Intelligent irrigation control method and system, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses an intelligent irrigation control method and system, electronic equipment and a storage medium. The method comprises the following steps: acquiring growth stage information of a target crop, and determining environmental parameter conditions based on the growth stage information; acquiring soil environment parameters related to the crop root zone of the target crop; judging whether the soil environment parameters meet environment parameter conditions or not; if not, whether the target crop needs supplementary irrigation is determined according to the illumination accumulated radiation quantity from the last irrigation moment to the current moment; if yes, determining that the target crop does not need supplementary irrigation; when the target crop needs supplementary irrigation, the supplementary irrigation water and fertilizer amount is determined according to the illumination accumulated radiation amount, and the supplementary irrigation water and fertilizer amount is sent to the water and fertilizer machine to control the water and fertilizer machine to execute supplementary irrigation. According to the scheme, decision errors caused by single parameters can be effectively avoided, and the irrigation decision accuracy is improved.

Description

Technical Field

[0001] This invention relates to the field of smart agriculture technology, specifically to a smart irrigation control method, system, electronic device, storage medium, and computer program product. Background Technology

[0002] In facility agriculture and precision irrigation management, a reasonable supply of water and fertilizer is crucial for ensuring healthy crop growth and improving yield and quality. Currently, most mainstream automated irrigation systems rely on threshold triggering by soil moisture sensors or simple timed control to manage irrigation in the crop root zone. Existing irrigation control schemes often suffer from limited parameters and rigid models, making them unable to quickly respond to environmental fluctuations and change irrigation decisions. This leads to inaccurate irrigation decisions and problems such as water and fertilizer waste or crop water stress. Summary of the Invention

[0003] The present invention was proposed in view of the above-mentioned problems. Embodiments of the present invention disclose an intelligent irrigation control method, an intelligent irrigation control system, an electronic device, a storage medium, and a computer program product.

[0004] According to one aspect of the present invention, an intelligent irrigation control method is provided, comprising the following control operations: acquiring growth stage information of a target crop and determining environmental parameter conditions based on the growth stage information, wherein the growth stage information is used to indicate the current growth stage of the target crop and the environmental parameter conditions are preset parameter conditions corresponding to the current growth stage; acquiring soil environmental parameters related to the root zone of the target crop, wherein the soil environmental parameters are used to reflect the current moisture status of the crop root zone; determining whether the soil environmental parameters meet the environmental parameter conditions; if not, determining whether the target crop needs supplementary irrigation based on the cumulative light radiation from the last irrigation time to the current time; if it meets the conditions, determining that the target crop does not need supplementary irrigation; when the target crop needs supplementary irrigation, determining the amount of supplementary irrigation water and fertilizer based on the cumulative light radiation, and sending the amount of supplementary irrigation water and fertilizer to the water and fertilizer generator to control the water and fertilizer generator to perform supplementary irrigation.

[0005] For example, soil environmental parameters include one or more of the following sub-parameters: soil temperature, overall soil moisture, soil electrical conductivity, soil depth moisture, meteorological data, crop canopy temperature, air temperature, air humidity, and atmospheric carbon dioxide concentration.

[0006] For example, soil depth moisture is obtained by simultaneously collecting moisture data at different depths in the crop root zone using the same sensor.

[0007] For example, the soil environmental parameters include at least two sub-parameters, each of which has a corresponding preset parameter range. The environmental parameter conditions include preset parameter ranges corresponding to each of the at least two sub-parameters. Determining whether the soil environmental parameters meet the environmental parameter conditions includes: normalizing and weighting the parameter deviations corresponding to each of the at least two sub-parameters according to preset weights to obtain a comprehensive score for the soil environmental parameters, where the parameter deviation is the deviation between the sub-parameter and its corresponding preset parameter range; comparing the comprehensive score with a preset score threshold; if the comprehensive score exceeds the preset score threshold, the soil environmental parameters are determined to meet the environmental parameter conditions; otherwise, the soil environmental parameters are determined not to meet the environmental parameter conditions.

[0008] For example, each sub-parameter in the soil environmental parameters has a corresponding preset parameter range. Determining whether the target crop needs supplemental irrigation based on the cumulative light radiation from the last irrigation time to the current time includes: determining that the target crop needs supplemental irrigation when the cumulative light radiation is greater than or equal to a preset light threshold; determining that the target crop needs supplemental irrigation when the cumulative light radiation is less than the preset light threshold and there is a first preset number of sub-parameters in the soil environmental parameters whose parameter deviation from the corresponding preset parameter range is greater than or equal to a preset deviation threshold; and determining that the target crop does not need supplemental irrigation when the cumulative light radiation is less than the preset light threshold and there is no first preset number of sub-parameters in the soil environmental parameters whose parameter deviation from the corresponding preset parameter range is greater than or equal to a preset deviation threshold.

[0009] For example, determining whether the target crop needs supplemental irrigation based on the cumulative light radiation from the last irrigation time to the current time further includes: using a crop water requirement model and determining a preset light threshold corresponding to the current growth stage based on growth stage information. The crop water requirement model is a correlation model between the growth stage of a reference crop and the light threshold, and the reference crop is a crop of the same variety as the target crop.

[0010] For example, before determining whether the target crop needs supplemental irrigation based on the cumulative light radiation from the last irrigation time to the current time, the control operation further includes: acquiring photosynthetically active radiation data collected by a light sensor, or acquiring total radiation data collected by a light sensor and determining photosynthetically active radiation data based on the total radiation data; calculating the cumulative light radiation based on the photosynthetically active radiation data and the light time interval, wherein the light time interval is the time interval between the last irrigation time and the current time.

[0011] For example, soil environmental parameters include overall soil moisture and soil electrical conductivity. Overall soil moisture has a corresponding preset parameter range. Supplementary irrigation water and fertilizer includes supplementary irrigation water and supplementary irrigation fertilizer. The supplementary irrigation water and fertilizer is determined based on cumulative solar radiation, including: determining the water requirement of the target crop based on growth stage information, cumulative solar radiation, and the evapotranspiration requirement formula corresponding to the reference crop; determining the total soil moisture content in the crop root zone based on the parameter deviation between overall soil moisture and the corresponding preset parameter range and the preset soil moisture coefficient; determining the water content gap value based on the difference between the water requirement and the total soil moisture content; determining the supplementary irrigation water based on the water content gap value and the preset water replenishment rate; and determining the irrigation fertilizer amount corresponding to the soil electrical conductivity and the current growth stage from the first preset database based on soil environmental parameters and growth stage information, as the supplementary irrigation fertilizer amount. The first preset database is used to store a ratio table of reference crops, which records the irrigation fertilizer amount corresponding to different growth stages and different soil electrical conductivity. The reference crops are crops of the same variety as the target crop.

[0012] For example, determining environmental parameter conditions based on growth stage information includes: searching a second preset database for preset parameter conditions corresponding to the current growth stage based on the growth stage information to determine the environmental parameter conditions, wherein the second preset database is used to associate and store the growth stages of a reference crop and the preset parameter conditions corresponding to each growth stage, and the reference crop is a crop of the same variety as the target crop.

[0013] For example, the control operation is performed at preset time intervals, where the preset time interval is less than or equal to 1 hour.

[0014] For example, the soil environmental parameters include one or more sub-parameters, each of which has a corresponding preset parameter range. After sending the supplementary irrigation water and fertilizer amount to the water and fertilizer machine to control the machine to perform supplementary irrigation, the control operation further includes: recording the execution parameters corresponding to this supplementary irrigation, which include the irrigation water and fertilizer amount and the water pump flow rate of the water and fertilizer machine. The irrigation water and fertilizer amount includes the irrigation water volume, and the irrigation water volume and the water pump flow rate are positively correlated and have a conversion coefficient. The method further includes: obtaining the soil environmental parameters at a target time, where the target time is the time reached after a preset time after the supplementary irrigation is completed. If there is a second preset number of sub-parameters in the soil environmental parameters at the target time that are less than the lower limit of the corresponding preset parameter range, the conversion coefficient is increased based on the most recent conversion coefficient. If there is a third preset number of sub-parameters that are greater than the upper limit of the corresponding preset parameter range, the conversion coefficient is decreased based on the most recent conversion coefficient. The most recent conversion coefficient is the conversion coefficient between the water pump flow rate and the irrigation water volume in the most recently recorded execution parameters.

