Planting training scheme recommendation method and device and electronic equipment
By matching crops based on the environmental data of the target area and generating personalized planting training programs, the problem of poor adaptability of planting training programs in the existing technology is solved, and more efficient planting training results are achieved.
Patent Information
- Application Number
- CN202411988471.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-30
- Publication Date
- 2025-05-13
AI Technical Summary
The unified planting training program provided by the existing agricultural service system cannot effectively adapt to the climate and environmental differences in different regions, resulting in poor planting training results.
By determining the environmental data of the target area, matching the corresponding crops, and generating a personalized planting training plan based on the crops, pushing them to users to be recommended.
It improves the adaptability and accuracy of the planting training program, provides users with more accurate learning resources, and significantly improves the effectiveness of planting training.
Smart Images
Figure CN119990510A_ABST
Abstract
Description
Technical Field
[0001] The present application belongs to the field of agricultural technology, and in particular relates to a method, device and electronic equipment for recommending a planting training program. Background Art
[0002] The rapid development of agricultural technology has promoted the popularization of intelligent agricultural education, especially in the field of agricultural planting. The online planting training programs provided by the agricultural service system provide farmers and agricultural practitioners with a convenient learning channel.
[0003] The current agricultural service system usually adopts a unified planting training program, but environmental differences such as climate in different regions have a great impact on crop planting. The applicability of a single standardized planting training program is limited, resulting in poor planting training results. Summary of the invention
[0004] The embodiments of the present application provide a planting training program recommendation method, device and electronic equipment, which can improve the effect of agricultural planting training.
[0005] In a first aspect, an embodiment of the present application provides a method for recommending a planting training program, comprising:
[0006] Determining a target area, wherein the target area is an area where crops are to be planted;
[0007] Determining target crops according to environmental data corresponding to the target area, wherein the target crops include crops matching the environmental data;
[0008] generating a planting training program based on the target crops;
[0009] The planting training program is pushed to the user to be recommended.
[0010] In a second aspect, an embodiment of the present application provides a planting training program recommendation device, comprising:
[0011] A target area determination module is used to determine a target area, where the target area is an area where crops are to be planted;
[0012] A target crop determination module, configured to determine target crops according to environmental data corresponding to the target area, wherein the target crops include crops matching the environmental data;
[0013] A generating module, used for generating a planting training program according to the target crops;
[0014] The recommendation module is used to push the planting training program to the user to be recommended.
[0015] In a third aspect, an embodiment of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of the method for recommending a planting training program described in the first aspect are implemented.
[0016] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for recommending a planting training program described in the first aspect are implemented.
[0017] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on an electronic device, the electronic device executes the planting training program recommendation method described in the first aspect above.
[0018] Compared with the prior art, the embodiments of the present invention have the following beneficial effects:
[0019] In the embodiment of the present application, since the target crop is a crop that matches the environmental data of the target area, and the target area is the area where the crops are to be planted, that is, the target crop is a crop that matches the environmental data of the area where the crops are to be planted, therefore, a planting training plan with a high degree of matching with the area where the crops are to be planted can be generated based on the target crop, thereby effectively improving the adaptability of the planting training plan, providing users with more accurate learning resources, and helping to improve the planting training effect. BRIEF DESCRIPTION OF THE DRAWINGS
[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the embodiments or descriptions of the prior art.
[0021] Figure 1 It is a flowchart of a method for recommending a planting training program provided in an embodiment of the present application;
[0022] Figure 2 It is a structural schematic diagram of a planting training program recommendation device provided in an embodiment of the present application;
[0023] Figure 3 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION
[0024] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.
[0025] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.
[0026] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.
[0027] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.
[0028] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the phrases "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. appearing in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways.
[0029] Embodiment 1:
[0030] Figure 1 A flow chart of a method for recommending a planting training program provided in an embodiment of the present application is shown, and is described in detail as follows:
[0031] S110: Determine a target area, where the target area is an area where crops are to be planted.
[0032] It should be understood that the area where crops are to be planted (i.e., the target area) can be determined based on location information input or selected by the user, or based on location information in user information, or based on positioning information of a terminal device corresponding to the user. The embodiments of the present application do not impose specific restrictions on this.
