CN119273106A - Intelligent irrigation system for standardized production of forestry seedlings - Google Patents
Intelligent irrigation system for standardized production of forestry seedlings Download PDFInfo
- Publication number
- CN119273106A CN119273106A CN202411796543.9A CN202411796543A CN119273106A CN 119273106 A CN119273106 A CN 119273106A CN 202411796543 A CN202411796543 A CN 202411796543A CN 119273106 A CN119273106 A CN 119273106A
- Authority
- CN
- China
- Prior art keywords
- irrigation
- fertilization
- fertilizer
- data
- water
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01C—PLANTING; SOWING; FERTILISING
- A01C23/00—Distributing devices specially adapted for liquid manure or other fertilising liquid, including ammonia, e.g. transport tanks or sprinkling wagons
- A01C23/007—Metering or regulating systems
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/12—Computing arrangements based on biological models using genetic models
- G06N3/126—Evolutionary algorithms, e.g. genetic algorithms or genetic programming
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Life Sciences & Earth Sciences (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Data Mining & Analysis (AREA)
- Economics (AREA)
- Mathematical Physics (AREA)
- Evolutionary Biology (AREA)
- Strategic Management (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Bioinformatics & Computational Biology (AREA)
- Biophysics (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- General Health & Medical Sciences (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- General Engineering & Computer Science (AREA)
- Tourism & Hospitality (AREA)
- Water Supply & Treatment (AREA)
- Software Systems (AREA)
- Pure & Applied Mathematics (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Artificial Intelligence (AREA)
- Genetics & Genomics (AREA)
- Evolutionary Computation (AREA)
- Algebra (AREA)
- Databases & Information Systems (AREA)
- Environmental Sciences (AREA)
- Soil Sciences (AREA)
- Public Health (AREA)
- Biomedical Technology (AREA)
- Physiology (AREA)
- Primary Health Care (AREA)
Abstract
本发明涉及自动控制技术领域，具体为林业苗木标准化生产的智能灌溉系统，系统包括土壤水肥状态监测模块、水肥需求分析模块、水肥量调整模块、时段优化模块、执行控制模块和资源监控模块。本发明中，通过实时监测土壤水分和肥力状态，能够精准掌握苗木生长所需的水肥条，并与预设标准对比，可以精确评估灌溉和施肥需求，减少了资源浪费，提升了水肥使用的效率，通过考虑未来天气状况及土壤温度，调整水肥投放量，减少了因天气变化带来的不确定影响，并识别最佳的施肥和灌溉时段，提高了灌溉和施肥的时效性和有效性，通过实时监控资源使用状态，并及时反馈低存量信息，保证了灌溉施肥的连续运行，避免了因资源短缺导致的灌溉施肥中断。
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 required for seedling growth can be accurately grasped, and compared with preset standards, the irrigation and fertilization requirements can be accurately evaluated, resource waste is reduced, and the efficiency of water and fertilizer use is improved. By considering future weather conditions and soil temperature, the water and fertilizer input amount is adjusted, the uncertain effects caused by weather changes are reduced, and the best fertilization and irrigation time period is identified, the timeliness and effectiveness of irrigation and fertilization are improved, and the continuous operation of irrigation and fertilization is guaranteed by real-time monitoring of resource use status and timely feedback of low inventory information, avoiding the interruption of irrigation and fertilization due to resource shortage.
Description
Technical Field
The invention relates to the technical field of automatic control, in particular to an intelligent irrigation system for standardized production of forestry seedlings.
Background
The field of automatic control technology aims at monitoring and adjusting the operating state of a device or system by using a computer program or other automation mechanism, so that predetermined management and control targets can be achieved without direct manual intervention. The technical field of automatic control is widely applied to various scenes such as industrial production, environment management, traffic systems, household equipment, precision agriculture and the like. In the automatic control system, key technologies comprise a sensor technology, a data acquisition system, a real-time feedback mechanism, a control algorithm design and an executing mechanism, wherein the automatic control system can automatically detect environmental changes, process data in real time, and adjust operation parameters according to a preset program so as to achieve an automatic control effect.
The intelligent irrigation system for standardized production of the forestry seedlings is an automatic irrigation solution designed for cultivation and production of the forestry seedlings. The system is mainly used for ensuring that the seedlings are uniformly and properly supplied with water through intelligent management of irrigation process, thereby improving the growth quality and production efficiency of the seedlings. And the irrigation time and the water quantity are accurately regulated and controlled by integrating an environment monitoring sensor and an automatic control algorithm. Not only is beneficial to saving water and reducing labor cost, but also can optimize the distribution of water resources according to the actual demands of seedling growth, and supports sustainable forestry development.
The traditional irrigation system lacks quick response and accurate adjustment capability to real-time change, and the traditional system can not effectively integrate and utilize real-time environment data, so that water and fertilizer are unevenly utilized, the balance and quality of seedling growth are affected, the traditional system can not synthesize future weather prediction and soil real-time state, so that resource allocation can not be optimized, the condition of excessive or insufficient resources can occur, the production cost and the resource waste are increased, an effective resource monitoring and early warning mechanism is lacked, emergency situations of emergency supplement due to insufficient resources can occur in the irrigation process, and the continuity and efficiency of irrigation are affected.