[0015] According to another aspect of the present invention, an intelligent irrigation control system is provided, comprising: a first acquisition module, configured to acquire growth stage information of a target crop and determine environmental parameter conditions based on the growth stage information, wherein the growth stage information indicates the current growth stage of the target crop and the environmental parameter conditions are preset parameter conditions corresponding to the current growth stage; a second acquisition module, configured to acquire soil environmental parameters related to the root zone of the target crop, wherein the soil environmental parameters reflect the current moisture status of the crop root zone; a judgment module, configured to judge whether the soil environmental parameters meet the environmental parameter conditions; a determination module, configured to determine whether the target crop needs supplementary irrigation based on the cumulative light radiation from the last irrigation time to the current time if the soil environmental parameters do not meet the conditions; and a control module, configured to determine the amount of supplementary irrigation water and fertilizer based on the cumulative light radiation when the target crop needs supplementary irrigation, and send the amount of supplementary irrigation water and fertilizer to the water and fertilizer generator to control the water and fertilizer generator to perform supplementary irrigation, and control the water and fertilizer generator to maintain its existing working state when the target crop does not need supplementary irrigation.

[0016] According to another aspect of the present invention, an electronic device is also provided, comprising: a processor and a memory, wherein the memory stores computer program instructions, which are executed by the processor to perform the above-described intelligent irrigation control method.

[0017] According to another aspect of the present invention, a storage medium is also provided, on which program instructions are stored, which are used to execute the above-described intelligent irrigation control method when running.

[0018] According to another aspect of the present invention, a computer program product is also provided, including computer program instructions, which, when executed, are used to perform the intelligent irrigation control method as described above.

[0019] By employing the above technical solution, information on the target crop's growth stage and soil environmental parameters can be obtained. Based on the growth stage information, preset parameter conditions (i.e., environmental parameter conditions) corresponding to the current growth stage can be determined. When the soil environmental parameters of the target crop do not meet the environmental parameter conditions, i.e., the crop's suitable growth requirements are not met, the cumulative light radiation since the last irrigation can be further calculated, and whether supplemental irrigation is needed can be determined based on the cumulative light radiation. For cases requiring supplemental irrigation, the required amount of supplemental irrigation water and fertilizer can be determined based on the cumulative light radiation. The determined amount of supplemental irrigation water and fertilizer can be sent to the integrated water and fertilizer machine to achieve automatic and precise water and fertilizer supply. This technical solution comprehensively considers multiple factors such as crop growth stage, soil moisture status, and light radiation to manage supplemental irrigation, enabling dynamic assessment and differentiated replenishment of crop water requirements. This solution can effectively avoid decision-making errors caused by single parameters, improve the accuracy of irrigation decisions, thereby improving water and fertilizer utilization, reducing over-irrigation and nutrient loss, ensuring the precise needs of crops at different growth stages, improving crop quality and yield, and possessing good value for promotion and application.

[0020] The above description is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0021] The above and other objects, features, and advantages of the present invention will become more apparent from the more detailed description of the embodiments of the invention in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same parts or steps.

[0022] Figure 1 A flowchart illustrating the control operations included in an intelligent irrigation control method according to an embodiment of the present invention is shown.

[0023] Figure 2 A schematic flowchart illustrating an intelligent irrigation control method according to an embodiment of the present invention is shown; and

[0024] Figure 3 A schematic block diagram of an intelligent irrigation control system according to an embodiment of the present invention.

[0025] Figure 4 A schematic block diagram of an electronic device according to an embodiment of the present invention is shown. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of the present invention more apparent, exemplary embodiments according to the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely a part of the embodiments of the present invention, and not all of the embodiments of the present invention. It should be understood that the present invention is not limited to the exemplary embodiments described herein. Based on the embodiments of the present invention described herein, all other embodiments obtained by those skilled in the art without inventive effort should fall within the protection scope of the present invention.

[0027] In modern agriculture, crop water requirements are not constant; they are closely related to factors such as crop growth stage, soil water-holding capacity, and transpiration. Existing irrigation control schemes use single parameters and rigid models, failing to fully consider the dynamic water requirements of crops and the combined effects of environmental factors. Such schemes cannot quickly respond to environmental fluctuations and change irrigation decisions, leading to inaccurate irrigation decisions and problems such as water and fertilizer waste or crop water stress.

[0028] To at least partially solve the aforementioned technical problems, embodiments of the present invention provide an intelligent irrigation control method. This intelligent irrigation control method can be applied to any electronic device with data processing and / or instruction execution capabilities, including but not limited to one or more of personal computers, servers, and mobile terminals. The device used to execute the intelligent irrigation control method can be called an intelligent irrigation control system, which can be deployed in a distributed or centralized manner. Distributed deployment may involve some software and / or hardware located locally in the crop planting area, while other software and / or hardware are located in the cloud or other external locations. Centralized deployment may involve all software and hardware located locally in the crop planting area. The intelligent irrigation control method can be specifically executed by the main control unit of the intelligent irrigation control system. Through the intelligent irrigation control method provided by embodiments of the present invention, multiple factors such as crop growth stage, soil moisture status, and light radiation can be comprehensively considered to achieve automatic and precise water and fertilizer supply. The intelligent irrigation control method according to embodiments of the present invention can be applied to any planting scenario, including but not limited to facility agriculture scenarios such as greenhouses or polytunnels, open-field cultivation scenarios, etc.

[0029] The intelligent irrigation control method according to embodiments of the present invention includes control operations. Figure 1 This diagram illustrates a flow chart of control operations 100 included in an intelligent irrigation control method according to an embodiment of the present invention. Figure 1 As shown, the control operation 100 includes steps S110, S120, S130, S140 and S150.

[0030] In step S110, the growth stage information of the target crop is obtained, and the environmental parameter conditions are determined based on the growth stage information. The growth stage information is used to indicate the current growth stage of the target crop, and the environmental parameter conditions are preset parameter conditions corresponding to the current growth stage.

[0031] The target crop can be any variety, such as grapes, cucumbers, tomatoes, cabbage, etc. This document does not limit the variety of the target crop. Furthermore, the number of target crops can be one or more; for example, a single bunch of grapes can be the target crop, or all grapes in a planting area can be the target crop. When there are multiple target crops, the current growth stage of the multiple target crops can be determined comprehensively based on the current growth stage of each target crop. For example, the current growth stage that occurs most frequently among the current growth stages of the multiple target crops can be taken as the current growth stage of the target crop. Exemplarily, control operation 100 can be executed at preset time intervals. Correspondingly, step S110 can be executed at preset time intervals. Of course, the scheme of executing control operation 100 at preset time intervals is only an example; control operation 100 can also be executed based on other times, such as in response to user operation commands.

[0032] The information obtained in step S110 can be the growth stage information of the target crop at the current moment. This growth stage information indicates the current growth stage of the target crop. The target crop can include multiple preset growth stages, such as the vegetative growth stage, flowering and fruit setting stage, fruit enlargement stage, and ripening and harvesting stage. Each crop variety can have multiple corresponding preset growth stages. The number of preset growth stages corresponding to different crop varieties can be the same or different, and the preset growth stages corresponding to different crop varieties can be all the same, all different, or partially the same and partially different. Each preset growth stage of the crop can correspond to preset parameter conditions. These preset parameter conditions are the parameters that can meet the growth requirements of the target crop at the corresponding growth stage. The multiple preset growth stages corresponding to the target crop and the preset parameter conditions corresponding to each preset growth stage can be preset according to the variety of the target crop and user needs. The preset parameter conditions corresponding to the current growth stage can be determined based on the target crop's growth stage information, i.e., the environmental parameter conditions can be determined. Crops require varying amounts of light, water, and fertilizer at different growth stages. Therefore, adaptability analysis can be performed according to different growth stages to determine whether soil environmental parameters are suitable for the crop at the current growth stage (i.e., whether they meet environmental parameter conditions). This approach allows for automatic matching of differentiated irrigation needs across different growth stages, enabling more precise water and fertilizer management.

