Intelligent irrigation operation method, device, equipment and storage medium

Abstract

The application discloses an intelligent irrigation operation method and device, equipment and a storage medium, and relates to the technical field of irrigation. The technical scheme provided by the application comprises the following steps: obtaining crop information of crops to be irrigated and operation auxiliary information of an intelligent irrigation system, determining an initial irrigation strategy according to the crop information and the operation auxiliary information; receiving a correction operation, correcting the initial irrigation strategy according to the correction operation to obtain a corrected irrigation strategy; and irrigating the crops to be irrigated according to the corrected irrigation strategy. Through the technical means, the crop information of the crops to be irrigated and the operation auxiliary information of the intelligent irrigation system are used to generate a scientific irrigation strategy, then the irrigation strategy is corrected by farmers according to experience, and a combination of scientific recommendation and irrigation experience is formed to realize the simultaneous consideration of water-saving demand and crop yield demand of the intelligent irrigation system, and the problem of poor irrigation effect of the intelligent irrigation system in the prior art is solved.

Description

Technical Field

[0001] This application relates to the field of irrigation technology, and in particular to an intelligent irrigation operation method, apparatus, equipment and storage medium. Background Technology

[0002] Smart irrigation is a modern agricultural irrigation method that utilizes technologies such as the Internet of Things (IoT), sensors, and automatic control to achieve intelligent control and management of farmland irrigation. Smart irrigation systems are suitable for various farmland irrigation scenarios, including field crop cultivation, greenhouse flower cultivation, and orchard management. These systems can control the opening of electric valves according to the crop's water requirements, achieving precise irrigation, avoiding water waste associated with traditional irrigation methods, and eliminating the need for farmers to manually open and close valves, thus significantly saving labor costs.

[0003] In existing technologies, intelligent irrigation systems rely on farmers' planting experience to set crop irrigation needs (such as irrigation volume and / or irrigation flow rate) and automatically control irrigation. However, irrigation plans developed by farmers based on their planting experience are prone to errors, making it difficult to simultaneously meet water conservation and crop yield requirements, resulting in poor irrigation performance of intelligent irrigation systems. Summary of the Invention

[0004] This application provides an intelligent irrigation operation method, device, equipment, and storage medium to generate a scientific irrigation strategy using crop information of the crop to be irrigated and operation assistance information of the intelligent irrigation system. Farmers then manually correct the irrigation strategy based on their experience, forming an irrigation plan that combines scientific recommendations with irrigation experience. This achieves the simultaneous consideration of water-saving needs and crop yield needs by the intelligent irrigation system, solving the problem of poor irrigation effect in existing intelligent irrigation systems.

[0005] Firstly, this application provides an intelligent irrigation operation method, including:

[0006] Obtain crop information of the crop to be irrigated and operation assistance information of the intelligent irrigation system, and determine the initial irrigation strategy based on the crop information and the operation assistance information;

[0007] Receive a correction operation, and correct the initial irrigation strategy according to the correction operation to obtain a corrected irrigation strategy;

[0008] The crop to be irrigated is irrigated according to the corrective irrigation strategy.

[0009] Secondly, this application provides an intelligent irrigation operation device, comprising:

[0010] The irrigation strategy determination module is configured to acquire the operation assistance information of the intelligent irrigation system and determine the initial irrigation strategy based on the operation assistance information.

[0011] An irrigation strategy correction module is configured to receive a correction operation and correct the initial irrigation strategy according to the correction operation to obtain a corrected irrigation strategy.

[0012] The irrigation operation module is configured to irrigate the crop to be irrigated according to the corrected irrigation strategy.

[0013] Thirdly, this application provides an intelligent irrigation operation device, comprising:

[0014] One or more processors; a storage device storing one or more programs that, when executed by the one or more processors, cause the one or more processors to implement the intelligent irrigation operation method as described in the first aspect.

[0015] Fourthly, this application provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the intelligent irrigation operation method as described in the first aspect.

[0016] In this application, by acquiring crop information of the crop to be irrigated and operational assistance information of the intelligent irrigation system, an initial irrigation strategy is determined based on the crop information and operational assistance information; a correction operation is received, and the initial irrigation strategy is corrected according to the correction operation to obtain a corrected irrigation strategy; the crop to be irrigated is then irrigated according to the corrected irrigation strategy. Through the above technical means, the crop assistance information of the intelligent irrigation system and the crop information of the crop to be irrigated can be scientifically analyzed and adapted to the crop to be irrigated, thereby generating a scientific irrigation strategy. Based on farmers' manual correction of the irrigation strategy based on experience, an irrigation plan combining scientific recommendations and irrigation experience is formed, so as to achieve the simultaneous consideration of water-saving needs and crop yield needs of the intelligent irrigation system, solving the problem of poor irrigation effect of existing intelligent irrigation systems. Attached Figure Description

[0017] Figure 1 This is a flowchart of an intelligent irrigation operation method provided in an embodiment of this application;

[0018] Figure 2 This is a flowchart illustrating the generation of an initial irrigation strategy provided in an embodiment of this application;

[0019] Figure 3 This is a flowchart of the irrigation strategy generation method provided in the embodiments of this application;

[0020] Figure 4 This is one of the flowcharts for the irrigation demand-based correction irrigation strategy provided in the embodiments of this application;

[0021] Figure 5This is the second flowchart of the irrigation demand-based correction irrigation strategy provided in the embodiments of this application;

[0022] Figure 6 This is one of the schematic diagrams of the calibration interface provided in the embodiments of this application;

[0023] Figure 7 This is a second schematic diagram of the calibration interface provided in the embodiments of this application;

[0024] Figure 8 This is the third schematic diagram of the calibration interface provided in the embodiments of this application;

[0025] Figure 9 This is a flowchart of the irrigation process for the crop to be irrigated, provided in an embodiment of this application;

[0026] Figure 10 This is a schematic diagram of the structure of an intelligent irrigation operation device provided in an embodiment of this application;

[0027] Figure 11 This is a schematic diagram of the structure of an intelligent irrigation operation device provided in an embodiment of this application. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this application clearer, specific embodiments of this application will be described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely for explaining this application and not for limiting it. It should also be noted that, for ease of description, only the parts relevant to this application are shown in the drawings, not all of them. Before discussing exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. A process can be terminated when its operation is completed, but it may also have additional steps not included in the drawings. A process can correspond to a method, function, procedure, subroutine, subroutine, etc.

[0029] The terms "first," "second," etc., used in the specification and claims of this application are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this application can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0030] In some implementation methods, intelligent irrigation systems rely on farmers' planting experience to set the irrigation needs of crops (such as irrigation volume and / or irrigation flow rate) and then automatically control the irrigation. However, the irrigation plans formulated by farmers based on their planting experience are often flawed, making it difficult to simultaneously meet both water conservation and crop yield requirements, resulting in poor irrigation performance of intelligent irrigation systems.

[0031] To address the problems existing in the above-mentioned implementation methods, this embodiment provides an intelligent irrigation operation method. This method uses crop information of the crop to be irrigated and operation assistance information of the intelligent irrigation system to generate a scientific irrigation strategy. Farmers then manually correct the irrigation strategy based on their experience, forming an irrigation plan that combines scientific recommendations with irrigation experience. This allows the intelligent irrigation system to simultaneously meet the needs of water conservation and crop yield.

[0032] The intelligent irrigation method provided in this embodiment can be executed by intelligent irrigation equipment, which can be implemented through software and / or hardware. This intelligent irrigation equipment can consist of two or more physical entities, or it can consist of a single physical entity. For example, the intelligent irrigation equipment can be an intelligent irrigation system. An intelligent irrigation system is a system for irrigating crops planted within a planting area. It includes a control terminal, a monitoring terminal, and an execution terminal. The control terminal can be a cloud server deployed in the cloud or a computer device deployed on-site. The monitoring terminal is a sensor device deployed within the planting area to collect various sensor data, such as temperature and humidity sensors, pressure sensors, and weather sensors. The execution terminal is a response device deployed within the planting area to respond to control commands from the control terminal to irrigate or stop irrigation, such as a smart valve installed in the irrigation pipeline. Furthermore, the intelligent irrigation equipment can also be the control terminal of an intelligent irrigation system, such as a cloud server or a computer device.

[0033] The intelligent irrigation equipment is equipped with at least one type of operating system. Based on this operating system, the equipment can install at least one application. This application can be a built-in application of the operating system or an application downloaded from a third-party device or server. In this embodiment, the intelligent irrigation equipment has at least one application capable of executing intelligent irrigation methods.

[0034] For ease of understanding, this embodiment uses a computer device as the main body for executing the intelligent irrigation operation method as an example for description.

[0035] Figure 1 A flowchart of an intelligent irrigation operation method provided in an embodiment of this application is given. (Reference) Figure 1 The intelligent irrigation operation method specifically includes:

[0036] S110. Obtain crop information of the crop to be irrigated and operation assistance information of the intelligent irrigation system, and determine an initial irrigation strategy based on the crop information and the operation assistance information.