[0033] It should be understood that the granularity of the target area can be a city, county, township or village, etc., which can be set specifically according to the actual application scenario.
[0034] S120: Determine target crops according to the environmental data corresponding to the target area, where the target crops include crops matching the environmental data.
[0035] Optionally, the environmental data may include data of at least one type of climate, soil, natural resources, pollution, ecology, etc. For example, the environmental data may include data of climate type, and the climate data may include climate-related data such as temperature, precipitation, light, wind direction, wind speed, and humidity.
[0036] Since the environment in different regions usually varies to a certain extent, and the planting environment has a great impact on the planting of crops, in order to improve the applicability of the planting training program, the crops that match the environmental data of the target area can be determined based on the environmental data of the target area to obtain the target crops. Subsequently, the planting training program with higher adaptability to the target area can be generated based on the target crops, thereby providing users with more accurate learning resources.
[0037] S130, generating a planting training plan based on the above target crops.
[0038] Optionally, when generating a planting training plan based on the target crops, the planting training plan can be generated based on the growth cycle of the crops, the growth environment requirements and related planting techniques, planting tools, etc., so as to guide users on how to plant and manage the target crops through the planting training plan, which is conducive to improving the crop planting results.
[0039] S140: Pushing the above-mentioned planting training program to the user to be recommended.
[0040] It should be understood that the user to be recommended can be the user corresponding to the target area, or a designated user related to the target area, such as a user who inputs the area where the crops are to be planted. For example, assuming that user A logs in to the agricultural service system on the client and selects the area where the crops are to be planted, the agricultural service system can obtain the area where the crops are to be planted selected by user A and use it as the target area. At this time, user A is the user to be recommended. After generating the planting training plan, the planting training plan can be recommended to user A, and the planting training plan can also be pushed to other users whose location information in the user information matches the target area and who have recommendation needs.
[0041] Optionally, when pushing the planting training plan to the user to be recommended, the planting training plan can be pushed through message notification or home page recommendation, etc., and no specific limitation is made here.
[0042] In the embodiment of the present application, since the target crop is a crop that matches the environmental data of the target area, and the target area is the area where the crops are to be planted, that is, the target crop is a crop that matches the environmental data of the area where the crops are to be planted, therefore, a planting training plan with a high degree of matching with the area where the crops are to be planted can be generated based on the target crop, thereby effectively improving the adaptability of the planting training plan, providing more accurate learning resources for users corresponding to the area where the crops are to be planted, and helping to improve the planting training effect.
[0043] In some embodiments, the above step S110 includes:
[0044] The target area is determined based on the received location information, or the target area is determined based on the location information of the user who has logged into the agricultural service system.
[0045] Optionally, the received location information may be location information manually input or selected by a user through a terminal device.
[0046] To meet user needs, the agricultural service system can use the area corresponding to the received location information as the area to be planted crops when receiving the location information sent by the user, that is, determine the target area based on the received location information, so as to provide the user with a planting training plan that matches the location information sent by the user.
[0047] It should be understood that when the target area is determined according to the received location information, the user to be recommended may be the user who sent the location information, and the corresponding planting training program may be sent only to the user who sent the location information (ie, the user to be recommended).
[0048] Alternatively, the target area can be determined directly based on the location information of the user who has logged into the agricultural service system, so as to push a planting training program matching the location information to the logged in user. At this time, the user to be recommended can be the user who has logged into the agricultural service system corresponding to the target area.
[0049] Optionally, the location information of the user who has logged into the agricultural service system can be determined based on the positioning information of the user's terminal device or the location information in the user information, which can be specifically set according to the actual application scenario.
[0050] In the embodiment of the present application, since users who log in to the agricultural service system or actively send location information are usually users who have planting training needs, determining the target area based on the location information of these users can better generate and push corresponding planting training plans for users who have planting training needs, which can better improve the user experience.