[0033] For example, a crop growth model can be deployed in the intelligent irrigation control system, or it can be deployed at other model deployment locations, such as the cloud. For example, the crop growth model can be a neural network model. For example, the intelligent irrigation control system can call the crop growth model internally or by communicating with an external model deployment location. The communication described herein can be any wired and / or wireless communication. For example, crop data of the target crop, such as color (RGB) images and depth images of the target crop, can be collected by sensors deployed in the planting area of ​​the target crop. The crop growth model can determine the current growth stage of the target crop based on the crop data (i.e., using the crop data as input to the crop growth model) and obtain growth stage information (i.e., using the growth stage information as the output of the crop growth model). The intelligent irrigation control system can obtain the growth stage information of the target crop from the crop growth model by calling the crop generation model.

[0034] In step S120, soil environmental parameters related to the root zone of the target crop are obtained. These soil environmental parameters are used to reflect the current moisture status of the crop root zone.

[0035] Soil environmental parameters reflect the current moisture status of the crop root zone, i.e., soil moisture. The crop root zone is the area where the roots of the target crop are located, and its size can be preset as needed. Soil environmental parameters can include any type of parameter that reflects the moisture status of the crop root zone, including but not limited to soil temperature, total soil moisture, soil electrical conductivity, soil depth moisture, and meteorological data. The intelligent irrigation control system may include sensors for collecting soil environmental parameters or be communicatively connected to sensors for collecting soil environmental parameters. The communication connection described herein can be any wired and / or wireless communication connection. The intelligent irrigation control system can acquire soil environmental parameters related to the crop root zone of the target crop from sensors.

[0036] In step S130, it is determined whether the soil environmental parameters meet the environmental parameter conditions.

[0037] Intelligent irrigation control systems can compare soil environmental parameters with the environmental parameters required by the target crop at its current growth stage to determine whether the current soil environmental parameters can meet the crop's growth needs. In this way, differentiated irrigation needs can be automatically matched at different growth stages, enabling more precise water and fertilizer management. It also helps to accurately supply water and fertilizer during key growth periods, promote balanced crop growth, improve quality indicators such as fruit size, sugar-acid ratio, and color, and enhance commercial value.

[0038] In step S140, if the condition is not met, it is determined whether the target crop needs supplementary irrigation based on the cumulative light radiation from the last irrigation time to the current time; if the condition is met, it is determined that the target crop does not need supplementary irrigation.

[0039] If the soil environmental parameters meet the requirements, i.e., satisfy the crop's growth needs, then supplemental irrigation is unnecessary for the target crop. Supplemental irrigation refers to additional irrigation on top of the normal irrigation provided by the fertigation system to supplement the target crop with extra water and fertilizer. If the soil environmental parameters do not meet the requirements, the cumulative solar radiation from the last irrigation time to the current time can be determined, and whether supplemental irrigation is needed can be further determined based on this cumulative solar radiation. The fertigation system can be included in the irrigation control system or operate independently of it. The fertigation system communicates with the main control unit of the irrigation control system. The fertigation system may include a water pump and a fertilizer applicator, and may also include other components such as solenoid valves. By linking with fertigation systems in greenhouses or fields, fully automated irrigation control can be achieved, reducing manual intervention.

[0040] In step S150, when the target crop requires supplemental irrigation, the amount of water and fertilizer for supplemental irrigation is determined based on the cumulative solar radiation, and this amount is sent to the fertigation machine to control it to perform supplemental irrigation. When the target crop does not require supplemental irrigation, the intelligent irrigation control system can enter a standby state to await the next control operation, or control the fertigation machine to maintain its current operating state.

[0041] When soil environmental parameters do not meet the requirements, the target crop does not require supplemental irrigation. In this case, the water and fertilizer machine can be left on standby or kept operating as is. If, when soil environmental parameters meet the requirements, further analysis based on cumulative solar radiation indicates that supplemental irrigation is not needed, the water and fertilizer machine can be left on standby or kept operating as is. If, when soil environmental parameters meet the requirements, further analysis based on cumulative solar radiation indicates that supplemental irrigation is needed, the amount of water and fertilizer required for supplemental irrigation can be determined based on the cumulative solar radiation, and the water and fertilizer machine can be controlled to perform supplemental irrigation according to the determined amount. Solar radiation is related to transpiration. Low cumulative solar radiation results in low water evaporation, and supplemental irrigation may be unnecessary or only minimal. Conversely, high cumulative solar radiation results in high water evaporation, and more supplemental irrigation may be required. Therefore, incorporating cumulative solar radiation into the determination of whether supplemental irrigation is needed and the amount of water and fertilizer required can help achieve accurate calculation of the amount of water and fertilizer needed for supplemental irrigation, avoiding water and fertilizer waste or crop water stress. Furthermore, this approach is environmentally friendly, reducing nitrogen and phosphorus loss, minimizing pollution to water and soil, conserving agricultural irrigation water, lowering electricity consumption and operation and maintenance costs, and aligning with sustainable development goals. The approach supports various crop types and different regional planting conditions, making it easy to promote.

[0042] The above technical solution allows for the acquisition of growth stage information and soil environmental parameters for the target crop. Based on the growth stage information, preset parameter conditions (i.e., environmental parameter conditions) corresponding to the current growth stage can be determined. When the soil environmental parameters of the target crop do not meet the environmental parameter conditions, i.e., the crop's suitable growth requirements are not met, the cumulative light radiation since the last irrigation can be further calculated. Based on the cumulative light radiation, it can be determined whether supplemental irrigation is needed. For cases requiring supplemental irrigation, the required amount of supplemental irrigation water and fertilizer can be determined based on the cumulative light radiation. The determined amount of supplemental irrigation water and fertilizer can be sent to the integrated water and fertilizer machine for automatic and precise water and fertilizer supply. This technical solution comprehensively considers multiple factors such as crop growth stage, soil moisture status, and light radiation for supplemental irrigation management, enabling dynamic assessment and differentiated replenishment of crop water requirements. This solution effectively avoids decision-making errors caused by single parameters, improves the accuracy of irrigation decisions, thereby improving water and fertilizer utilization, reducing over-irrigation and nutrient loss, ensuring precise crop needs at different growth stages, improving crop quality and yield, and possessing good value for widespread application.

[0043] According to embodiments of the present invention, soil environmental parameters include one or more of the following sub-parameters: soil temperature, overall soil moisture, soil electrical conductivity, soil depth moisture, meteorological data, crop canopy temperature, air temperature, air humidity, and carbon dioxide concentration in the air.

[0044] For example, soil temperature, overall soil moisture, soil electrical conductivity, soil depth moisture, crop canopy temperature, air temperature, air humidity, and air carbon dioxide concentration can be acquired through corresponding sensors. Meteorological data can be obtained from a meteorological data center via network connection or through small weather stations deployed locally in the crop planting area. For example, in a crop planting area, such as a greenhouse, one or more sensors can be installed, including but not limited to one or more of the following: soil temperature sensor, soil moisture sensor, soil electrical conductivity sensor, stratified soil moisture sensor, crop canopy temperature sensor, air temperature sensor, air humidity sensor, and gas concentration sensor. These sensors can be used to collect soil temperature, overall soil moisture, soil electrical conductivity, soil depth moisture, crop canopy temperature, and air carbon dioxide concentration in a one-to-one correspondence. For each sensor, it can be included in the smart irrigation system (i.e., part of the smart irrigation system) or it can be independent of the smart irrigation system. Any two or more of the following sensors—soil temperature sensor, soil moisture sensor, soil conductivity sensor, and stratified soil moisture sensor—can be the same sensor, meaning that a single sensor can be used to collect multiple sub-parameters. For example, a stratified soil moisture sensor can collect soil temperature, soil conductivity, and soil depth moisture. Similarly, any two or more of the following sensors—air temperature sensor, air humidity sensor, and gas concentration sensor—can be the same sensor.

[0045] Soil temperature, overall soil moisture, soil electrical conductivity, and soil depth moisture can be collected by sensors buried in the soil within the crop root zone. The main root layer of a crop typically has a certain depth, for example, 0-30 cm. For example, separate soil temperature sensors and separate soil moisture sensors, or a composite soil temperature and moisture sensor, can be installed within a preset depth range below the soil surface in the crop root zone. The preset depth range can be, for example, 0-30 cm. It should be understood that the function of the composite temperature and moisture sensor is equivalent to the combined function of separate soil temperature and moisture sensors, achieving the same technical effect. Overall soil moisture refers to the overall moisture value of the soil, which can be collected by any single soil moisture sensor. Alternatively, overall soil moisture can be determined based on soil depth moisture without the need for a separate soil moisture sensor; for example, overall soil moisture can be equal to the average, median, or maximum soil depth moisture. Soil depth moisture is the stratified moisture at different depths of the crop root system. For example, stratified soil moisture sensors can be installed on the same vertical profile within a preset depth range in the crop root zone to collect soil depth moisture. For example, a soil conductivity sensor can be installed within a preset depth range of the crop root zone to monitor the ion concentration of salts and nutrients in the soil solution and obtain the soil conductivity.

