Intelligent irrigation system for standardized production of forestry seedlings

Abstract

The present invention relates to the field of automatic control technology, specifically to an intelligent irrigation system for standardized production of forestry seedlings, the system comprising a soil water and fertilizer status monitoring module, a water and fertilizer demand analysis module, a water and fertilizer quantity adjustment module, a time period optimization module, an execution control module, and a resource monitoring module. In the present invention, by real-time monitoring of soil moisture and fertility status, the water and fertilizer requirements required for seedling growth can be accurately grasped, and compared with preset standards, the irrigation and fertilization requirements can be accurately assessed, thereby reducing resource waste and improving the efficiency of water and fertilizer use. By considering future weather conditions and soil temperature, the water and fertilizer input amount is adjusted, reducing the uncertain effects caused by weather changes, and identifying the optimal fertilization and irrigation time period, thereby improving the timeliness and effectiveness of irrigation and fertilization. By real-time monitoring of resource usage status and timely feedback of low inventory information, the continuous operation of irrigation and fertilization is guaranteed, and irrigation and fertilization interruptions caused by resource shortages are avoided.

Description

Technical Field

[0001] The present invention relates to the field of automatic control technology, in particular to an intelligent irrigation system for standardized production of forestry seedlings. Background Art

[0002] The field of automatic control technology aims to monitor and adjust the operating status of equipment or systems using computer programs or other automated mechanisms, thereby achieving predetermined management and control objectives without direct human intervention. This field is widely used in a variety of scenarios, including industrial production, environmental management, transportation systems, household appliances, and precision agriculture. Key technologies in automatic control systems include sensor technology, data acquisition systems, real-time feedback mechanisms, control algorithm design, and actuators. Automatic control systems can automatically detect environmental changes, process data in real time, and adjust operating parameters according to preset programs to achieve automated control effects.

[0003] The intelligent irrigation system for standardized forestry seedling production is an automated irrigation solution designed for forestry seedling cultivation and production. This system's primary purpose is to intelligently manage the irrigation process, ensuring uniform and appropriate water supply to the seedlings, thereby improving their growth quality and production efficiency. By integrating environmental monitoring sensors and automatic control algorithms, it precisely regulates irrigation timing and water volume. This not only helps conserve water and reduce labor costs, but also optimizes water allocation based on the actual needs of seedling growth, supporting sustainable forestry development.

[0004] Traditional irrigation systems lack the ability to respond quickly and adjust precisely to real-time changes. Traditional systems fail to effectively integrate and utilize real-time environmental data, resulting in uneven water and fertilizer utilization, affecting the balance and quality of seedling growth. Traditional systems are unable to integrate future weather forecasts with real-time soil conditions, resulting in unoptimized resource allocation, and there will be excess or insufficient resources, increasing production costs and resource waste. The lack of effective resource monitoring and early warning mechanisms will lead to emergency situations during the irrigation process where resources are urgently needed due to insufficient resources, affecting the continuity and efficiency of irrigation. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose an intelligent irrigation system for standardized production of forestry seedlings.

[0006] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solution: an intelligent irrigation system for standardized production of forestry seedlings, the system comprising:

[0007] The soil water and fertilizer status monitoring module is based on the forestry seedling planting environment, collects the current soil moisture and fertility status data, and obtains real-time water and fertilizer data information;

[0008] The water and fertilizer demand analysis module analyzes the deviation between the real-time water and fertilizer data and the preset standard based on the real-time water and fertilizer data information, evaluates the irrigation and fertilization requirements of the forestry seedlings, and obtains the irrigation and fertilization demand data;

[0009] The water and fertilizer amount adjustment module adjusts the irrigation and fertilization amounts based on the irrigation and fertilization demand data, combined with the weather conditions in the future period and the current soil temperature, to obtain optimized irrigation and fertilization amount information;

[0010] The time period optimization module identifies the target irrigation and fertilization time period based on the optimized irrigation and fertilization amount information, combined with the weather conditions in the future period, the growth stage of forestry seedlings and the type of fertilizer, and obtains the optimized irrigation and fertilization time information.

[0011] The execution control module performs irrigation and fertilization operations on the forestry seedlings based on the optimized irrigation and fertilization amount information and the optimized irrigation and fertilization time information to obtain irrigation and fertilization implementation information;

[0012] The resource monitoring module monitors the remaining amount of fertilizer liquid and irrigation water based on the irrigation and fertilization implementation information, and notifies the management personnel to add fertilizer liquid and irrigation water when the remaining amount of fertilizer liquid and irrigation water is lower than the preset threshold, thereby obtaining fertilizer liquid and irrigation water storage control information.