[0051] In some embodiments, the above step S120 includes:
[0052] S1201. Determine a first matching degree corresponding to each crop according to a matching degree between a planting environment requirement of the crop and the above environmental data, wherein the above planting environment requirement reflects the requirements of the planting environment of the crop.
[0053] S1202: Determine the target crop according to the crops whose first matching degree is greater than or equal to a matching threshold.
[0054] It should be understood that the planting environment requirements of crops include but are not limited to climate requirements, soil requirements (such as acidity and alkalinity requirements) and resource requirements (such as requirements for nutrient elements such as nitrogen or potassium).
[0055] Since the planting environment requirements of crops can better reflect the required planting environment, the matching degree between the planting environment requirements and the environmental data of the target area is used as the first matching degree corresponding to the crops. The first matching degree can better reflect the adaptability of the crops to the target area. Furthermore, according to whether the first matching degree is greater than or equal to the matching threshold (such as 0.7), it can be better judged whether the crops are suitable for planting in the target area, which is conducive to improving the accuracy of the determined target crops.
[0056] Optionally, the matching threshold may be a threshold set by the agricultural service system, or a threshold set or input by the user.
[0057] For example, when user A sends location information B to the application service system through the terminal device, the matching threshold C can be sent together to the agricultural service system. After the agricultural service system determines the target area b based on the location information B, when determining the target crop based on the target area b, the crop with a first matching degree greater than or equal to the matching threshold C can be determined as the target crop.
[0058] In the embodiment of the present application, the first matching degree reflects the matching degree between the planting environment requirements of the crop and the environmental data of the target area. The crop whose first matching degree is greater than or equal to the matching threshold is determined as the target crop, so that the environment of the target area can better meet the planting environment requirements of the target crop, effectively improving the matching of the target crop and the target area to be planted.
[0059] In some embodiments, the environmental data includes different types of data, and the step S1201 includes:
[0060] The first matching degree corresponding to each crop is determined according to the matching degree between the planting environment requirements of the crop and the above environmental data, including:
[0061] The matching degree between the above planting environment requirements and various types of data in the above environmental data is determined respectively, and a second matching degree corresponding to each of the above types is obtained.
[0062] The first matching degree is determined according to the second matching degrees and weights corresponding to the respective types.
[0063] Optionally, the environmental data includes at least climate data, and may also include data on soil, pollution, natural resources, and other types of data.
[0064] Since the growth of crops is usually affected by multiple environmental factors, and the degree to which crops are affected by different types of environmental factors usually varies, when determining the degree of matching between crops and the environmental data of the target area, the matching degrees between the planting environment requirements and various types of data in the environmental data can be calculated separately according to the planting environment requirements of the crops, and the second matching degrees corresponding to each type can be obtained. Then, the overall matching degree between the planting environment requirements of the crops and the environmental data can be calculated according to the second matching degrees corresponding to each type and the weights corresponding to each type, to obtain the first matching degree.
[0065] As an example, the weight corresponding to each type can be determined according to the degree to which the growth of crops is affected by the data of that type.
[0066] As another example, the weight corresponding to each type can be set or input by the user.
[0067] In an embodiment of the present application, the second matching degree between each type of data in the environmental data and the planting environment requirements, as well as the weight corresponding to each type, are used to comprehensively evaluate the matching degree between the crops and the environmental data of the target area, thereby improving the accuracy of the first matching degree obtained, thereby improving the matching of the target crops and the target area finally determined.
[0068] In some embodiments, before the above step S130, the method further includes:
[0069] When the user information of the user to be recommended is obtained, the target crops are screened according to the user information to obtain the screened target crops, and the user information includes at least one of economic information and demand information.
[0070] Correspondingly, the above step S130 also includes:
[0071] The above-mentioned planting training program is generated based on the above-mentioned target crops after screening.
[0072] It should be understood that the demand information may include at least one of the user's demand for the type of crops to be recommended (legume crops, oil crops or vegetable crops, etc.), production cycle requirements and yield requirements.
[0073] It should be understood that the economic information includes but is not limited to information such as economic status, income level and consumption capacity, which is used to reflect the economic level of the user to be recommended.