Disclosure of Invention
The invention aims to solve the defects in the prior art, and provides an intelligent irrigation system for standardized production of forestry seedlings.
In order to achieve the purpose, the intelligent irrigation system adopts the following technical scheme that the intelligent irrigation system for standardized production of forestry seedlings comprises:
The soil water and fertilizer state monitoring module collects current water and fertilizer state data of soil based on forestry seedling planting environments to obtain real-time water and fertilizer data information;
The water and fertilizer demand analysis module is used for analyzing the deviation of the real-time water and fertilizer data and a preset standard based on the real-time water and fertilizer data information, evaluating the irrigation and fertilizer demand of forestry seedlings and obtaining irrigation and fertilizer demand data;
The water and fertilizer amount adjusting module is used for adjusting the irrigation and fertilizer amount based on the irrigation and fertilizer amount demand data and combining the weather state of the future period and the current soil temperature to obtain optimized irrigation and fertilizer amount information;
the time period optimizing module is used for identifying a target irrigation and fertilization time period based on the optimized irrigation and fertilization amount information and combining the weather state of a future time period, the growth stage of forestry seedlings and the fertilizer type to obtain optimized irrigation and fertilization time information;
The execution control module performs irrigation and fertilization operation 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;
The resource monitoring module monitors the residual quantity of the fertilizer liquid and the irrigation water based on the irrigation and fertilization implementation information, and notifies a manager to add the fertilizer liquid and the irrigation water when the residual quantity of the fertilizer liquid and the irrigation water is lower than a preset threshold value, so as to obtain the storage control information of the fertilizer liquid and the irrigation water.
As a further aspect of the present invention, the real-time water and fertilizer data information includes real-time humidity level and fertility status index of soil, the irrigation and fertilizer demand data includes target water amount, target fertilizer type and target fertilizer amount, the optimized irrigation and fertilizer amount information includes adjusted irrigation amount and fertilizer amount, the optimized irrigation and fertilizer time information includes irrigation start time, fertilizer start time and predicted irrigation and fertilizer duration, the irrigation and fertilizer implementation information includes irrigation execution time, fertilizer execution amount and execution error record, and the fertilizer liquid and irrigation liquid storage control information includes current fertilizer liquid storage, current irrigation liquid storage and next supplement early warning time.
As a further aspect of the present invention, the soil water and fertilizer status monitoring module includes:
The sensor calibration submodule calibrates the soil fertilizer sensor and the soil humidity sensor based on the forestry seedling planting environment, compares sensor output by using known standard samples, adjusts sensor parameters, optimizes sensor errors and obtains a sensor precision adjustment result;
The environmental data acquisition submodule periodically reads sensor data based on the sensor precision adjustment result, collects soil moisture and fertility data in a forestry seedling planting area, screens the data, eliminates abnormal data and generates real-time soil condition information;
And the data recording submodule carries out formatting treatment on the data based on the real-time soil condition information, carries out time marking, site classification and parameter indexing on the data, optimizes the traceability and accessibility of the data and obtains real-time water and fertilizer data information.
As a further aspect of the present invention, the water and fertilizer requirement analysis module includes:
The standard value obtaining submodule obtains standard planting moisture and fertility values of the current forestry seedlings through a forestry seedling planting history record according to the type of the current forestry seedlings and combining with a generation stage of the forestry seedlings based on the real-time water and fertilizer data information to obtain standard planting information;
The deviation calculating submodule compares the current water and fertilizer data with the standard planting water and fertilizer values based on the standard planting information, calculates and analyzes the deviation values of the soil humidity and the fertilizer to obtain a demand deviation analysis result;
and the demand evaluation submodule calculates the irrigation quantity and the fertilization quantity required by the forestry seedlings by utilizing a linear regression algorithm according to the deviation value based on the demand deviation analysis result, and obtains irrigation and fertilization demand data.
As a further aspect of the present invention, the linear regression algorithm is according to the formula:
;
Calculating data of the irrigation and fertilization demand quantity, wherein, Is predicted fertigation demand data,Is the intercept point of the beam,Is the slope of the slope,Is a coefficient of the square of the deviation value,Is a temperature adjustment coefficient, and the temperature adjustment coefficient,Is the actual measured temperature of the soil,Is the influence coefficient of the soil saturation,Is the saturation of the soil.
As a further aspect of the present invention, the water and fertilizer amount adjustment module includes:
The weather data integration submodule collects weather forecast information of a future period from a plurality of weather data sources based on the irrigation and fertilization demand data, wherein the weather forecast information comprises rainfall probability, rainfall and temperature, and acquires current soil temperature information through a temperature sensor to integrate data so as to obtain weather condition data;
The weather effect evaluation submodule evaluates the influence of rainfall on soil humidity and the influence of temperature change on the fertilizer absorption rate based on the weather condition data to obtain a weather effect evaluation result;
And the strategy generation submodule calculates the required irrigation and fertilization amount under the differentiated weather conditions by utilizing a genetic algorithm based on the weather effect evaluation result and the irrigation and fertilization demand amount data, and formulates a matched irrigation and fertilization strategy comprising the irrigation and fertilization amount and the fertilization concentration, so as to obtain optimized irrigation and fertilization amount information.
