Water and fertilizer precision regulation platform

Abstract

The application discloses a water and fertilizer precision regulation platform, comprising the following architectures: a perception layer, a communication layer, a data layer, an intelligent decision layer, a control execution layer and an application layer. The application constructs a perception-decision-execution-feedback closed loop system, deeply couples meteorological prediction, soil characteristics and equipment state multi-dimensional dynamic parameters, breaks through the limitation of traditional static threshold regulation through a cross-level collaborative optimization model, realizes environment adaptive response resource efficient utilization and operation unmanned decision intelligence, provides a full-link precision management and control scheme for modern agriculture, solves the resource mismatch problem caused by environmental mutation through a dynamic irrigation water demand model combined with meteorological forecast and soil moisture data, avoids nutrient leaching and water resource waste caused by invalid irrigation, and solves the problem of accelerated water loss in sandy soil special working conditions through the linkage of a rule engine and a leaching risk early warning mechanism to analyze soil texture, and improves soil fertilizer retention capacity.

Description

Technical Field

[0001] This invention belongs to the field of control systems, and more specifically, relates to a precision water and fertilizer control platform. Background Technology

[0002] Current precision water and fertilizer control systems in agriculture are typically built on an Internet of Things (IoT) architecture, including soil moisture sensors, weather sensors, wireless transmission such as LoRa / NB-IoT, threshold rules or basic crop models, and execution layer irrigation pumps and fertilizer applicators. Such systems can collect environmental data, remotely control equipment, and automatically irrigate and fertilize based on preset rules, thus initially meeting the basic automation needs of agricultural production.

[0003] However, traditional systems rely on static thresholds, such as triggering irrigation when soil moisture is less than 60%, but cannot dynamically integrate multi-dimensional variables such as future rainfall forecasts and soil sand content. This leads to irrigation operations being performed before heavy rain, exacerbating nutrient leaching or ignoring differences in soil water retention capacity, such as accelerated water loss in sandy soil, resulting in resource waste. In addition, fertilization deviation correction relies on manual inspection and cannot adjust the fertilization pump speed in real time through dynamic compensation algorithms, resulting in the actual fertilization amount being consistently lower than the target value. Therefore, we propose a water and fertilizer precision control platform to specifically address the above problems. Summary of the Invention

[0004] The purpose of this invention is to address the shortcomings of existing technologies by proposing a precise water and fertilizer regulation platform. This platform constructs a closed-loop system of perception, decision-making, execution, and feedback, deeply coupling multi-dimensional dynamic parameters of weather forecasting, soil characteristics, and equipment status. Through a cross-level collaborative optimization model, it breaks through the limitations of traditional static threshold regulation, achieving environmental adaptive response, efficient resource utilization, unmanned operation, and intelligent decision-making, thus providing a precise full-chain management solution for modern agriculture.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] The water and fertilizer precision regulation platform includes the following architecture:

[0007] The sensing layer deploys soil moisture sensors, soil nutrient sensors, meteorological sensors, and crop growth sensors to collect environmental data in real time; at the same time, it monitors the operating parameters and fault status of irrigation pumps, fertilizer applicators, and solenoid valves through the equipment status acquisition module.

[0008] The communication layer employs a multi-protocol fusion wireless communication module and a wired communication module, combined with a protocol adaptation module to achieve unified encapsulation for cross-layer data transmission;

[0009] The data layer uses a time-series database to store real-time environmental data and a relational database to store historical data. It also uses a data processing module to perform data cleaning, missing value imputation, and standardized integration of multi-source data.

[0010] The intelligent decision-making layer includes: an agricultural model module that integrates crop water and fertilizer requirement models and calculates water and fertilizer requirements based on crop variety parameters; an intelligent algorithm module that applies machine learning algorithms to optimize irrigation duration, fertilizer ratio, and execution timing, and generates energy-saving strategies based on historical energy consumption data; a rules engine module that dynamically adjusts decisions according to preset rules; and a scheme generation module that integrates model output and optimization suggestions to generate water and fertilizer regulation schemes that can be manually intervened.

[0011] The control execution layer includes: a protocol adaptation module, which parses the decision-making layer instructions and drives the equipment through the Modbus / PLC protocol; an equipment control module, which dynamically adjusts the irrigation pump flow rate, fertilizer applicator ratio, and solenoid valve switching status; and an execution monitoring module, which compares the equipment execution data with the scheme target value in real time, triggers deviation alarms and strategy feedback.

