CN106960392B - Planting technology service method for small and medium-sized planters - Google Patents
Planting technology service method for small and medium-sized planters Download PDFInfo
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Abstract
The invention relates to a planting technique service method for small and medium-sized planters, wherein a user inputs the variety, stubble period, planting time and geographic position information of planted crops and sends a request to a server; the server generates relevant data according to the user request, and the user receives planting plan, planting process and pest control process data from the server; then the user downloads the related data and displays the related data in stages according to the local time and the time calculated by the planting plan; after the user finishes the farming methods suggested by the system, the user side returns the user finishing time, operation type and recording parameters to the server, and then sends a planting plan optimization request; after optimization, the user side downloads a new planting plan, and displays and pushes a planting process; the user side actively acquires local weather data from the server side and sends corresponding planting suggestions. The invention has the advantages that the invention can accurately and directly serve the planting, so that the small and medium-sized planters can obtain effective low-cost technical service.
Description
Technical Field
The invention relates to the technical field of agricultural technical service, in particular to a planting technical service method for small and medium-sized planters.
Background
In China, the agricultural production has the following characteristics:
1. the overall scale is large, the individual scale is small, a large number of small-sized planters with low cultural degree and low planting technology exist. 2. The plague is wide, and the planting varieties and time and methods of the various places are different due to the factors such as the environment and the planting method. 3. The lack of a technical service system or product directly oriented to small and medium-sized growers, or the inability of existing network technical service products to provide acceptably accurate technical services oriented to small and medium-sized growers.
Currently, the network technology methods in this field are as follows:
1. a common internet of things method.
And deploying the sensor in the field, acquiring data through sensing the local environment data, and further making decisions and services according to the data. The drawbacks of this solution are as follows: a. high cost and is not beneficial to large-scale popularization. b. Inconvenient use, high requirements on site environment and often needs power supply and maintenance. c. The lack of conversion from data to production guidelines is inconvenient for the grower to use and is inefficient.
2. Common internet methods.
The existing method is to carry out related arrangement on agricultural production technology through the Internet and form a database for growers to use and search. This solution does not provide accurate service contents and at the same time does not allow active service.
Disclosure of Invention
The invention aims to provide a planting technology service method for small and medium-sized planters, which overcomes the defect that the existing method cannot accurately and effectively serve the planters directly, and aims to accurately and directly serve planting, combine the planting varieties and geographic position information of the planters to realize the whole process of omnibearing service production, so that the small and medium-sized planters obtain effective low-cost technology service.
In order to achieve the above object, the present invention adopts the following technical scheme: a planting technology service method for small and medium-sized planters comprises the following steps:
(1) The user inputs the variety, stubble period (tree age), planting time and geographic position information of the planted crops at the user end, and sends a request to a server;
the server generates relevant data according to the user request, and the user receives planting plan, planting process and pest control process data from the server;
then the user downloads the related data and displays the related data in stages according to the local time and the time calculated by the planting plan;
1) The data model of the planting plan is as follows:
r3 (p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12, p13, p14, p15, p16, p17, p 18) { p1=period, p2=period, p3=period description, p4=shortest period, p5=longest period, p6=transmission time, p7=end time, p8=relative time, p9=absolute period, p10=level, p11=time reference point, p12=process period, p13=operation type, p14=operation type code };
2) The data model of the planting process is as follows:
r4 (p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12) { p1=variety, p2=process type, p3=operation type, p4=operation type code, p5=operation description, p6=content, p7=stage, p9=suitable weather, p10=highest frequency, p11=lowest frequency, p12=level, p13=picture/video };
(2) After the user finishes the farming methods suggested by the system, the user side returns parameters such as user finishing time, operation type, operation record and the like to the server, then a planting plan optimization request is sent, after the server side finishes planting plan optimization, the user side downloads a new planting plan, and displays and pushes planting process data according to the new planting plan;
(3) The user side can actively acquire local weather data from the server side, calculates whether weather processes affecting agriculture are available, and if yes, selects a corresponding planting process against weather changes to push to the user.
Further, in the data model of the planting plan, p2 is defined for the crop development stage; p4 and p5 are respectively the preset shortest and longest development time of the stage; p6, p7 are pushing time and pushing end time of the operation in the plan, and are backup basis of operation pushing; p8 and p9 are the time distance between the operation and the operation confirmed by the latest user, and are the main basis of operation pushing; p10 is an operation level for distinguishing between developmental reference points throughout the planting cycle, single agronomic operations, important agronomic operations to be tracked, and daily agronomic operations.
Further, in the data model of the planting process, p6 is a description of the process, p9 is weather suitable for the process, p10 and p11 are frequencies of execution of the process in actual operation, and p12 is a grade of the process.