[0046] Meteorological data can reflect current weather conditions. For example, meteorological data may include one or more of the following: air temperature, air humidity, rainfall, wind speed, light intensity, air pressure, and extreme weather events. Incorporating meteorological data enables irrigation strategies to be dynamically adjusted to cope with sudden weather changes and soil heterogeneity, helping to reduce the risk of crop yield reduction due to drought, flooding, or abnormal climate. When meteorological data includes air temperature and / or air humidity, air temperature and / or air humidity may not exist as separate sub-parameters in soil environmental parameters. For example, a small weather station can be suspended at a height in the middle of the crop canopy, integrating sensors to measure air temperature, humidity, light intensity, and wind speed to collect meteorological data. Crop canopy temperature can be monitored non-contactly using an infrared thermal imager mounted above the target crop. Furthermore, for example, multiple gas concentration sensors can be distributed within the active growth canopy area of ​​the target crop (e.g., inside a greenhouse) or along the main trunk of the target crop to collect real-time air carbon dioxide concentrations to determine the distribution of photosynthetic raw materials.

[0047] The aforementioned sensors can be connected to the main control unit of the irrigation control system using communication methods such as Bluetooth and WiFi, allowing the sensors to upload collected data to the main control unit. Those skilled in the art should understand that data transmission is not limited to Bluetooth or WiFi; any method that can achieve a stable connection between the sensors and the main control unit and transmit data can be applied. For example, low-power wide-area network protocols or short-range wireless networks can aggregate data and send it to gateways or nodes deployed at the edge of farmland, and then use Ethernet or cellular networks to stably and in real-time transmit the aggregated multi-source sensor data back to the main control unit located in the control center or cloud. Similarly, using satellite IoT for interconnection can also achieve the above technical effects; the specific transmission method chosen depends on the actual crop planting environment and the area occupied.

[0048] Using the above technical solution, soil environmental parameters can include parameters within the soil and / or environmental parameters outside the soil. Internal soil parameters, such as soil temperature, provide a more direct and clear indication of the moisture status in the crop root zone. Fluctuations in external environmental parameters, such as meteorological data, also affect soil moisture content; therefore, external environmental parameters can also reflect the moisture status of the crop root zone to some extent, and collecting these parameters is relatively inexpensive. Combining these two parameter methods can improve the accuracy of determining the moisture status of the crop root zone.

[0049] According to embodiments of the present invention, soil depth moisture is obtained by simultaneously collecting moisture data at different depths within the crop root zone using the same sensor. For example, when collecting soil depth moisture, the same layered soil moisture sensor can simultaneously collect soil moisture at depths of 10cm, 20cm, and 30cm.

[0050] The above technical solution allows for the simultaneous collection of soil moisture at different depths using the same sensor. This enables the handling of rapid humidity fluctuations that occur on a minute-by-minute basis when the target crop is in a greenhouse environment, ensuring the synchronization of soil moisture collected at different depths and improving the accuracy of irrigation control.

[0051] According to an embodiment of the present invention, soil environmental parameters include at least two types of sub-parameters, each of which has a corresponding preset parameter range. Environmental parameter conditions include preset parameter ranges corresponding to each of the at least two types of sub-parameters. Determining whether the soil environmental parameters meet the environmental parameter conditions includes: normalizing and weighting the parameter deviations corresponding to each of the at least two types of sub-parameters according to preset weights to obtain a comprehensive score for the soil environmental parameters, wherein the parameter deviation is the deviation between the sub-parameter and the preset parameter range corresponding to the sub-parameter; comparing the comprehensive score with a preset score threshold; if the comprehensive score exceeds the preset score threshold, it is determined that the soil environmental parameters meet the environmental parameter conditions; otherwise, it is determined that the soil environmental parameters do not meet the environmental parameter conditions.

[0052] Each sub-parameter in the soil environmental parameters can have a corresponding preset parameter range. The preset parameter range is a range of parameters that suits the growth needs of the target crop at its current growth stage. For example, for grapes in the flowering and fruit-setting stage, the preset parameter range for soil temperature is 20℃-28℃, and the preset parameter range for overall soil moisture is 50-65%. Other sub-parameters are similar, each with its own corresponding preset parameter range, which will not be listed here. Each sub-parameter in the soil environmental parameters obtained in step S120 can be compared with its corresponding preset parameter range to determine the deviation between them, i.e., the parameter deviation. The parameter deviation described herein is the absolute value of the difference between the sub-parameter and its corresponding preset parameter range, i.e., a non-negative value. When the sub-parameter is greater than or equal to the upper limit of the preset parameter range, the difference between the sub-parameter and its corresponding preset parameter range is the difference between the sub-parameter and the upper limit of the preset parameter range; when the sub-parameter is less than or equal to the lower limit of the preset parameter range, the difference between the sub-parameter and its corresponding preset parameter range is the difference between the sub-parameter and the lower limit of the preset parameter range. A comprehensive score can be determined based on the parameter deviations corresponding to at least two sub-parameters. For example, for at least two sub-parameters, the parameter deviations corresponding to each sub-parameter can be normalized, and then the normalized results can be weighted to determine the comprehensive score of the soil environmental parameters. The weighting operation can be a weighted average or a weighted summation. Preset weights can be configured for each sub-parameter; for example, preset weights can be set for sub-parameters such as overall soil moisture, soil temperature, and soil electrical conductivity, and the weighting operation can be performed based on these preset weights. The preset weights for any two sub-parameters can be the same or different. The comprehensive score can be inversely proportional to the parameter deviations corresponding to each sub-parameter; that is, with the parameter deviations of other sub-parameters remaining constant, the larger the parameter deviation of any sub-parameter, the smaller the comprehensive score. Those skilled in the art will understand the implementation method of normalizing the parameter deviations corresponding to different types of sub-parameters to determine the comprehensive score, which will not be elaborated here. The preset parameter range can be obtained through long-term planting experiments, agronomic expert experience, and crop parameter models, and can be dynamically updated according to crop varieties and facility conditions.

[0053] After determining the comprehensive score, it can be compared with a preset scoring threshold. The preset scoring threshold can be set to any suitable value as needed. For example, the preset scoring threshold could be such as 0.8, 0.9, or 0.95. If the comprehensive score exceeds (i.e., is greater than) the preset scoring threshold, it is considered that the comprehensive score meets the standard, and it can be determined that the soil environmental parameters meet the environmental parameter conditions. If the comprehensive score does not exceed (i.e., is less than or equal to) the preset scoring threshold, it is considered that the comprehensive score does not meet the standard, and it can be determined that the soil environmental parameters do not meet the environmental parameter conditions. The subsequent step of determining whether the target crop needs supplemental irrigation based on the cumulative light radiation from the last irrigation time to the current time can then proceed.

[0054] By employing the above technical solution, a comprehensive score is determined by normalizing and weighting the parameter deviations corresponding to different types of sub-parameters. The comparison between the comprehensive score and a preset score threshold then determines whether the soil environmental parameters meet the environmental parameter conditions. This approach comprehensively considers the degree of deviation of multiple sub-parameters relative to preset parameter ranges to determine whether the current soil environmental parameters are suitable for the growth needs of the target crop, helping to avoid excessive deviations in some sub-parameters that could negatively impact the normal growth of the target crop.

[0055] According to an embodiment of the present invention, each sub-parameter in the soil environmental parameters has a corresponding preset parameter range. Determining whether the target crop needs supplemental irrigation based on the cumulative light radiation from the last irrigation time to the current time includes: determining that the target crop needs supplemental irrigation when the cumulative light radiation is greater than or equal to a preset light threshold; determining that the target crop needs supplemental irrigation when the cumulative light radiation is less than the preset light threshold, and there is a first preset number of sub-parameters in the soil environmental parameters whose parameter deviation from the corresponding preset parameter range is greater than or equal to a preset deviation threshold; and determining that the target crop does not need supplemental irrigation when the cumulative light radiation is less than the preset light threshold, and there is no first preset number of sub-parameters in the soil environmental parameters whose parameter deviation from the corresponding preset parameter range is greater than or equal to a preset deviation threshold.