As a further aspect of the present invention, the genetic algorithm is as follows:
;
Calculating an optimized irrigation and fertilization strategy, wherein, In order to optimize the irrigation and fertilization strategy,As a current policy of the present application,AndCandidate strategies for differential gas condition generation,As a result of the crossover factor,In order to be the current state of the environment,For the historical average environmental state of the vehicle,As an environmental impact factor, a factor of the environmental impact,Is an adjustment factor.
As a further aspect of the present invention, the period optimization module includes:
the growth stage analysis submodule analyzes the characteristics of the different growth stages of the forestry seedlings according to the historical planting records of the forestry seedlings based on the optimized irrigation and fertilization amount information, and identifies the absorption period of moisture and nutrition of each stage to obtain a growth stage characteristic analysis result;
The time window calculation submodule calculates a target irrigation and fertilization time window based on the growth stage characteristic analysis result and in combination with the weather condition, the soil temperature and the growth period of forestry seedlings in a future period, optimizes irrigation and fertilization efficiency and obtains an optimized time window selection result;
and the time scheduling submodule establishes the matched irrigation and fertilization time based on the optimized time window selection result, adjusts and schedules a corresponding operation schedule, matches the environmental conditions of the future period and the growth requirements of the seedlings, and obtains optimized irrigation and fertilization time information.
As a further aspect of the present invention, the execution control module includes:
The electromagnetic valve operation submodule performs irrigation and fertilization operation on forestry seedlings by controlling an electromagnetic valve of the fertilizer liquid tank and an electromagnetic valve of the irrigation water tank based on the optimized irrigation and fertilization amount information and the optimized irrigation and fertilization time information to obtain electromagnetic valve operation information;
The quantitative monitoring submodule monitors irrigation and fertilization processes in real time based on the electromagnetic valve operation information, records the flow rate and the application amount of water and fertilizer through a flowmeter and a pressure sensor, analyzes the consistency of data and target parameters, and obtains quantitative execution feedback information;
and the execution recording submodule records and files the operation process of each irrigation and fertilization based on the quantitative execution feedback information, wherein the operation process comprises operation time, duration and actual consumption, and stores the information to obtain irrigation and fertilization implementation information.
As a further aspect of the present invention, the resource monitoring module includes:
the liquid level monitoring submodule monitors the liquid level heights of the fertilizer liquid tank and the irrigation water tank through a liquid level sensor based on the irrigation and fertilization implementation information to obtain real-time liquid level monitoring data;
The stock evaluation submodule evaluates the residual quantity of the current fertilizer liquid and irrigation water based on the real-time liquid level monitoring data, analyzes the resource exhaustion time based on the current exhaustion rate, and obtains a residual resource evaluation result;
and the resource replenishment alarm submodule informs a manager to replenish the fertilizer liquid and the irrigation water to obtain the fertilizer liquid and irrigation water reserve control information when the residual quantity of the fertilizer liquid and the irrigation water is lower than a preset threshold value based on the residual resource evaluation result.
Compared with the prior art, the invention has the advantages and positive effects that:
According to the invention, the water and fertilizer strips required by the growth of seedlings can be accurately mastered by monitoring the soil moisture and fertility state in real time, compared with the preset standard, the irrigation and fertilizer application requirements can be accurately evaluated, the resource waste is reduced, the water and fertilizer application efficiency is improved, the water and fertilizer application amount is adjusted by considering the future weather condition and the soil temperature, the resource allocation is optimized, the uncertain influence caused by weather change is reduced, the optimal fertilizer application and the optimal fertilizer application period are identified, the timeliness and the effectiveness of irrigation and fertilizer application are improved, the low-stock information is timely fed back by monitoring the resource use state, the continuous operation of irrigation and fertilizer application is ensured, and the interruption of irrigation and fertilizer application caused by resource shortage is avoided.
Drawings
FIG. 1 is a system flow diagram of the present invention;
FIG. 2 is a schematic diagram of a system framework of the present invention;
FIG. 3 is a flow chart of the soil water and fertilizer status monitoring module of the present invention;
FIG. 4 is a flow chart of the water and fertilizer demand analysis module of the present invention;
FIG. 5 is a flow chart of the water and fertilizer amount adjustment module of the present invention;
FIG. 6 is a flow chart of the period optimization module of the present invention;
FIG. 7 is a flow chart of an execution control module of the present invention;
FIG. 8 is a flow chart of a resource monitoring module of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
In the description of the present invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate orientations or positional relationships based on the orientation or positional relationships shown in the drawings, merely to facilitate describing the present invention and simplify the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present invention. Furthermore, in the description of the present invention, the meaning of "a plurality" is two or more, unless explicitly defined otherwise.