Further, the user planting plan generation and process data assembly flow is as follows:
(1) inputting variety, stubble period (tree age) and planting time, and selecting whether seedling raising is needed;
(2) if seedling is needed, inputting an R1 planting variety, an R2 planting type and an R3 planting plan data model, generating a user planting plan, and updating the user planting plan before seedling according to seedling time by R3 (p 4, p5, p6 and p 7); if seedling raising is not needed, inputting an R1 planting variety, an R2 planting type and an R3 planting plan data model, and generating a user planting plan, wherein the follow-up flow is the same;
(3) and according to the field planting time, R3 (p 4, p5, p6, p 7) updates the user planting plan, R4 (p 9, p10, p11, p 12) assembles the user planting process, and finally generates the user planting plan and the planting process.
Further, the server side comprises an agronomic process module, a planting plan module, a weather and price data module, a user data module and a data interface;
the user terminal comprises a user interaction module, a planting data pushing module, a communication module and a user data module;
the agronomic process module comprises a variety library, a water and fertilizer process library, a daily process library, an environmental process library, a pest process library, a special process library and an agronomic process data interface;
the planting plan module comprises a planting plan model, a planting plan generation algorithm, a crop plan adjustment algorithm, a process data extraction algorithm and a planting plan data interface;
the user data module comprises a user planting plan, a user planting plan state, user operation data, user record data and a user data interface.
The invention has the beneficial effects that:
the method not only can provide accurate services for the growers according to varieties and regions, but also can provide different services at different stages of crop growth; and the content of the service is comprehensive and suitable, the planting process is serviced from different aspects such as water and fertilizer management, field management, pest management, special operation and the like, and meanwhile, the content of the service can be automatically adjusted according to the growth vigor of crops and the change of weather. The service range is wide, the cost is low, and the method is suitable for large-area popularization and application.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only for the purpose of more clearly illustrating the embodiments of the present invention or the technical solutions in the prior art, and that the drawings required for the description of the embodiments or the prior art will be briefly described below, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a server-side architecture;
FIG. 2 is a schematic diagram of an agronomic process module;
FIG. 3 is a schematic view of a planting plan module;
FIG. 4 is a schematic diagram of a user data module;
FIG. 5 is a schematic diagram of a client module;
FIG. 6 is a flow chart of interaction between a planting plan generating user side and a server;
FIG. 7 is a schematic diagram of a method for obtaining server process data at a client;
FIG. 8 is a user planting plan generation and process set-up flow;
FIG. 9 is a user planting plan optimization interaction flow;
FIG. 10 is a schematic diagram of a method of user planting plan optimization;
FIG. 11 is a user planting plan optimization and process set-up flow;
FIG. 12 is a user process push optimization interaction flow;
FIG. 13 is a user planting plan optimization and process set-up flow;
fig. 14 is a schematic view of a planting plan.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1 to 5, the system used with the planting technology service method for small and medium-sized planters comprises a server side for providing service for users and a user side for facilitating planting users to receive data sent by the server side;
the server side comprises an agricultural process module, a planting plan module, a weather and price data module, a user data module and a data interface;
the user terminal comprises a user interaction module, a planting data pushing module, a communication module and a user data module;
the agronomic process module comprises a variety library, a water and fertilizer process library, a daily process library, an environmental process library, a pest process library, a special process library and an agronomic process data interface;
the planting plan module comprises a planting plan model, a planting plan generation algorithm, a crop plan adjustment algorithm, a process data extraction algorithm and a planting plan data interface;
the user data module comprises a user planting plan, a user planting plan state, user operation data, user record data and a user data interface.
1. And the user side acquires a planting plan and a planting process from the server according to the variety, the geographic position and the planting mode. The user terminal selects an accurate planting process pushed to the user according to the planting plan of the user. The specific explanation is as follows:
A. planting plan, fig. 14.
The planting plan is as follows: firstly, the cultivation is divided into a plurality of stages according to different cultivars and modes, and the divided basis is based on the growth and development of crops and the change of the development stage and cultivation method of the crops as check points. And then different agronomic production processes are matched according to different stages. And finally, continuously adjusting the optimal planting plan of planting according to the confirmation time, weather change and growth condition analysis of the user, and accurately tracking production.
B. Key data structure definition:
and (3) planting variety definition:
r1 (p 1, p2, p3, p4 … pn) { p1=cucumber, p2=tomato, p3=kidney bean, p4=eggplant, … pn=apple };
planting type definition:
r2 (p 1, p2, p 3) { p1=open field, p2=sunlight greenhouse, p2=booth };
the data model of the planting plan is:
r3 (p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12, p13, p14, p15, p16, p17, p 18) { p1=period, p2=period, p3=period description, p4=shortest period, p5=longest period, p6=transmission time, p7=end time, p8=relative time, p9=absolute period, p10=level, p11=time reference point, p12=process period, p13=operation type, p14=operation type code };
wherein p2 is defined as the stage of crop development; p4 and p5 are respectively the preset shortest and longest development time of the stage; p6, p7 are pushing time and pushing end time of the operation in the plan, and are backup basis of operation pushing; p8 and p9 are the time distance between the operation and the latest user confirmation operation, and are the main basis for operation pushing.