[0013] As a further solution of the present invention, the real-time water and fertilizer data information includes the real-time moisture level and fertility status index of the soil, the irrigation and fertilization demand data includes the target water volume, target fertilizer type and target fertilizer amount, the optimized irrigation and fertilization amount information includes the adjusted irrigation amount and fertilization amount, the optimized irrigation and fertilization time information includes the irrigation start time, the fertilization start time and the expected irrigation and fertilization duration period, the irrigation and fertilization implementation information includes the irrigation execution time, the fertilization execution amount and the execution error record, and the fertilizer liquid and irrigation water storage control information includes the current fertilizer liquid storage, the current irrigation water storage and the next replenishment warning time.

[0014] As a further solution of the present invention, the soil water and fertilizer status monitoring module includes:

[0015] The sensor calibration submodule calibrates the soil fertility sensor and soil moisture sensor based on the forestry seedling planting environment, compares the sensor output with known standard samples, adjusts the sensor parameters, optimizes the sensor error, and obtains the sensor accuracy adjustment result;

[0016] The environmental data acquisition submodule collects soil moisture and fertility data in the forestry seedling planting area by periodically reading sensor data based on the sensor accuracy adjustment result, and screens the data to eliminate abnormal data to generate real-time soil condition information;

[0017] The data recording submodule formats the data based on the real-time soil condition information, and performs time stamping, location classification and parameter indexing on the data, thereby optimizing the traceability and accessibility of the data and obtaining real-time water and fertilizer data information.

[0018] As a further solution of the present invention, the water and fertilizer demand analysis module includes:

[0019] The standard value acquisition submodule obtains the standard planting water and fertility values ​​of the current forestry seedlings based on the real-time water and fertilizer data information, the type of the current forestry seedlings, the generation stage of the forestry seedlings, and the forestry seedling planting history records to obtain standard planting information;

[0020] The deviation calculation submodule compares the current water and fertilizer data with the standard planting moisture and fertility values ​​based on the standard planting information, calculates and analyzes the deviation values ​​of soil moisture and fertility, and obtains the demand deviation analysis results;

[0021] The demand assessment submodule calculates the irrigation and fertilization amounts required for forestry seedlings based on the demand deviation analysis results and the size of the deviation value using a nonlinear regression algorithm to obtain irrigation and fertilization demand data.

[0022] As a further solution of the present invention, the nonlinear regression algorithm is according to the formula:

[0023]

[0024] Calculate the fertigation demand data, where: is the predicted fertigation demand data, is the intercept, is the slope, is the coefficient of the square of the deviation, is the temperature regulation coefficient, is the actual measured soil temperature, is the influence coefficient of soil saturation, is the soil saturation.

[0025] As a further solution of the present invention, the water and fertilizer amount adjustment module includes:

[0026] The weather data integration submodule collects weather forecast information for future periods from multiple meteorological data sources based on the irrigation and fertilization demand data, including rainfall probability, rainfall amount, and temperature, and obtains current soil temperature information through temperature sensors, integrates the data, and obtains weather condition data;

[0027] The weather impact assessment submodule assesses the impact of rainfall on soil moisture and the impact of temperature changes on fertilizer absorption rate based on the weather condition data to obtain a weather impact assessment result;

[0028] The strategy generation submodule uses a genetic algorithm based on the weather impact assessment results and the irrigation and fertilization demand data to calculate the required irrigation and fertilization amounts under differentiated weather conditions, formulate matching irrigation and fertilization strategies, including the amount and concentration of irrigation and fertilization, and obtain optimized irrigation and fertilization amount information.

[0029] As a further solution of the present invention, the genetic algorithm is according to the formula:

[0030] ;

[0031] Calculate the optimized irrigation and fertilization strategy, where For the optimized irrigation and fertilization strategy, For the current strategy, and Candidate strategies generated for differentiated gas conditions, is the cross factor, is the current environment status, is the historical average environmental state, is the environmental impact factor, is the adjustment factor.

[0032] As a further solution of the present invention, the time period optimization module includes:

[0033] The growth stage analysis submodule analyzes the differentiated growth stage characteristics of forestry seedlings based on the optimized irrigation and fertilization information and the historical planting records of forestry seedlings, identifies the water and nutrient absorption period of each stage, and obtains the growth stage characteristic analysis results;

[0034] The time window calculation submodule calculates the target irrigation and fertilization time windows based on the growth stage characteristic analysis results, combined with the weather conditions, soil temperature and growth cycle of forestry seedlings in the future period, optimizes the irrigation and fertilization efficiency, and obtains the optimized time window selection result;

[0035] The time scheduling submodule formulates matching irrigation and fertilization times based on the optimization time window selection results, adjusts and arranges corresponding operation schedules, matches the environmental conditions of the future period and the growth requirements of the seedlings, and obtains optimized irrigation and fertilization time information.