[0037] The term "crop to be irrigated" refers to crops within the irrigated planting area. Crop information includes one or more of the following: crop type, growth stage, planting information, and pest and disease information. For example, a user can log into the management interface of the intelligent irrigation system using a computer device. When configuring the irrigation task in the management interface, the user can add the crop information of the crop to be irrigated to the task. In addition, the management interface can display multiple planting areas. The user can select one of these areas as the planting area for the crop to be irrigated in the task, thereby obtaining the crop type, growth stage, planting information, and pest and disease information based on the planting area. Specifically, the planting area is equipped with a visual sensor that can collect images of the crop to be irrigated within the planting area. The image analysis reveals the growth stage and pest and disease information of the crop to be irrigated. The planting area is then associated with and saved with the latest analyzed growth stage and pest and disease information of the crop to be irrigated, so that the latest growth stage and pest and disease information of the crop to be irrigated can be obtained based on the planting area when generating the irrigation strategy. The crop type and planting information can be associated and saved with the corresponding planting area when the crop to be irrigated is initially planted. When generating an irrigation strategy, the crop type and planting information of the crop to be irrigated can be directly obtained based on the planting area.

[0038] Operational support information refers to information used to help determine the irrigation strategy for the crop to be irrigated. For example, crop support information can be preset irrigation needs, historical operation data, and real-time sensor data. The initial irrigation strategy is an irrigation strategy scientifically implemented after using the crop information of the crop to be irrigated based on the operational support information. It includes irrigation duration, irrigation frequency, and irrigation water volume.

[0039] For example, crop-aided information includes preset irrigation requirements, which are the irrigation needs of the crops to be irrigated configured by the user. These requirements can be specific irrigation parameters or goals for saving water resources or increasing crop yield. The range of irrigation parameters for the crops to be irrigated is determined based on the preset requirements, and then appropriate parameter values ​​are selected within this range based on the crop information to generate an initial irrigation strategy. Alternatively, crop-aided information includes multiple sets of historical operational data. The mapping relationship between the crop information of historically irrigated crops and the corresponding suitable irrigation strategies under various conditions can be analyzed based on these historical data. An initial irrigation strategy is then generated based on this mapping relationship and the crop information of the crops to be irrigated. In addition, crop-aided information includes real-time sensor data, such as current soil moisture and weather information. An initial irrigation strategy can be generated based on this real-time sensor data and the crop information of the crops to be irrigated.

[0040] Optionally, the operational support information includes multiple sets of historical operational data and preset irrigation requirements. An irrigation strategy can be generated using the historical operational data, and then the initial irrigation strategy can be obtained by making preliminary adjustments based on the preset irrigation requirements. For example, Figure 2 This is a flowchart illustrating the generation of an initial irrigation strategy provided in an embodiment of this application. For example... Figure 2 As shown, the steps for generating the initial irrigation strategy specifically include S1101-S1102:

[0041] S1101. Based on historical operation data and crop information of the crop to be irrigated, determine the irrigation strategy for the crop to be irrigated.

[0042] For example, a set of historical operation data is the data recorded by the intelligent irrigation system when it previously irrigated the crops in the planting area. It includes crop information in the planting area at the time of the corresponding irrigation operation, various sensor data collected by the monitoring terminal during the irrigation process, and irrigation data when the irrigation pipeline irrigates the crops in the planting area.

[0043] Optionally, crop information includes crop type, growth stage, planting information, and pest and disease information; sensor data includes actual soil moisture and actual pipeline pressure; and irrigation data includes actual irrigation duration, actual irrigation frequency, and actual irrigation water volume. Planting information can include crop planting density, planting quantity, and / or planting area. The actual irrigation frequency refers to the number of times the irrigation pipeline irrigates the crop within the corresponding irrigation operation cycle. For example, if the irrigation operation cycle is 0:00–24:00, and the irrigation pipeline irrigates the crop three times during this period, with each irrigation occurring between 7:00–10:00, 12:00–15:00, and 16:00–19:00, then the actual irrigation frequency for this operation is 3. The actual irrigation duration is the duration of one irrigation operation within the corresponding irrigation operation cycle, such as 3 hours for the above-mentioned irrigation operation. The actual irrigation water volume is the amount of water used for one irrigation operation within the corresponding irrigation operation cycle.

[0044] For example, before irrigating crops in a planting area, staff configure the corresponding irrigation task information on a computer. This task information may include preset irrigation times, preset irrigation duration, and preset irrigation water volume. The computer generates control commands for the smart valve based on these preset parameters, sending them to the smart valve to control the irrigation pipeline and irrigate the crops in the planting area. Since the computer generates the control commands based on the task information, the preset irrigation times, duration, and volume are equivalent to the actual number of irrigations, duration, and volume for this operation. These parameters can be recorded as the actual number of irrigations, duration, and volume for the corresponding irrigation operation. Alternatively, during irrigation, staff can remotely control the opening, closing, and degree of the smart valve via the computer. The opening and closing of the smart valve determines the actual number of irrigations and duration, while the degree of opening determines the actual irrigation water volume.

[0045] During irrigation, soil moisture sensors installed in the planting area collect moisture data as the actual soil moisture for the operation, and pressure gauges installed in the irrigation pipeline collect pressure data as the actual pressure for the operation. Visual sensors are installed in the planting area to capture crop images, identifying crop type, growth stage, and planting information, as well as analyzing crop pest and disease information. Alternatively, drones can fly over the planting area to take aerial images of the crops, identifying crop type, growth stage, and planting information, and analyzing pest and disease information. In addition, staff can manually input crop type, growth stage, planting information, and pest and disease information for the operation.

[0046] Afterwards, the irrigation data, sensor data, and crop information from each irrigation operation are linked and saved as corresponding historical operation data.

[0047] When generating irrigation strategies, a set of historical operation data can be used as a set of sample data, with crop information from the historical operation data serving as input data and irrigation data from the historical operation data serving as label information. An irrigation strategy prediction model is trained based on multiple sets of sample data, enabling the trained model to predict the corresponding irrigation strategy based on the crop information of the crop to be irrigated. The irrigation strategy prediction model can be a deep neural network or a random forest network, etc.

[0048] Understandably, irrigation data in historical irrigation records is set by staff based on practical experience. By analyzing and modeling this historical data, vague concepts such as "appropriate irrigation" from manual irrigation experience can be transformed into specific quantitative indicators, thereby achieving more precise irrigation control. Moreover, manual irrigation experience often considers multiple factors such as crop type, growth stage, planting quantity, planting density, and pests and diseases to determine irrigation strategies. Historical irrigation data also contains information about these factors. During training, the model can learn the complex relationship between these factors and irrigation strategies, thus providing more accurate irrigation predictions under different planting conditions, which is more comprehensive and accurate than relying solely on manual experience for irrigation.

[0049] Because manual irrigation can lead to misjudgments, historical data may contain instances of inappropriate irrigation. To address this, reasonable irrigation data can be selected as positive samples, and inappropriate irrigation data as negative samples. An irrigation strategy prediction model can then be trained using these positive and negative samples to determine the appropriate irrigation strategy for the crop, thereby improving the accuracy of irrigation control. Optionally, Figure 3 This is a flowchart illustrating the irrigation strategy generation method provided in an embodiment of this application. Figure 3 As shown, the steps for generating the irrigation strategy specifically include S11011-S11013:

[0050] S11011. Based on the sensor data and irrigation data in the historical operation data, the historical operation data is divided into positive sample data or negative sample data, and the irrigation data of the historical operation data is used as the label information of the corresponding sample data.

[0051] For example, the actual number of irrigations, actual irrigation duration, and actual irrigation volume in the irrigation data are set by workers based on their assessment of crop type, growth stage, soil moisture, and pipe size. During operation, the pipe pressure and soil moisture values ​​remain at normal levels. If they exceed these levels, it indicates an anomaly in the operation, and a correct mapping relationship cannot be formed between the irrigation data and crop information. Therefore, historical operation data corresponding to pipe pressure and soil moisture values ​​not exceeding normal levels during the operation are used as positive sample data, while historical operation data corresponding to pipe pressure and soil moisture values ​​exceeding normal levels are used as negative sample data. This allows the irrigation strategy prediction model to learn the correct mapping relationship between irrigation data and crop information from the positive sample data when training the model, while the negative sample data helps the model better learn the decision boundary, avoiding overfitting to the positive samples and enhancing the model's generalization ability.