P10 is an operational level that distinguishes between a developmental reference point (30), a single agronomic operation (25), important agronomic operations to track (20 such as water and fertilizer, medication), daily agronomic operations (10), etc. throughout the planting cycle.
C. Planting technology
The planting technology is divided into agriculture types: water and fertilizer technology, daily technology, environmental technology, pest technology and special technology.
The planting process is divided into the following steps in terms of operation time: a common process, a global process and a special process.
The data model of the planting process is as follows:
r4 (p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12) { p1=variety, p2=process type, p3=operation type, p4=operation type code, p5=operation description, p6=content, p7=stage, p9=suitable weather, p10=highest frequency, p11=lowest frequency, p12=level, p13=picture/video };
where p6 is a description of the process, p9 is weather for which the process is suitable, p10 and p11 are frequencies at which the process is performed in actual operation, and p12 is a level of the process (corresponding to p10 in a planting plan).
The interaction between the user side and the server in the planting plan generation is shown in fig. 6: the user side inputs variety and geographic position information and sends a request to the server; the server generates a planting plan and process data; the user side then downloads the relevant data.
The user inputs the variety, stubble period (tree age), planting time and geographic position information of the planted crops at the user end, and sends a request to a server; the server generates relevant data according to the user request, and the user receives planting plan, planting process and pest control process data from the server; and then the user side downloads the related data and displays the related data in stages according to the local time and the time calculated by the planting plan. As shown in fig. 7.
The specific flow method of the user planting plan generation and the process data assembly is shown in fig. 8: inputting variety, stubble period (tree age) and field planting time, selecting whether seedling raising is needed, if so, inputting an R1 planting variety, an R2 planting type and an R3 planting plan data model, generating a user planting plan, and updating the user planting plan before seedling raising according to the seedling raising time R3 (p 4, p5, p6 and p 7); if seedling is not needed, inputting an R1 planting variety, an R2 planting type and an R3 planting plan data model, generating a user planting plan, wherein the subsequent processes are the same, updating the user planting plan according to the fixed planting time by R3 (p 4, p5, p6 and p 7), assembling a user planting process by R4 (p 9, p10, p11 and p 12), and finally generating the user planting plan and the planting process.
2. Planting plan and process optimization
During the use process, the user needs to confirm the agricultural activities with the level R3 (p 10) defined as 30 in the planting plan, and further requests the server to optimize the planting plan and the process. As shown in fig. 9.
After the user finishes the farming method suggested by the planting system, the user side returns parameters such as user finishing time, operation type, operation record and the like to the server, then a planting plan optimization request is sent, after the server finishes planting plan optimization, the user side downloads a new planting plan, and the planting process data are displayed and pushed according to the new planting plan. As shown in fig. 10.
The specific flow method of the optimization of the planting plan of the server user and the assembly of the process data is shown in fig. 11: inputting the farming operation time with the level of 30, updating the user planting plan by R3 (P8, P9) according to the time and the farming completion, assembling the user planting process by R4 () according to the customizing time, and finally generating the optimized user planting plan and process. (dynamic procedure)
3. Optimizing agronomic process pushing according to weather process
When the weather process is unfavorable for the process or change of agriculture, the system can select the corresponding agriculture process according to the weather change to be pushed to the user.
The interaction between the client and the server is as shown in fig. 12: the user side sends the geographic position information to the server side, the server side generates local 10-day weather data, the user side obtains the weather data, and the user side adjusts the process according to the weather data.
The specific flow method of the user pushing plan according to the weather optimization user planting process is shown in fig. 13: after the user side obtains the local weather data, the pushing process is optimized according to the data change of the past 5 days and the future 5 days and R4 (P9), and the pushing process is pushed to the user to optimize the user planting process.
4. Planting process tracking
The system will track the main planting process of the crop:
by tracking the 30 points, the development and growth process of the crops is mastered.
The planting files of plants are mastered through tracking 20 points (water fertilizer and pesticide).
