A remote control system, method and storage medium for a flower field water and fertilizer integrated machine

Abstract

The present invention discloses a remote control system, method and storage medium for a flower field water and fertilizer integrated machine, which relates to the field of remote control; it includes a data acquisition module, a planting management database, an irrigation analysis module, a fertilizer analysis module and an operation display module; the management mode of the system mainly relies on manual experience and manual operation, and there are problems such as low efficiency, insufficient precision and waste of resources. With the rapid development of the Internet of Things, big data and artificial intelligence technologies, agricultural production is gradually shifting towards intelligence and refinement. Therefore, there is an urgent need for a remote control system for a flower field water and fertilizer integrated machine; this system generates signals through analysis by an irrigation analysis module and a fertilizer analysis module, and then controls and displays through an operation display module, thereby realizing the intelligence and refinement of flower field water and fertilizer management, greatly reducing manpower input, and improving the efficiency and benefits of agricultural production.

Description

Technical Field

[0001] The present invention relates to the field of remote control technology, and in particular to a remote control system, method and storage medium for a flower field water and fertilizer integrated machine. Background Art

[0002] In modern agriculture, water and fertilizer management in flower fields is a key link that affects crop growth and yield. Traditional management methods mainly rely on human experience and manual operations, which have problems such as low efficiency, lack of precision and waste of resources. With the rapid development of the Internet of Things, big data and artificial intelligence technologies, agricultural production is gradually shifting towards intelligence and refinement. Therefore, there is an urgent need for a water-fertilizer integrated system that can achieve remote control and intelligent management. By real-time monitoring and analysis of soil, environment and crop growth data, it can automatically allocate and apply water and fertilizer, improve resource utilization efficiency, increase crop yield and quality, reduce labor costs, and promote the process of agricultural modernization. Summary of the invention

[0003] The present invention provides a remote control system, method and storage medium for a flower field water and fertilizer integrated machine, which are used to solve the above-mentioned technical problems existing in the prior art.

[0004] A first aspect of the present invention provides a remote control system for a flower field water and fertilizer integrated machine, comprising an irrigation analysis module and a fertilizer analysis module;

[0005] The irrigation analysis module is used to obtain and analyze the flower field data in the planting management database, specifically:

[0006] Step 1: Analyze crop growth data: obtain high-resolution images, use convolutional neural networks to identify crop types in high-resolution images, divide large-area crop images into regions according to crop types, and number regions corresponding to different crop types, and obtain normal growth stage data and normal growth index data of crop types in corresponding regions through the planting management database; similarly, use convolutional neural networks to perform feature comparison on normal growth stage data and normal growth index data with real-time growth stage data and real-time growth index data to determine whether real-time growth stage data and real-time growth index data have growth stage anomalies and growth index anomalies; if there are growth stage anomalies, generate growth stage anomaly signals; if there are growth index anomalies, generate growth index anomaly signals; analyze health status to generate poor health status signals;

[0007] Step 2: Analyze the soil data to obtain the soil comprehensive value of the corresponding area; then compare the soil comprehensive value with the corresponding preset soil comprehensive range in the planting management database. If the soil comprehensive value falls within the preset soil comprehensive range, there is no abnormality, and step 3 is executed; otherwise, when the soil comprehensive value does not fall within the preset soil comprehensive range, the data in the soil data n are detected for abnormalities one by one;

[0008] Step 3: Analyze the environmental data and meteorological data to obtain the total value of the ambient air;

[0009] The fertilizer analysis module obtains the data of the integrated water and fertilizer machine from the planting management database for analysis. The specific process is: numbering the water and fertilizer data and the water content data, then mixing and deploying the water and fertilizer data, and numbering and storing the deployed mixed water and fertilizer.

[0010] Optionally, the device further includes a data acquisition module, a planting management database and an operation display module;

[0011] The data acquisition module obtains the flower field data and the integrated water and fertilizer machine data by installing corresponding sensors on the integrated water and fertilizer machine; the flower field data includes soil data, environmental data, crop growth data and meteorological data; the integrated water and fertilizer machine data includes water and fertilizer data and mixed data; and the obtained flower field data and integrated water and fertilizer machine data are saved in the planting management database;

[0012] The planting management database is used to store data acquired by the data acquisition module and preset data;

[0013] The operation display module is used to receive all signals generated by the irrigation analysis module and perform corresponding operations on the received signals.