[0056] Both the preset light threshold and the preset deviation threshold can be set to any suitable value as needed. When the cumulative light radiation is greater than or equal to the preset light threshold, the crop root zone has lost a significant amount of water through evaporation since the last irrigation. In this case, it can be determined that the target crop needs supplemental irrigation, triggering the step of determining the amount of water and fertilizer for supplemental irrigation. When the cumulative light radiation is less than the preset light threshold, it can be further determined whether the target crop needs supplemental irrigation based on the parameter deviation corresponding to the sub-parameters. It should be noted that the above scheme is only an example, and the present invention is not limited to the above embodiments. For example, when the cumulative light radiation is greater than or equal to the preset light threshold, it can be determined that the target crop needs supplemental irrigation; when the cumulative light radiation is less than the preset light threshold, it can be determined that the target crop does not need supplemental irrigation. This scheme has a simple judgment logic and low implementation cost.

[0057] For example, the preset deviation threshold can be in the range of 1%-10%, such as 3%. The preset deviation threshold is the safety lower limit corresponding to the sub-parameter. When a sub-parameter exceeds the preset parameter range, and the degree of exceeding (i.e., parameter deviation) is greater than or equal to the preset deviation threshold, it is considered to have exceeded the safety lower limit. For example, when the cumulative light radiation is less than the preset light threshold, if there is a first preset number of sub-parameters with parameter deviations greater than or equal to the preset deviation threshold between them and the corresponding preset parameter range, such as when the overall soil moisture is lower than the safety lower limit, the intelligent irrigation control system can trigger the step of determining the amount of supplementary irrigation water and fertilizer to perform supplementary irrigation to ensure the safety of the crop root system. The first preset number can be set as needed and can be any size. For example, the first preset number can be in the range of 1-5, such as 1, 2, or 3. It is preferable that the first preset number is 1, that is, when the cumulative light radiation is less than the preset light threshold, if there is any parameter deviation corresponding to any sub-parameter greater than or equal to the preset deviation threshold, it can be determined that the target crop needs supplementary irrigation. When the cumulative light radiation is less than the preset light threshold, if there is no parameter deviation between the first preset number of sub-parameters and the corresponding preset parameter interval in the soil environmental parameters that is greater than or equal to the preset deviation threshold, it is determined that the target crop does not need supplemental irrigation. The intelligent irrigation control system can enter standby mode and wait for the next cycle to make an evaluation and judgment, or control the water and fertilizer machine to maintain the existing working state.

[0058] By adopting the above technical solution, it is possible to determine whether the target crop needs supplemental irrigation by combining the magnitude of cumulative light radiation and the deviation of sub-parameters. This solution is more comprehensive and can promptly supplement irrigation when the cumulative light radiation is not large but the sub-parameters deviate significantly from their preset parameter range, so as to better maintain the soil environmental parameters within the suitable range for the target crop and improve the growth quality of the target crop.

[0059] According to an embodiment of the present invention, determining whether the target crop needs supplemental irrigation based on the cumulative light radiation from the last irrigation time to the current time further includes: using a crop water requirement model and determining a preset light threshold corresponding to the current growth stage based on growth stage information. The crop water requirement model is a correlation model between the growth stage of a reference crop and the light threshold, and the reference crop is a crop of the same variety as the target crop.

[0060] Similar to crop growth models, crop water requirement models can be deployed within or independently of intelligent irrigation control systems. These models can be pre-configured, representing the correlation between the growth stages of a reference crop and light thresholds. In other words, the light thresholds corresponding to each growth stage of the reference crop can be determined using the crop water requirement model. The crop water requirement model can be a tabular file or a neural network model, etc. For example, if the target crop is grape A, the growth stages of grapes of the same variety as the target crop, along with the corresponding light thresholds, can be stored in a tabular file. The intelligent irrigation control system can then retrieve the light threshold corresponding to the current growth stage of grape A from the tabular file to obtain the preset light threshold.

[0061] By adopting the above technical solution, the corresponding light threshold can be configured according to different growth stages through crop water requirement model. The root water storage capacity and water and fertilizer requirements of crops at different growth stages are different, so their tolerance to light is also different. Therefore, this adaptive configuration of light threshold can further improve the accuracy of water and fertilizer irrigation and achieve more refined water and fertilizer management.

[0062] According to an embodiment of the present invention, before determining whether the target crop needs supplemental irrigation based on the cumulative light radiation from the last irrigation time to the current time, the control operation further includes: acquiring photosynthetically active radiation data collected by a light sensor, or acquiring total radiation data collected by a light sensor and determining photosynthetically active radiation data based on the total radiation data; calculating the cumulative light radiation based on the photosynthetically active radiation data and the light time interval, wherein the light time interval is the time interval between the last irrigation time and the current time.

[0063] For example, the cumulative solar radiation can be determined based on photosynthetically active radiation (PAR) or total radiation data collected by a light sensor. The light sensor can be located within or around the crop planting area, such as outside a greenhouse. The light sensor can be included within or communicate with the intelligent irrigation control system. Total radiation data is the statistically analyzed range of all wavelengths of solar radiation, while photosynthetically active radiation is the wavelength portion that can be absorbed by the target crop (e.g., 400-700 nm). For example, when the light sensor collects total radiation data, the main control unit of the intelligent irrigation system can determine the photosynthetically active radiation based on the total radiation data and a preset absorption coefficient, and then determine the cumulative solar radiation based on the photosynthetically active radiation. The aforementioned photosynthetically active radiation is the photosynthetically active radiation per unit time. The cumulative solar radiation can be calculated based on the photosynthetically active radiation and the time window (i.e., the light interval) from the last irrigation time to the current time. For example, the calculation method for the cumulative solar radiation can be: Cumulative solar radiation = ∑(Photosynthetically active radiation per unit time × Light interval).

[0064] For example, when the soil environmental parameters do not meet the environmental parameter conditions, the steps of "acquiring photosynthetically active radiation data collected by the light sensor, or acquiring total radiation data collected by the light sensor and determining photosynthetically active radiation data from the total radiation data" and "calculating cumulative light radiation based on the photosynthetically active radiation data and the light time interval" can be performed.

[0065] The above scheme allows for the assessment of crop water requirements based on the cumulative solar radiation from the last irrigation time to the current time. The "solar radiation interval" is defined as the duration between the completion of the last irrigation operation and the current time. During calculation, the radiation intensity data continuously collected within this time window is integrated and accumulated with the corresponding time increment to obtain the cumulative solar radiation. This cumulative solar radiation can be compared with a preset solar radiation threshold, providing crucial information for intelligent decision-making regarding whether to trigger supplemental irrigation. The above scheme for determining cumulative solar radiation requires low hardware and algorithm costs, has fast computation speed, and high accuracy.

[0066] According to an embodiment of the present invention, soil environmental parameters include overall soil moisture and soil electrical conductivity. Overall soil moisture has a corresponding preset parameter range. Supplementary irrigation water and fertilizer includes supplementary irrigation water and supplementary irrigation fertilizer. The supplementary irrigation water and fertilizer is determined based on cumulative solar radiation, including: determining the water requirement of the target crop based on growth stage information, cumulative solar radiation, and the evapotranspiration requirement formula corresponding to the reference crop; determining the total soil moisture content in the crop root zone based on the parameter deviation between overall soil moisture and the corresponding preset parameter range and a preset soil moisture coefficient; determining the water content gap value based on the difference between the water requirement and the total soil moisture content; determining the supplementary irrigation water based on the water content gap value and a preset water replenishment rate; and determining the irrigation fertilizer amount corresponding to the soil electrical conductivity and the current growth stage from a first preset database based on soil environmental parameters and growth stage information, as the supplementary irrigation fertilizer amount. The first preset database is used to store a ratio table of reference crops, which records the irrigation fertilizer amount corresponding to different growth stages and different soil electrical conductivity. The reference crops are crops of the same variety as the target crop.