[0012] The application layer includes: a real-time monitoring module that provides multi-terminal visualization of environmental parameters, equipment status, and irrigation progress; a remote control module that supports manual adjustment or emergency termination of tasks; a data analysis module that correlates environmental data with water and fertilizer consumption to generate crop yield prediction reports and optimization strategies; and an early warning and alarm module that triggers multi-level alarms based on threshold rules.

[0013] Preferably, the perception layer and the intelligent decision-making layer form a closed-loop feedback mechanism, and the device status data of the execution layer is transmitted back to the data layer in real time. After cleaning, it is used to optimize the parameters of the crop water and fertilizer requirement model.

[0014] The rule engine module is deeply integrated with the meteorological data module. When the cumulative rainfall in the next 72 hours is detected to be greater than 20mm, the irrigation plan is automatically delayed and the fertilizer concentration is recalculated.

[0015] The data analysis module introduces an input-output ratio quantification model, combining water and fertilizer costs, equipment energy consumption, and predicted output to generate economic benefit optimization strategies.

[0016] Preferably, the control execution layer adjusts the execution deviation through a dynamic compensation algorithm. When the actual fertilization amount is 10% lower than the plan value, the fertilization time is automatically extended and the historical model data is corrected simultaneously.

[0017] The application layer's energy consumption analysis module identifies high-energy-consuming devices and recommends off-peak execution strategies to take advantage of the peak-valley electricity price difference.

[0018] Preferably, the early warning alarm module and the control execution layer form a closed-loop feedback. When the soil EC value sensor detects that the value exceeds the preset threshold, it automatically triggers the equipment control module to stop the operation of the fertilizer applicator and initiates a clean water flushing command to the solenoid valve through the protocol adaptation module.

[0019] Preferably, the protocol adaptation module of the communication layer has a built-in multi-protocol fusion communication mechanism. When the LoRa signal strength is detected to be <-80dBm, it automatically switches to NB-IoT transmission mode and sends the switching log back to the historical database module of the data layer.

[0020] Preferably, when generating an irrigation plan, the intelligent algorithm module calls historical data from the energy consumption analysis module and dynamically adjusts the start-up time of the irrigation pump in conjunction with the peak and valley cycles of electricity prices;

[0021] The execution monitoring module corrects execution deviations through a dynamic compensation algorithm: when the actual fertilization amount is 10% lower than the plan value, the fertilization time is automatically extended and the speed of the fertilization pump is increased proportionally, and the deviation correction record is synchronously updated to the real-time database module of the data layer.

[0022] Preferably, the execution monitoring module corrects execution deviations through a dynamic compensation algorithm: when the actual fertilization amount is 10% lower than the plan value, the fertilization time is automatically extended and the speed of the fertilization pump is increased proportionally, and the deviation correction record is synchronously updated to the real-time database module of the data layer.

[0023] Preferably, the intelligent decision-making layer calculates the daily irrigation water requirement. The formula for calculation is:

[0024] ,in, This refers to daily evaporation and transpiration. Crop coefficients set for the crop management module; The area of ​​the irrigated region; Provides the effective rainfall forecast for the next 48 hours for the meteorological data module; The efficiency coefficient of the irrigation system is preset to 0.85; The soil moisture deficit compensation coefficient is the percentage of soil moisture sensor readings that are below a threshold. This formula integrates weather forecasts with real-time soil moisture data to dynamically offset rainfall interference and improve irrigation accuracy.

[0025] Preferably, the fertilizer pump speed compensation amount in the dynamic compensation algorithm is... The formula for calculation is:

[0026] ,in, The target fertilization amount is set for the scheme generation module; To execute the monitoring module to read the actual cumulative fertilizer application amount; This is the maximum speed of the fertilizer pump; The fertilizer solubility compensation factor is preset to 0.9, which is suitable for highly crystalline fertilizers. When the actual amount of fertilizer applied is 10% lower than the planned value, the pump speed is increased to apply fertilizer in real time, thus shortening the deviation correction time.

[0027] The technical effects and advantages of this invention are as follows: Compared with traditional technologies, the water and fertilizer precision regulation platform provided by this invention solves the resource mismatch problem caused by sudden environmental changes by integrating weather forecasts and soil moisture data through a dynamic irrigation water demand model, thus avoiding nutrient leaching and water waste caused by ineffective irrigation; and solves the problem of accelerated water loss under special working conditions of sandy soil by linking a rule engine and a leaching risk early warning mechanism with soil texture analysis, thereby improving the soil's fertilizer retention capacity.