[0036] As a further solution of the present invention, the execution control module includes:

[0037] The solenoid valve operation submodule performs irrigation and fertilization operations on forestry seedlings by controlling the solenoid valve of the fertilizer liquid tank and the solenoid valve of the irrigation water tank based on the optimized irrigation and fertilization amount information and the optimized irrigation and fertilization time information, thereby obtaining solenoid valve operation information;

[0038] The quantitative monitoring submodule monitors the irrigation and fertilization process in real time based on the solenoid valve operation information, records the flow rate and application amount of water and fertilizer through flow meters and pressure sensors, analyzes the consistency of data with target parameters, and obtains quantitative execution feedback information;

[0039] The execution record submodule records and archives each irrigation and fertilization operation process based on the quantitative execution feedback information, including operation time, duration and actual amount, stores the information, and obtains irrigation and fertilization implementation information.

[0040] As a further solution of the present invention, the resource monitoring module includes:

[0041] The liquid level monitoring submodule monitors the liquid level heights of the fertilizer liquid tank and the irrigation water tank through liquid level sensors based on the irrigation and fertilization implementation information to obtain real-time liquid level monitoring data;

[0042] The stock assessment submodule assesses the current remaining amount of fertilizer liquid and irrigation water based on the real-time liquid level monitoring data, analyzes the resource depletion time based on the current consumption rate, and obtains the remaining resource assessment result;

[0043] The resource replenishment alarm submodule is based on the remaining resource evaluation result. When the remaining amount of fertilizer liquid and irrigation water is lower than a preset threshold, it notifies the management personnel to replenish the fertilizer liquid and irrigation water and obtains the fertilizer liquid and irrigation water storage control information.

[0044] Compared with the prior art, the advantages and positive effects of the present invention are:

[0045] In the present invention, by real-time monitoring of soil moisture and fertility status, the water and fertilizer requirements for seedling growth can be accurately grasped, and compared with preset standards, irrigation and fertilization needs can be accurately evaluated, reducing resource waste and improving the efficiency of water and fertilizer use. By considering future weather conditions and soil temperature, the amount of water and fertilizer input is adjusted, resource allocation is optimized, the uncertain impact caused by weather changes is reduced, and the optimal fertilization and irrigation time periods are identified, thereby improving the timeliness and effectiveness of irrigation and fertilization. By real-time monitoring of resource usage status and timely feedback of low inventory information, the continuous operation of irrigation and fertilization is guaranteed, and irrigation and fertilization interruptions due to resource shortages are avoided. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is a system flow chart of the present invention;

[0047] Figure 2 Schematic diagram of the system framework of the present invention;

[0048] Figure 3 This is a flow chart of the soil water and fertilizer status monitoring module of the present invention;

[0049] Figure 4 This is a flow chart of the water and fertilizer demand analysis module of the present invention;

[0050] Figure 5 This is a flow chart of the water and fertilizer adjustment module of the present invention;

[0051] Figure 6 This is a flow chart of the time period optimization module of the present invention;

[0052] Figure 7 A flowchart of the control module for executing the present invention;

[0053] Figure 8 This is a flow chart of the resource monitoring module of the present invention. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0055] In the description of the present invention, it should be understood that the terms "length," "width," "up," "down," "front," "back," "left," "right," "vertical," "horizontal," "top," "bottom," "inside," "outside," and the like, indicating positions or relationships, are based on the positions or relationships shown in the accompanying drawings and are intended only to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, in the description of the present invention, "plurality" means two or more, unless otherwise expressly and specifically defined.

[0056] Example 1

[0057] See also Figure 1 , intelligent irrigation system for standardized production of forestry seedlings, the system includes:

[0058] The soil water and fertilizer status monitoring module is based on the forestry seedling planting environment. It monitors the seedling growth data through soil fertility sensors and soil moisture sensors, collects the current soil moisture and fertility status data, and obtains real-time water and fertilizer data information;

[0059] The water and fertilizer demand analysis module compares the real-time water and fertilizer data with the preset standard water and fertility values ​​for forestry seedling planting, analyzes the deviation between the real-time water and fertilizer data and the preset standards, evaluates the irrigation and fertilization needs of forestry seedlings, and obtains irrigation and fertilization demand data;

[0060] The water and fertilizer adjustment module adjusts the irrigation and fertilizer amounts based on the irrigation and fertilization demand data, combined with the weather conditions in the future period and the current soil temperature. The weather conditions include rainfall probability, rainfall and temperature changes, and obtains the optimized irrigation and fertilization amount information;

[0061] The time period optimization module is based on the optimized irrigation and fertilization information, combined with the weather conditions in the future period, the growth stage of forestry seedlings and the type of fertilizer, to identify the target irrigation and fertilization time period, optimize the timeliness and effectiveness of irrigation and fertilization, and obtain the optimized irrigation and fertilization time information.