The invention builds the service module through a series of methods, and aims to accurately and directly service planting. The basic data comprise planting data, weather data, market data and the like, and the whole production process is comprehensively serviced by combining planting varieties and geographic position information of the growers, so that the small and medium-sized growers can obtain effective low-cost technical service.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (4)
1. The planting technology service method for small and medium-sized planters is characterized by comprising the following steps of:
s1: the user inputs the variety, stubble period, planting time and geographic position information of the planted crops at the user end, and sends a request to the server end;
the server side generates relevant data according to the user request, and the user side receives planting plan, planting process and pest control process data from the server side; then the user downloads the related data and displays the related data in stages according to the local time and the time calculated by the planting plan;
the data model of the planting plan is as follows:
and (3) planting variety definition:
r1 (p 1, p2, p3, p4 … pn) { p1=cucumber, p2=tomato, p3=kidney bean, p4=eggplant, … … pn=apple };
planting type definition:
r2 (p 1, p2, p 3) { p1=open field, p2=sunlight greenhouse, p3=booth };
the data model of the planting plan is:
r3 (p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12, p13, p14) { p1=period, p2=period, p3=period description, p4=shortest period, p5=longest period, p6=transmission time, p7=end time, p8=relative time, p9=absolute period, p10=level, p11=time reference point, p12=process period, p13=operation type, p14=operation type code };
in the data model of the planting plan, p2 is defined in the crop development stage; p4 and p5 are respectively the preset shortest and longest development time of the stage; p6, p7 are pushing time and pushing end time of the operation in the plan, and are backup basis of operation pushing; p8 and p9 are the time distance between the operation and the operation confirmed by the latest user, and are the main basis of operation pushing; p10 is an operation level used for distinguishing a development reference point in the whole planting period, a single agronomic operation, an important agronomic operation to be tracked and a daily agronomic operation;
the data model of the planting process is as follows:
r4 (p1, p2, p3, p4, p5, p6, p7, p8, p9, p10, p11, p12) { p1=variety, p2=process type, p3=operation type, p4=operation type code, p5=operation description, p6=content, p7=stage, p8=suitable weather, p9=highest frequency, p10=lowest frequency, p11=level, p12=picture and video };
in the data model of the planting process, p6 is the description of the process, p8 is the weather suitable for the process, p9 and p10 are the executing frequency of the process in actual operation, and p11 is the grade of the process;
the user planting plan generation and process data assembly flow is as follows:
(1) inputting varieties, ages of trees in stubble periods and planting time, and selecting whether seedling raising is needed;
(2) if seedling is needed, inputting an R1 planting variety, an R2 planting type and an R3 planting plan data model, generating a user planting plan, and updating the user planting plan before seedling according to seedling time by R3 (p 4, p5, p6 and p 7); if seedling raising is not needed, inputting an R1 planting variety, an R2 planting type and an R3 planting plan data model, and generating a user planting plan, wherein the follow-up flow is the same;
(3) according to the field planting time, R3 (p 4, p5, p6, p 7) updates a user planting plan, R4 (p 9, p10, p11, p 12) assembles a user planting process, and finally generates a user planting plan and a planting process;
s2: after the user finishes the farming methods suggested by the system, the user side returns the user finishing time, operation type and operation record parameters to the server side, then a planting plan optimization request is sent, after the server side finishes the planting plan optimization, the user side downloads a new planting plan, and displays and pushes planting process data according to the new planting plan;
s3: the user side can actively acquire local weather data from the server side, calculates whether weather processes affecting agriculture work exist or not, and if so, selects a corresponding planting process for resisting weather changes and pushes the planting process to the user;
the method comprises the steps that a user side sends geographical position information to a server side, the server side generates local 10-day weather data, the user side obtains the weather data, and the user side adjusts a process according to the weather data; after the user side obtains the local weather data, the pushing process is optimized according to the data change of the past 5 days and the future 5 days and R4 (P8), and the pushing process is pushed to the user to optimize the user planting process.
2. A planting technique service method for small and medium-sized planters according to claim 1, wherein: the optimizing of the planting plan in the step S2 specifically comprises the following steps: inputting farming operation time, updating a user planting plan according to the time and the farming completion, assembling a user planting process according to the customization time, and finally generating an optimized user planting plan and process.
3. A planting technique service method for small and medium-sized planters according to claim 1, wherein: the server side provides services for users and comprises an agronomic process module, a planting plan module, a weather and price data module, a user data module and a data interface;
the user terminal is used for receiving the data sent by the server terminal by the planting user and comprises a user interaction module, a planting data pushing module, a communication module and a user data module.
4. A planting technique service method for small and medium-sized planters according to claim 3, wherein: the agronomic process module comprises a variety library, a water and fertilizer process library, a daily process library, an environmental process library, a pest process library, a special process library and an agronomic process data interface;
the planting plan module comprises a planting plan model, a planting plan generation algorithm, a crop plan adjustment algorithm, a process data extraction algorithm and a planting plan data interface;
the user data module comprises a user planting plan, a user planting plan state, user operation data, user record data and a user data interface.
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