[0052] Optionally, if the sensor data in the historical operation data includes actual soil moisture and actual pipeline pressure, and the irrigation data in the historical operation data includes actual irrigation duration, actual irrigation frequency, and actual irrigation water volume, the expected soil moisture can be determined based on the actual irrigation duration, actual irrigation frequency, and actual irrigation water volume, and the expected pipeline pressure can be determined based on the actual irrigation duration and actual irrigation water volume. If the difference between the expected soil moisture and the actual soil moisture is greater than a preset moisture difference, or the difference between the expected pipeline pressure and the actual pipeline pressure is greater than a preset pressure difference, the historical operation data is classified as negative sample data. If the difference between the expected soil moisture and the actual soil moisture is less than or equal to the preset moisture difference, and the difference between the expected pipeline pressure and the actual pipeline pressure is less than or equal to the preset pressure difference, the historical operation data is classified as positive sample data.

[0053] The desired soil moisture is the soil moisture value that workers expect when irrigating crops based on irrigation data. The total irrigation water volume during the operation is determined based on the actual irrigation duration, number of irrigations, and actual irrigation water volume. The average soil moisture is then determined based on the total irrigation water volume and weather information, and this average soil moisture is defined as the desired soil moisture. The average moisture data collected by the soil moisture sensor during the operation is defined as the actual soil moisture, and the difference between the desired and actual soil moisture is calculated. If the moisture difference is less than or equal to the preset moisture difference, it indicates that the actual soil moisture is within the normal range; if the moisture difference is greater than the preset moisture difference, it indicates that the actual soil moisture exceeds the normal range.

[0054] The desired pipeline pressure is the pressure value that workers expect to apply when irrigating crops based on irrigation data. The irrigation flow rate during the operation can be determined based on the actual irrigation volume and duration. The average pipeline pressure is then determined based on the irrigation flow rate and pipeline dimensions, and this average pressure is defined as the desired pipeline pressure. The average pressure data collected by the pipeline pressure gauge during the operation is defined as the actual pipeline pressure. The pressure difference between the desired and actual pipeline pressures is calculated. If the pressure difference is less than or equal to the preset pressure difference, the actual pipeline pressure is within the normal pressure range. If the pressure difference is greater than the preset pressure difference, the actual pipeline pressure exceeds the normal pressure range.

[0055] When both actual pipeline pressure and actual soil moisture are within the normal range, a correct mapping relationship is formed between irrigation data and crop information in the corresponding historical operation data. Therefore, the historical operation data is used as positive sample data. When at least one of the actual pipeline pressure and actual soil moisture exceeds the normal range, a correct mapping relationship cannot be formed between irrigation data and crop information in the corresponding historical operation data. Therefore, the historical operation data is used as negative sample data.

[0056] This embodiment utilizes irrigation data to analyze the expected soil moisture and expected pipeline pressure during the corresponding operation process. Based on the expected soil moisture and expected pipeline pressure, it determines whether the actual soil moisture and actual pipeline pressure during the corresponding operation process are within the normal range. This effectively distinguishes abnormal data from normal data in historical operation data, thereby accurately classifying positive sample data from negative sample data and improving the accuracy of sample data acquisition.

[0057] S11012. Based on the positive sample data and negative sample data of each group, construct an irrigation strategy prediction model.

[0058] This embodiment uses a neural network model as an example to describe the irrigation strategy prediction model. Crop information from the sample data is input into a pre-built neural network model. The model extracts crop features from the crop information and predicts irrigation strategies based on these features, including the number of irrigations, irrigation duration, and irrigation water volume. A loss value is calculated between the predicted irrigation strategy and the label information of the sample data (i.e., the irrigation data) based on a preset loss function. The model parameters of the neural network model are then optimized through backpropagation based on this loss value.

[0059] Optionally, if the crop information in the historical operation data includes crop type, growth stage, planting information, and pest and disease information, and the irrigation data includes actual irrigation frequency, actual irrigation duration, actual irrigation water volume, pesticide type, and pesticide concentration, the crop type, growth stage, planting information, and pest and disease information from the positive or negative sample data can be input into the irrigation strategy prediction model to obtain the irrigation strategy output by the irrigation strategy prediction model. The irrigation strategy includes irrigation duration, irrigation frequency, irrigation water volume, pesticide type, and pesticide concentration. The loss value is determined based on the output irrigation strategy and the label information of the positive or negative sample data, and the model parameters of the irrigation strategy prediction model are adjusted based on the loss value.

[0060] For example, crop type, growth stage, planting information, and pest and disease information from sample data are input into a pre-built neural network model. The neural network model extracts and concatenates feature information from these data, and then predicts and outputs irrigation duration, irrigation frequency, irrigation water volume, pesticide type, and pesticide concentration based on the concatenated feature information. The loss value is calculated by comparing the predicted irrigation duration, irrigation frequency, irrigation water volume, pesticide type, and pesticide concentration with the actual irrigation frequency, actual irrigation duration, actual irrigation water volume, pesticide type, and pesticide concentration from the label information of the sample data. The model parameters of the neural network model are then optimized through backpropagation based on the loss value. This is the process of training a neural network model once using sample data. Once the training iterations of the neural network model reach their maximum or the model parameters meet the convergence condition, the training is considered complete, and the trained neural network model is used as the irrigation strategy prediction model. Understandably, the neural network model, after multiple training sessions, learns the complex mapping relationship between crop type, growth stage, planting information, and pest and disease information and irrigation duration, irrigation frequency, irrigation water volume, pesticide type, and pesticide concentration. Thus, when the irrigation strategy prediction model is formally applied to the irrigation system, it can accurately predict the appropriate irrigation duration, irrigation frequency, irrigation water volume, pesticide type, and pesticide concentration based on the crop type, growth stage, planting information, and pest and disease information of the crop to be irrigated.

[0061] This embodiment enriches the feature information of the sample data by adding crop disease and pest information to the crop information, and enriches the content of irrigation strategies by adding pesticide concentration and pesticide type to the irrigation data. When training the irrigation strategy prediction model, it delves into the degree of influence of various information in the crop information on the irrigation data, thereby improving the prediction accuracy of irrigation strategies.

[0062] S11013. Determine the irrigation strategy for the crop to be irrigated by using the irrigation strategy prediction model and the crop information of the crop to be irrigated.

[0063] For example, crop information such as crop type, growth stage, planting quantity, and planting area can be input into the irrigation strategy prediction model to obtain the irrigation duration, number of irrigations, and irrigation volume output by the model. Alternatively, crop information such as crop type, growth stage, planting quantity, planting area, and pest and disease information can be input into the irrigation strategy prediction model to obtain the irrigation duration, number of irrigations, irrigation volume, pesticide type, and pesticide concentration output by the model.

[0064] This embodiment trains an irrigation strategy prediction model using historical operation data as sample data. The irrigation strategy prediction model delves into the mapping relationship between crop information and irrigation strategy, and can quickly and accurately predict the irrigation strategy for the crop to be irrigated based on the corresponding input crop information.

[0065] S1102. The irrigation strategy is corrected according to the preset irrigation requirements to obtain the initial irrigation strategy.

[0066] For example, when the irrigation demand is to conserve water resources, the total irrigation water volume can be determined based on the irrigation water volume and irrigation frequency in the irrigation strategy. The total irrigation water volume of the irrigation strategy can be assessed based on the local water resource situation to determine whether it exceeds the standard. If it does, the irrigation water volume, irrigation duration, or irrigation frequency can be reduced.

[0067] Optionally, irrigation requirements may include a preset total irrigation volume and a preset irrigation flow rate. The preset total irrigation volume is the total water volume for the crop to be irrigated during the current irrigation operation, as set by the user. The preset total irrigation volume and preset irrigation flow rate can be configured by the user via computer. For example, when configuring the irrigation task in the management interface of the intelligent irrigation system using a computer, the user can input the preset total irrigation volume and preset irrigation flow rate for the crop to be irrigated. Assuming the irrigation strategy includes irrigation duration, number of irrigations, and irrigation water volume... Figure 4 This is one of the flowcharts for an irrigation demand-based correction irrigation strategy provided in this application embodiment. For example... Figure 4 As shown, the steps for adjusting irrigation strategies based on irrigation demand specifically include S11021-S11022:

[0068] S11021. Determine the expected total irrigation amount based on irrigation water volume and irrigation frequency, and determine the expected irrigation flow rate based on irrigation water volume and irrigation duration.

[0069] For example, the product of irrigation water volume and irrigation frequency is used as the expected total irrigation volume, and the ratio of irrigation water volume to irrigation duration is used as the expected irrigation flow rate.

[0070] S11022. Based on the expected total irrigation volume, expected irrigation flow rate, preset total irrigation volume, and preset irrigation flow rate, adjust the irrigation duration, number of irrigations, and / or irrigation water volume in the irrigation strategy to obtain the initial irrigation strategy.

[0071] For example, if the expected total irrigation volume is less than or equal to the preset total irrigation volume and the expected irrigation flow rate is less than or equal to the preset irrigation flow rate, the irrigation strategy is not adjusted. If the expected total irrigation volume is greater than the preset total irrigation volume, the irrigation water volume in the irrigation strategy is adjusted to the ratio of the preset total irrigation volume to the number of irrigations in the irrigation strategy. Then, the expected irrigation flow rate is re-determined based on the adjusted irrigation water volume and irrigation duration. If the newly determined expected irrigation flow rate is greater than the preset irrigation flow rate, the irrigation duration in the irrigation strategy is adjusted to the ratio of the adjusted irrigation water volume to the preset irrigation flow rate.