[0062] The execution control module irrigates and fertilizes forestry seedlings based on the optimized irrigation and fertilization amount information and the optimized irrigation and fertilization time information by controlling the solenoid valve of the fertilizer liquid tank and the solenoid valve of the irrigation water tank, and records the irrigation and fertilization process to obtain irrigation and fertilization implementation information;

[0063] The resource monitoring module monitors the water levels of the fertilizer tank and irrigation water tank in real time through liquid level sensors based on irrigation and fertilization implementation information, monitors the remaining amount of fertilizer liquid and irrigation water, and notifies the management personnel to add fertilizer liquid and irrigation water when the remaining amount of fertilizer liquid and irrigation water falls below the preset threshold, thereby obtaining fertilizer liquid and irrigation water storage control information;

[0064] Real-time water and fertilizer data information includes the real-time moisture level and fertility status indicators of the soil; irrigation and fertilization demand data includes target water volume, target fertilizer type and target fertilizer amount; optimized irrigation and fertilization amount information includes adjusted irrigation amount and fertilization amount; optimized irrigation and fertilization time information includes irrigation start time, fertilization start time and expected irrigation and fertilization duration; irrigation and fertilization implementation information includes irrigation execution time, fertilization execution amount and execution error records; fertilizer liquid and irrigation water storage control information includes current fertilizer liquid storage, current irrigation water storage and next replenishment warning time.

[0065] See also Figure 2 and Figure 3 ,The soil water and fertilizer status monitoring module includes a sensor calibration submodule, an ,environmental data acquisition submodule, and a data recording submodule;

[0066] The sensor calibration submodule calibrates the soil fertility sensor and soil moisture sensor based on the forestry seedling planting environment. It uses known standard samples to compare sensor outputs, adjust sensor parameters, optimize sensor errors, and obtain sensor accuracy adjustment results. The specific process is as follows:

[0067] The sensor calibration submodule calibrates soil fertility and soil moisture sensors based on forestry seedling planting environments. It uses standard soil samples with known fertility and moisture values ​​to provide a calibration baseline for the sensors. By measuring the difference between the sensor output and the standard sample and adjusting the error adjustment factor using the formula "adjusted output = original output + error adjustment factor × (standard sample value - original output)", the sensor output accurately reflects actual soil conditions, optimizing sensor errors and achieving sensor accuracy adjustment results.

[0068] The environmental data acquisition submodule collects soil moisture and fertility data within the forestry seedling planting area by periodically reading sensor data based on the sensor accuracy adjustment results. It then screens the data, removes abnormal data, and generates real-time soil condition information. The specific process is as follows:

[0069] Based on the sensor accuracy adjustment results, the environmental data collection submodule periodically reads sensor data to collect soil moisture and fertility data within the forestry seedling planting area. During data collection, a data quality control formula ("valid data = (current data point - minimum threshold) / (maximum threshold - minimum threshold)") is set to filter data that meets quality standards. This effectively removes abnormal data from all reads, such as data points outside the preset fertility and moisture ranges, and generates real-time soil condition information.

[0070] The data recording submodule formats the data based on real-time soil condition information, and performs time stamping, location classification, and parameter indexing on the data to optimize data traceability and accessibility. The specific process for obtaining real-time water and fertilizer data information is as follows:

[0071] The data recording submodule formats the data based on real-time soil condition information, and performs time stamping, location classification and parameter indexing on the data. The formula "recorded data = total data volume / number of data categories" is used to optimize the data organization structure, enhance data traceability and accessibility, ensure that each type of data can be accurately archived and quickly retrieved, and obtain real-time water and fertilizer data information.

[0072] See also Figure 2 and Figure 4 ,The water and fertilizer demand analysis module includes the standard value acquisition ,submodule, the deviation calculation submodule, and demand assessment ,submodule;

[0073] The standard value acquisition submodule is based on real-time water and fertilizer data information, according to the type of current forestry seedlings, combined with the generation stage of forestry seedlings, and through the forestry seedling planting history records, to obtain the standard planting water and fertility values ​​of the current forestry seedlings. The specific process of obtaining standard planting information is as follows;

[0074] The standard value acquisition submodule is based on real-time water and fertilizer data information. According to the current forestry seedling type and its growth stage, combined with historical planting records, it obtains the standard planting water and fertility values ​​suitable for the current stage. By analyzing the average water and fertility requirements of each growth stage in the historical data set, the formula "standard value = total / sample number" is used to calculate the standard value of each stage, thereby guiding current planting management and obtaining standard planting information.