[0014] Optionally, the specific process of analyzing the health status by collecting high-resolution images using drones and satellite images is as follows:

[0015] The normal healthy color data of the crop types in the corresponding area are obtained through the planting management database, the color of the corresponding crop type in the high-resolution image is converted into RGB value, marked as RGB1, and then the color of the corresponding crop type in the normal healthy color data is converted into RGB value, marked as RGB2; RGB1 is divided by RGB2 to obtain the health status coefficient; the health status coefficient is matched with the preset health status interval, if the health status coefficient does not belong to the preset health status interval, a poor health status signal is generated; when an abnormal growth stage signal or an abnormal growth index signal or a poor health status signal is generated, step two is executed.

[0016] Optionally, the specific process of analyzing the soil data is:

[0017] By obtaining soil data n in the corresponding area ZQYn that generates abnormal growth stage signals, abnormal growth index signals, or poor health status signals; substituting the soil data n into the standardization formula: corresponding standardized value = corresponding collected value - corresponding average value / corresponding standard deviation to obtain corresponding standardized data, which are Stn, Wtn, pHn and Dtn respectively; Stn is the standardized soil moisture, Wtn is the standardized soil temperature, pHn is the standardized soil pH value and Dtn is the standardized soil conductivity; then output the soil comprehensive value of the corresponding area through the formula, and then compare the soil comprehensive value with the corresponding preset soil comprehensive range in the planting management database. If the soil comprehensive value belongs to the preset soil comprehensive range, there is no abnormality, and step three is executed; otherwise, when the soil comprehensive value does not belong to the preset soil comprehensive range, the data in the soil data n are detected for abnormalities one by one.

[0018] Optionally, the data in the soil data n are detected for anomalies one by one, specifically:

[0019] Abnormal detection of soil moisture: soil moisture St is obtained and matched with the preset normal soil moisture interval of the corresponding crop type. If the soil moisture St does not belong to the preset normal soil moisture interval of the corresponding crop type, and the soil moisture St is less than the minimum value in the preset normal soil moisture interval, a low soil moisture signal is generated; if the soil moisture St does not belong to the preset normal soil moisture interval of the corresponding crop type, and the soil moisture St is greater than the maximum value in the preset normal soil moisture interval, abnormal detection of soil conductivity is performed: soil conductivity Dt is compared with the preset normal soil conductivity threshold of the corresponding crop type, the preset normal soil conductivity threshold is threshold one and threshold two, and threshold one < threshold two; if soil conductivity Dt is less than threshold one, a low soil conductivity signal is generated; if soil conductivity Dt is greater than threshold two, a high soil conductivity signal is generated; abnormal detection of soil pH value is performed: the obtained soil pH value is compared with the preset normal soil pH value range of the corresponding crop type. If the soil pH value does not belong to the preset normal soil pH value range of the corresponding crop type, a soil pH value abnormal signal is generated.

[0020] Optionally, the specific process of analyzing the environmental data and meteorological data is:

[0021] Substitute environmental data and meteorological data into the curve graph to obtain an aura analysis graph, analyze the aura analysis graph, obtain a certain time period t on the time axis of the aura analysis graph, obtain the corresponding normal standard intervals in the planting management database for the environmental humidity, environmental temperature, light intensity, rainfall and wind speed within the time period t, if the environmental humidity, environmental temperature, light intensity, rainfall and wind speed do not belong to the corresponding normal standard interval, count the time duration during which the corresponding data does not belong to the corresponding normal standard interval within the time period t, analyze the time duration corresponding to the environmental humidity, environmental temperature, light intensity, rainfall and wind speed that do not belong to the corresponding normal standard interval to obtain the total aura value, match the total aura value with the preset aura value interval, the preset aura value intervals are aura value interval one and aura value interval two, if the total aura value belongs to the aura value interval one, generate a slight aura abnormality signal, if the total aura value belongs to the aura value interval two, generate a medium to heavy aura abnormality signal.