[0072] In addition, the desired irrigation flow rate and the preset irrigation flow rate can be weighted and summed, and the desired irrigation water volume and the preset irrigation water volume can be weighted and summed. Based on the irrigation flow rate and irrigation water volume obtained by the weighted summation, the irrigation duration, irrigation frequency and / or irrigation water volume in the irrigation strategy can be adjusted. The weight coefficients of the desired irrigation flow rate, the preset irrigation flow rate, the desired irrigation water volume and the preset irrigation water volume can be set according to actual needs.

[0073] In another embodiment, the predicted irrigation demand includes a preset total irrigation volume, a preset irrigation flow rate, a preset pesticide type, and a preset pesticide concentration; the irrigation strategy includes irrigation duration, irrigation frequency, irrigation water volume, pesticide type, and pesticide concentration. Accordingly, Figure 5 This is the second flowchart of the irrigation demand-based correction irrigation strategy provided in the embodiments of this application. Figure 5 As shown, the steps for adjusting irrigation strategies based on irrigation demand specifically include S11023-S11025:

[0074] S11023. Display the preset pesticide type and the pesticide type in the irrigation strategy on the calibration interface.

[0075] For example, after a user configures preset irrigation total volume, preset irrigation flow rate, preset pesticide type, and preset pesticide concentration in the management interface displayed on the computer device, the computer device compares whether the preset pesticide type is consistent with the pesticide type in the irrigation strategy. If they are inconsistent, a calibration interface is opened through the management interface, displaying both the preset pesticide type and the pesticide type in the irrigation strategy. Specifically, Figure 6 This is one of the schematic diagrams of the calibration interface provided in the embodiments of this application. For example... Figure 6 As shown, the calibration interface 10 displays a first selection control 11 corresponding to a preset pesticide type and a second selection control 12 for pesticide types in the irrigation strategy. The preset pesticide type is pesticide A, and the pesticide type in the irrigation strategy is pesticide B. Users can select pesticide A or pesticide B as the pesticide to be sprayed for the crop to be irrigated according to the actual situation of the crop.

[0076] S11024. Receive a selection operation for a preset pesticide type or a pesticide type in an irrigation strategy, and use the selected type corresponding to the selection operation as the pesticide type of the initial irrigation strategy.

[0077] refer to Figure 6 When the user clicks the first selection control 11 or the second selection control 12, a selection operation is triggered. Based on the control triggered by the selection operation, the pesticide type selected by the user is determined to be pesticide A or pesticide B, and thus the selected pesticide type is used as the pesticide type in the initial irrigation strategy.

[0078] S11025. Based on the preset total irrigation volume, preset irrigation flow rate, and preset pesticide concentration, adjust the irrigation duration, irrigation frequency, irrigation water volume, and / or pesticide concentration in the irrigation strategy to obtain the initial irrigation strategy.

[0079] For example, if the pesticide concentration is higher than the preset pesticide concentration, the preset pesticide concentration can be used as the pesticide concentration in the initial irrigation strategy. Then, the irrigation duration, number of irrigations, and / or irrigation volume in the irrigation strategy are adjusted according to the process shown in step S11022, and the adjusted irrigation duration, number of irrigations, and / or irrigation volume are used as the irrigation duration, number of irrigations, and / or irrigation volume in the initial irrigation strategy. This embodiment corrects the predicted irrigation strategy by using preset irrigation total volume, preset irrigation flow rate, preset pesticide concentration, and / or preset pesticide type configured by the user in the irrigation requirements, so that the initial irrigation strategy meets the irrigation requirements while highly adapting to the growth requirements of the crop to be irrigated, thus improving irrigation accuracy.

[0080] This embodiment utilizes crop information from historical irrigation data of an intelligent irrigation system to scientifically analyze the precise mapping relationship between irrigated crops and suitable irrigation strategies under various conditions. Based on this precise mapping relationship and crop information of the crop to be irrigated, a scientific irrigation strategy is generated. The irrigation strategy is then adjusted based on preset irrigation needs to form a scientifically recommended irrigation plan that meets those needs, thus achieving a balance between water conservation and crop yield requirements within the intelligent irrigation system.

[0081] S120: Receive the correction operation, correct the initial irrigation strategy according to the correction operation, and obtain the corrected irrigation strategy.

[0082] The corrected irrigation strategy is the irrigation strategy after correcting the initial irrigation strategy. For example, after determining the initial irrigation strategy, it can be displayed in the correction interface so that the user can manually adjust the irrigation frequency, irrigation water volume, irrigation duration, pesticide concentration, and pesticide type in the initial irrigation strategy. The corrected irrigation strategy is obtained after the user manually adjusts the initial irrigation strategy. The correction operation is the operation entered by the user when adjusting the data in the initial irrigation strategy through the correction interface.

[0083] Furthermore, after determining the initial irrigation strategy based on preset irrigation requirements, the initial irrigation strategy and the preset irrigation requirements can be presented in a data comparison on the calibration interface. This allows users to more intuitively understand the difference between the initial irrigation strategy and the preset irrigation requirements. If the difference is too large, users can directly adjust various data in the initial irrigation strategy through the calibration interface. Optionally, after obtaining the initial irrigation strategy, the data in the initial irrigation strategy and the data in the preset irrigation requirements are displayed on the calibration interface; adjustment operations on the data in the initial irrigation strategy are received, and the data in the initial irrigation strategy is adjusted according to the adjustment operations to obtain the calibrated irrigation strategy. Figure 7 This is a second schematic diagram of the calibration interface provided in the embodiments of this application. For example... Figure 7 As shown, the total irrigation volume and irrigation flow rate are calculated based on the irrigation frequency, irrigation water volume, and irrigation duration in the initial irrigation strategy. The calculated total irrigation volume, irrigation flow rate, and pesticide concentration corresponding to the initial irrigation strategy, as well as the preset total irrigation volume, preset irrigation flow rate, and preset pesticide concentration from the preset irrigation requirements, are displayed in the calibration interface as bar charts, with data of the same type displayed close together. For example, two bars representing total irrigation volumes are displayed together, two bars representing irrigation flow rates are displayed together, and two bars representing pesticide concentrations are displayed together. The greater the height difference between the bars displayed together, the greater the difference in the corresponding data type. Figure 7 The large height difference in the bars representing the total irrigation amount indicates that the total irrigation amount calculated according to the initial irrigation strategy is much smaller than the preset total irrigation amount. If the user believes that the total irrigation amount calculated according to the initial irrigation strategy is too small, they can select the bar representing the total irrigation amount corresponding to the initial irrigation strategy and stretch it upwards to trigger an adjustment operation. The adjusted total irrigation amount is determined based on the movement distance during the adjustment operation, and the irrigation water volume and / or irrigation frequency in the initial irrigation strategy are adjusted based on the adjusted total irrigation amount. Similarly, when the irrigation flow rate or pesticide concentration corresponding to the initial irrigation strategy is selected and stretched or compressed, an adjustment operation for the irrigation flow rate or pesticide concentration is triggered. The adjusted irrigation flow rate or pesticide concentration is determined based on the movement distance during the adjustment operation, and the irrigation water volume and / or irrigation duration in the initial irrigation strategy are adjusted based on the adjusted irrigation flow rate, and the pesticide concentration in the initial irrigation strategy is adjusted based on the adjusted pesticide concentration.

[0084] In addition, the correction interface can display a comparison of the corrected irrigation strategies and irrigation requirements of the current job and historical jobs, so that users can refer to the differences in the corrected irrigation strategies and irrigation requirements of historical jobs to adjust the initial irrigation strategy of the current job. Figure 8 This is the third schematic diagram of the calibration interface provided in the embodiments of this application. For example... Figure 8As shown, T3 represents the operation time of this irrigation operation, T1 represents the historical operation time at a preset interval of T3, and T2 represents the historical operation time of an irrigation operation between T1 and T3. Based on the preset duration, the corrected irrigation strategies and irrigation requirements of all historical operations prior to this operation are obtained. The total irrigation volume corresponding to the obtained corrected irrigation strategies and irrigation requirements is displayed in a bar chart. The total irrigation volume corresponding to the corrected irrigation strategies and irrigation requirements within the same historical operation is displayed together to show the differences in the total irrigation volume corresponding to the corrected irrigation strategies and irrigation requirements within the corresponding historical operations. Users can select the bar corresponding to the total irrigation volume of the initial irrigation strategy for the current operation (T3) and drag it upwards to trigger an adjustment operation on the total irrigation volume. The adjusted total irrigation volume is determined based on the movement distance during the adjustment operation, and the irrigation water volume and / or irrigation frequency in the initial irrigation strategy are adjusted based on the adjusted total irrigation volume. Similarly, the initial irrigation strategy and irrigation requirements of the current operation, as well as the irrigation flow rate and pesticide concentration corresponding to the corrected irrigation strategies and irrigation requirements of historical operations, can also be displayed in a bar chart. The format of the bar chart is referenced below. Figure 8 The initial irrigation strategy for the current operation can be adjusted by using a bar chart corresponding to irrigation flow rate and pesticide concentration. The adjustment process is similar to the adjustment process for total irrigation volume.