[0067] For example, during the decision-making process, the intelligent irrigation control system can first calculate the water requirement of the target crop under the current environment based on the target crop's current growth stage, the cumulative cumulative solar radiation since the last irrigation, and the standard evapotranspiration formula corresponding to the same crop variety (i.e., the reference crop). The evapotranspiration demand (ETc) formula is: ETc = ETo × Kc. ETc is the actual evapotranspiration, i.e., the water requirement, which refers to the total water consumed by a healthy, well-watered reference crop field throughout its entire growth period under preset conditions. ETo is the reference evapotranspiration, which refers to the evapotranspiration of a hypothetical reference surface (usually vigorous, uniformly tall, fully covered, and well-watered grass). It is only related to meteorological information and is independent of crop type and soil conditions. Meteorological information may include cumulative solar radiation and other information such as air temperature, sunshine duration, air humidity, wind speed, and air pressure, among others. The reference evapotranspiration ETo can be determined based on meteorological information, i.e., combining cumulative solar radiation and other information within the meteorological data. Kc is the crop coefficient, a dimensionless coefficient used to convert reference crop evapotranspiration (ETo) into actual crop evapotranspiration (ETc). Different crops have different leaf morphologies, stomatal behaviors, growth cycles, and canopy structures, resulting in differences in their evapotranspiration compared to the reference surface. Kc quantifies this difference. The crop coefficient Kc corresponding to different growth stages is preset. Based on growth stage information, the crop coefficient Kc corresponding to the current growth stage can be determined. Therefore, based on growth stage information, cumulative light radiation, and the evapotranspiration demand formula corresponding to the reference crop, the water requirement of the target crop can be determined.

[0068] The real-time monitored overall soil moisture can be compared with the suitable moisture range for the current growth stage (i.e., the preset parameter range). The parameter deviation between the two can be combined with the preset soil moisture coefficient in the crop root zone to calculate the actual total water storage of the soil (i.e., total soil moisture content). For example, the product of the parameter deviation and the preset soil moisture coefficient can be used as the total soil moisture content. The preset soil moisture coefficient can be set based on experience or experiments. By comparing the water requirement with the total soil moisture content, the existing soil moisture deficit can be quantitatively determined. Combined with the preset water replenishment rate, this deficit value can be converted into the required supplementary irrigation water. Specifically, the difference between the water requirement and the total soil moisture content can be used as the moisture deficit value, and the product of the moisture deficit value and the preset water replenishment rate can be used as the supplementary irrigation water. The preset water replenishment rate can be set based on experience or experiments and can be a value greater than 0 and less than or equal to 1, such as 0.7, 0.8, 0.9, etc. Simultaneously, real-time monitoring data of soil electrical conductivity can be analyzed and linked to information on the current crop growth stage to query a pre-established fertilization knowledge base (i.e., the first preset database) for the same crop variety. The first preset database can be deployed within the intelligent irrigation control system or independently, for example, in the cloud. It stores optimized fertilizer ratios for different growth stages and soil electrical conductivity, enabling the system to automatically determine the appropriate amount of supplemental fertilizer to match the current supplemental irrigation water volume, thus forming a quantitative set of integrated water and fertilizer irrigation execution instructions.

[0069] By employing the above technical solution, the water content gap value can be determined based on the difference between the target crop's water requirement and the total soil moisture content, and then the supplementary irrigation water volume can be determined based on this water content gap value. This solution ensures that irrigation meets the crop's needs without exceeding the soil's carrying capacity, contributing to multiple goals such as water conservation and environmental protection. Furthermore, the above solution can determine the supplementary irrigation fertilizer amount appropriate for the soil's electrical conductivity and current growth stage based on soil environmental parameters and growth stage information. This allows for dynamic adjustment of fertilizer concentration based on the actual soil salinity, effectively avoiding fertilizer waste and secondary soil salinization.

[0070] According to an embodiment of the present invention, determining environmental parameter conditions based on growth stage information includes: searching a second preset database for preset parameter conditions corresponding to the current growth stage based on the growth stage information to determine the environmental parameter conditions, wherein the second preset database is used to associate and store the growth stages of a reference crop and the preset parameter conditions corresponding to each growth stage, and the reference crop is a crop of the same variety as the target crop.

[0071] The second preset database can be deployed within the intelligent irrigation control system or independently, such as in the cloud. For example, when the intelligent irrigation control system determines that the target crop has entered any growth stage, it can automatically access the second preset database (e.g., an agronomic knowledge database embedded in the intelligent irrigation control system) based on the growth stage information as a query command. The second preset database can pre-store mapping relationships established for reference crops, which are mapping relationships between each growth stage and corresponding preset parameter conditions. Preset parameter conditions are parameters that meet the growth requirements of the corresponding growth stage, i.e., parameters suitable for growth at that stage. Preset parameter conditions can be preset based on experience or experiments. As mentioned above, soil environmental parameters can include one or more sub-parameters; correspondingly, preset parameter conditions can include one or more preset parameter ranges corresponding to these sub-parameters. The meaning of preset parameter ranges can be understood with reference to the description above. By matching the current growth stage of the target crop, a complete set of associated preset parameter conditions can be extracted from the second preset database, such as the preset parameter ranges corresponding to soil temperature, overall soil moisture, soil electrical conductivity, air temperature, and air humidity.

[0072] By adopting the above technical solution, the corresponding preset parameter conditions can be configured according to different growth stages through the second preset database. Different growth stages require different suitable soil environments. Therefore, this adaptive configuration of preset parameter conditions can further improve the accuracy of water and fertilizer irrigation and achieve more refined water and fertilizer management.

[0073] According to an embodiment of the present invention, the control operation is performed at preset time intervals, wherein the preset time interval is less than or equal to 1 hour.

[0074] The preset time interval can be set as needed, for example, it can fall within the range of 0.25 hours to 2 hours, including but not limited to 0.5 hours, 1 hour, 1.5 hours, etc. A preset time interval of 1 hour is preferable. During crop growth, environmental conditions and water requirements may fluctuate rapidly with weather and light conditions, potentially on the order of minutes or even faster. Performing control operations once per hour ensures that irrigation decisions are highly aligned with environmental dynamics. Compared to schemes that perform control operations daily or at longer intervals (e.g., every few hours), hourly control operations significantly reduce irrigation trigger delays, preventing insufficient or excessive soil moisture. Furthermore, high-frequency control operations accumulate denser growth-environment data, facilitating the training and parameter correction of subsequent crop growth models and / or crop water requirement models, thus improving the intelligence level of the intelligent irrigation control system. Additionally, using hourly intervals as a standard monitoring cycle for other environmental control modules (such as temperature and humidity control, and light management) facilitates the integrated operation of the agricultural planting system. The agricultural planting system includes the intelligent irrigation control system described herein and other environmental control modules.

[0075] According to an embodiment of the present invention, the soil environmental parameters include one or more sub-parameters, each of which has a corresponding preset parameter range. After sending the supplementary irrigation water and fertilizer amount to the water and fertilizer machine to control the machine to perform supplementary irrigation, the control operation further includes: recording the execution parameters corresponding to this supplementary irrigation, the execution parameters including the irrigation water and fertilizer amount and the water pump flow rate of the water and fertilizer machine, the irrigation water and fertilizer amount including the irrigation water volume, the irrigation water volume and the water pump flow rate being positively correlated and having a conversion coefficient; the method further includes: obtaining the soil environmental parameters at a target time, the target time being the time reached after a preset time after the supplementary irrigation is completed; if there is a second preset number of sub-parameters in the soil environmental parameters at the target time that are less than the lower limit of the corresponding preset parameter range, the conversion coefficient is increased based on the most recent conversion coefficient; if there is a third preset number of sub-parameters that are greater than the upper limit of the corresponding preset parameter range, the conversion coefficient is decreased based on the most recent conversion coefficient, the most recent conversion coefficient being the conversion coefficient between the water pump flow rate and the irrigation water volume in the most recently recorded execution parameters.