[0028] The system solves the problem of insufficient fertilizer application caused by manual inspection in traditional systems by using a dynamic compensation algorithm for fertilizer pump speed to correct execution deviations in real time; it solves the problem of the disconnect between agronomic decision-making and energy economy by integrating electricity pricing policies and equipment degradation curves through an energy cost model, thereby maximizing agricultural production benefits; and it solves the problem of data transmission interruption in harsh field environments by using a multi-protocol communication adaptive switching mechanism, thereby ensuring the real-time reliability of the decision-making and execution links. Attached Figure Description

[0029] Figure 1 This is a system diagram of the water and fertilizer precision regulation platform of the present invention. Detailed Implementation

[0030] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without inventive effort are within the scope of protection of this invention.

[0031] This invention provides, for example Figure 1 The water and fertilizer precision regulation platform shown integrates soil moisture stratification monitoring, weather forecasts, equipment energy consumption, and crop growth stage data to construct a dynamic water and fertilizer demand map. Based on power peak-valley rules and pipeline pressure sensor data, it automatically calculates the optimal pressure value of the pipeline network to reduce water pump energy consumption. The protocol adaptation module of the communication layer supports the mutual translation of instructions between NB-IoT sensors and Modbus irrigation equipment, enabling seamless access of old equipment to the intelligent decision-making system. When the soil EC value rises abnormally, the system automatically stops fertilization and injects clean water to flush the pipeline, while simultaneously pushing fertilizer solubility optimization solutions to the application layer.

[0032] Includes the following architecture:

[0033] The sensing layer deploys soil moisture sensors, soil nutrient sensors, meteorological sensors, and crop growth sensors to collect environmental data in real time; at the same time, it monitors the operating parameters and fault status of irrigation pumps, fertilizer applicators, and solenoid valves through the equipment status acquisition module.

[0034] One specific embodiment comprises an electromagnetic flowmeter, a pressure transmitter, and a radar level gauge. It provides real-time control and monitoring of the operation of the water source, water pump, and filter equipment. It also provides real-time monitoring and early warning of the pressure and flow rate at the water pump outlet, the differential pressure of the filter, and the three-phase electrical parameters of the water pump motor. In the event of a system failure, it protects the safety of the water pump, motor, filter, and piping network. Its main monitoring functions are as follows:

[0035] The pump outlet pressure and filter outlet pressure are detected to determine the pressure difference before and after the filter and to trigger an alarm for abnormal pressure.

[0036] Enables remote communication and human-computer interaction with the irrigation cloud platform, ensuring that the irrigation system operates safely and reliably according to the set irrigation schedule and operating parameters.

[0037] The communication layer employs a multi-protocol fusion wireless communication module and a wired communication module, combined with a protocol adaptation module to achieve unified encapsulation of data transmission across layers; the protocol adaptation module of the communication layer has a built-in multi-protocol fusion communication mechanism, which automatically switches to NB-IoT transmission mode when LoRa signal strength is detected to be <-80dBm, and sends the switching log back to the historical database module of the data layer.

[0038] Signal strength threshold for switching transmission modes in wired communication modules Dynamically generated from formulas:

[0039] Where -80 is the critical value of LoRa signal strength (dBm); The actual transmission delay (in seconds) is given; the denominator constant 25 is an empirical fitting factor; when the delay is greater than 3 seconds, the signal strength threshold is automatically reduced to prioritize data real-time performance and reduce offline time.

[0040] The data layer uses a time-series database to store real-time environmental data and a relational database to store historical data. It also uses a data processing module to perform data cleaning, missing value imputation, and standardized integration of multi-source data.

[0041] The intelligent decision-making layer includes: an agricultural model module, which integrates crop water and fertilizer requirement models and calculates water and fertilizer requirements based on crop variety parameters; an intelligent algorithm module, which applies machine learning algorithms to optimize irrigation duration, fertilizer ratio, and execution timing, and generates energy-saving strategies based on historical energy consumption data; a rule engine module, which dynamically adjusts decisions according to preset rules; and a scheme generation module, which integrates model output and optimization suggestions to generate water and fertilizer control schemes that can be manually intervened. When generating irrigation schemes, the intelligent algorithm module calls historical data from the energy consumption analysis module and dynamically adjusts the start-up time of irrigation pumps based on electricity price peak and valley cycles to reduce total energy costs. The rule engine module and the meteorological data module work in real time. When the cumulative rainfall in the next 72 hours is greater than 20mm, the irrigation plan in the scheme generation module is automatically delayed, and the fertilizer ratio is recalculated to offset nutrient leaching losses.