[0075] The deviation calculation submodule compares the current water and fertilizer data with the standard planting moisture and fertility values ​​based on the standard planting information, calculates and analyzes the deviation values ​​of soil moisture and fertility, and obtains the demand deviation analysis results. The specific process is as follows:

[0076] The Deviation Calculation submodule compares current water and fertilizer data with standard planting moisture and fertility values ​​based on standard planting information. By applying the formula "Deviation = Current Value - Standard Value," it calculates the deviation in soil moisture and fertility, helping to determine the current state of the soil and providing a basis for adjusting management measures, ultimately generating demand deviation analysis results.

[0077] The demand assessment submodule calculates the irrigation and fertilization requirements of forestry seedlings based on the demand deviation analysis results and the size of the deviation value using a nonlinear regression algorithm. The specific process for obtaining the irrigation and fertilization demand data is as follows:

[0078] The demand assessment submodule is based on the demand deviation analysis results. According to the size of the deviation value, it uses a nonlinear regression algorithm to calculate the necessary irrigation and fertilization amounts, ensuring the accuracy of irrigation and fertilization to adapt to current soil conditions, obtain irrigation and fertilization demand data, and fine-tune the supply of water and fertilizer to support the healthy growth of forestry seedlings in the best way.

[0079] Nonlinear regression algorithm, according to the formula:

[0080] ;

[0081] Calculate the fertigation demand data, where: is the predicted fertigation demand data, is the intercept, representing the basic irrigation and fertilization requirements, is the slope, indicating the deviation value Direct impact on fertigation requirements, It is the input deviation value, usually the difference between the actual soil water and fertilizer conditions and the preset standard. is the coefficient of the square of the deviation value, which is used to adjust the nonlinear effect and enhance the sensitivity of the model. is the temperature regulation coefficient, which is related to the temperature Combined effect, reflecting the impact of temperature changes on irrigation needs, is the actual measured soil temperature, is the soil saturation The influence coefficient of soil moisture is increased by the weight of soil moisture state. is the soil saturation.

[0082] The specific execution process of the formula is as follows:

[0083] Collect input deviation values , soil temperature and soil saturation ,use Calculate the base effect of the deviation and add To take into account the nonlinear effect of the deviation value, Introducing the regulatory effects of temperature and soil saturation to obtain irrigation and fertilization demand data , and the coefficient , and Optimize through historical data regression analysis to improve forecast accuracy.

[0084] See also Figure 2 and Figure 5 ,The water and fertilizer adjustment module includes a weather data integration submodule, a weather impact assessment submodule, and a ,strategy generation submodule;

[0085] The weather data integration submodule collects weather forecast information for future periods from multiple meteorological data sources based on irrigation and fertilization demand data, including rainfall probability, rainfall amount, and temperature. It also obtains current soil temperature information through temperature sensors, integrates the data, and obtains weather condition data in the following process:

[0086] The weather data integration submodule, based on irrigation and fertilization demand data, collects weather forecast information for future periods from multiple meteorological data sources, covering rainfall probability, rainfall amount, and temperature. It also uses soil-installed temperature sensors to obtain real-time soil temperature information. All collected data is aggregated and analyzed using the formula "Integrated data = (rainfall + temperature + soil temperature) / number of data sources" to ensure comprehensive and accurate weather data for subsequent processing and finalization.

[0087] The weather impact assessment submodule evaluates the impact of rainfall on soil moisture and the impact of temperature changes on fertilizer absorption rate based on weather condition data. The specific process for obtaining the weather impact assessment results is as follows:

[0088] The Weather Impact Assessment submodule uses integrated weather data to analyze how upcoming rainfall and temperature changes will affect soil moisture and fertilizer absorption. This analysis uses the formula "Moisture Adjustment = Rainfall × Soil Water Absorption Coefficient." It also analyzes the impact of temperature on fertilizer absorption using the formula "Fertilizer Absorption Rate = Base Absorption Rate + Temperature Adjustment Coefficient × (Current Temperature - Average Temperature)." This assessment helps farm managers understand how weather affects crop growth requirements and provide a weather impact assessment.

[0089] The strategy generation submodule uses a genetic algorithm based on the weather impact assessment results and irrigation and fertilization demand data to calculate the required irrigation and fertilization amounts under differentiated weather conditions and formulate matching irrigation and fertilization strategies, including the amount and concentration of irrigation and fertilization. The specific process of obtaining optimized irrigation and fertilization information is as follows:

[0090] The strategy generation submodule is based on the weather impact assessment results and irrigation and fertilization demand data. By deeply analyzing the differences between weather forecasts and crop needs, and using genetic algorithms, it calculates the irrigation and fertilization amounts under specific weather conditions, thereby formulating irrigation and fertilization strategies that are both water-saving and efficient, and obtaining irrigation and fertilization amount information optimized for specific weather conditions, which can ensure that crops receive the best growth support under different weather conditions.