[0085] This embodiment presents a bar chart comparing the initial irrigation strategy's total irrigation volume, irrigation flow rate, and pesticide concentration with the preset irrigation volume, preset irrigation flow rate, and preset pesticide concentration in the preset irrigation requirements on the calibration interface. This allows users to intuitively understand the differences between the initial irrigation strategy and the preset irrigation volume, thereby enabling them to adjust the initial irrigation strategy more quickly and improving the ease of adjustment.

[0086] S130. Irrigate the crop to be irrigated according to the corrected irrigation strategy.

[0087] For example, the specific irrigation time period in the current irrigation operation is determined based on the irrigation duration and number of irrigations in the corrected irrigation strategy. The opening and closing times of the electric valves of the irrigation pipelines deployed in the planting area are determined based on the irrigation time period. The irrigation flow rate for each irrigation time period in the current irrigation operation is determined based on the irrigation duration and irrigation volume in the corrected irrigation strategy. The valve opening degree of the electric valves in each irrigation time period is determined based on the irrigation flow rate. The irrigation pipelines are controlled to irrigate the crops in the planting area at the corresponding irrigation flow rate during the corresponding irrigation time period based on the opening and closing times and valve opening degrees of the electric valves.

[0088] Optionally, soil moisture and weather conditions in the planting area can affect the actual water requirements of crops and pesticide concentrations. Therefore, irrigation can be carried out on crops to be irrigated based on soil moisture and / or weather information, while adjusting irrigation strategies. Figure 9This is a flowchart illustrating the irrigation process for crops to be irrigated, provided in an embodiment of this application. For example... Figure 9 As shown, the steps for irrigating the crop to be irrigated specifically include S1301-S1303:

[0089] S1301. Obtain soil moisture and / or weather information.

[0090] For example, soil moisture is collected in real time by a soil moisture sensor, and / or weather information is collected in real time by a weather sensor. The weather information includes the weather type at various times during the current irrigation process, such as cloudy, sunny and rainy days, as well as key data corresponding to each weather type, such as the light intensity on cloudy and sunny days and the rainfall on rainy days.

[0091] S1302. Based on soil moisture and / or weather information and adjusted irrigation strategies, determine the opening time, valve opening degree, and closing time of the electric valves in the irrigation pipeline.

[0092] For example, the specific irrigation time period in the current irrigation operation is determined based on the irrigation duration and number of irrigations in the corrected irrigation strategy. The opening and closing times of the electric valves of the irrigation pipelines deployed in the planting area are then determined based on the irrigation time period. The irrigation flow rate for each irrigation time period in the current irrigation operation is determined based on the irrigation duration and irrigation water volume in the corrected irrigation strategy. The valve opening degree of the electric valve is determined based on the real-time soil moisture and irrigation flow rate for each irrigation time period to avoid over-irrigation or under-irrigation of crops.

[0093] Alternatively, based on the irrigation duration and frequency in the corrected irrigation strategy, as well as weather information, the specific irrigation time periods during the current irrigation operation can be determined. The opening and closing times of the electric valves in the irrigation pipelines deployed in the planting area can then be determined based on these irrigation time periods. Furthermore, the irrigation flow rate for each irrigation time period can be determined based on the irrigation duration and water volume in the corrected irrigation strategy. Finally, the valve opening degree of the electric valves can be determined based on the rainfall or sunlight intensity and the irrigation flow rate during each irrigation time period, thus preventing over-irrigation or under-irrigation of crops.

[0094] In addition, rainfall and sunshine periods can be determined based on weather information, along with the rainfall amount during rainfall periods and the light intensity during sunshine periods. Based on soil moisture, rainfall periods and corresponding rainfall amounts, sunshine periods and corresponding light intensities, and adjusted irrigation strategies, the irrigation time period and irrigation flow rate for each irrigation can be determined. Furthermore, based on the irrigation time period and irrigation flow rate for each irrigation, the opening time, valve opening degree, and closing time of the electric valves in the irrigation pipeline can be determined. For example, the periods of rainfall in the weather information are defined as rainfall periods, and the rainfall amount within these periods is obtained. The periods of no rainfall in the weather information are defined as sunshine periods, and the light intensity within these sunshine periods is obtained. To conserve irrigation water, irrigation should ideally be carried out during rainfall periods, allowing for the addition of a small amount of water or even no irrigation at all to meet the crop's water requirements. To address this, at least one irrigation period can be determined based on the rainfall period, irrigation duration, and number of irrigations. If there are still irrigations remaining after determining at least one irrigation period during the rainfall period, the remaining irrigation periods should be determined during the sunshine period. During the sunshine period, periods with lower light intensity should be selected for irrigation to avoid rapid evaporation of irrigation water and sudden drops in soil temperature. After determining the irrigation period, the irrigation water volume should be adjusted based on the rainfall or light intensity and real-time soil moisture. The irrigation flow rate should be determined based on the adjusted irrigation water volume and the duration of the irrigation period. The opening and closing times of the electric valve should be determined based on the irrigation period, and the valve opening degree should be determined based on the irrigation flow rate.

[0095] Optionally, when irrigating crops with pesticides, a proportional valve can be used as the electric valve of the irrigation pipeline to control the pesticide concentration of the water discharged from the irrigation pipeline. The proportional valve outputs water and pesticide through a first outlet and a second outlet, respectively. When using a proportional valve to control the irrigation pipeline for irrigating crops, the irrigation time period, irrigation flow rate, and irrigation concentration for each irrigation can be determined based on soil moisture, rainfall period and corresponding rainfall amount, sunshine period and corresponding light intensity, as well as the irrigation duration, number of irrigations, irrigation water volume, and pesticide concentration in the corrected irrigation strategy. Based on the irrigation time period, irrigation flow rate, and irrigation concentration for each irrigation, the opening time and closing time of the proportional valve, and the opening degree of the first and second outlets can be determined.

[0096] For example, the irrigation period is determined based on the rainfall period and corresponding rainfall amount, the sunshine period and corresponding light intensity, and the irrigation duration and number of irrigations in the corrected irrigation strategy. Then, the irrigation volume is adjusted based on the rainfall or light intensity during the irrigation period and the real-time soil moisture. The irrigation flow rate is determined based on the adjusted irrigation volume and the duration of the irrigation period. If the pesticide concentration in the corrected irrigation strategy changes after the irrigation volume changes, the total pesticide amount will change. To maintain a constant total pesticide amount, the pesticide concentration in the corrected irrigation strategy can be increased or decreased based on the adjusted irrigation volume, and the adjusted pesticide concentration is used as the irrigation concentration. The opening and closing times of the proportional valve are determined based on the irrigation period. The total opening of the proportional valve is determined based on the irrigation flow rate. The openings of the first and second outlets are determined based on the total opening of the proportional valve and the water-to-pesticide ratio in the irrigation concentration. The openings of the first and second outlets are equal to the total opening of the proportional valve, and the ratio of the openings of the first and second outlets is equal to the water-to-pesticide ratio in the irrigation concentration. This embodiment comprehensively considers multiple factors such as rainfall period, rainfall amount, sunshine duration, light intensity, and irrigation duration and frequency in the corrected irrigation strategy to accurately determine the irrigation period, making the irrigation schedule more scientific and reasonable. Based on the rainfall or light intensity and real-time soil moisture during the irrigation period, the irrigation water volume is adjusted, and the corresponding irrigation flow rate is determined, achieving dynamic adjustment of irrigation water volume and flow rate, improving irrigation efficiency and water resource utilization, and adapting to different environmental conditions. When the irrigation water volume changes, the pesticide concentration is adjusted to maintain a constant total pesticide amount, ensuring the stability of pesticide application effects and avoiding the impact of improper pesticide concentration on control efficacy due to water volume changes.

[0097] Optionally, the historical operation data also includes data on the opening degree of the first and second outlets, which respectively characterize the opening degree of the first and second outlets of the proportional valve during the corresponding irrigation operation. The sensor data in the historical operation data also includes conductivity data and pressure data. The conductivity data is collected by a conductivity sensor installed in the irrigation pipeline, representing the pesticide concentration in the effluent. The pressure data is collected by a pressure gauge installed in the irrigation pipeline, representing the pressure in the pipeline. To more accurately control the opening degree of the proportional valve based on irrigation flow rate and irrigation concentration, the mapping relationship between the first and second outlet opening degree data and the conductivity and pressure data in the historical operation data can be analyzed. The opening degree of the first and second outlets can then be determined based on this mapping relationship, as well as the irrigation flow rate and irrigation concentration.