Example 1
Referring to fig. 1, an intelligent irrigation system for standardized production of forestry seedlings, the system comprising:
The soil water and fertilizer state monitoring module monitors seedling growth data through a soil fertilizer sensor and a soil humidity sensor based on forestry seedling planting environments, and collects current soil moisture and fertility state data to obtain real-time water and fertilizer data information;
The water and fertilizer demand analysis module is used for comparing the water and fertilizer demand analysis module with the water and fertilizer values of the planting of the preset standard forestry seedlings based on the real-time water and fertilizer data information, analyzing the deviation of the real-time water and fertilizer data and the preset standard, evaluating the irrigation and fertilizer demand of the forestry seedlings, and obtaining irrigation and fertilizer demand data;
The water and fertilizer amount adjusting module is used for adjusting the irrigation and fertilizer amount based on the irrigation and fertilizer amount demand data and combining the weather state of the future period with the current soil temperature, wherein the weather state comprises rainfall probability, rainfall amount and temperature change, so as to obtain optimized irrigation and fertilizer amount information;
The time period optimizing module is used for identifying a target irrigation and fertilization time period based on optimized irrigation and fertilization amount information and combining the weather state of a future time period, the growth stage of forestry seedlings and the fertilizer type, and optimizing the timeliness and effectiveness of irrigation and fertilization to obtain optimized irrigation and fertilization time information;
The execution control module performs irrigation and fertilization operation on forestry seedlings by controlling an electromagnetic valve of a fertilizer liquid tank and an electromagnetic valve of an irrigation water tank based on the optimized irrigation and fertilization amount information and the optimized irrigation and fertilization time information, and records the irrigation and fertilization process to obtain irrigation and fertilization implementation information;
The resource monitoring module monitors the water level height of the fertilizer liquid tank and the irrigation water tank in real time through the liquid level sensor based on the irrigation and fertilization implementation information, monitors the residual quantity of the fertilizer liquid and the irrigation water, and informs a manager to add the fertilizer liquid and the irrigation water when the residual quantity of the fertilizer liquid and the irrigation water is lower than a preset threshold value, so as to obtain the storage control information of the fertilizer liquid and the irrigation water;
The real-time water and fertilizer data information comprises real-time humidity level and fertility state indexes of soil, the irrigation and fertilizer demand data comprises target water quantity, target fertilizer type and target fertilizer quantity, the optimized irrigation and fertilizer quantity information comprises adjusted irrigation quantity and fertilizer quantity, the optimized irrigation and fertilizer time information comprises irrigation starting time, fertilizer starting time and predicted irrigation and fertilizer duration, the irrigation and fertilizer implementation information comprises irrigation execution time, fertilizer execution quantity and execution error record, and the fertilizer liquid and irrigation water storage quantity control information comprises current fertilizer liquid storage quantity, current irrigation water storage quantity and next supplement early warning time.
Referring to fig. 2 and 3, the soil water and fertilizer state monitoring module includes a sensor calibration sub-module, an environmental data acquisition sub-module, and a data recording sub-module;
the sensor calibration submodule calibrates a soil fertilizer sensor and a soil humidity sensor based on a forestry seedling planting environment, compares sensor output by using a known standard sample, adjusts sensor parameters, optimizes sensor errors and obtains a sensor precision adjustment result, wherein the process specifically comprises the following steps of;
The sensor calibration submodule calibrates the soil fertilizer sensor and the soil humidity sensor based on forestry seedling planting environments, and uses standard soil samples, wherein the samples have known fertility values and humidity values, and provide calibration references for the sensors. By measuring the difference between the sensor output and the standard sample, the parameter adjustment is performed by adopting the formula of ' output after adjustment=original output+error adjustment factor x (standard sample value-original output) ', according to the error adjustment factor ', so that the output of the sensor can accurately reflect the actual soil condition, the sensor error is optimized, and the sensor precision adjustment result is obtained.
The environment data acquisition sub-module is used for periodically reading sensor data based on a sensor precision adjustment result, collecting soil moisture and fertility data in a forestry seedling planting area, screening the data, and removing abnormal data, wherein the process for generating real-time soil condition information specifically comprises the following steps of;
the environmental data acquisition sub-module collects soil moisture and fertility data in the forestry seedling planting area by periodically reading sensor data based on the sensor accuracy adjustment result. In the data acquisition process, a data quality control formula of "effective data= (current data point-minimum threshold)/(maximum threshold-minimum threshold)" is set to screen data meeting quality standards. Abnormal data such as data points exceeding the preset fertility and humidity range can be effectively removed from all the read data, and real-time soil condition information is generated.
The data recording submodule carries out formatting treatment on the data based on the real-time soil condition information, carries out time marking, site classification and parameter indexing on the data, optimizes the traceability and accessibility of the data, and obtains the flow of the real-time water and fertilizer data information specifically as follows;
The data recording submodule carries out formatting treatment on the data based on the real-time soil condition information, and carries out time marking, place classification and parameter indexing on the data, and the formula of recorded data = total data quantity/data category quantity is adopted to optimize the organization structure of the data, so that the traceability and accessibility of the data are enhanced, each type of data can be accurately filed and quickly searched, and the real-time water and fertilizer data information is obtained.