[0074] Since the economic conditions and crops that different users want to grow may differ, before generating the planting training courses corresponding to the users to be recommended, the preliminarily determined target crops can be screened based on the user information of the users to be recommended, so as to obtain screened crops that are more closely matched with the users to be recommended. This can further improve the matching degree between the finally generated planting training program and the users to be recommended, i.e., improve the recommendation effect of the planting training courses.
[0075] Optionally, when the user information includes economic information and demand information, target crops (assuming they are called candidate target crops) that match the user's needs can be preliminarily screened out from the target crops based on the demand information, and then candidate target crops that match the user's economic level can be screened out from the candidate target crops based on the user's economic information to obtain the screened target crops.
[0076] In an embodiment of the present application, the target crops are screened according to the economic level of the user to be recommended, so that the screened target crops are crops within the economic tolerance of the user, and / or the target crops are screened according to the planting needs of the user to be recommended, so that the screened target crops are crops that meet the user's needs. Through the above processing, the screened target crops are crops that have a certain degree of matching with the area where the user to be recommended plants crops and the personal conditions of the user to be recommended. Then, a planting training program is generated based on the screened target crops, which can recommend personalized planting learning resources to the user to be recommended, help the user to be recommended improve the planting level, and help improve the efficiency of agricultural planting.
[0077] In some embodiments, after the above step S130, the method further includes:
[0078] The planting training program is updated according to the climate data in the target time period, and the updated planting training program is pushed to the recommended users. The target time period is the time period after the planting training program is generated.
[0079] Optionally, the target time period may be a time period corresponding to a preset time after the planting training program is generated, such as one month or one quarter after the planting training program is generated.
[0080] Optionally, the preset duration can be determined by a deep learning model such as a big model, an intelligent algorithm or other methods according to the growth characteristics of the target crop, or can be set or input by a user.
[0081] Due to factors such as seasonal changes or environmental pollution, the climate data of the target area may change. These changes may affect the growth of target crops, such as causing an increase in pests and diseases. Therefore, to ensure the effectiveness of the planting training plan, after generating a planting training plan based on the target crops, the planting training plan can be updated based on the climate data within a certain period of time after the planting training plan is generated, and the updated planting training plan can be recommended to the recommended users.
[0082] As an example, when updating the planting training plan based on the climate data within the target time period, one or more plans such as the planting plan, irrigation and fertilization plan, and pest and disease control plan in the planting training plan may be updated, or one or more of the above plans may be added to the planting training plan. The specific updating method may be determined based on the content included in the planting training plan.
[0083] It should be understood that after a planting training plan is generated according to the target crops, the planting training plan will be recommended to the user to be recommended; after the planting training plan is updated, the updated planting training plan will be recommended to the user to be recommended.
[0084] In some embodiments, the target time period may also be the time period after the planting training plan is updated, that is, based on the environmental data within the target time period corresponding to the preset time after the planting training plan is updated, the planting training plan is updated and the updated planting training plan is recommended to the recommended users, thereby improving the real-time and effectiveness of the planting training plan by continuously updating the planting training plan.
[0085] In some embodiments, after the above step S140, the method further includes:
[0086] In case of receiving feedback information from the user to be recommended regarding the planting training program, the planting training program is updated according to the feedback information, and the updated planting training program is pushed to the user to be recommended.
[0087] It should be understood that the feedback information from the recommended users regarding the implant training program includes but is not limited to program shortcomings, doubts, satisfaction, and expansion needs.
[0088] For example, assuming that the feedback information received includes questions from the users to be recommended, detailed answers to the questions are added to the chapters corresponding to the questions in the planting training program based on the received questions, so as to help the users to be recommended better understand and master the planting training program, that is, help the users to be recommended learn and master the planting techniques, and help promote the application of planting techniques.
[0089] In an embodiment of the present application, after pushing a planting training video to the user to be recommended, feedback information from the user to be recommended regarding the planting training program can be obtained. Then, based on the obtained feedback information, the planting training program can be adjusted and optimized in a targeted manner, so that the updated planting training program is closer to the actual needs and application scenarios of the user to be recommended, which is conducive to improving the targetedness and practicality of the planting training program.