[0091] Genetic algorithm, according to the formula:

[0092] ;

[0093] Calculate the optimized irrigation and fertilization strategy, where For the optimized irrigation and fertilization strategy, For the current strategy, and Candidate strategies generated for differentiated gas conditions, is the cross factor, is the current environment status, is the historical average environmental state, is the environmental impact factor, It is an adjustment factor used to balance the impact of environmental changes on the strategy.

[0094] The specific execution process of the formula is as follows:

[0095] First, select two parent individuals and , based on different weather forecast models, calculate the current strategy The difference from the parent strategy is determined by the crossover factor Determine the impact strength of the difference and introduce environmental status and historical average state To assess the deviation of the current environment from the normal state, through the environmental impact factors Calculate the intensity of environmental deviation and adjust the factor Used to adjust the influence of environmental changes on the final strategy to ensure that the strategy reflects actual needs. The final strategy is calculated through the above steps. , ensuring that irrigation and fertilization strategies are adapted to actual environmental conditions.

[0096] See also Figure 2 and Figure 6 ,The time period optimization module includes the growth stage analysis submodule, the time window calculation submodule, and the time scheduling submodule;

[0097] The growth stage analysis submodule is based on optimized irrigation and fertilization information and historical planting records of forestry seedlings. It analyzes the differentiated growth stage characteristics of forestry seedlings, identifies the water and nutrient absorption period of each stage, and obtains the growth stage characteristic analysis results. The specific process is as follows:

[0098] The growth stage analysis submodule uses information on optimized irrigation and fertilization rates and historical forestry planting records to conduct a detailed analysis of seedlings at different growth stages. The formula "absorption efficiency = (cumulative absorption / total demand) × 100%) calculates the water and nutrient absorption efficiency for each growth stage. This analysis helps identify changes in the water and nutrient requirements of seedlings at different stages of their growth cycle, clarifying the characteristics of each stage and generating growth stage characteristic analysis results.

[0099] The time window calculation submodule calculates the target irrigation and fertilization time windows based on the growth stage characteristic analysis results, combined with the weather conditions, soil temperature and growth cycle of forestry seedlings in the future period, optimizes the irrigation and fertilization efficiency, and obtains the optimized time window selection result. The specific process is as follows;

[0100] The time window calculation submodule calculates the time window for irrigation and fertilization based on the analysis of growth stage characteristics, combined with upcoming weather conditions and soil temperature data. Using the formula "time window = (weather forecast period - minimum demand response time) / adjustment factor," this module optimizes irrigation and fertilization timing, taking into account the uncertainty of weather changes and the crop's response to immediate environmental changes. This ensures that crops receive adequate water and nutrients when they need them most, ultimately selecting the optimal time window.

[0101] The time scheduling submodule formulates matching irrigation and fertilization times based on the results of the optimized time window selection, adjusts and arranges the corresponding operation schedule, matches the environmental conditions of the future period with the growth needs of the seedlings, and obtains the optimized irrigation and fertilization time information in the following process:

[0102] The time scheduling submodule develops specific irrigation and fertilization plans based on the optimized time window selection results. Using the formula "scheduling time = current date + (growth cycle / number of stages)," the appropriate irrigation and fertilization schedule is matched to each growth stage. This strategy not only considers future environmental conditions but also adjusts to the specific growth needs of the seedlings, ensuring that irrigation and fertilization activities are optimally matched to the seedling's growth stage and environmental conditions. This optimizes irrigation and fertilization timing information, improves the timeliness and accuracy of irrigation and fertilization, and contributes to overall agricultural production efficiency.

[0103] See also Figure 2 and Figure 7 ,The execution control module includes a solenoid valve operation submodule, a quantified monitoring submodule, and an execution record submodule;

[0104] The solenoid valve operation submodule irrigates and fertilizes forestry seedlings based on the optimized irrigation and fertilization amount information and the optimized irrigation and fertilization time information by controlling the solenoid valves of the fertilizer liquid tank and the irrigation water tank. The specific process of obtaining the solenoid valve operation information is as follows:

[0105] The solenoid valve operation submodule accurately controls the solenoid valves of the fertilizer liquid tank and irrigation water tank based on the optimized irrigation and fertilization amount information and the optimized irrigation and fertilization time information. It uses the formula "opening time = (demand / flow rate)" to calculate the specific opening time of each solenoid valve according to the set fertilization and irrigation demand and the maximum flow rate of the system, ensuring that each operation can accurately provide sufficient water and nutrients to the forestry seedlings according to the predetermined needs, thereby obtaining the solenoid valve operation information.