[0042] It should be noted in this embodiment that the intelligent decision-making layer calculates the daily irrigation water demand. The formula for calculation is:

[0043] ,in, This refers to daily evaporation and transpiration. Crop coefficients set for the crop management module; The area of ​​the irrigated region; Provides the effective rainfall forecast for the next 48 hours for the meteorological data module; The efficiency coefficient of the irrigation system is preset to 0.85; The soil moisture deficit compensation coefficient is the percentage of soil moisture sensor readings that are below a threshold. This formula integrates weather forecasts with real-time soil moisture data to dynamically offset rainfall interference and improve irrigation accuracy.

[0044] In addition, the energy consumption analysis module calculates the unit time cost savings rate during peak and off-peak electricity price periods. The formula for calculation is:

[0045] ,in The off-peak electricity price is yuan / kW·h; Peak electricity price, yuan / kW·h; This represents the average annual operating power of the irrigation pump. The rated power of the irrigation pump is used; combined with the equipment efficiency degradation curve, the threshold is set to 0.7, and irrigation is dynamically recommended during low-price periods to reduce annual costs.

[0046] Specifically, the rule engine determines the nutrient leaching risk index. The formula for calculation is:

[0047] ,in This is the predicted cumulative rainfall for the next 72 hours; The percentage of sand content detected by the soil sensor in the sensing layer; Soil cation exchange capacity (cmol / kg), when When the concentration is greater than 0.5, an alarm will be automatically triggered and the fertilizer concentration will be reduced to minimize nitrogen loss.

[0048] The control execution layer includes: a protocol adaptation module, which parses the decision-making layer instructions and drives the equipment via the Modbus / PLC protocol; an equipment control module, which dynamically adjusts the irrigation pump flow rate, fertilizer applicator ratio, and solenoid valve switching status; an execution monitoring module, which compares the equipment execution data with the plan target value in real time, triggers deviation alarms and strategy feedback; the execution monitoring module corrects execution deviations through a dynamic compensation algorithm: when the actual fertilizer application is 10% lower than the plan value, it automatically extends the fertilization time and increases the fertilizer pump speed proportionally, and the deviation correction record is synchronously updated to the real-time database module of the data layer;

[0049] Fertilizer pump speed compensation amount in dynamic compensation algorithm The formula for calculation is:

[0050] ,in, The target fertilization amount is set for the scheme generation module; To execute the monitoring module to read the actual cumulative fertilizer application amount; This is the maximum speed of the fertilizer pump; The fertilizer solubility compensation factor is preset to 0.9, which is suitable for highly crystalline fertilizers. When the actual amount of fertilizer applied is 10% lower than the planned value, the pump speed is increased to apply fertilizer in real time, thus shortening the deviation correction time.

[0051] As an optional component of this embodiment, it consists of a booster pump, an electric valve, a weighing device, a fertilizer tank, a flow meter, a water distribution network including a three-level pipeline consisting of a main pipe, branch pipes, and capillary pipes, and an irrigation device, which is divided into drippers and drip irrigation pipes.

[0052] Automated fertilizer applicators consist of a fertilizer pump, a fertilizer tank, and an intelligent fertilization system. The entire automated fertilization process is supported by five major systems: a mixing system, a main pipeline system, a fertilizer injection system, a detection system, and a control system. The main flow is as follows: The mixing system consists of a fertilizer mixing pipeline and a fertilizer injection pipeline, where fertilizer and water are mixed and proportioned; the main pipeline system consists of a water pump and corresponding pipelines, providing pressure and water flow to the system; the fertilizer injection system consists of a fertilizer injection pump, an electronic flow meter, a float flow meter, a pressure relief valve, and corresponding pipelines. Among these, the fertilizer injection pump is a key component, and its speed is controlled by the control system to adjust the fertilizer injection volume. The pressure relief valve ensures the pressure of the fertilizer solution injected into the main pipeline.

[0053] The application layer includes: a real-time monitoring module that provides multi-terminal visualization of environmental parameters, equipment status, and irrigation progress; a remote control module that supports manual adjustment or emergency termination of tasks; a data analysis module that correlates environmental data with water and fertilizer consumption to generate crop yield prediction reports and optimization strategies; and an early warning and alarm module that triggers multi-level alarms based on threshold rules.