[0090] It should be understood that the size of the serial numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.
[0091] Embodiment 2:
[0092] Corresponding to the planting training program recommendation method described in the above embodiment, Figure 2 A structural block diagram of a planting training program recommendation device provided in an embodiment of the present application is shown. For ease of explanation, only the parts related to the embodiment of the present application are shown.
[0093] Reference Figure 2 The device comprises: a target area determination module 21, a target crop determination module 22, a generation module 23 and a recommendation module 24.
[0094] The target area determination module 21 is used to determine the target area, where the target area is the area where crops are to be planted.
[0095] The target crop determination module 22 is used to determine the target crops according to the environmental data corresponding to the target area, and the target crops include crops matching the environmental data.
[0096] The generating module 23 is used to generate a planting training plan according to the above target crops.
[0097] The recommendation module 24 is used to push the above-mentioned planting training program to the user to be recommended.
[0098] In the embodiment of the present application, since the target crop is a crop that matches the environmental data of the target area, and the target area is the area where the crops are to be planted, that is, the target crop is a crop that matches the environmental data of the area where the crops are to be planted, therefore, a planting training plan with a high degree of matching with the area where the crops are to be planted can be generated based on the target crop, thereby effectively improving the adaptability of the planting training plan, providing more accurate learning resources for users corresponding to the area where the crops are to be planted, and helping to improve the planting training effect.
[0099] In some embodiments, the target crop determination module 22 includes:
[0100] The first matching degree calculation unit is used to determine the first matching degree corresponding to each crop according to the matching degree between the planting environment requirements of the crop and the above-mentioned environmental data, and the above-mentioned planting environment requirements reflect the requirements of the planting environment of the crop.
[0101] The target crop determining unit is used to determine the target crop according to the crops whose first matching degree is greater than or equal to the matching threshold.
[0102] In some embodiments, the target crop determination module 22 further includes:
[0103] The second matching degree calculation unit is used to respectively determine the matching degree between the above-mentioned planting environment requirements and various types of data in the above-mentioned environmental data, and obtain the second matching degree corresponding to each of the above-mentioned types.
[0104] A weighting unit is used to determine the first matching degree according to the second matching degree corresponding to each of the types and the weight.
[0105] In some embodiments, the implant training program recommendation device further comprises:
[0106] The screening module is used to screen the target crops according to the user information of the user to be recommended, and obtain the screened target crops, wherein the user information includes at least one of economic information and demand information.
[0107] Correspondingly, the above-mentioned generating module 23 includes:
[0108] A generating unit is used to generate the above-mentioned planting training program according to the above-mentioned screened target crops.
[0109] In some embodiments, the implant training program recommendation device further comprises:
[0110] The climate update module is used to update the above-mentioned planting training program according to the climate data in the target time period, and push the updated planting training program to the above-mentioned recommended users. The above-mentioned target time period is the time period after the above-mentioned planting training program is generated.
[0111] In some embodiments, the implant training program recommendation device further comprises:
[0112] The feedback update module is used to update the planting training program according to the feedback information received from the user to be recommended regarding the planting training program, and push the updated planting training program to the user to be recommended.
[0113] In some embodiments, the target area determination module 21 includes:
[0114] The target area determination unit is used to determine the target area according to the received location information, or to determine the target area according to the location information of the user who has logged into the agricultural service system.
[0115] It should be noted that the information interaction, execution process, etc. between the above-mentioned devices / units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.
[0116] Embodiment three:
[0117] Figure 3 This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. Figure 3 As shown, the electronic device 3 of this embodiment includes: at least one processor 30 ( Figure 3 Only one processor is shown in the figure), a memory 31, and a computer program 32 stored in the memory 31 and executable on the at least one processor 30, wherein the processor 30 implements the steps in any of the above-mentioned method embodiments when executing the computer program 32.
[0118] The electronic device 3 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The electronic device may include, but is not limited to, a processor 30 and a memory 31. Those skilled in the art will appreciate that Figure 3 It is only an example of the electronic device 3 and does not constitute a limitation on the electronic device 3. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, etc.