[0076] During the supplementary irrigation process controlled by the fertigation machine, the execution parameters corresponding to this supplementary irrigation can be recorded, forming traceable data for easy subsequent management and research. The preset duration can be set as needed, ranging from 0.5 hours to 3 hours, for example, 2 hours. For instance, soil environmental parameters can be monitored 2 hours after supplementary irrigation. Each sub-parameter in the soil environmental parameters is compared with its corresponding preset parameter range to determine deviations. If, at the target time, a second preset number of sub-parameters are less than the lower limit of their corresponding preset parameter range, the conversion coefficient between pump flow and irrigation water volume can be increased. By increasing the conversion coefficient, the corresponding pump flow can be increased while maintaining the same irrigation water volume, thus increasing pump output. Conversely, if a third preset number of sub-parameters are greater than the upper limit of their corresponding preset parameter range, the conversion coefficient can be decreased. By decreasing the conversion coefficient, the corresponding pump flow can be decreased while maintaining the same irrigation water volume, thus decreasing pump output. Any two of the first, second, and third preset quantities can be equal or unequal. The second and third preset quantities can be set as needed. For example, the second preset quantity and the third preset quantity can each be in the range of 1 to 5, such as 1, 2 or 3. It is preferable that the second preset quantity and the third preset quantity are both 1.

[0077] Most conventional irrigation control systems lack adaptive correction during long-term operation, failing to dynamically adjust control parameters based on irrigation results. This makes them prone to control failure due to sensor drift or environmental changes. The above solution records the execution parameters of the current irrigation session for future reference. If, after supplemental irrigation, a second preset number of sub-parameters are detected to be below the lower limit of their corresponding preset parameter range, the pump output can be increased by increasing the conversion coefficient. Conversely, if, after supplemental irrigation, a third preset number of sub-parameters are detected to be above the lower limit of their corresponding preset parameter range, the pump output can be decreased by decreasing the conversion coefficient. This solution adjusts water output without affecting the overall control logic, further optimizing irrigation control accuracy.

[0078] Figure 2 A schematic flowchart of an intelligent irrigation control method according to an embodiment of the present invention is shown. Note that... Figure 2 This is merely an example and not a limitation of the invention. See also Figure 2The system can perform a control operation once per hour. The control operation includes steps S210-S280. In step S210, the growth stage information of the target crop can be obtained, and the current growth stage can be determined by calling the crop growth model. In step S220, the environmental parameter conditions corresponding to the current growth stage can be determined. In step S230, soil environmental parameters related to the crop root zone of the target crop can be obtained, and it can be determined whether the soil environmental parameters meet the environmental parameter conditions. If they do, step S240 is executed, controlling the water and fertilizer machine to maintain its current working state. If they do not meet the conditions, step S250 is executed, determining the cumulative light radiation from the last irrigation time to the current time. Subsequently, in step S260, it can be determined whether supplementary irrigation is needed based on the cumulative light radiation. If supplementary irrigation is needed, steps S270 and S280 are executed. In step S270, the amount of water and fertilizer for supplementary irrigation is determined based on the cumulative light radiation. In step S280, the water and fertilizer machine is controlled to perform supplementary irrigation according to the amount of water and fertilizer for supplementary irrigation. If supplementary irrigation is not needed, step S240 is executed, controlling the water and fertilizer machine to maintain its current working state.

[0079] For example, the irrigation control system can provide an HTTP interface to the outside world through software. External systems can apply the experience data accumulated by this irrigation control system. For example, if the external system provides environmental data such as greenhouse area, soil data for the past few days, and light intensity for the past few days, the interface of the irrigation control system can return information such as whether supplementary irrigation is needed, the planned time for supplementary irrigation, and the amount of water and fertilizer for supplementary irrigation.

[0080] According to another aspect of the present invention, an intelligent irrigation control system is provided; see [link to relevant documentation]. Figure 3 The diagram shown is a schematic block diagram of an intelligent irrigation control system 300 according to an embodiment of the present invention. The intelligent irrigation control system 300 includes:

[0081] The first acquisition module 310 is used to acquire the growth stage information of the target crop and determine the environmental parameter conditions based on the growth stage information. The growth stage information is used to indicate the current growth stage of the target crop, and the environmental parameter conditions are preset parameter conditions corresponding to the current growth stage.

[0082] The second acquisition module 320 is used to acquire soil environmental parameters related to the root zone of the target crop. The soil environmental parameters are used to reflect the current water status of the crop root zone.

[0083] The judgment module 330 is used to determine whether the soil environmental parameters meet the environmental parameter conditions.

[0084] The determination module 340 is used to determine whether the target crop needs supplementary irrigation if the condition is not met, based on the cumulative light radiation from the last irrigation time to the current time; if the condition is met, it is determined that the target crop does not need supplementary irrigation.

[0085] The control module 350 determines the amount of supplemental irrigation water and fertilizer based on the cumulative radiation of sunlight when the target crop needs supplemental irrigation, and sends the amount of supplemental irrigation water and fertilizer to the water and fertilizer machine to control the water and fertilizer machine to perform supplemental irrigation.

[0086] According to another aspect of the present invention, an electronic device is also provided. See also... Figure 4 As shown, the electronic device 400 includes a processor 410 and a memory 420, wherein the memory stores computer program instructions, which are executed by the processor to perform the above-mentioned intelligent irrigation control method.

[0087] According to another aspect of the present invention, a storage medium is also provided, on which program instructions are stored. When the program instructions are executed by a computer or processor, the computer or processor performs corresponding steps of the intelligent irrigation control method described in the embodiments of the present invention, and is used to implement corresponding modules in the intelligent irrigation control method system according to the embodiments of the present invention, or the corresponding modules in the intelligent irrigation control method system described above. The storage medium may, for example, include a memory card of a smartphone, a storage component of a tablet computer, a hard disk of a personal computer, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disc read-only memory (CD-ROM), a USB memory, or any combination of the above storage media. A computer-readable storage medium may be any combination of one or more computer-readable storage media.

[0088] According to another aspect of the present invention, a computer program product is also provided, including computer program instructions, which, when executed, are used to perform the intelligent irrigation control method as described above.

[0089] Those skilled in the art can understand the specific implementation and beneficial effects of the above-described intelligent irrigation control system, electronic equipment, storage medium, and computer program products by reading the detailed description of the intelligent irrigation control method above. For the sake of brevity, they will not be described in detail here.

[0090] Although exemplary embodiments have been described herein with reference to the accompanying drawings, it should be understood that the above exemplary embodiments are merely illustrative and are not intended to limit the scope of the invention. Various changes and modifications can be made therein by those skilled in the art without departing from the scope and spirit of the invention. All such changes and modifications are intended to be included within the scope of the invention as defined by the appended claims.

[0091] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0092] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed.

[0093] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0094] Similarly, it should be understood that, in order to streamline the invention and aid in understanding one or more of the various aspects of the invention, features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof in the description of exemplary embodiments of the invention. However, this method of the invention should not be construed as reflecting an intention that the inventive conditions protected include more features than are expressly recited in each claim. Rather, as reflected in the corresponding claims, the inventive point lies in solving the corresponding technical problem with fewer features than all of those in a single disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the invention.

[0095] Those skilled in the art will understand that, apart from the mutual exclusion of features, all features disclosed in this specification (including the accompanying claims, abstract, and drawings) and all processes or units of any method or apparatus so disclosed can be combined in any combination. Unless otherwise expressly stated, each feature disclosed in this specification (including the accompanying claims, abstract, and drawings) may be replaced by an alternative feature that serves the same, equivalent, or similar purpose.

[0096] Furthermore, those skilled in the art will understand that although some embodiments herein include certain features included in other embodiments but not others, combinations of features from different embodiments are intended to be within the scope of the invention and form different embodiments. For example, any of the embodiments protected in the claims can be used in any combination.

[0097] The various component embodiments of the present invention can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some modules in an intelligent irrigation control system according to embodiments of the present invention. The present invention can also be implemented as a system program (e.g., a computer program and computer program product) for performing part or all of the methods described herein. Such programs implementing the present invention can be stored on a computer-readable medium, or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0098] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0099] The above are merely specific embodiments or descriptions of the present invention, and the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. The scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A smart irrigation control method, characterized in that, Includes the following control operations: The growth stage information of the target crop is obtained, and environmental parameter conditions are determined based on the growth stage information. The growth stage information is used to indicate the current growth stage of the target crop, and the environmental parameter conditions are preset parameter conditions corresponding to the current growth stage. Obtain soil environmental parameters related to the root zone of the target crop, the soil environmental parameters being used to reflect the current moisture status of the crop root zone; Determine whether the soil environmental parameters meet the environmental parameter conditions; If the conditions are not met, then the cumulative light radiation from the last irrigation time to the current time is used to determine whether the target crop needs supplementary irrigation; if the conditions are met, then the target crop does not need supplementary irrigation. When the target crop needs supplemental irrigation, the amount of supplemental irrigation water and fertilizer is determined based on the cumulative light radiation, and the amount of supplemental irrigation water and fertilizer is sent to the water and fertilizer machine to control the water and fertilizer machine to perform supplemental irrigation.