[0098] The specific implementation process is as follows: Based on the opening data of the first and second outlets, determine the historical opening ratio and the total historical opening; determine the first mapping relationship based on conductivity data and the historical opening ratio, and determine the second mapping relationship based on pressure data and the total historical opening; determine the opening ratio of the first and second outlets based on the first mapping relationship and irrigation concentration, and determine the total opening of the first and second outlets based on the second mapping relationship and irrigation flow rate; determine the opening of the first and second outlets based on the opening ratio of the first and second outlets and the total opening. For example, the ratio of the first outlet opening to the second outlet opening during historical operations is determined as the historical opening ratio for the corresponding historical operation, and the cumulative value of the first and second outlet openings during historical operations is determined as the total historical opening for the corresponding historical operation. Based on the historical opening ratio and conductivity data corresponding to multiple historical operations, a polynomial fitting is performed to determine the expression for the first mapping relationship between the opening ratio and conductivity. Based on historical total opening and pressure data from multiple historical operation processes, a polynomial fitting is performed to determine the expression for the second mapping relationship between total opening and pressure. The corresponding conductivity is determined based on the irrigation concentration, and this conductivity is substituted into the expression for the first mapping relationship to calculate the opening ratio of the first and second outlets. The corresponding pressure is determined based on the irrigation flow rate, and this pressure is substituted into the expression for the second mapping relationship to calculate the total opening of the first and second outlets. Based on the opening ratio of the first and second outlets, their respective opening percentages are determined. Multiplying the opening percentages of the first and second outlets by the total opening yields the opening of the first and second outlets.

[0099] This embodiment accurately analyzes the expressions for the first and second outlet openings, conductivity, and pressure from historical operation data. These expressions represent the first mapping relationship between conductivity and the opening ratio, as well as the second mapping relationship between pressure and the total opening. By utilizing these first and second mapping relationships, the openings of the first and second outlets are determined, thereby achieving precise control of the proportional valve and improving irrigation accuracy.

[0100] S1303. Based on the opening time, valve opening degree, and closing time of the electric valve, control the irrigation pipeline to irrigate the crops to be irrigated.

[0101] For example, when the current time reaches the opening time of the electric valve, an opening command is sent to the electric valve. The opening command includes the corresponding valve opening degree. Based on the opening command, the electric valve opens to the corresponding opening degree, allowing the irrigation pipe to drain water into the planting area, thereby irrigating the crops. When the current time reaches the closing time of the electric valve, a closing command is sent to the electric valve. Based on the closing command, the electric valve closes, stopping the irrigation pipe from draining water into the planting area.

[0102] If the computer valve is a proportional valve, the opening command includes the opening degree of the first outlet and the opening degree of the second outlet. The proportional valve opens the first outlet and the second outlet to the corresponding opening degree based on the opening degree of the first outlet and the second outlet in the opening command.

[0103] This embodiment accurately matches the actual water requirements of crops by combining soil moisture and weather conditions with irrigation strategies, including irrigation volume, duration, and frequency. By controlling the opening and closing times and valve opening degree of valves, the actual irrigation water volume is precisely controlled to meet crop needs, avoiding problems of insufficient or excessive irrigation and improving water resource utilization.

[0104] In summary, the intelligent irrigation method provided in this application obtains crop information of the crop to be irrigated and operational assistance information of the intelligent irrigation system, determines an initial irrigation strategy based on the crop information and operational assistance information, receives a correction operation, corrects the initial irrigation strategy according to the correction operation, and obtains a corrected irrigation strategy; and irrigates the crop to be irrigated according to the corrected irrigation strategy. Through the above technical means, the crop assistance information of the intelligent irrigation system and the crop information of the crop to be irrigated can be scientifically analyzed and adapted to the crop, thereby generating a scientific irrigation strategy. Based on farmers' manual correction of the irrigation strategy based on experience, an irrigation plan combining scientific recommendations and irrigation experience is formed, so as to achieve a balance between water-saving needs and crop yield needs in the intelligent irrigation system, solving the problem of poor irrigation effect in existing intelligent irrigation systems.

[0105] Based on the above embodiments, Figure 10 This is a schematic diagram of a smart irrigation operation device provided in an embodiment of this application. (Reference) Figure 10 The intelligent irrigation operation device provided in this embodiment specifically includes: an irrigation strategy determination module 21, an irrigation strategy correction module 22, and an irrigation operation module 23.

[0106] Among them, the irrigation strategy determination module 21 is configured to acquire the operation assistance information of the intelligent irrigation system and determine the initial irrigation strategy based on the operation assistance information.

[0107] Irrigation strategy correction module 22 is configured to receive correction operations and correct the initial irrigation strategy according to the correction operations to obtain a corrected irrigation strategy;

[0108] Irrigation operation module 23 is configured to irrigate the crop to be irrigated according to the corrected irrigation strategy.

[0109] Based on the above embodiments, the operation assistance information includes multiple sets of historical operation data and preset irrigation requirements. Each set of historical operation data includes crop information, irrigation data, and sensor data of the corresponding historical irrigated crop. Correspondingly, the irrigation strategy determination module 21 includes: a first strategy determination submodule, configured to determine the irrigation strategy of the crop to be irrigated based on the historical operation data and the crop information of the crop to be irrigated; and a second strategy determination submodule, configured to correct the irrigation strategy based on the preset irrigation requirements to obtain an initial irrigation strategy.

[0110] Based on the above embodiments, the first strategy determination submodule includes: a sample data acquisition unit, configured to divide historical operation data into positive sample data or negative sample data according to sensor data and irrigation data in historical operation data, with irrigation data of historical operation data serving as label information for the corresponding sample data; a prediction model construction unit, configured to construct an irrigation strategy prediction model based on each group of positive sample data and each group of negative sample data; and an irrigation strategy determination unit, configured to determine the irrigation strategy for the crop to be irrigated through the irrigation strategy prediction model and crop information of the crop to be irrigated.

[0111] Based on the above embodiments, the sensor data includes actual soil moisture and actual pipeline pressure; the irrigation data includes actual irrigation duration, actual irrigation frequency, and actual irrigation water volume; correspondingly, the sample data acquisition unit includes: a desired pressure determination subunit, configured to determine desired soil moisture based on actual irrigation duration, actual irrigation frequency, and actual irrigation water volume, and to determine desired pipeline pressure based on actual irrigation duration and actual irrigation water volume; a negative sample data acquisition subunit, configured to classify historical operation data as negative sample data when the difference between desired soil moisture and actual soil moisture is greater than a preset humidity difference, or the difference between desired pipeline pressure and actual pipeline pressure is greater than a preset pressure difference; and a positive sample data acquisition subunit, configured to classify historical operation data as positive sample data when the difference between desired soil moisture and actual soil moisture is less than or equal to a preset humidity difference, and the difference between desired pipeline pressure and actual pipeline pressure is less than or equal to a preset pressure difference.

[0112] Based on the above embodiments, crop information includes crop type, growth stage, planting information, and pest and disease information, and irrigation data also includes pesticide type and pesticide concentration. Correspondingly, the prediction model construction unit includes: a sample input subunit, configured to input crop type, growth stage, planting information, and pest and disease information from positive or negative sample data into the irrigation strategy prediction model to obtain the irrigation strategy output by the irrigation strategy prediction model, wherein the irrigation strategy includes irrigation duration, irrigation frequency, irrigation water volume, pesticide type, and pesticide concentration; and a parameter optimization subunit, configured to determine the loss value based on the output irrigation strategy and the label information of positive or negative sample data, and adjust the model parameters of the irrigation strategy prediction model based on the loss value.

[0113] Based on the above embodiments, the irrigation strategy includes irrigation duration, irrigation frequency, and irrigation water volume, and the preset irrigation demand includes preset total irrigation volume and preset irrigation flow rate; correspondingly, the second strategy determination submodule includes: a desired parameter determination unit, configured to determine the desired total irrigation volume based on the irrigation water volume and irrigation frequency, and to determine the desired irrigation flow rate based on the irrigation water volume and irrigation duration; and a first adjustment unit, configured to adjust the irrigation duration, irrigation frequency, and / or irrigation water volume in the irrigation strategy based on the desired total irrigation volume, desired irrigation flow rate, preset total irrigation volume, and preset irrigation flow rate, to obtain an initial irrigation strategy.

[0114] Based on the above embodiments, the irrigation strategy includes irrigation duration, irrigation frequency, irrigation water volume, pesticide type, and pesticide concentration. The preset irrigation requirements include preset total irrigation volume, preset irrigation flow rate, preset pesticide type, and preset pesticide concentration. Correspondingly, the second strategy determination submodule includes: a first display unit configured to display the preset pesticide type and the pesticide type in the irrigation strategy on the calibration interface; a second adjustment unit configured to receive a selection operation on the preset pesticide type or the pesticide type in the irrigation strategy, and use the selected type corresponding to the selection operation as the pesticide type of the calibration irrigation strategy; and a third adjustment unit configured to adjust the irrigation duration, irrigation frequency, irrigation water volume, and / or pesticide concentration in the irrigation strategy according to the preset total irrigation volume, preset irrigation flow rate, and preset pesticide concentration to obtain an initial irrigation strategy.

