incomplete time period during the period without water supply is proportionally calculated to obtain the incomplete evaporation amount ZL, and the water evaporation amount SZLj of the complete time period during the period without water supply is extracted; the plant available water amount ZCL is obtained based on the formula ZCL=β×(δ×SL-(∑(SZLj)+ZL)); wherein j is the number of the complete time period, the value range is [0,n], and n is the number of complete time periods during the period without water supply; ∑ is the summation symbol, and the summation range is [0,n]; β is the plant water storage coefficient greater than 0, and δ is the proportional adjustment coefficient greater than 0.

6. The agricultural information management system based on big data according to claim 5, characterized in that: The method of proportionally calculating the water evaporation amount SZL in the incomplete time period during the water supply failure period to obtain the incomplete evaporation amount ZL includes: Extract the water evaporation amount SZL of each incomplete time period during the water non-supply period, obtain the duration SC of the incomplete time period during the water non-supply period in turn, obtain the water evaporation amount of the current incomplete time period during the water non-supply period based on the formula = SZL × SC / WSC, add the water evaporation amount of each incomplete time period during the water non-supply period to obtain the incomplete evaporation amount ZL; wherein WSC is the duration of the complete time period.

7. The agricultural information management system based on big data according to claim 1, characterized in that: The pre-watering time is obtained by analyzing the available water amount of the plant, including: Extract the historical plant available water from the database, the characteristic values ​​of temperature, light intensity and wind speed in the next r time periods corresponding to the historical plant available water, and the pre-watering time corresponding to the historical plant available water; Integrate the historical available water volume for plants, characteristic values ​​of temperature, light intensity and wind speed in r time periods, and pre-watering time into several groups of training data and test data; use the training data to train the artificial intelligence model; use the test data to test the trained artificial intelligence model, and adjust the artificial intelligence model according to the test results; finally obtain a time evaluation model with inputs of the available water volume for plants ZCL, characteristic values ​​of temperature, light intensity and wind speed in the next r time periods, and output of the pre-watering time; wherein the artificial intelligence model includes a BP neural network model or an RBF neural network model; The temperature, light intensity and wind speed for the next r time periods are obtained by computer, and the temperature, light intensity and wind speed are input into the time evaluation model as characteristic values. At the same time, the available water volume ZCL of the plant analyzed this time is input into the time evaluation model to obtain the pre-watering time.

8. The agricultural information management system based on big data according to claim 1, characterized in that: The step of analyzing the pre-water supply time to obtain the operation instruction includes: C1: Extract the pre-water supply time, and determine whether the time difference between the pre-water supply time and the last water supply time GST is greater than the protection time; if yes, jump to C2; if no, do not issue an operation instruction; C2: Determine whether there is effective rainfall between the pre-water supply time and the current time; if yes, do not issue an operation instruction; if no, jump to C3; C3: Determine whether there is a water supply target time point between the pre-water supply time and the current time; if yes, jump to C4; if no, issue operation instruction 1; C4: Mark the minimum time among the water supply target time points as the target time, mark the time difference between the current time and the pre-water supply time as duration one SH1, and mark the time difference between the current time and the target time as duration two SH2; obtain the control ratio TB based on the formula TB=SH1 / SH2, and issue operation instruction two; wherein the operation instructions include operation instruction one and operation instruction two.

9. The agricultural information management system based on big data according to claim 8, characterized in that: The controlling of the water supply to the control area based on the operation instruction includes: Extract the operation instruction and determine whether the operation instruction is operation instruction one; if yes, supply water to the control area according to the fixed water supply volume GSL when the pre-water supply time is reached; if no, extract the control ratio TB corresponding to operation instruction two, obtain the dynamic water supply volume DSL based on the formula DSL=TB×GSL, and supply water to the control area according to the dynamic water supply volume DSL when the target time is reached.

10. A method for managing agricultural information based on big data, operating based on an agricultural information management system based on big data according to any one of claims 1 to 9, characterized in that: S1: Obtain basic data, target data and weather conditions of the control area; S2: The amount of water evaporation in each time period is obtained based on the basic data, the amount of water available for plants in the control area is obtained based on the amount of water evaporation and the target data, and the pre-water supply time is obtained based on the analysis of the amount of water available for plants; S3: Analyze the pre-water supply time to obtain an operation instruction, and control the water supply of the control area based on the operation instruction.

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