[0106] The quantitative monitoring submodule monitors the irrigation and fertilization process in real time based on the solenoid valve operation information. It records the flow rate and application amount of water and fertilizer through flow meters and pressure sensors, analyzes the consistency of data with target parameters, and obtains quantitative execution feedback information. The specific process is as follows:

[0107] The quantitative monitoring submodule monitors the irrigation and fertilization process in real time based on solenoid valve operation information. Flow meters and pressure sensors continuously record the flow rate and amount of water and fertilizer applied. The module then compares actual operating data with predetermined target parameters using the formula "actual amount applied = flow rate x operation duration." This real-time monitoring and data analysis ensures operational accuracy and efficiency, while enabling immediate adjustment of operating parameters to accommodate any deviations, providing quantitative feedback on performance.

[0108] The execution record submodule records and archives each irrigation and fertilization operation process based on the quantitative execution feedback information, including the operation time, duration and actual amount, and stores the information to obtain the specific process of irrigation and fertilization implementation information:

[0109] The execution record submodule, based on quantified execution feedback, records the details of each irrigation and fertilization operation, including operation time, duration, and actual application rate. The efficiency and accuracy of each operation are assessed using the formula "Recording Efficiency = (Actual Application Rate / Planned Application Rate) × 100%." ​​All operation data is systematically stored and archived for easy future query and analysis, resulting in detailed information on irrigation and fertilization implementation. These records not only serve as a reference for future operations but also provide real-time data support and historical data review capabilities for management, ensuring transparency and traceability in agricultural management.

[0110] See also Figure 2 and Figure 8 ,The resource monitoring module includes a liquid level monitoring submodule, a stock assessment submodule, and a resource replenishment alarm submodule;

[0111] The liquid level monitoring submodule monitors the liquid level of the fertilizer tank and the irrigation water tank through the liquid level sensor based on the irrigation and fertilization implementation information, and obtains the real-time liquid level monitoring data in the following process:

[0112] The liquid level monitoring submodule uses level sensors to precisely monitor the liquid levels in fertilizer and irrigation tanks based on irrigation and fertilization information. By reading the liquid level in real time and converting it into volume using the formula "current liquid level = maximum capacity × (current height / total container height)," accurate real-time liquid level monitoring data is generated. This process ensures continuous monitoring of liquid resources in the irrigation and fertilization systems, providing foundational data for subsequent resource management.

[0113] The stock assessment submodule evaluates the current remaining amount of fertilizer liquid and irrigation water based on real-time liquid level monitoring data, analyzes the resource depletion time based on the current consumption rate, and obtains the remaining resource assessment results in the following process:

[0114] The inventory assessment submodule estimates the current remaining amount of fertilizer and irrigation water based on real-time liquid level monitoring data. Combined with historical consumption rate data, the formula "estimated depletion time = current amount / average daily consumption" is applied to calculate the time until resources are depleted without replenishment. This assessment helps determine the resource's sustainable use cycle and adjust resource management strategies to produce a remaining resource assessment result.

[0115] The resource replenishment alarm submodule notifies the management personnel to replenish fertilizer liquid and irrigation water based on the remaining resource assessment results when the remaining amount of fertilizer liquid and irrigation water falls below the preset threshold. The specific process of obtaining fertilizer liquid and irrigation water storage control information is as follows:

[0116] The resource replenishment alarm submodule monitors the remaining levels of fertilizer and irrigation water in real time based on remaining resource assessment results. If the level of either resource falls below a preset safety threshold, an alarm automatically sounds, notifying management to promptly replenish it. This alarm uses the formula "trigger alarm = remaining level < threshold." This mechanism ensures that irrigation and fertilization operations are not interrupted due to resource depletion, thereby ensuring the continued healthy growth of forestry seedlings. Management personnel can respond promptly, maintaining efficient system operation and obtaining control information on fertilizer and irrigation water reserves.