[0115] Based on the above embodiments, the irrigation strategy correction module 22 includes: a display submodule, configured to display the data in the initial irrigation strategy and the data in the irrigation demand on the correction interface after the irrigation strategy is corrected according to the preset irrigation demand to obtain the initial irrigation strategy; and a correction submodule, configured to receive an adjustment operation on the data in the initial irrigation strategy, adjust the data in the initial irrigation strategy according to the adjustment operation, and obtain a corrected irrigation strategy.

[0116] Based on the above embodiments, the irrigation operation module 23 includes: an additional information acquisition submodule, configured to acquire soil moisture and / or weather information; a valve control information determination submodule, configured to determine the opening time, valve opening degree, and closing time of the electric valve of the irrigation pipeline according to the soil moisture and / or weather information and the corrected irrigation strategy; and an irrigation control submodule, configured to control the irrigation pipeline to irrigate the crop to be irrigated according to the opening time, valve opening degree, and closing time of the electric valve.

[0117] Based on the above embodiments, the valve control information determination submodule includes: a time period parameter determination unit, configured to determine the rainfall period and sunshine period based on weather information, and determine the rainfall amount during the rainfall period and the light intensity during the sunshine period; an irrigation parameter determination unit, configured to determine the irrigation time period and irrigation flow rate for each irrigation based on soil moisture, the rainfall period and corresponding rainfall amount, the sunshine period and corresponding light intensity, and a corrected irrigation strategy; and a valve control information determination unit, configured to determine the opening time, valve opening degree, and closing time of the electric valve of the irrigation pipeline based on the irrigation time period and irrigation flow rate for each irrigation.

[0118] Based on the above embodiments, the electric valve is a proportional valve, which outputs water and pesticide through the first outlet and the second outlet respectively; correspondingly, the irrigation parameter determination unit includes an irrigation parameter determination subunit, configured to determine the irrigation time period, irrigation flow rate and irrigation concentration for each irrigation based on soil moisture, rainfall period and corresponding rainfall amount, sunshine period and corresponding light intensity, as well as irrigation duration, irrigation frequency, irrigation water volume and pesticide concentration in the corrected irrigation strategy; correspondingly, the valve control information determination unit includes a first control information determination subunit, configured to determine the opening time, closing time, first outlet opening degree and second outlet opening degree of the proportional valve based on the irrigation time period, irrigation flow rate and irrigation concentration for each irrigation.

[0119] Based on the above embodiments, the historical operation data also includes first outlet opening data and second outlet opening data, and the sensor data includes conductivity data and pressure data; correspondingly, the valve control information determination subunit further includes: a mapping relationship determination subunit, configured to determine the historical opening ratio and the historical total opening based on the first outlet opening data and the second outlet opening data; determine a first mapping relationship based on conductivity data and the historical opening ratio, and determine a second mapping relationship based on pressure data and the historical total opening; a total opening determination subunit, configured to determine the opening ratio of the first outlet and the second outlet based on the first mapping relationship and the irrigation concentration, and determine the total opening of the first outlet and the second outlet based on the second mapping relationship and the irrigation flow rate; and an outlet opening determination subunit, configured to determine the opening of the first outlet and the second outlet based on the opening ratio of the first outlet and the second outlet and the total opening.

[0120] The intelligent irrigation device provided in this application, as described above, obtains crop information of the crop to be irrigated and operational assistance information of the intelligent irrigation system, determines an initial irrigation strategy based on the crop information and operational assistance information, receives a correction operation, corrects the initial irrigation strategy according to the correction operation, and obtains a corrected irrigation strategy; then irrigates the crop to be irrigated according to the corrected irrigation strategy. Through the above technical means, the crop assistance information of the intelligent irrigation system and the crop information of the crop to be irrigated can be scientifically analyzed and adapted to the crop, thereby generating a scientific irrigation strategy. Based on farmers' manual correction of the irrigation strategy based on experience, an irrigation plan combining scientific recommendations and irrigation experience is formed, so as to achieve a balance between water-saving needs and crop yield needs in the intelligent irrigation system, solving the problem of poor irrigation effect in existing intelligent irrigation systems.

[0121] The intelligent irrigation operation device provided in this application embodiment can be used to execute the intelligent irrigation operation method provided in the above embodiment, and has corresponding functions and beneficial effects.

[0122] Figure 11 This is a schematic diagram of the structure of an intelligent irrigation operation device provided in an embodiment of this application, with reference to... Figure 11 The intelligent irrigation equipment includes a processor 31, a memory 32, a communication device 33, an input device 34, and an output device 35. The intelligent irrigation equipment may have one or more processors 31 and one or more memory units 32. The processor 31, memory 32, communication device 33, input device 34, and output device 35 of the intelligent irrigation equipment can be connected via a bus or other means.

[0123] The memory 32, as a computer-readable storage medium, can be used to store software programs, computer-executable programs, and modules, such as program instructions / modules corresponding to the intelligent irrigation operation method in any embodiment of this application (e.g., irrigation strategy determination module 21, irrigation strategy correction module 22, and irrigation operation module 23 in the intelligent irrigation operation device). The memory 32 may primarily include a program storage area and a data storage area. The program storage area may store the operating system and at least one application program required for a function; the data storage area may store data created based on the use of the device, etc. Furthermore, the memory 32 may include high-speed random access memory and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to the device via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0124] The communication device 33 is used for data transmission.

[0125] The processor 31 executes various functional applications and data processing of the device by running software programs, instructions and modules stored in the memory 32, thereby realizing the above-mentioned intelligent irrigation operation method.

[0126] Input device 34 can be used to receive input digital or character information, and to generate key signal inputs related to user settings and function control of the device. Output device 35 may include display devices such as a display screen.

[0127] The intelligent irrigation equipment provided above can be used to perform the intelligent irrigation operation method provided in the above embodiments, and has corresponding functions and beneficial effects.

[0128] This application embodiment also provides a storage medium containing computer-executable instructions. When executed by a computer processor, the computer-executable instructions are used to perform an intelligent irrigation operation method. The intelligent irrigation operation method includes: acquiring crop information of the crop to be irrigated and operation assistance information of an intelligent irrigation system; determining an initial irrigation strategy based on the crop information and operation assistance information; receiving a correction operation; correcting the initial irrigation strategy based on the correction operation to obtain a corrected irrigation strategy; and irrigating the crop to be irrigated according to the corrected irrigation strategy.

[0129] Storage medium – any type of memory device or storage device. The term “storage medium” is intended to include: mounting media, such as CD-ROM, floppy disk, or magnetic tape devices; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. Storage medium may also include other types of memory or combinations thereof. Furthermore, storage medium may reside in a first computer system in which the program is executed, or it may reside in a different second computer system connected to the first computer system via a network (such as the Internet). The second computer system can provide program instructions to the first computer for execution. The term “storage medium” can include two or more storage media residing in different locations (e.g., in different computer systems connected via a network). Storage medium may store program instructions (e.g., specifically implemented as a computer program) executable by one or more processors.

[0130] Of course, the computer-executable instructions provided in the embodiments of this application are not limited to the intelligent irrigation operation method described above, but can also perform related operations in the intelligent irrigation operation method provided in any embodiment of this application.

[0131] The intelligent irrigation operation device, storage medium, and intelligent irrigation operation equipment provided in the above embodiments can execute the intelligent irrigation operation method provided in any embodiment of this application. For technical details not described in detail in the above embodiments, please refer to the intelligent irrigation operation method provided in any embodiment of this application.

[0132] The above description is merely a preferred embodiment and the technical principles employed in this application. This application is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions that can be made by those skilled in the art will not depart from the scope of protection of this application. Therefore, although this application has been described in detail through the above embodiments, this application is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of this application. The scope of this application is determined by the scope of the claims.

Claims

1. A smart irrigation operation method, characterized in that, include: Obtain crop information of the crop to be irrigated and operation assistance information of the intelligent irrigation system, and determine the initial irrigation strategy based on the crop information and the operation assistance information; Receive a correction operation, and correct the initial irrigation strategy according to the correction operation to obtain a corrected irrigation strategy; The crop to be irrigated is irrigated according to the corrective irrigation strategy.

2. The intelligent irrigation operation method according to claim 1, characterized in that, The operational assistance information includes multiple sets of historical operational data and preset irrigation requirements. Each set of historical operational data includes crop information, irrigation data, and sensor data for the corresponding historically irrigated crop. Correspondingly, determining the initial irrigation strategy based on the crop information and the operational assistance information includes: Based on the historical operation data and the crop information of the crop to be irrigated, the irrigation strategy for the crop to be irrigated is determined; The irrigation strategy is adjusted according to the preset irrigation requirements to obtain an initial irrigation strategy.