[0119] The processor 30 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.
[0120] In some embodiments, the memory 31 may be an internal storage unit of the electronic device 3, such as a hard disk or memory of the electronic device 3. In other embodiments, the memory 31 may also be an external storage device of the electronic device 3, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the electronic device 3. Further, the memory 31 may also include both an internal storage unit of the electronic device 3 and an external storage device. The memory 31 is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program, etc. The memory 31 may also be used to temporarily store data that has been output or is to be output.
[0121] The technicians in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.
[0122] An embodiment of the present application also provides a network device, which includes: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor implements the steps in any of the above-mentioned method embodiments when executing the computer program.
[0123] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps in the above-mentioned method embodiments can be implemented.
[0124] An embodiment of the present application provides a computer program product. When the computer program product runs on an electronic device, the electronic device can implement the steps in the above-mentioned method embodiments when executing the computer program product.
[0125] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device that can carry the computer program code to the camera / electronic device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, RandomAccess Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.
[0126] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.
[0127] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.
[0128] In the embodiments provided in the present application, it should be understood that the disclosed devices / network equipment and methods can be implemented in other ways. For example, the device / network equipment embodiments described above are merely schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.
[0129] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0130] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.
Claims
1. A method for recommending a planting training program, characterized in that: Applied to agricultural service systems, including: Determining a target area, wherein the target area is an area where crops are to be planted; Determining target crops according to environmental data corresponding to the target area, wherein the target crops include crops matching the environmental data; generating a planting training program based on the target crops; The planting training program is pushed to the user to be recommended.
2. The method for recommending a planting training program according to claim 1, characterized in that: The step of determining the target crop according to the environmental data corresponding to the target area includes: determining a first matching degree corresponding to each crop according to a matching degree between a planting environment requirement of the crop and the environmental data, wherein the planting environment requirement reflects a requirement of a planting environment of the crop; The target crop is determined according to the crops whose first matching degree is greater than or equal to a matching threshold.
3. The method for recommending a planting training program according to claim 2, characterized in that: The environmental data includes different types of data, and determining the first matching degree corresponding to each crop according to the matching degree between the planting environment requirements of the crop and the environmental data includes: Respectively determining the matching degree between the planting environment requirements and various types of data in the environmental data, and obtaining a second matching degree corresponding to each type; The first matching degree is determined according to the second matching degrees and weights corresponding to each of the types.
4. The method for recommending a planting training program according to claim 1, characterized in that: Before generating a planting training program according to the target crops, the method further includes: When user information of the user to be recommended is obtained, the target crops are screened according to the user information to obtain the screened target crops, wherein the user information includes at least one of economic information and demand information; Correspondingly, generating a planting training program according to the target crop includes: The planting training program is generated according to the screened target crops.
5. The method for recommending a planting training program according to claim 1, characterized in that: After generating the planting training program according to the target crops, the method further includes: The planting training program is updated according to the climate data in a target time period, and the updated planting training program is pushed to the user to be recommended, wherein the target time period is a time period after the planting training program is generated.
6. The method for recommending a planting training program according to claim 1, characterized in that: After the planting training program is pushed to the user to be recommended, the method further includes: When feedback information regarding the planting training program is received from the user to be recommended, the planting training program is updated according to the feedback information, and the updated planting training program is pushed to the user to be recommended.
7. The method for recommending a planting training program according to any one of claims 1 to 6, characterized in that: Determining the target area includes: The target area is determined according to the received position information, or the target area is determined according to the position information of the user who has logged into the agricultural service system.
8. A planting training program recommendation device, characterized in that: include: A target area determination module is used to determine a target area, where the target area is an area where crops are to be planted; A target crop determination module, configured to determine target crops according to environmental data corresponding to the target area, wherein the target crops include crops matching the environmental data; A generating module, used for generating a planting training program according to the target crops; The recommendation module is used to push the planting training program to the user to be recommended.
9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method according to any one of claims 1 to 7 is implemented.
10. A computer program product, characterized in that When the computer program product runs on an electronic device, the electronic device is enabled to execute the method according to any one of claims 1 to 7.