[0054] Furthermore, the early warning and alarm module forms a closed-loop feedback with the control execution layer. When the soil EC value sensor detects that the value exceeds the preset threshold, it automatically triggers the equipment control module to stop the operation of the fertilizer applicator and initiates a water flushing command to the solenoid valve through the protocol adaptation module. The input-output ratio quantification model of the data analysis module links water and fertilizer costs, equipment energy consumption data and crop yield prediction reports, and outputs an economic benefit optimization strategy that includes a path to improve fertilizer utilization to the remote control module of the application layer for manual confirmation.

[0055] In the above system, the interaction logic between the modules is as follows:

[0056] Data-driven decision-making flow: data from the perception layer is uploaded to the data layer via the communication layer; the intelligent decision-making layer calls the cleaned data and combines it with agricultural models and real-time rules to generate a solution; the control execution layer parses the solution into equipment instructions; and the execution status is sent back to the perception layer.

[0057] Human-machine collaborative intervention: The application layer receives alarm information from the execution layer, the operator adjusts equipment parameters via a remote control module, and the corrected instruction is sent to the execution layer via the communication layer.

[0058] The closed loop is continuously optimized, and the data analysis module compares the effects of historical solutions to output indicators such as fertilizer utilization rate and water production efficiency. The decision-making level updates the parameters of the machine learning model based on this.

[0059] Based on the above, the specific advantages of the implementation plan are shown in the table below:

[0060] Table 1 System Module Collaboration Mechanism Table

[0061] Technology ownership Technical means System coordination mechanism Irrigation water demand Real-time linkage between meteorology, crops, and soil: Incorporating future rainfall data to dynamically adjust artificial irrigation amounts. Meteorological data - agricultural model - soil moisture sensor form a closed-loop input. Communication switching Delay response threshold: Breaking through the limitations of traditional fixed thresholds, ensuring transmission reliability in high-latency scenarios. Communication performance monitoring - protocol adaptation module decision-making - seamless switching of execution layer Fertilizer compensation Solubility compensation factor δ: Addressing the issue of decreased pumping efficiency for highly crystalline fertilizers. Fertilizer damage early warning - execution monitoring - equipment control module linkage speed adjustment Energy-saving model application Equipment efficiency degradation correction: Introducing a power attenuation coefficient (∑Pt / Pmax) to objectively reflect the equipment status. Energy consumption analysis, rule engine, and scheme generation form an economic regulation closed loop. Leaching warning Quantitative Involvement of Soil Texture in Decision Making: Joint Assessment of Nutrient Leaching Risk Based on Sand Content and Rainfall Intensity Weather forecasting, soil property database, and fertilizer formula management enable cross-layer prevention and control.

[0062] In summary, this invention addresses the resource misallocation problem caused by sudden environmental changes by integrating a dynamic irrigation water demand model with weather forecasts and soil moisture data, thus avoiding nutrient leaching and water waste caused by ineffective irrigation. Furthermore, it addresses the problem of accelerated water loss in sandy soil under special conditions by linking a rule engine and a leaching risk early warning mechanism with soil texture analysis, thereby improving soil fertility retention capacity.

[0063] The system solves the problem of insufficient fertilizer application caused by manual inspection in traditional systems by using a dynamic compensation algorithm for fertilizer pump speed to correct execution deviations in real time; it solves the problem of the disconnect between agronomic decision-making and energy economy by integrating electricity pricing policies and equipment degradation curves through an energy cost model, thereby maximizing agricultural production benefits; and it solves the problem of data transmission interruption in harsh field environments by using a multi-protocol communication adaptive switching mechanism, thereby ensuring the real-time reliability of the decision-making and execution links.