3. The intelligent irrigation operation method according to claim 2, characterized in that, The step of determining the irrigation strategy for the crop to be irrigated based on the historical operation data and crop information includes: Based on the sensor data and irrigation data in the historical operation data, the historical operation data is divided into positive sample data or negative sample data, and the irrigation data of the historical operation data is used as the label information of the corresponding sample data. Based on the positive sample data and negative sample data of each group, an irrigation strategy prediction model is constructed. The irrigation strategy for the crop to be irrigated is determined by using the irrigation strategy prediction model and the crop information of the crop to be irrigated.

4. The intelligent irrigation operation method according to claim 3, characterized in that, The sensor data includes actual soil moisture and actual pipeline pressure; the irrigation data includes actual irrigation duration, actual number of irrigations, and actual irrigation water volume. Accordingly, the step of dividing the historical operation data into positive sample data or negative sample data based on crop information, sensor data, and irrigation data in the historical operation data includes: The desired soil moisture is determined based on the actual irrigation duration, the actual number of irrigations, and the actual irrigation water volume; the desired pipeline pressure is determined based on the actual irrigation duration and the actual irrigation water volume. If the difference between the expected soil moisture and the actual soil moisture is greater than a preset moisture difference, or if the difference between the expected pipeline pressure and the actual pipeline pressure is greater than a preset pressure difference, the historical operation data will be classified as negative sample data. If the difference between the expected soil moisture and the actual soil moisture is less than or equal to a preset moisture difference, and the difference between the expected pipeline pressure and the actual pipeline pressure is less than or equal to a preset pressure difference, the historical operation data will be classified as positive sample data.

5. The intelligent irrigation operation method according to claim 3, characterized in that, The crop information includes crop type, growth stage, planting information, and pest and disease information; the irrigation data also includes pesticide type and pesticide concentration. Accordingly, the step of constructing an irrigation strategy prediction model based on each group of positive sample data and each group of negative sample data includes: The crop type, growth stage, planting information, and pest and disease information from the positive sample data or the negative sample data are input into the irrigation strategy prediction model to obtain the irrigation strategy output by the irrigation strategy prediction model. The irrigation strategy includes irrigation duration, irrigation frequency, irrigation water volume, pesticide type, and pesticide concentration. The loss value is determined based on the output irrigation strategy and the label information of the positive or negative sample data, and the model parameters of the irrigation strategy prediction model are adjusted based on the loss value.

6. The intelligent irrigation operation method according to claim 2, characterized in that, The irrigation strategy includes irrigation duration, irrigation frequency, and irrigation water volume; the preset irrigation demand includes a preset total irrigation volume and a preset irrigation flow rate; correspondingly, the step of correcting the irrigation strategy according to the preset irrigation demand to obtain an initial irrigation strategy includes: The expected total irrigation amount is determined based on the irrigation water volume and the number of irrigations, and the expected irrigation flow rate is determined based on the irrigation water volume and the irrigation duration. Based on the expected total irrigation volume, the expected irrigation flow rate, the preset total irrigation volume, and the preset irrigation flow rate, the irrigation duration, irrigation frequency, and / or irrigation water volume in the irrigation strategy are adjusted to obtain the initial irrigation strategy.

7. The intelligent irrigation operation method according to claim 1, characterized in that, The irrigation strategy includes irrigation duration, irrigation frequency, irrigation water volume, pesticide type, and pesticide concentration. The preset irrigation requirements include preset total irrigation volume, preset irrigation flow rate, preset pesticide type, and preset pesticide concentration. Correspondingly, the step of correcting the irrigation strategy based on the preset irrigation requirements to obtain an initial irrigation strategy includes: The preset pesticide type and the pesticide type in the irrigation strategy are displayed on the calibration interface; Receive a selection operation for a preset pesticide type or a pesticide type in the irrigation strategy, and use the selected type corresponding to the selection operation as the pesticide type for the corrected irrigation strategy; Based on the preset total irrigation volume, preset irrigation flow rate, and preset pesticide concentration, the irrigation duration, number of irrigations, irrigation water volume, and / or pesticide concentration in the irrigation strategy are adjusted to obtain the initial irrigation strategy.

8. The intelligent irrigation operation method according to claim 2, characterized in that, After correcting the irrigation strategy according to the preset irrigation requirements to obtain the initial irrigation strategy, the method further includes: The data from the initial irrigation strategy and the data from the irrigation demand are displayed on the calibration interface; Accordingly, the receiving correction operation, which corrects the initial irrigation strategy according to the correction operation to obtain a corrected irrigation strategy, includes: The system receives an adjustment operation on the data in the initial irrigation strategy, adjusts the data in the initial irrigation strategy according to the adjustment operation, and obtains a corrected irrigation strategy.

9. The intelligent irrigation operation method according to claim 1, characterized in that, The step of irrigating the crop to be irrigated according to the corrected irrigation strategy includes: Obtain soil moisture and / or weather information; Based on the soil moisture and / or the weather information and the corrective irrigation strategy, determine the opening time, valve opening degree and closing time of the electric valve of the irrigation pipeline; The irrigation pipeline is controlled to irrigate the crop to be irrigated based on the opening time, valve opening degree, and closing time of the electric valve.

10. The intelligent irrigation operation method according to claim 9, characterized in that, The step of determining the opening time, valve opening degree, and closing time of the electric valve of the irrigation pipeline based on the soil moisture and / or the weather information and the corrected irrigation strategy includes: Based on the weather information, determine the rainfall period and sunshine period, and determine the rainfall amount during the rainfall period and the light intensity during the sunshine period; Based on the soil moisture, the rainfall period and corresponding rainfall amount, the sunshine period and corresponding light intensity, and the corrected irrigation strategy, determine the irrigation period and irrigation flow rate for each irrigation; Based on the irrigation time period and irrigation flow rate for each irrigation, determine the opening time, valve opening degree, and closing time of the electric valve in the irrigation pipeline.

11. The intelligent irrigation operation method according to claim 10, characterized in that, The electric valve is a proportional valve, which outputs water and pesticide through the first outlet and the second outlet, respectively. Accordingly, determining the irrigation time period and irrigation flow rate for each irrigation based on the soil moisture, the rainfall period and corresponding rainfall amount, the sunshine period and corresponding light intensity, and the corrected irrigation strategy includes: Based on the soil moisture, the rainfall period and corresponding rainfall amount, the sunshine period and corresponding light intensity, and the irrigation duration, irrigation frequency, irrigation water volume and pesticide concentration in the corrected irrigation strategy, determine the irrigation period, irrigation flow rate and irrigation concentration for each irrigation; Accordingly, determining the opening time, valve opening degree, and closing time of the electric valve in the irrigation pipeline based on the irrigation time period and irrigation flow rate for each irrigation includes: Based on the irrigation time period, irrigation flow rate, and irrigation concentration for each irrigation, determine the opening time, closing time, first outlet opening degree, and second outlet opening degree of the proportional valve.

12. The intelligent irrigation operation method according to claim 11, characterized in that, The historical operation data also includes the opening data of the first outlet and the opening data of the second outlet, and the sensor data includes conductivity data and pressure data; Accordingly, determining the opening and closing times of the proportional valve in the irrigation pipeline, the opening degree of the first outlet, and the opening degree of the second outlet based on the irrigation time period, irrigation flow rate, and irrigation concentration for each irrigation includes: Based on the opening data of the first outlet and the opening data of the second outlet, determine the historical opening ratio and the total historical opening. A first mapping relationship is determined based on the conductivity data and the historical opening ratio, and a second mapping relationship is determined based on the pressure data and the historical total opening. The opening ratio of the first outlet and the second outlet is determined according to the first mapping relationship and the irrigation concentration, and the total opening of the first outlet and the second outlet is determined according to the second mapping relationship and the irrigation flow rate. The opening degree of the first outlet and the opening degree of the second outlet are determined based on the opening ratio of the first outlet and the second outlet and the total opening degree.

13. An intelligent irrigation operation device, characterized in that, include: The irrigation strategy determination module is configured to acquire crop information of the crop to be irrigated and operation assistance information of the intelligent irrigation system, and determine an initial irrigation strategy based on the crop information and the operation assistance information. An irrigation strategy correction module is configured to receive a correction operation and correct the initial irrigation strategy according to the correction operation to obtain a corrected irrigation strategy. The irrigation operation module is configured to irrigate the crop to be irrigated according to the corrected irrigation strategy.

14. An intelligent irrigation operation device, characterized in that, include: One or more processors; A storage device for storing one or more programs that, when executed by one or more processors, cause the one or more processors to implement the intelligent irrigation operation method as described in any one of claims 1-12.

15. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the intelligent irrigation operation method as described in any one of claims 1-12.

Images