2. The method according to claim 1, characterized in that, The soil environmental parameters include one or more of the following sub-parameters: soil temperature, overall soil moisture, soil electrical conductivity, soil depth moisture, meteorological data, crop canopy temperature, air temperature, air humidity, and carbon dioxide concentration in the air.

3. The method according to claim 2, characterized in that, The soil depth moisture was obtained by simultaneously collecting moisture data at different depths in the crop root zone using the same sensor.

4. The method according to claim 2 or 3, characterized in that, The soil environmental parameters include at least two sub-parameters, each of which has a corresponding preset parameter range. The environmental parameter conditions include the preset parameter ranges corresponding to each of the at least two sub-parameters. Determining whether the soil environmental parameters meet the environmental parameter conditions includes: According to preset weights, the parameter deviations corresponding to each of the at least two sub-parameters are normalized and weighted to obtain a comprehensive score for the soil environmental parameters. The parameter deviation is the deviation between the sub-parameters and the preset parameter intervals corresponding to the sub-parameters. The comprehensive score is compared with a preset scoring threshold. If the comprehensive score exceeds the preset scoring threshold, the soil environmental parameter is determined to meet the environmental parameter conditions; otherwise, the soil environmental parameter is determined to not meet the environmental parameter conditions.

5. The method according to claim 2 or 3, characterized in that, Each sub-parameter in the soil environmental parameters has a corresponding preset parameter range. Determining whether the target crop needs supplemental irrigation based on the cumulative solar radiation from the last irrigation time to the current time includes: When the cumulative light radiation is greater than or equal to a preset light threshold, it is determined that the target crop needs supplemental irrigation; When the cumulative light radiation is less than the preset light threshold, and the parameter deviation between a first preset number of sub-parameters and the corresponding preset parameter interval in the soil environmental parameters is greater than or equal to the preset deviation threshold, it is determined that the target crop needs supplemental irrigation. When the cumulative light radiation is less than the preset light threshold, and there is no parameter deviation between the first preset number of sub-parameters and the corresponding preset parameter interval in the soil environmental parameters that is greater than or equal to the preset deviation threshold, it is determined that the target crop does not need supplemental irrigation.

6. The method according to claim 5, characterized in that, The method of determining whether the target crop needs supplemental irrigation based on the cumulative solar radiation from the last irrigation time to the current time also includes: Using a crop water requirement model and based on the growth stage information, a preset light threshold corresponding to the current growth stage is determined. The crop water requirement model is a correlation model between the growth stage of a reference crop and the light threshold. The reference crop is a crop of the same variety as the target crop.

7. The method according to any one of claims 1-3, characterized in that, Before determining whether the target crop needs supplemental irrigation based on the cumulative solar radiation from the last irrigation time to the current time, the control operation further includes: Acquire photosynthetically active radiation data collected by a light sensor, or acquire total radiation data collected by a light sensor and determine photosynthetically active radiation data based on the total radiation data; The cumulative light radiation is calculated based on the photosynthetically active radiation data and the light interval, wherein the light interval is the time interval between the last irrigation time and the current time.

8. The method according to any one of claims 1-3, characterized in that, The soil environmental parameters include overall soil moisture and soil electrical conductivity. The overall soil moisture has a corresponding preset parameter range. The supplementary irrigation water and fertilizer amount includes supplementary irrigation water amount and supplementary irrigation fertilizer amount. Determining the supplementary irrigation water and fertilizer amount based on the cumulative solar radiation includes: Based on the growth stage information, the cumulative light radiation, and the evapotranspiration requirement formula corresponding to the reference crop, the water requirement of the target crop is determined. Based on the parameter deviation between the overall soil moisture and the corresponding preset parameter range, and the preset soil moisture coefficient, the total soil moisture content of the crop root zone is determined. The water content deficit value is determined based on the difference between the water demand and the total soil moisture content; The amount of supplementary irrigation water is determined based on the water content deficit value and the preset water replenishment rate. Based on the soil environmental parameters and the growth stage information, the amount of irrigation fertilizer corresponding to the soil conductivity and the current growth stage is determined from the first preset database as the supplementary irrigation fertilizer amount. The first preset database is used to store the ratio table of the reference crop, and the ratio table is used to record the amount of irrigation fertilizer corresponding to different growth stages and different soil conductivity. The reference crop is a crop of the same variety as the target crop.

9. The method according to any one of claims 1-3, characterized in that, The determination of environmental parameter conditions based on the growth stage information includes: Based on the growth stage information, preset parameter conditions corresponding to the current growth stage are searched from the second preset database to determine the environmental parameter conditions. The second preset database is used to associate and store the growth stages of reference crops and the preset parameter conditions corresponding to each growth stage. The reference crops are crops of the same variety as the target crop.

10. The method according to any one of claims 1-3, characterized in that, The control operation is performed at preset time intervals, where the preset time interval is less than or equal to 1 hour.

11. The method according to any one of claims 1-3, characterized in that, The soil environmental parameters include one or more sub-parameters, each of which has a corresponding preset parameter range. After sending the supplemental irrigation water and fertilizer volume to the fertigation machine to control the fertigation machine to perform supplemental irrigation, the control operation further includes: Record the execution parameters corresponding to this supplementary irrigation. The execution parameters include the amount of irrigation water and fertilizer and the water pump flow rate of the water and fertilizer machine. The amount of irrigation water and fertilizer includes the amount of irrigation water. The amount of irrigation water and the water pump flow rate are positively correlated and have a conversion coefficient. The method further includes: The soil environmental parameters at the target time are obtained, where the target time is the time reached after a preset time after the completion of the supplementary irrigation. If, at the target time, there is a second preset number of sub-parameters in the soil environmental parameters that are less than the lower limit of the corresponding preset parameter range, then the conversion coefficient is increased based on the most recent conversion coefficient. If there is a third preset number of sub-parameters that are greater than the upper limit of the corresponding preset parameter range, then the conversion coefficient is decreased based on the most recent conversion coefficient. The most recent conversion coefficient is the conversion coefficient between the pump flow rate and the irrigation water volume in the most recently recorded execution parameters.

12. An intelligent irrigation control system, characterized in that, include: The first acquisition module is used to acquire the growth stage information of the target crop and determine the environmental parameter conditions based on the growth stage information. The growth stage information is used to indicate the current growth stage of the target crop, and the environmental parameter conditions are preset parameter conditions corresponding to the current growth stage. The second acquisition module is used to acquire soil environmental parameters related to the root zone of the target crop, the soil environmental parameters being used to reflect the current moisture status of the crop root zone; The judgment module is used to determine whether the soil environmental parameters meet the environmental parameter conditions; The determination module is used to determine whether the target crop needs supplemental irrigation if the conditions are not met, based on the cumulative light radiation from the last irrigation time to the current time; if the conditions are met, the target crop is determined not to need supplemental irrigation. The control module is used to determine the amount of supplemental irrigation water and fertilizer based on the cumulative light radiation when the target crop needs supplemental irrigation, and send the amount of supplemental irrigation water and fertilizer to the water and fertilizer machine to control the water and fertilizer machine to perform supplemental irrigation. When the target crop does not need supplemental irrigation, the control module controls the water and fertilizer machine to maintain its existing working state.

13. An electronic device comprising a processor and a memory, characterized in that, The memory stores computer program instructions, which, when executed by the processor, are used to perform the intelligent irrigation control method as described in any one of claims 1-11.

14. A computer-readable storage medium, characterized in that, The storage medium stores program instructions, which, when executed, are used to perform the intelligent irrigation control method as described in any one of claims 1-11.

15. A computer program product comprising computer program instructions, characterized in that, The computer program instructions, when executed, are used to perform the intelligent irrigation control method as described in any one of claims 1-11.

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