Referring to fig. 2 and fig. 4, the water and fertilizer requirement analysis module includes a standard value acquisition sub-module, a deviation calculation sub-module, and a requirement evaluation sub-module;
The standard value obtaining submodule obtains standard planting moisture and fertility values of the current forestry seedlings by combining the generation stage of the forestry seedlings according to the type of the current forestry seedlings and the forestry seedling planting history record based on the real-time water and fertilizer data information, and the process of obtaining the standard planting information is specifically as follows;
The standard value obtaining submodule obtains standard planting water and fertility values suitable for the current stage according to the type of the current forestry nursery stock and the growth stage thereof and combining with the historical planting records, obtains the standard value of each stage by analyzing the average water and fertility requirements of each growth stage in the historical data set and calculating the formula of standard value = sum/sample number, so as to guide the current planting management and obtain standard planting information.
The deviation calculation sub-module is used for comparing the current water and fertilizer data with the standard planting water and fertilizer values based on the standard planting information, calculating and analyzing the deviation values of soil humidity and fertilizer, and obtaining a flow of a demand deviation analysis result specifically comprises the following steps of;
The deviation calculation sub-module compares the current water and fertilizer data with the standard planting moisture and fertility values based on the standard planting information. By applying the formula of 'deviation value=current value-standard value', the deviation of soil humidity and fertility is calculated, the current state of soil is helped to be determined, a basis is provided for adjusting management measures, and a demand deviation analysis result is obtained.
The demand assessment submodule calculates irrigation and fertilization amount required by forestry seedlings by utilizing a linear regression algorithm based on a demand deviation analysis result according to the magnitude of the deviation value, and the flow for obtaining irrigation and fertilization demand data is specifically as follows;
The demand evaluation submodule calculates necessary irrigation and fertilization amount by utilizing a linear regression algorithm based on a demand deviation analysis result and according to the magnitude of the deviation value, ensures the accuracy of irrigation and fertilization, adapts to the current soil condition, obtains irrigation and fertilization demand data, finely regulates and controls the supply of moisture and fertilizer, and supports healthy growth of forestry seedlings in an optimal mode.
Linear regression algorithm, according to the formula:
;
Calculating data of the irrigation and fertilization demand quantity, wherein, Is predicted fertigation demand data,Is the intercept, which represents the irrigation and fertilization requirements of the foundation,Is a slope, representing the deviation valueThe direct impact on fertigation requirements,Is an input deviation value, usually the difference between the actual soil water and fertilizer conditions and a preset standard,Is a coefficient of the square of the deviation value, is used for adjusting nonlinear effects, enhancing the sensitivity of the model,Is the temperature regulation coefficient and the temperatureThe combined action reflects the influence of temperature change on irrigation demand,Is the actual measured temperature of the soil,Is the saturation of soilIncreases the weight of the soil moisture state,Is the saturation of the soil.
The specific implementation process of the formula is as follows:
Collecting input offset values Soil temperatureSaturation of soilUsingCalculate the basic influence of the deviation and addTo take into account the nonlinear effect of the deviation value byIntroducing the regulation effect of temperature and soil saturation to obtain irrigation and fertilization demand dataCoefficient of,AndAnd optimizing through historical data regression analysis to improve the accuracy of prediction.
Referring to fig. 2 and 5, the water and fertilizer amount adjustment module includes a weather data integration sub-module, a weather influence evaluation sub-module, and a strategy generation sub-module;
The weather data integration sub-module collects weather forecast information of future time periods from a plurality of weather data sources based on irrigation and fertilization demand data, wherein the weather forecast information comprises rainfall probability, rainfall and temperature, current soil temperature information is obtained through a temperature sensor, and data integration is carried out to obtain the flow of weather condition data specifically as follows;
The weather data integration sub-module collects weather forecast information of a future period from a plurality of weather data sources based on irrigation and fertilization demand data, covers rainfall probability, rainfall and temperature, and acquires current soil temperature information in real time through a temperature sensor installed in soil. All the collected data are summarized and analyzed through the formula of 'integrated data= (rainfall + temperature + soil temperature)/number of data sources', so that comprehensive and accurate weather condition data are ensured to be provided for subsequent processing, and the weather condition data are obtained.
The weather effect evaluation submodule evaluates the influence of rainfall on soil humidity and the influence of temperature change on fertilizer absorption rate based on weather condition data, and the process for obtaining a weather effect evaluation result is specifically as follows;
the weather effect assessment submodule analyzes how upcoming rainfall and temperature changes affect soil humidity and fertilizer absorption based on the integrated weather condition data. The analysis was carried out using the formula "humidity adjustment=rainfall x soil water absorption coefficient", while analyzing the effect of temperature on fertilizer absorption, and the formula "fertilizer absorption rate=basal absorption rate+temperature adjustment coefficient x (current temperature-average temperature)". The assessment helps farm managers understand how weather affects the growth needs of crops, and weather effect assessment results are obtained.