[0022] Optionally, the specific process of numbering the water-fertilizer data and the water content data is:

[0023] Water and fertilizer data are numbered, including water content data and fertilizer data. Several fertilizer data of different specifications are numbered; several water with different contents in the water content data are numbered; water and fertilizer data are mixed and deployed: different crop types and problems that often occur in the growth stages corresponding to different crop types; mix and deploy in advance, obtain solutions to the problems that often occur in the corresponding crops through the planting management database, and then mix fertilizer and water in a fixed mixing ratio according to the solution, and number the deployed mixed water and fertilizer.

[0024] A second aspect of the present invention provides a remote control method for a flower field water and fertilizer integrated machine, comprising the following steps:

[0025] S100: Acquire flower field data and data of the integrated water-fertilizer machine by installing corresponding sensors on the integrated water-fertilizer machine, and save the flower field data and data of the integrated water-fertilizer machine to a planting management database;

[0026] S200: obtaining and analyzing the flower field data of the planting management database through the irrigation analysis module, including analyzing the crop growth data, analyzing the soil data, and analyzing the environmental data and meteorological data;

[0027] S300: Obtaining the data of the integrated water and fertilizer machine in the planting management database through the fertilizer analysis module for analysis, numbering the water and fertilizer data, wherein the water and fertilizer data include water content data and fertilizer data, and numbering the fertilizer data and the water content data; then, mixing the fertilizer and water in a fixed mixing ratio according to the solution, and storing the mixed water and fertilizer;

[0028] S400: Receive all signals generated by the irrigation analysis module through the operation display module, and perform corresponding operations on the received signals.

[0029] A third aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-mentioned remote control method for a flower field water and fertilizer integrated machine.

[0030] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects:

[0031] The present invention provides a remote control system for a flower field water and fertilizer integrated machine, which has many significant advantages. Through the data acquisition module and the planting management database, the system can acquire and store soil, environment, crop growth and meteorological data in real time, providing a basis for precise management. By using drones and satellite images combined with convolutional neural networks, accurate monitoring and abnormality identification of crop growth conditions can be achieved, thereby improving management efficiency and accuracy. Through the irrigation analysis module and the fertilizer analysis module, the system can perform intelligent analysis based on real-time data, generate corresponding abnormal signals, and facilitate timely adjustment of irrigation and fertilization strategies.

[0032] The present invention provides a remote control system for a flower field water and fertilizer integrated machine. The system ensures the suitability of the crop growth environment and improves the overall yield and quality of the flower field through comprehensive analysis of soil, environmental and meteorological data. The system integrates advanced data collection, analysis and management technologies, realizes the intelligent and refined management of flower field water and fertilizer, greatly reduces manpower input, and improves the efficiency and benefits of agricultural production.

[0033] 3. The fertilizer analysis module of the present invention combines with the planting management database to carry out accurate water and fertilizer allocation and management, which has multiple advantages; through the numbering system and mixed allocation mechanism, personalized water and fertilizer management for different crops and growth stages is realized, and the accuracy and effect of fertilization are improved; the system automatically matches the stored mixed water and fertilizer or instantly allocates the required water and fertilizer, which greatly reduces the complexity and time of manual operation and improves management efficiency and response speed; the system uses advanced water and fertilizer management technology to significantly improve the automation, intelligence and refinement level of agricultural production, increase crop yield and quality, and reduce resource waste and management costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 It is a principle block diagram of the present invention;

[0035] Figure 2 It is a diagram of the method steps of the present invention;

[0036] Figure 3 This is the ring gas analysis diagram of the present invention. DETAILED DESCRIPTION

[0037] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 In the embodiment of the present invention, the present invention adopts a remote control system for a flower field water and fertilizer integrated machine, including a data acquisition module, a planting management database, an irrigation analysis module, a fertilizer analysis module and an operation display module;

[0038] The data acquisition module obtains the flower field data and the integrated water and fertilizer machine data by installing corresponding sensors on the integrated water and fertilizer machine; the flower field data includes but is not limited to soil data, environmental data, crop growth data and meteorological data; the integrated water and fertilizer machine data includes but is not limited to water and fertilizer data and mixed data; and the obtained flower field data and integrated water and fertilizer machine data are saved in the planting management database;

[0039] The irrigation analysis module obtains the flower field data from the planting management database for analysis, specifically:

[0040] Step 1: Analyze crop growth data, which includes growth stage data, growth index data and health status. Crop growth data is obtained by using drones and satellite images to monitor large-scale crop growth and obtain high-resolution images. Then, the crop types in the high-resolution images are identified through convolutional neural networks. The large-scale crop images monitored by drones and satellite images are divided into regions according to crop types, and the regions corresponding to different crop types are numbered as ZQYn, n=1, 2, 3, ..., m-1, m. Then, the normal growth stage data and normal growth index data of the crop types in the corresponding regions are obtained through the planting management database. The real-time growth stage data and real-time growth index data are obtained through high-resolution images collected by drones and satellite images. Similarly, the convolutional neural network performs feature comparison on the normal growth stage data and normal growth index data with the real-time growth stage data and real-time growth index data to obtain the real-time growth Check whether there are growth stage anomalies and growth index anomalies in the stage data and real-time growth index data; if there are growth stage anomalies, generate growth stage anomaly signals; if there are growth index anomalies, generate growth index anomaly signals; the health status is analyzed by collecting high-resolution images through drones and satellite images, and the normal health color data of the crop types in the corresponding area are obtained through the planting management database; the color of the corresponding crop type in the collected high-resolution image is converted into RGB value, marked as RGB1, and the color of the corresponding crop type in the normal health color data is converted into RGB value, marked as RGB2; RGB1 is divided by RGB2 to obtain the health status coefficient; then the health status coefficient is matched with the preset health status interval, and if the health status coefficient does not belong to the preset health status interval, a poor health status signal is generated; when a growth stage anomaly signal, a growth index anomaly signal or a poor health status signal is generated, execute step 2;

[0041] Step 2: Analyze the soil data by obtaining the soil data n of the area ZQYn corresponding to the abnormal growth stage signal or the abnormal growth index signal or the poor health signal; the soil data includes soil moisture, soil temperature, soil pH value and soil conductivity. The soil moisture St (expressed as volume water content) is collected by a humidity sensor, the soil temperature Wt is usually collected by a temperature sensor, the soil pH value is measured by a pH sensor, and then the change of the soil pH value is analyzed by the soil average pHp and the soil standard deviation pHb. The conductivity Dt sensor directly provides readings. Similarly, the change of the conductivity Dt value is analyzed by the conductivity average Dtp and the conductivity standard deviation Dtb; Substitute the soil data n into the standardization formula: corresponding standardized value = corresponding collected value - corresponding average value / corresponding standard deviation to obtain the corresponding standardized data; Stn, Wtn, pHn and Dtn respectively; Stn is the standardized soil moisture, Wtn is the standardized soil temperature, pHn is the standardized soil pH value and Dtn is the standardized soil conductivity;

[0042] By formula Output the soil comprehensive value TRHZn of the corresponding area ZQYn; wherein a1, a2, a3 and a4 are all preset weight factors; then compare the soil comprehensive value TRHZn with the corresponding preset soil comprehensive range in the planting management database. If the soil comprehensive value TRHZn belongs to the preset soil comprehensive range, there is no abnormality, and execute step 3; otherwise, when the soil comprehensive value TRHZn does not belong to the preset soil comprehensive range, perform abnormality detection on the data in the soil data n one by one;

[0043] Abnormal detection of soil moisture: soil moisture St is obtained and matched with the preset normal soil moisture interval of the corresponding crop type. If the soil moisture St does not belong to the preset normal soil moisture interval of the corresponding crop type, and the soil moisture St is less than the minimum value in the preset normal soil moisture interval, a low soil moisture signal is generated; if the soil moisture St does not belong to the preset normal soil moisture interval of the corresponding crop type, and the soil moisture St is greater than the maximum value in the preset normal soil moisture interval, abnormal detection of soil conductivity is performed; abnormal detection of soil conductivity: soil conductivity Dt is compared with the preset normal soil conductivity threshold of the corresponding crop type, the preset normal soil conductivity threshold is threshold one and threshold two, and threshold one < threshold two; if the soil conductivity Dt is less than threshold one, a low soil conductivity signal is generated; if the soil conductivity Dt is greater than threshold two, a high soil conductivity signal is generated; abnormal detection of soil pH value is performed, the obtained soil pH value is compared with the preset normal soil pH value range of the corresponding crop type, and if the soil pH value does not belong to the preset normal soil pH value range of the corresponding crop type, a soil pH value abnormal signal is generated;

