A method and system for standardizing farming in greenhouses

Abstract

The present invention provides a method and system for standardizing farming in greenhouses, which obtain parameter data and the current crop planting stage in the greenhouse; obtain a farming plan for the current planting stage according to the obtained parameter data and the planting stage in combination with a pre-trained farming experience model; wherein the training of the farming experience model at least includes: screening out farmer experience data with crop yields greater than an average value, comparing the frequencies of farming operations, and directly including operations with a frequency greater than a first ratio in a standard farming list, operations less than or equal to the first ratio and greater than a second ratio in a to-be-confirmed farming list, which are imported into a model training set and continue the next round of model training, and data less than or equal to a third ratio are abandoned; the present invention automatically generates an optimal farming plan according to the collected parameter data of the greenhouse and the current growth stage, thereby greatly improving the yield and quality of farming production.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural data processing, and in particular to an agricultural standardization method and system for greenhouses. Background Art

[0002] The statements in this section merely provide background art related to the present invention and do not necessarily constitute prior art.

[0003] At present, although the area of ​​greenhouses continues to grow, there are still many development bottlenecks in the actual operation and management, especially in terms of agricultural experience. Most of them still rely on farmers' own experience to plant or manually record through paper agricultural record sheets, and there is no way to conduct statistical and experience analysis.

[0004] The inventor found that there are some agricultural recording systems on the market, but they can only record the agricultural process, without analyzing the agricultural and crop planting stages, and cannot achieve the purpose of experience conversion. Summary of the invention

[0005] In order to address the deficiencies of the prior art, the present invention provides a method and system for standardizing agricultural activities for greenhouses, which automatically generates an optimal agricultural plan based on the collected parameter data of the greenhouse and the current growth stage, thereby greatly improving the output and quality of agricultural production.

[0006] In order to achieve the above object, the present invention adopts the following technical solution:

[0007] A first aspect of the present invention provides a method for standardizing farming in a greenhouse.

[0008] A method for standardizing greenhouse farming, comprising the following steps:

[0009] Obtain parameter data in the greenhouse and the current crop planting stage;

[0010] Based on the acquired parameter data and planting stage, combined with the pre-trained farming experience model, the farming plan for the current planting stage is obtained;

[0011] Among them, the training of the agricultural experience model at least includes: screening out farmers' experience data with crop yields greater than the average, comparing the frequencies of agricultural operations, and directly including operations with frequencies greater than the first proportion in the standard agricultural list; operations less than or equal to the first proportion and greater than the second proportion are included in the agricultural list to be confirmed and imported into the model training set to continue the next round of model training; data less than or equal to the third proportion are discarded.

[0012] Furthermore, the farming plan at least includes: farming matters, farming duration and farming content.

[0013] Furthermore, the farming matter of each crop includes a unique identifier, including: the first letter of each crop, the first letter of the growth stage, the first letter of the farming matter and a multi-digit self-incremental number.

[0014] Furthermore, the farming experience model is trained based on historical data, wherein the historical data includes: manually collected farming standard list data and parameter data in the greenhouse collected by IoT devices.

[0015] Furthermore, the parameter data includes at least: equipment type, working hours, work content and consumables usage.

[0016] Furthermore, in the agricultural experience model, the agricultural plan that should be carried out in each growth stage is obtained under the condition of optimal input-output ratio.

[0017] Furthermore, in the agricultural experience model, the input-output ratio is obtained based on at least the yield, pesticide and fertilizer input, and agricultural product quality.

[0018] A second aspect of the present invention provides a farming standardization system for a greenhouse.

[0019] A standardized farming system for greenhouses, characterized by:

[0020] include:

[0021] The data acquisition module is configured to: acquire parameter data in the greenhouse and the current crop planting stage;

[0022] The farming plan production module is configured to: obtain the farming plan for the current planting stage based on the acquired parameter data and the planting stage in combination with the pre-trained farming experience model;

[0023] Among them, the training of the agricultural experience model at least includes: screening out farmers' experience data with crop yields greater than the average, comparing the frequencies of agricultural operations, and directly including operations with frequencies greater than the first proportion in the standard agricultural list; operations less than or equal to the first proportion and greater than the second proportion are included in the agricultural list to be confirmed and imported into the model training set to continue the next round of model training; data less than or equal to the third proportion are discarded.

[0024] A third aspect of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps of the agricultural standardization method for greenhouses as described in the first aspect of the present invention.

[0025] The fourth aspect of the present invention provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the agricultural standardization method for greenhouses as described in the first aspect of the present invention are implemented.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] The agricultural standardization method and system for greenhouses described in the present invention automatically generate the optimal agricultural plan based on the collected parameter data of the greenhouse and the current growth stage, thereby greatly improving the output and quality of agricultural production.