The strategy generation submodule calculates the irrigation and fertilization amount required under the differential weather conditions by utilizing a genetic algorithm based on the weather effect evaluation result and the irrigation and fertilization demand data, and formulates a matched irrigation and fertilization strategy comprising the irrigation and fertilization amount and the fertilization concentration, and the flow for obtaining the optimized irrigation and fertilization amount information is specifically as follows;
The strategy generation sub-module calculates irrigation and fertilization quantities under specific weather conditions by deeply analyzing differences between weather forecast and crop demands based on weather effect evaluation results and irrigation and fertilization demand data and utilizing a genetic algorithm, so that a water-saving and efficient irrigation and fertilization strategy is formulated, irrigation and fertilization quantity information optimized for specific weather conditions is obtained, and optimal growth support of crops under different weather conditions can be ensured.
Genetic algorithm, according to the formula:
;
Calculating an optimized irrigation and fertilization strategy, wherein, In order to optimize the irrigation and fertilization strategy,As a current policy of the present application,AndCandidate strategies for differential gas condition generation,As a result of the crossover factor,In order to be the current state of the environment,For the historical average environmental state of the vehicle,As an environmental impact factor, a factor of the environmental impact,To adjust the factor, to balance the impact of environmental changes on the policy.
The specific implementation process of the formula is as follows:
first, two parent individuals are selected AndBased on different weather prediction model generation, calculating current strategyDifferences from parent policy by crossover factorsDetermining the strength of influence of the difference, introducing an environmental conditionAnd historical average statusTo evaluate the deviation of the current environment from normal by an environmental impact factorCalculating the intensity of environmental deviations, adjusting the factorThe method is used for adjusting the influence of environmental change on the final strategy, ensuring that the strategy reflects the actual requirement, and calculating the final strategy through the stepsEnsuring that the irrigation and fertilization strategies are adapted to the actual environmental conditions.
Referring to fig. 2 and 6, the period optimization module includes a growth stage analysis sub-module, a time window calculation sub-module, and a time scheduling sub-module;
the growth stage analysis submodule analyzes the characteristics of the different growth stages of the forestry seedlings according to the historical planting records of the forestry seedlings based on the optimized irrigation and fertilization amount information, and identifies the absorption period of moisture and nutrition of each stage, and the flow for obtaining the analysis result of the characteristics of the growth stages is specifically as follows;
The growth stage analysis submodule is used for carrying out detailed analysis on the seedlings in different growth stages by utilizing the historical planting records of the forestry seedlings based on the optimized irrigation and fertilization amount information. The moisture and nutrient absorption efficiency at each growth stage was calculated by the formula "absorption efficiency= (cumulative absorption/total demand) ×100%". The analysis helps to identify the change of the water and nutrition requirements of the seedlings in each stage of the growth period, so that the characteristics of each stage are defined, and the analysis result of the growth stage characteristics is obtained.
The time window calculation submodule calculates a target irrigation and fertilization time window based on a growth stage characteristic analysis result and by combining the weather condition, the soil temperature and the growth period of forestry seedlings in a future period, and optimizes irrigation and fertilization efficiency, and a flow for obtaining an optimized time window selection result is specifically as follows;
The time window calculation submodule is used for carrying out time window calculation of irrigation and fertilization according to the characteristic analysis result of the growth stage and the upcoming weather condition and soil temperature data. The formula of 'time window= (weather forecast period-minimum demand response time)/adjustment coefficient' is applied, uncertainty of weather change and response speed of crops to immediate environment change are considered, so that irrigation and fertilization time is optimized, sufficient moisture and nutrition of crops are ensured when the crops are most needed, and an optimized time window selection result is obtained.
The time scheduling submodule sets the matched irrigation and fertilization time based on the optimized time window selection result, adjusts and arranges a corresponding operation schedule, and matches the environmental conditions of the future period and the growth requirements of the seedlings to obtain the optimized irrigation and fertilization time information;
The time scheduling sub-module makes specific irrigation and fertilization plans based on the optimized time window selection result. The appropriate irrigation and fertilization times are matched for each growth phase by the formula "schedule time = current date + (growth cycle/phase number)". The strategy not only considers future environmental conditions, but also adjusts according to the specific growth requirements of the seedlings, so that the optimal matching of the irrigation and fertilization activities with the growth stages of the seedlings and the environmental conditions is ensured, the optimized irrigation and fertilization time information is obtained, the timeliness and the accuracy of the irrigation and fertilization are improved, and the overall agricultural production efficiency is improved.
Referring to fig. 2 and 7, the execution control module includes an electromagnetic valve operation sub-module, a quantization monitoring sub-module, and an execution recording sub-module;
the electromagnetic valve operation submodule performs irrigation and fertilization operation on forestry seedlings by controlling an electromagnetic valve of the fertilizer liquid tank and an electromagnetic valve of the irrigation water tank based on the optimized irrigation and fertilization amount information and the optimized irrigation and fertilization time information, and the flow for obtaining the electromagnetic valve operation information is specifically as follows;
The electromagnetic valve operation submodule accurately controls electromagnetic valves of the fertilizer liquid tank and the irrigation water tank based on the optimized irrigation and fertilization amount information and the optimized irrigation and fertilization time information, calculates specific time length of each electromagnetic valve to be opened according to the set fertilization and irrigation demand and the maximum flow rate of the system by using a formula of 'opening time= (demand/flow rate)', and ensures that each operation can accurately provide enough moisture and nutrition for forestry seedlings according to preset demands, thereby obtaining electromagnetic valve operation information.