[0044] Step 3: Please refer to Figure 3 As shown; the environmental data and meteorological data are analyzed, wherein the environmental data include environmental humidity and environmental temperature, and the meteorological data include light intensity, rainfall and wind speed, and the environmental data and meteorological data are substituted into the curve to obtain the annular analysis diagram; by analyzing the annular analysis diagram, through a certain time period t on the time axis of the annular analysis diagram, the corresponding normal standard intervals in the planting management database are obtained for the environmental humidity, environmental temperature, light intensity, rainfall and wind speed within the time period t, if the corresponding data (environmental humidity, ambient temperature, light intensity, rainfall and wind speed) do not belong to the corresponding normal standard interval, and by counting the time length during which the corresponding data does not belong to the corresponding normal standard interval within the time period t, the time lengths of the environmental humidity, ambient temperature, light intensity, rainfall and wind speed that do not belong to the corresponding normal standard interval are TS1, TW1, TG1, TJ1 and TF1 respectively; and by the formula Output the total value of the ring gas HQZZ, where HQZ1 is the ring gas value one, HQZ2 is the ring gas value two, and b1, b2, b3, b4 and b5 are all preset weight factors; match the total value of the ring gas HQZZ with the preset ring gas value interval, the preset ring gas value interval is the ring gas value interval one and the ring gas value interval two, if the total value of the ring gas HQZZ belongs to the ring gas value interval one, generate a slight ring gas abnormality signal, if the total value of the ring gas HQZZ belongs to the ring gas value interval two, generate a medium to heavy ring gas abnormality signal;

[0045] The fertilizer analysis module obtains the data of the integrated water and fertilizer machine from the planting management database for analysis. The specific process is as follows:

[0046] The water and fertilizer data are numbered. The water and fertilizer data include water content data and fertilizer data. The fertilizer data (fertilizer data is fertilizer data of several different specifications) are numbered as FLo, o=1, 2, 3, ..., p, and the water content data (water content data is water of several different contents) are numbered as Si, i=1, 2, 3, ..., u;

[0047] Mix and deploy water and fertilizer data, specifically: different crop types and problems that often occur in the growth stages of different crop types; mix and deploy in advance, and obtain solutions to the problems that often occur in the corresponding crops through the planting management database, and then mix fertilizer and water in a fixed mixing ratio according to the solutions, and number the prepared mixed water and fertilizer, which is NFLoSiZ, N=1, 2, 3, ..., Y; and then store the prepared mixed water and fertilizer;

[0048] The operation display module is used to receive all signals generated by the irrigation analysis module (including medium and heavy abnormal air flow signals, slight abnormal air flow signals, abnormal soil pH value signals, high soil conductivity signals, low soil conductivity signals, low soil moisture signals, poor health status signals, abnormal growth stage signals and abnormal growth index signals). When a poor health status signal, an abnormal growth stage signal or an abnormal growth index signal is received, the remote communication device transmits the poor health status signal, the abnormal growth stage signal or the abnormal growth index signal to the user terminal, and the user uses the display device corresponding to the terminal to issue abnormal alarms for different crop types. , and the user operates through the corresponding operation page on the display device; when a medium or heavy abnormal air environment signal or a slight abnormal air environment signal or a soil pH abnormality signal or a high soil conductivity signal or a low soil conductivity signal or a low soil moisture signal is received, the corresponding solution number NFLoSiZ is obtained through the planting management database, and then matched with the mixed water and fertilizer storage information in the planting management database. If the mixed water and fertilizer storage information in the planting management database is displayed as none, it is deployed according to the corresponding solution. If the mixed water and fertilizer storage information in the planting management database is displayed as yes, the corresponding equipment is controlled to apply fertilizer.

[0049] like Figure 2 As shown, the present invention also provides a remote control method for a flower field water and fertilizer integrated machine, the specific steps are:

[0050] S100: Acquire flower field data and data of the integrated water-fertilizer machine by installing corresponding sensors on the integrated water-fertilizer machine, and save the acquired flower field data and data of the integrated water-fertilizer machine into a planting management database;

[0051] S200: The irrigation analysis module obtains the flower field data from the planting management database for analysis, analyzes the crop growth data, analyzes the soil data, and analyzes the environmental data and meteorological data;

[0052] S300: The fertilizer analysis module obtains the data of the integrated water and fertilizer machine in the planting management database for analysis, and numbers the water and fertilizer data, which includes water content data and fertilizer data. The fertilizer data and the water content data are numbered; and then the fertilizer and water are mixed in a fixed mixing ratio according to the solution, and the mixed water and fertilizer are stored;

[0053] S400: receiving all signals generated by the irrigation analysis module through the operation display module, and performing corresponding operations on the received signals;

[0054] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the remote control method for a flower field water and fertilizer integrated machine.