[0028] The agricultural standardization method and system for greenhouses described in the present invention screen out farmers' experience data with crop yields greater than the average, compare the frequencies of agricultural operation items, and directly include operations with agricultural operation frequencies greater than a first ratio into the standard agricultural list, operations less than or equal to the first ratio and greater than a second ratio into the agricultural list to be confirmed and imported into the model training set to continue the next round of model training, and data less than or equal to the third ratio is discarded, thereby improving the accuracy of the agricultural plan. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0030] Figure 1 A schematic diagram of the flow chart of the agricultural standardization method for greenhouses provided in Example 1 of the present invention.

[0031] Figure 2 The farming standard list provided in Example 1 of the present invention - the farming plan (tomato flowering and fruiting period and fruiting period). DETAILED DESCRIPTION

[0032] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0033] It should be noted that the following detailed descriptions are all illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0034] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0035] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0036] Embodiment 1:

[0037] like Figure 1 As shown, Embodiment 1 of the present invention provides a method for standardizing farming in a greenhouse, comprising the following processes:

[0038] Step 1: Prepare a list of agricultural standards, manually establish agricultural standard items for different growth stages of different crops, and establish a unique identifier for each crop, and output the list of agricultural standards. The unique identifier is composed of the first letter of each crop as a prefix, plus the first letter of the growth stage, plus the first letter of the agricultural item and a 6-digit self-incremental number. For example, for tomatoes, the watering items for promoting flowering are numbered: XHS-CHQ-JS-000001. The agricultural standard list is an agricultural plan for each type of crop, and outputs information such as agricultural items, agricultural duration, and agricultural content that need to be carried out at different growth stages of each crop.

[0039] Step 2: Manually collect agricultural data.

[0040] (1) Determine the farming matters, farming duration, farming content and other information through the farming standard list output in step 1, and record the farming operation information.

[0041] (2) If the agricultural standard list output in step 1 cannot meet the current agricultural record requirements, the staff can add agricultural input information items through the custom form function, continuously enrich the model training set, optimize the agricultural experience model, and guide agricultural production.

[0042] Step 3: Automatically collect agricultural data. Establish a connection with the IoT device through MQTT, Modbus, Lora, TCP and other protocols or interfaces, collect the IoT device operation data and store it in the database. The IoT device operation data includes the device type, working hours, working content, consumables usage and other contents of the IoT device; the database includes time series database, MongDB, Mysql and so on.

[0043] Step 4: Build the model training set.

[0044] (1) obtaining training data, wherein the training data includes the agricultural historical data collected manually and automatically in steps 2 and 3, and also requires manual input of the agricultural product quality score of each greenhouse, where the score ranges from 0 to 100, with 100 being the best;

[0045] (2) The training data are grouped according to the unique identifier of the agricultural item, with the same growth stage of the same crop as one group. Each group of data is automatically labeled and the model training set is output.

[0046] Step 5: Model training. The model training set output from step 4 is trained by artificial intelligence, deep learning and other methods to output a farming experience model. The core of the farming experience model is the optimal matching relationship between the crop planting stage and farming matters, that is, the farming matters, farming duration, and the amount of inputs such as agricultural materials that should be carried out at each growth stage under the condition of optimal input-output ratio. Figure 2 As shown in the figure, it is the standard list of farming - farming plan (flowering and fruiting period of tomatoes). On the 16th of the flowering and fruiting period, if the greenhouse area is 667㎡, the farmer can see the output result of watering 6m 3 The optimal input-output ratio mentioned above refers to the situation where the output is high, the inputs such as pesticides and fertilizers are reasonable, and the quality of agricultural products is the best.

[0047] (1) Filter out the model training set with higher agricultural product quality scores;

[0048] (2) Input the model training set into the preset screening model for training, and select the qualified farmer experience data according to the screening conditions. The screening method is as follows: select the farmer experience data with crop yield greater than the average value, compare the frequency of agricultural operation items in these data, and directly include the operation with a frequency greater than 80% in the standard agricultural list, and include the operation with a frequency less than 80% and greater than 50% in the agricultural list to be confirmed and imported into the model training set to continue the next round of model training. If it is less than 50%, no further analysis will be performed.

[0049] Step 6: Model application. The staff will confirm the agricultural experience model output in step 5, and update the agricultural standard list in step 1 after it is confirmed, and use the latest agricultural standards to collect agricultural data to improve the scientific nature of agricultural standards.