[0117] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. Intelligent irrigation system for standardized production of forestry seedlings, characterized by: The system comprises: The soil water and fertilizer status monitoring module is based on the forestry seedling planting environment, collects the current soil moisture and fertility status data, and obtains real-time water and fertilizer data information; The water and fertilizer demand analysis module analyzes the deviation between the real-time water and fertilizer data and the preset standard based on the real-time water and fertilizer data information, and uses a nonlinear regression algorithm to calculate the irrigation and fertilization amounts required for forestry seedlings to obtain irrigation and fertilization demand data; The water and fertilizer amount adjustment module adjusts the irrigation and fertilization amounts based on the irrigation and fertilization demand data, combined with the weather conditions in the future period and the current soil temperature, to obtain optimized irrigation and fertilization amount information; The water and fertilizer amount adjustment module includes: The weather data integration submodule collects weather forecast information for future periods from multiple meteorological data sources based on the irrigation and fertilization demand data, including rainfall probability, rainfall amount, and temperature, and obtains the current soil temperature through a temperature sensor, integrates the data, and obtains weather condition data; The weather impact assessment submodule assesses the impact of rainfall on soil moisture and the impact of temperature changes on fertilizer absorption rate based on the weather condition data to obtain a weather impact assessment result; The strategy generation submodule calculates the required irrigation and fertilization amounts under differentiated weather conditions based on the weather impact assessment results and the irrigation and fertilization demand data using a genetic algorithm to obtain optimized irrigation and fertilization amount information; The time period optimization module calculates the target irrigation and fertilization time period based on the optimized irrigation and fertilization amount information, combined with the weather conditions in the future period and the growth stage of the forestry seedlings, and obtains the optimized irrigation and fertilization time information; The time period optimization module includes: The growth stage analysis submodule analyzes the differentiated growth stage characteristics of forestry seedlings based on the optimized irrigation and fertilization information and the historical planting records of forestry seedlings, identifies the water and nutrient absorption period of each stage, and obtains the growth stage characteristic analysis results; The time window calculation submodule calculates the target irrigation and fertilization time periods based on the growth stage characteristic analysis results, combined with the weather conditions in the future period and the growth stage of the forestry seedlings, optimizes the irrigation and fertilization efficiency, and obtains the optimized time window selection result; The time scheduling submodule formulates matching irrigation and fertilization times based on the optimized time window selection result, adjusts and arranges corresponding operation schedules, and obtains optimized irrigation and fertilization time information; The execution control module performs irrigation and fertilization operations on the forestry seedlings based on the optimized irrigation and fertilization amount information and the optimized irrigation and fertilization time information to obtain irrigation and fertilization implementation information.

2. The intelligent irrigation system for standardized production of forestry seedlings according to claim 1 is characterized in that: The soil water and fertilizer status monitoring module includes: The sensor calibration submodule calibrates the soil fertility sensor and soil moisture sensor based on the forestry seedling planting environment, compares the sensor output with known standard samples, adjusts the sensor parameters, optimizes the sensor error, and obtains the sensor accuracy adjustment result; The environmental data acquisition submodule collects the current moisture and fertility status data of the soil in the forestry seedling planting area by periodically reading the sensor data based on the sensor accuracy adjustment result, and screens the data to eliminate abnormal data to generate real-time soil condition information; The data recording submodule formats the data based on the real-time soil condition information, and performs time stamping, location classification and parameter indexing on the data, thereby optimizing the traceability and accessibility of the data and obtaining real-time water and fertilizer data information.

3. The intelligent irrigation system for standardized production of forestry seedlings according to claim 1 is characterized in that: The water and fertilizer demand analysis module includes: The standard value acquisition submodule obtains the standard planting moisture and fertility values ​​of the current forestry seedlings according to the type of the current forestry seedlings, combined with the generation stage of the forestry seedlings, and through the forestry seedling planting history records, and obtains the standard planting information; The deviation calculation submodule compares the current moisture and fertility status data with the standard planting moisture and fertility values ​​based on the standard planting information, calculates and analyzes the deviation values ​​of soil moisture and fertility, and obtains the demand deviation analysis results; The demand assessment submodule calculates the irrigation and fertilization amounts required for forestry seedlings based on the demand deviation analysis results and the size of the deviation value using a nonlinear regression algorithm to obtain irrigation and fertilization demand data.

4. The intelligent irrigation system for standardized production of forestry seedlings according to claim 3 is characterized in that: The nonlinear regression algorithm is based on the formula: ； Calculate the amount of irrigation and fertilizer required for forestry seedlings respectively, among which, It is the amount of irrigation or fertilizer required for forestry seedlings. is the intercept, is the slope, is the coefficient of the square of the deviation, is the temperature regulation coefficient, is the current soil temperature, is the influence coefficient of soil saturation, is the soil saturation, It is the deviation value of soil moisture or fertility.

5. The intelligent irrigation system for standardized production of forestry seedlings according to claim 1 is characterized in that: The execution control module includes: The solenoid valve operation submodule performs irrigation and fertilization operations on forestry seedlings by controlling the solenoid valve of the fertilizer liquid tank and the solenoid valve of the irrigation water tank based on the optimized irrigation and fertilization amount information and the optimized irrigation and fertilization time information, thereby obtaining solenoid valve operation information; The quantitative monitoring submodule monitors the irrigation and fertilization process in real time based on the solenoid valve operation information, records the flow rate and application amount of water and fertilizer through flow meters and pressure sensors, analyzes the consistency of data with target parameters, and obtains quantitative execution feedback information; The execution record submodule records and archives each irrigation and fertilization operation process based on the quantitative execution feedback information, including operation time, duration and actual amount, stores the information, and obtains irrigation and fertilization implementation information.

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