[0055] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A remote control system for a flower field water and fertilizer integrated machine, comprising an irrigation analysis module and a fertilizer analysis module, characterized in that: The irrigation analysis module is used to obtain and analyze the flower field data in the planting management database, specifically: Step 1: Analyze crop growth data: obtain high-resolution images, use convolutional neural networks to identify crop types in high-resolution images, divide large-area crop images into regions according to crop types, and number regions corresponding to different crop types, and obtain normal growth stage data and normal growth index data of crop types in corresponding regions through the planting management database; similarly, use convolutional neural networks to perform feature comparison on normal growth stage data and normal growth index data with real-time growth stage data and real-time growth index data to determine whether real-time growth stage data and real-time growth index data have growth stage anomalies and growth index anomalies; if there are growth stage anomalies, generate growth stage anomaly signals; if there are growth index anomalies, generate growth index anomaly signals; analyze health status to generate poor health status signals; Step 2: Analyze the soil data to obtain the comprehensive soil value of the corresponding area; Then compare the soil comprehensive value with the corresponding preset soil comprehensive range in the planting management database. If the soil comprehensive value is within the preset soil comprehensive range, there is no abnormality, and step three is executed; otherwise, when the soil comprehensive value is not within the preset soil comprehensive range, the data in the soil data n are detected for abnormalities one by one; Step 3: Analyze the environmental data and meteorological data to obtain the total value of the ambient air; The fertilizer analysis module obtains the data of the integrated water and fertilizer machine from the planting management database for analysis. The specific process is: numbering the water and fertilizer data and the water content data, then mixing and deploying the water and fertilizer data, and numbering and storing the deployed mixed water and fertilizer; The specific process of analyzing the soil data is as follows: by acquiring soil data n in the area ZQYn corresponding to the generation of abnormal growth stage signals or abnormal growth index signals or poor health status signals; substituting the soil data n into the standardization formula: corresponding standardized value = corresponding collected value - corresponding average value / corresponding standard deviation to obtain corresponding standardized data, which are Stn, Wtn, pHn and Dtn respectively; Stn is the standardized soil moisture, Wtn is the standardized soil temperature, pHn is the standardized soil pH value and Dtn is the standardized soil conductivity; then outputting the soil comprehensive value of the corresponding area through the formula, and then comparing the soil comprehensive value with the corresponding preset soil comprehensive range in the planting management database. If the soil comprehensive value belongs to the preset soil comprehensive range, there is no abnormality, and step three is executed; otherwise, when the soil comprehensive value does not belong to the preset soil comprehensive range, the data in the soil data n are detected for abnormalities one by one; The data in the soil data n are detected for abnormality one by one, specifically: abnormality detection of soil moisture: soil moisture St is obtained and matched with the normal soil moisture interval preset for the corresponding crop type. If the soil moisture St does not belong to the normal soil moisture interval preset for the corresponding crop type, and the soil moisture St is less than the minimum value in the preset normal soil moisture interval, a low soil moisture signal is generated; If the soil moisture St does not belong to the preset normal soil moisture range of the corresponding crop type, and the soil moisture St is greater than the maximum value in the preset normal soil moisture range, then the soil conductivity is detected as abnormal: the soil conductivity Dt is compared with the preset normal soil conductivity threshold of the corresponding crop type, the preset normal soil conductivity threshold is threshold one and threshold two, and threshold one is less than threshold two; if the soil conductivity Dt is less than threshold one, a low soil conductivity signal is generated; if the soil conductivity Dt is greater than threshold two, a high soil conductivity signal is generated; the soil pH value is detected as abnormal: the obtained soil pH value is compared with the preset normal soil pH value range of the corresponding crop type, and if the soil pH value does not belong to the preset normal soil pH value range of the corresponding crop type, a soil pH value abnormal signal is generated; The specific process of analyzing the environmental data and meteorological data is as follows: substituting the environmental data and meteorological data into a curve graph to obtain an anomaly analysis graph, analyzing the anomaly analysis graph, obtaining a certain time period t on the time axis of the anomaly analysis graph, respectively obtaining the corresponding normal standard intervals in the planting management database for the environmental humidity, environmental temperature, light intensity, rainfall and wind speed within the time period t, if the environmental humidity, environmental temperature, light intensity, rainfall and wind speed do not belong to the corresponding normal standard interval, counting the duration of the corresponding data not belonging to the corresponding normal standard interval within the time period t, analyzing the duration of the environmental humidity, environmental temperature, light intensity, rainfall and wind speed not belonging to the corresponding normal standard interval to obtain the total anomaly value, matching the total anomaly value with a preset anomaly value interval, the preset anomaly value intervals are anomaly value interval one and anomaly value interval two, if the total anomaly value belongs to anomaly value interval one, generating a slight anomaly abnormal signal, if the total anomaly value belongs to anomaly value interval two, generating a medium to heavy anomaly abnormal signal; The specific process of numbering the water-fertilizer data and the water content data is as follows: numbering the water-fertilizer data, which includes water content data and fertilizer data, and numbering several fertilizer data of different specifications; numbering several waters of different contents in the water content data; mixing and deploying the water-fertilizer data: numbering the problems that often occur in different crop types and the growth stages corresponding to different crop types; Carry out mixing and blending in advance, obtain solutions to common problems of corresponding crops through the planting management database, and then mix fertilizer and water in a fixed mixing ratio according to the solutions, and number the prepared mixed water and fertilizer.