[0064] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A water and fertilizer precision regulation platform, characterized in that, Includes the following architecture: The sensing layer deploys soil moisture sensors, soil nutrient sensors, meteorological sensors, and crop growth sensors to collect environmental data in real time; at the same time, it monitors the operating parameters and fault status of irrigation pumps, fertilizer applicators, and solenoid valves through the equipment status acquisition module. The communication layer employs a multi-protocol fusion wireless communication module and a wired communication module, combined with a protocol adaptation module to achieve unified encapsulation for cross-layer data transmission; The data layer uses a time-series database to store real-time environmental data and a relational database to store historical data. It also uses a data processing module to perform data cleaning, missing value imputation, and standardized integration of multi-source data. The intelligent decision-making layer includes: an agricultural model module, which integrates crop water and fertilizer requirement models and calculates water and fertilizer requirements based on crop variety parameters; an intelligent algorithm module, which applies machine learning algorithms to optimize irrigation duration, fertilizer ratio, and execution timing, and generates energy-saving strategies based on historical energy consumption data; a rule engine module, which dynamically adjusts decisions according to preset rules; and a scheme generation module, which integrates model outputs and optimization suggestions to generate water and fertilizer regulation schemes that can be manually intervened. The intelligent decision-making layer calculates the daily irrigation water requirement. The formula for calculation is: ,in, This refers to daily evaporation and transpiration. Crop coefficients set for the crop management module; The area of ​​the irrigated region; Provides the effective rainfall forecast for the next 48 hours for the meteorological data module; The efficiency coefficient of the irrigation system is preset to 0.85; The soil moisture deficit compensation coefficient is the percentage of soil moisture sensor readings that are below a threshold. This formula integrates weather forecasts with real-time soil moisture data to dynamically offset rainfall interference and improve irrigation accuracy. The control execution layer includes: a protocol adaptation module, which parses the decision-making layer instructions and drives the equipment via the Modbus / PLC protocol; an equipment control module, which dynamically adjusts the irrigation pump flow rate, fertilizer applicator ratio, and solenoid valve switching status; and an execution monitoring module, which compares the equipment execution data with the plan target value in real time, triggering deviation alarms and strategy feedback. The execution monitoring module corrects execution deviations through a dynamic compensation algorithm: when the actual fertilizer application is 10% lower than the plan value, it automatically extends the fertilization time and increases the fertilizer pump speed proportionally, and the deviation correction record is synchronously updated to the real-time database module of the data layer. The fertilizer pump speed compensation amount in the dynamic compensation algorithm The formula for calculation is: ,in, The target fertilization amount is set for the scheme generation module; To execute the monitoring module to read the actual cumulative fertilizer application amount; This is the maximum speed of the fertilizer pump; The fertilizer solubility compensation factor is preset to 0.9, which is suitable for highly crystalline fertilizers. When the actual fertilizer application rate is 10% lower than the planned value, the pump speed is increased to apply fertilizer in real time, thus shortening the deviation correction time. The application layer includes: a real-time monitoring module that provides multi-terminal visualization of environmental parameters, equipment status, and irrigation progress; a remote control module that supports manual adjustment or emergency termination of tasks; a data analysis module that correlates environmental data with water and fertilizer consumption to generate crop yield prediction reports and optimization strategies; and an early warning and alarm module that triggers multi-level alarms based on threshold rules.

2. The water and fertilizer precision regulation platform according to claim 1, characterized in that, The perception layer and the intelligent decision-making layer form a closed-loop feedback mechanism. The device status data of the execution layer is transmitted back to the data layer in real time. After cleaning, it is used to optimize the parameters of the crop water and fertilizer requirement model. The rule engine module is deeply integrated with the meteorological data module. When the cumulative rainfall in the next 72 hours is detected to be greater than 20mm, the irrigation plan is automatically delayed and the fertilizer concentration is recalculated. The data analysis module introduces an input-output ratio quantification model, combining water and fertilizer costs, equipment energy consumption, and predicted output to generate economic benefit optimization strategies.

3. The water and fertilizer precision regulation platform according to claim 1, characterized in that, The control execution layer adjusts the execution deviation through a dynamic compensation algorithm. When the actual fertilization amount is 10% lower than the plan value, the fertilization time is automatically extended and the historical model data is corrected simultaneously. The application layer's energy consumption analysis module identifies high-energy-consuming devices and recommends off-peak execution strategies to take advantage of the peak-valley electricity price difference.

4. The water and fertilizer precision regulation platform according to claim 1, characterized in that, The early warning alarm module and the control execution layer form a closed-loop feedback. When the soil EC value sensor detects that the value exceeds the preset threshold, it automatically triggers the equipment control module to stop the operation of the fertilizer applicator and initiates a clean water flushing command to the solenoid valve through the protocol adaptation module.

5. The water and fertilizer precision regulation platform according to claim 1, characterized in that, The protocol adaptation module of the communication layer has a built-in multi-protocol fusion communication mechanism. When the LoRa signal strength is detected to be less than -80dBm, it automatically switches to NB-IoT transmission mode and sends the switching log back to the historical database module of the data layer.

6. The water and fertilizer precision regulation platform according to claim 1, characterized in that, When generating an irrigation plan, the intelligent algorithm module calls upon historical data from the energy consumption analysis module and dynamically adjusts the start-up time of the irrigation pump in conjunction with the peak and off-peak electricity price cycle.

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