[0050] Embodiment 2:

[0051] Embodiment 2 of the present invention provides a farming standardization system for greenhouses, which is characterized by:

[0052] include:

[0053] The data acquisition module is configured to: acquire parameter data in the greenhouse and the current crop planting stage;

[0054] The farming plan production module is configured to: obtain the farming plan for the current planting stage based on the acquired parameter data and the planting stage in combination with the pre-trained farming experience model;

[0055] Among them, the training of the agricultural experience model at least includes: screening out farmers' experience data with crop yields greater than the average, comparing the frequencies of agricultural operations, and directly including operations with frequencies greater than the first proportion in the standard agricultural list; operations less than or equal to the first proportion and greater than the second proportion are included in the agricultural list to be confirmed and imported into the model training set to continue the next round of model training; data less than or equal to the third proportion are discarded.

[0056] The working method of the system is a schematic diagram of the flow chart of the agricultural standardization method for greenhouses provided in Example 1.

[0057] Embodiment 3:

[0058] Embodiment 3 of the present invention provides a computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps of the agricultural standardization method for greenhouses as described in Embodiment 1 of the present invention.

[0059] Embodiment 4:

[0060] Embodiment 4 of the present invention provides an electronic device, including a memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the agricultural standardization method for greenhouses as described in Embodiment 1 of the present invention are implemented.

[0061] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0062] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0063] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0064] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0065] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0066] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for standardizing farming in greenhouses, characterized in that: The process includes: Obtain parameter data in the greenhouse and the current crop planting stage; Based on the acquired parameter data and planting stage, combined with the pre-trained farming experience model, the farming plan for the current planting stage is obtained; The farming experience model is trained based on historical data, which includes: manually collected farming standard list data and greenhouse parameter data collected by IoT devices; The standard farming list is a farming plan for each type of crop, outputting the farming items, farming duration and farming content information required for each crop at different growth stages; The parameter data at least includes: equipment type, working hours, work content and consumables usage; The farming plan shall at least include: farming matters, farming duration and farming content; The core of the agricultural experience model is the optimal matching relationship between the crop planting stage and agricultural matters, and the agricultural plan that should be carried out at each growth stage is obtained under the condition of optimal input-output ratio; Among them, the training of the agricultural experience model at least includes: screening out farmers' experience data with crop yields greater than the average, comparing the frequencies of agricultural operations, and directly including operations with frequencies greater than the first proportion in the standard agricultural list; operations less than or equal to the first proportion and greater than the second proportion are included in the agricultural list to be confirmed and imported into the model training set to continue the next round of model training; data less than or equal to the third proportion are discarded.

2. The agricultural standardization method for greenhouses according to claim 1, characterized in that: The agricultural matter of each crop includes a unique identifier, including: the first letter of each crop, the first letter of the growth stage, the first letter of the agricultural matter and a multi-digit self-incremental number.

3. The agricultural standardization method for greenhouses according to claim 2, characterized in that: In the agricultural experience model, the input-output ratio is obtained based on at least the yield, pesticide and fertilizer input and agricultural product quality.

4. A farming standardization system for greenhouses, characterized by: include: The data acquisition module is configured to: acquire parameter data in the greenhouse and the current crop planting stage; The farming plan production module is configured to: obtain the farming plan for the current planting stage based on the acquired parameter data and planting stage combined with the pre-trained farming experience model; The farming experience model is trained based on historical data, which includes: manually collected farming standard list data and greenhouse parameter data collected by IoT devices; The standard farming list is a farming plan for each type of crop, outputting the farming items, farming duration and farming content information required for each crop at different growth stages; The parameter data at least includes: equipment type, working hours, work content and consumables usage; The farming plan shall at least include: farming matters, farming duration and farming content; The core of the agricultural experience model is the optimal matching relationship between the crop planting stage and agricultural matters, and the agricultural plan that should be carried out at each growth stage is obtained under the condition of optimal input-output ratio; Among them, the training of the agricultural experience model at least includes: screening out farmers' experience data with crop yields greater than the average, comparing the frequencies of agricultural operations, and directly including operations with frequencies greater than the first proportion in the standard agricultural list; operations less than or equal to the first proportion and greater than the second proportion are included in the agricultural list to be confirmed and imported into the model training set to continue the next round of model training; data less than or equal to the third proportion are discarded.

5. A computer-readable storage medium having a program stored thereon, characterized in that: When the program is executed by a processor, the steps of the agricultural standardization method for greenhouses as described in any one of claims 1 to 3 are implemented.

6. An electronic device comprising a memory, a processor, and a program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the agricultural standardization method for greenhouses as described in any one of claims 1-3 are implemented.

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