2. A remote control system for a flower field water and fertilizer integrated machine according to claim 1, characterized in that: It also includes a data acquisition module, a planting management database and an operation display module; The data acquisition module obtains the flower field data and the integrated water and fertilizer machine data by installing corresponding sensors on the integrated water and fertilizer machine; the flower field data includes soil data, environmental data, crop growth data and meteorological data; the integrated water and fertilizer machine data includes water and fertilizer data and mixed data; and the obtained flower field data and integrated water and fertilizer machine data are saved in the planting management database; The planting management database is used to store data acquired by the data acquisition module and preset data; The operation display module is used to receive all signals generated by the irrigation analysis module and perform corresponding operations on the received signals.

3. A remote control system for a flower field water and fertilizer integrated machine according to claim 1, characterized in that: The specific process of analyzing the health status by collecting high-resolution images using drones and satellite images is as follows: The normal healthy color data of the crop types in the corresponding area are obtained through the planting management database, the color of the corresponding crop type in the high-resolution image is converted into RGB value, marked as RGB1, and then the color of the corresponding crop type in the normal healthy color data is converted into RGB value, marked as RGB2; RGB1 is divided by RGB2 to obtain the health status coefficient; the health status coefficient is matched with the preset health status interval, if the health status coefficient does not belong to the preset health status interval, a poor health status signal is generated; when an abnormal growth stage signal or an abnormal growth index signal or a poor health status signal is generated, step two is executed.

4. A remote control method for a flower field water and fertilizer integrated machine, characterized in that A remote control system for a flower field water and fertilizer integrated machine as described in any one of claims 1 to 3, comprising the following steps: S100: Acquire flower field data and data of the integrated water-fertilizer machine by installing corresponding sensors on the integrated water-fertilizer machine, and save the flower field data and data of the integrated water-fertilizer machine to a planting management database; S200: obtaining and analyzing the flower field data of the planting management database through the irrigation analysis module, including analyzing the crop growth data, analyzing the soil data, and analyzing the environmental data and meteorological data; S300: Obtaining the data of the integrated water and fertilizer machine in the planting management database through the fertilizer analysis module for analysis, numbering the water and fertilizer data, wherein the water and fertilizer data include water content data and fertilizer data, and numbering the fertilizer data and the water content data; then, mixing the fertilizer and water in a fixed mixing ratio according to the solution, and storing the mixed water and fertilizer; S400: Receive all signals generated by the irrigation analysis module through the operation display module, and perform corresponding operations on the received signals.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, the steps of a remote control method for a flower field water and fertilizer integrated machine as described in claim 4 are implemented.

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