The quantitative monitoring submodule monitors irrigation and fertilization processes in real time based on electromagnetic valve operation information, records flow velocity and application amount of water and fertilizer through a flowmeter and a pressure sensor, analyzes consistency of data and target parameters, and obtains a process of quantitatively executing feedback information specifically;
The quantitative monitoring submodule is used for monitoring the irrigation and fertilization process in real time based on the electromagnetic valve operation information, continuously recording the flow rates and the application amounts of water and fertilizer through the flowmeter and the pressure sensor, and comparing the consistency of the actual operation data with the preset target parameters by adopting the formula of 'actual application amount=flow rate x operation duration'. Such real-time monitoring and data analysis ensures accuracy and efficiency of operation while helping to adjust operating parameters in real-time to accommodate any deviations, thereby yielding quantitative performance feedback information.
The execution recording submodule records and files the operation process of each irrigation and fertilization based on the quantitative execution feedback information, wherein the operation process comprises operation time, duration time and actual consumption, the information is stored, and the flow for obtaining the irrigation and fertilization implementation information is specifically as follows;
The execution recording submodule records the specific conditions of each irrigation and fertilization operation based on the quantitative execution feedback information, including the operation time, the duration and the actual usage. The efficiency and accuracy of each operation were evaluated by the formula "recording efficiency= (actual usage/planned usage) ×100%". All operational data is systematically stored and archived for future queries and analysis to yield detailed irrigation and fertigation performance information. The records not only provide references for future operations, but also provide real-time data support and historical data review capabilities for management, ensuring transparency and traceability of agricultural management.
Referring to fig. 2 and 8, the resource monitoring module includes a liquid level monitoring sub-module, a stock assessment sub-module, and a resource replenishment alert sub-module;
The flow of the liquid level monitoring submodule for monitoring the liquid level heights of the fertilizer liquid tank and the irrigation water tank through the liquid level sensor based on irrigation and fertilization implementation information to obtain real-time liquid level monitoring data is specifically as follows;
The liquid level monitoring submodule accurately monitors the liquid level height of the fertilizer liquid tank and the irrigation water tank by using a liquid level sensor based on irrigation and fertilization implementation information. The accurate real-time liquid level monitoring data is obtained by reading the liquid level height in real time and converting the height data into corresponding volume information by adopting the formula of 'current liquid level=maximum capacity× (current height/total height of the container)', the process ensures continuous monitoring of liquid resources in the irrigation and fertilization system, and basic data is provided for subsequent resource management.
The stock evaluation submodule evaluates the residual quantity of the current fertilizer liquid and irrigation water based on the real-time liquid level monitoring data, and analyzes the resource exhaustion time based on the current consumption rate, and the flow for obtaining the residual resource evaluation result is specifically as follows;
The stock evaluation submodule evaluates the residual amounts of the current fertilizer liquid and the irrigation water based on the real-time liquid level monitoring data. In combination with the historical consumption rate data, a formula of 'predicted depletion time=current quantity/average daily consumption quantity' is applied, the time that resources are likely to be depleted without replenishment is calculated, the continuous use period of the resources is estimated to be helped to be determined, and a resource management strategy is adjusted to obtain a residual resource estimation result.
The resource replenishment alarm sub-module informs a manager to replenish the fertilizer liquid and the irrigation water when the residual quantity of the fertilizer liquid and the irrigation water is lower than a preset threshold value based on the residual resource evaluation result, and the flow of obtaining the storage control information of the fertilizer liquid and the irrigation water is specifically as follows;
The resource replenishment alert sub-module monitors the remaining amounts of the fertilizer liquid and the irrigation water in real time based on the remaining resource evaluation result. When any resource amount is detected to be lower than a preset safety threshold, an alarm is automatically sent out, and management personnel are notified to timely supplement. The alarm adopts a formula of triggering alarm=residual quantity < threshold value ", and the mechanism ensures that the irrigation and fertilization operation cannot be interrupted due to resource exhaustion, so that the continuous healthy growth of forestry seedlings is ensured, management staff can timely react, the efficient operation of the system is maintained, and the fertilizer liquid and irrigation water reserve control information is obtained.
The present invention is not limited to the above embodiments, and any equivalent embodiments which can be changed or modified by the technical disclosure described above can be applied to other fields, but any simple modification, equivalent changes and modification made to the above embodiments according to the technical matter of the present invention will still fall within the scope of the technical disclosure.
Claims (10)
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411796543.9A CN119273106B (en) | 2024-12-09 | 2024-12-09 | Intelligent irrigation system for standardized production of forestry seedlings |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202411796543.9A CN119273106B (en) | 2024-12-09 | 2024-12-09 | Intelligent irrigation system for standardized production of forestry seedlings |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN119273106A true CN119273106A (en) | 2025-01-07 |
| CN119273106B CN119273106B (en) | 2025-09-23 |
Family
ID=94108756
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202411796543.9A Active CN119273106B (en) | 2024-12-09 | 2024-12-09 | Intelligent irrigation system for standardized production of forestry seedlings |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN119273106B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119837023A (en) * | 2025-01-16 | 2025-04-18 | 如皋市机电排灌管理站 | Farmland irrigation management and control system based on Internet of things |
| CN120584624A (en) * | 2025-08-06 | 2025-09-05 | 中国水利水电第六工程局有限公司 | Adaptive fertilization methods for landscaping |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150040473A1 (en) * | 2011-07-15 | 2015-02-12 | Earthtec Solutions LLS | Crop-specific automated irrigation and nutrient management |
| US20190230875A1 (en) * | 2015-08-05 | 2019-08-01 | Clearag, Inc. | Customized land surface modeling in a soil-crop system using satellite data to detect irrigation and precipitation events for decision support in precision agriculture |
| CN110692338A (en) * | 2019-10-30 | 2020-01-17 | 北京农业智能装备技术研究中心 | Control method of water-fertilizer integrated irrigation system and water-fertilizer integrated irrigation system |
| CN117669885A (en) * | 2023-12-06 | 2024-03-08 | 云南省烟草农业科学研究院 | Intelligent tobacco planting management system and method |
-
2024
- 2024-12-09 CN CN202411796543.9A patent/CN119273106B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20150040473A1 (en) * | 2011-07-15 | 2015-02-12 | Earthtec Solutions LLS | Crop-specific automated irrigation and nutrient management |
| US20190230875A1 (en) * | 2015-08-05 | 2019-08-01 | Clearag, Inc. | Customized land surface modeling in a soil-crop system using satellite data to detect irrigation and precipitation events for decision support in precision agriculture |
| CN110692338A (en) * | 2019-10-30 | 2020-01-17 | 北京农业智能装备技术研究中心 | Control method of water-fertilizer integrated irrigation system and water-fertilizer integrated irrigation system |
| CN117669885A (en) * | 2023-12-06 | 2024-03-08 | 云南省烟草农业科学研究院 | Intelligent tobacco planting management system and method |
Non-Patent Citations (2)
| Title |
|---|
| 陈智芳等: "节水灌溉管理与决策支持系统", 农业工程学报, no. 2, 31 October 2009 (2009-10-31), pages 1 - 6 * |
| 马建琴等: "农业多水源灌溉实时优化配置", 江苏农业科学, no. 07, 5 April 2018 (2018-04-05), pages 211 - 214 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN119837023A (en) * | 2025-01-16 | 2025-04-18 | 如皋市机电排灌管理站 | Farmland irrigation management and control system based on Internet of things |
| CN120584624A (en) * | 2025-08-06 | 2025-09-05 | 中国水利水电第六工程局有限公司 | Adaptive fertilization methods for landscaping |
Also Published As
| Publication number | Publication date |
|---|---|
| CN119273106B (en) | 2025-09-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN119273106B (en) | Intelligent irrigation system for standardized production of forestry seedlings | |
| CN112602563B (en) | Water-saving irrigation system and accurate irrigation method | |
| Lea-Cox et al. | Advancing wireless sensor networks for irrigation management of ornamental crops: An overview | |
| CN117893346A (en) | AI intelligent agriculture harvesting management system based on Internet of things and application thereof | |
| CN119226958B (en) | Water-fertilizer integrated irrigation control method based on wheat growth cycle | |
| CN117296538B (en) | Green plant maintenance method, device and system based on vegetation soil component detection | |
| CN117063818A (en) | A precise control system for water and fertilizer | |
| CN118674571A (en) | Afforestation management method and system based on artificial intelligence | |
| CN118569508A (en) | A smart garden monitoring and management system | |
| CN119861778B (en) | Automatic regulation and control system of environment for planting chinese-medicinal material | |
| CN120435969A (en) | Organic fertilizer application method and system for dynamic management of farmland nutrients | |
| CN119866755A (en) | Integrated control system for potato stock production | |
| CN118917806A (en) | Agricultural intelligent management system based on Internet of things | |
| CN118872579A (en) | A hedge maintenance device capable of automatically adjusting water volume | |
| CN119837023A (en) | Farmland irrigation management and control system based on Internet of things | |
| CN117223459A (en) | Automatic fertilizer mixing system based on data analysis | |
| CN119721969A (en) | A method, system and computing device for measuring agricultural carbon sinks | |
| Han et al. | Contrasting response of water use efficiency to soil moisture availability: From leaf to ecosystem in an arid oasis | |
| CN120391311B (en) | Agricultural water-saving irrigation intelligent control system | |
| Carrasquilla-Batista et al. | IoT applications: On the path of Costa Rica's commitment to becoming carbon-neutral | |
| CN119278838B (en) | Intelligent drip irrigation method and system for growing dendrobium seedlings in greenhouse | |
| Macabiog et al. | Soil moisture and rain prediction based irrigation controller for the strawberry farm of La Trinidad, Benguet | |
| CN118765764A (en) | A garden irrigation information collection and monitoring method | |
| Martínez-Ruiz et al. | Uncertainty analysis of the HORTSYST model applied to fertigated tomatoes cultivated in a hydroponic greenhouse system | |
| Bacci et al. | A system for fertigation management in closed-loop soilless culture of tomato |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |