Intelligent agricultural management system

Abstract

The invention relates to an intelligent agricultural management system which comprises a farmland capturing mechanism, a multi-time training mechanism, a data acquisition mechanism and a soil moisture content analysis device. The intelligent agricultural management system is stable in operation and intelligent in design.

Description

Technical Field

[0001] The present invention relates to the field of smart agriculture, and more specifically, to a smart agriculture management system. Background Art

[0002] Agriculture is the foundation of my country's social development, and the high-quality development of agriculture has always been a hot topic of research. For example, CN119065327A discloses a smart agricultural data management method and system based on big data, which belongs to the field of artificial intelligence technology. The present invention includes the following steps: calculating the egg production of each chicken cage in different time periods, analyzing and marking abnormal chicken cages; calculating the correlation between the environmental parameters of the area to be managed and the egg production of each chicken; analyzing the influence of environmental parameters on egg production and screening out the influencing parameters; establishing a neural network model and training the neural network model; analyzing the optimal range of the influencing parameters according to the trained neural network model; judging whether the egg production abnormality is related to the environment; if the egg production abnormality is related to the environment, adjusting the environmental parameters.

[0003] CN119044164A discloses a smart agricultural Internet of Things information collection and management device, including a mobile platform and a carrier; a housing is arranged on the upper part of the mobile platform; the carrier moves telescopically on the side of the housing, a bearing ring is arranged on the lower part of the carrier, the lower surface of the bearing ring is flush with the lower surface of the carrier, a bearing seat is hinged on the lower part of the carrier, one end of the bearing seat is telescopically arranged with a movable seat, the lower part of the movable seat is vertically fixed with a vertical seat, and a threaded rod is hinged in the vertical seat. Through the rotation of the bearing seat, the data collector performs a circular comprehensive data scanning and collection around the center of the crop, and during the movement, the outer gear and the bearing ring are continuously engaged, and the outer gear moves through the bevel gear three-link bevel gear, so that the data collector can also be raised and lowered in height during the comprehensive scanning, thereby improving the accuracy of crop data collection. Summary of the invention

[0004] In order to solve the technical problems in the related fields, the present invention provides a smart agricultural management system, which performs multiple training operations on a feedforward neural network to obtain a feedforward neural network after completing the multiple training operations and outputs it as an AI analysis model, and uses the AI ​​analysis model to intelligently analyze the overall soil moisture value of the target farmland area according to multiple regional information of the target farmland area, various visual data of the imaging picture corresponding to the target farmland area, and the total number of each component pixel point of the imaging picture corresponding to the target farmland area, thereby providing key reference information for the subsequent prediction of the irrigation water volume, and also determines the irrigation water volume required for the target farmland area to reach a preset soil moisture value from the overall soil moisture value based on the overall soil moisture value of the target farmland area obtained by intelligent analysis, wherein the difference between the overall soil moisture value and the preset soil moisture value is calculated, and the determined irrigation water volume required for the target farmland area to reach the preset soil moisture value from the overall soil moisture value is positively correlated with the difference, thereby taking into account both the saving of irrigation water resources and the farmland irrigation effect.

[0005] According to the present invention, a smart agriculture management system is provided, the system comprising: A farmland capture mechanism is used to obtain multiple pieces of regional information of a target farmland area, wherein the multiple pieces of regional information of the target farmland area are the regional area, regional length, regional width, and the distance from the highest point of soil to the lowest point of soil of the target farmland area; A multiple training mechanism, used to perform multiple training operations on the feedforward neural network to obtain a feedforward neural network after completing multiple training operations and output it as an AI analysis model, wherein the number of training operations of the feedforward neural network is proportional to the area of ​​the target farmland area; A data collection mechanism is used to collect various visual data of the imaging picture corresponding to the target farmland area, wherein the various visual data of the imaging picture corresponding to the target farmland area are the respective red component values, the respective green component values, and the respective blue component values ​​corresponding to the respective component pixel points of the imaging picture corresponding to the target farmland area; A soil moisture analysis device is connected to the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism respectively, and is used to use the AI ​​analysis model to intelligently analyze the overall soil moisture value of the target farmland area according to multiple regional information of the target farmland area, various visual data of the imaging picture corresponding to the target farmland area, and the total number of each component pixel point of the imaging picture corresponding to the target farmland area; An irrigation allocation device, connected to the soil moisture analysis device, for determining the amount of irrigation water required for the target farmland area to reach a preset soil moisture value from the overall soil moisture value based on the received overall soil moisture value of the target farmland area; Among them, the irrigation allocation device is connected to the soil moisture analysis device, and is used to determine the amount of irrigation water required for the target farmland area to reach a preset soil moisture value from the overall soil moisture value based on the received overall soil moisture value of the target farmland area, including: calculating the difference between the overall soil moisture value and the preset soil moisture value, and the determined amount of irrigation water required for the target farmland area to reach the preset soil moisture value from the overall soil moisture value is positively correlated with the difference.

[0006] Therefore, the present invention has at least the following three beneficial technical effects: First, multiple training mechanisms are introduced to perform multiple training operations on the feedforward neural network to obtain the feedforward neural network after completing multiple training operations and output it as an AI analysis model. The number of training operations of the feedforward neural network is proportional to the area of ​​the target farmland area, so that AI analysis models with different structures are designed for different farmland areas, ensuring the reliability and stability of subsequent intelligent analysis results. Second: Use AI analysis models to intelligently analyze the overall soil moisture value of the target farmland area based on multiple regional information of the target farmland area, various visual data of the imaging picture corresponding to the target farmland area, and the total number of each component pixel point of the imaging picture corresponding to the target farmland area, thereby providing key reference information for the subsequent prediction of irrigation water volume; The third part: based on the overall soil moisture value of the target farmland area obtained by intelligent analysis, the amount of irrigation water required for the target farmland area to reach the preset soil moisture value from the overall soil moisture value is determined, wherein the difference between the overall soil moisture value and the preset soil moisture value is calculated, and the amount of irrigation water required for the target farmland area to reach the preset soil moisture value from the overall soil moisture value is positively correlated with the difference, thereby taking into account both the saving of irrigation water resources and the farmland irrigation effect.

[0007] The smart agricultural management system of the present invention is stable in operation and intelligent in design. Since it can use a targeted AI analysis model to intelligently analyze the overall soil moisture value of the target farmland area based on multiple regional information and various visual data of the target farmland area, it can provide key reference information for the subsequent prediction of irrigation water volume. DETAILED DESCRIPTION

[0008] Agriculture is a major water user, and its water use efficiency is not high, so there is great potential for water conservation. Vigorously developing agricultural water conservation, expanding the irrigation area and improving the irrigation guarantee rate while keeping the agricultural water consumption basically stable are important measures to promote the sustainable use of water resources, ensure food security, and accelerate the transformation of economic development methods. For example, the control layer of a general automatic irrigation system consists of three levels: the control center, the head control layer, and the field control layer. The control center adopts the "decentralized control, centralized management" mode. The head controller in the automatic irrigation system and the area it controls form a relatively independent intelligent irrigation unit, which can be operated separately. On this basis, the automatic irrigation units with close geographical locations and belonging to the same management agency are networked and connected to a central control room for centralized management. At the same time, they can cooperate with small meteorological stations and soil moisture monitoring stations to realize fully automated precision water-saving irrigation.

[0009] However, the key problem for automatic irrigation technology is that due to the different areas, regions and original soil moisture conditions of various farmlands, the same amount of water cannot obtain the overall soil moisture value of the farmland after irrigation. In other words, it is impossible to determine whether the expected irrigation target is achieved, and it is impossible to provide key reference information for the subsequent prediction of irrigation water volume. The simple and rough estimation mechanism of the overall soil moisture value in the existing technology can no longer meet the existing needs.

[0010] The implementation scheme of the smart agricultural management system of the present invention will be described in detail below. Example

[0011] The smart agricultural management system according to the first embodiment of the present invention includes: A farmland capture mechanism is used to obtain multiple pieces of regional information of a target farmland area, wherein the multiple pieces of regional information of the target farmland area are the regional area, regional length, regional width, and the distance from the highest point of soil to the lowest point of soil of the target farmland area; Specifically, the farmland capture mechanism is used to obtain multiple pieces of regional information of the target farmland area, and the multiple pieces of regional information of the target farmland area are the regional area, regional length, regional width and the distance from the highest point of the soil to the lowest point of the soil of the target farmland area. The farmland capture mechanism includes multiple parameter capture units, which are used to respectively obtain the regional area, regional length, regional width and the distance from the highest point of the soil to the lowest point of the soil of the target farmland area; A multiple training mechanism, used to perform multiple training operations on the feedforward neural network to obtain a feedforward neural network after completing multiple training operations and output it as an AI analysis model, wherein the number of training operations of the feedforward neural network is proportional to the area of ​​the target farmland area; A data collection mechanism is used to collect various visual data of the imaging picture corresponding to the target farmland area, wherein the various visual data of the imaging picture corresponding to the target farmland area are the respective red component values, the respective green component values, and the respective blue component values ​​corresponding to the respective component pixel points of the imaging picture corresponding to the target farmland area; A soil moisture analysis device is connected to the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism respectively, and is used to use the AI ​​analysis model to intelligently analyze the overall soil moisture value of the target farmland area according to multiple regional information of the target farmland area, various visual data of the imaging picture corresponding to the target farmland area, and the total number of each component pixel point of the imaging picture corresponding to the target farmland area; An irrigation allocation device, connected to the soil moisture analysis device, for determining the amount of irrigation water required for the target farmland area to reach a preset soil moisture value from the overall soil moisture value based on the received overall soil moisture value of the target farmland area; The irrigation allocation device is connected to the soil moisture analysis device and is used to determine the amount of irrigation water required for the target farmland area to reach a preset soil moisture value from the overall soil moisture value based on the received overall soil moisture value of the target farmland area, including: calculating the difference between the overall soil moisture value and the preset soil moisture value, and the determined amount of irrigation water required for the target farmland area to reach the preset soil moisture value from the overall soil moisture value is positively correlated with the difference; Among them, using the AI ​​analysis model to intelligently analyze the overall soil moisture value of the target farmland area according to multiple regional information of the target farmland area, various visual data of the imaging picture corresponding to the target farmland area, and the total number of each component pixel points of the imaging picture corresponding to the target farmland area includes: synchronously inputting the multiple regional information of the target farmland area, the various visual data of the imaging picture corresponding to the target farmland area, and the total number of each component pixel points of the imaging picture corresponding to the target farmland area into the AI ​​analysis model; Among them, using the AI ​​analysis model to intelligently analyze the overall soil moisture value of the target farmland area according to multiple regional information of the target farmland area, various visual data of the imaging picture corresponding to the target farmland area, and the total number of each component pixel point of the imaging picture corresponding to the target farmland area also includes: using MATLAB toolbox to realize simulation and testing of the AI ​​analysis model. Example

[0012] A second embodiment of the present invention shows a smart agriculture management system.

[0013] Different from the first embodiment, the smart agriculture management system in the second embodiment may further include the following components: The SOC control chip is connected to the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism respectively, and is used to provide configuration operations of working parameters for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in a time-sharing manner; The SOC control chip is respectively connected to the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism, and is used to provide the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism with the configuration operation of the working parameters in a time-sharing manner, including: the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism share the same working parameter configuration interface; Wherein, the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data collection mechanism use different configuration address data; Wherein, a parallel connection of a communication data link is established between each of the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism through a parallel data bus; Among them, the parallel connection of the communication data link established between each of the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism through a parallel data bus includes: the parallel data bus is one of an 8-bit parallel data bus, a 16-bit parallel data bus and a 32-bit parallel data bus. Example

[0014] A third embodiment of the present invention shows a smart agriculture management system.

[0015] Different from the first embodiment, the smart agriculture management system in the third embodiment may further include the following components: An electric power support device is respectively connected to the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism, and is used to provide power distribution support of different working voltages for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in a time-sharing manner; The power support device is respectively connected to the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism, and is used to provide power distribution support of different working voltages for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in a time-sharing manner, including: two or more devices with the same working voltage requirements among the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism use the same power supply line; Among them, the power support device is respectively connected to the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism, and is used to provide power distribution support of different working voltages for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in time-sharing, and also includes: the power support device is an uninterruptible power supply device; Among them, the power support device is respectively connected to the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism, and is used to provide power distribution support with different working voltages for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in time-sharing, and also includes: providing different working voltages including 3.3V working voltage for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in time-sharing; And wherein, the power support device is respectively connected to the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism, and is used to provide power distribution support with different working voltages for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in a time-sharing manner, and also includes: providing different working voltages including 5V working voltage for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in a time-sharing manner.

[0016] In addition, in the smart agriculture management system, using the AI ​​analysis model to intelligently analyze the overall soil moisture value of the target farmland area based on multiple regional information of the target farmland area, various visual data of the imaging picture corresponding to the target farmland area, and the total number of each component pixel point of the imaging picture corresponding to the target farmland area also includes: executing the AI ​​analysis model to obtain the overall soil moisture value of the target farmland area outputted by it.

[0017] While the present invention has been described with reference to certain exemplary embodiments thereof, it will be understood by those skilled in the art that various modifications and changes may be made thereto without departing from the spirit or scope of the invention as defined in the appended claims and their equivalents.

Claims

1. A smart agricultural management system, characterized in that: The system comprises: A farmland capture mechanism is used to obtain multiple pieces of regional information of a target farmland area, wherein the multiple pieces of regional information of the target farmland area are the regional area, regional length, regional width, and the distance from the highest point of soil to the lowest point of soil of the target farmland area; A multiple training mechanism, used to perform multiple training operations on the feedforward neural network to obtain a feedforward neural network after completing multiple training operations and output it as an AI analysis model, wherein the number of training operations of the feedforward neural network is proportional to the area of ​​the target farmland area; A data collection mechanism is used to collect various visual data of the imaging picture corresponding to the target farmland area, wherein the various visual data of the imaging picture corresponding to the target farmland area are the respective red component values, the respective green component values, and the respective blue component values ​​corresponding to the respective component pixel points of the imaging picture corresponding to the target farmland area; A soil moisture analysis device is connected to the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism respectively, and is used to use the AI ​​analysis model to intelligently analyze the overall soil moisture value of the target farmland area according to multiple regional information of the target farmland area, various visual data of the imaging picture corresponding to the target farmland area, and the total number of each component pixel point of the imaging picture corresponding to the target farmland area; An irrigation allocation device, connected to the soil moisture analysis device, for determining the amount of irrigation water required for the target farmland area to reach a preset soil moisture value from the overall soil moisture value based on the received overall soil moisture value of the target farmland area; Among them, the irrigation allocation device is connected to the soil moisture analysis device, and is used to determine the amount of irrigation water required for the target farmland area to reach a preset soil moisture value from the overall soil moisture value based on the received overall soil moisture value of the target farmland area, including: calculating the difference between the overall soil moisture value and the preset soil moisture value, and the determined amount of irrigation water required for the target farmland area to reach the preset soil moisture value from the overall soil moisture value is positively correlated with the difference.

2. The smart agricultural management system according to claim 1, characterized in that: Using the AI ​​analysis model to intelligently analyze the overall soil moisture value of the target farmland area according to multiple regional information of the target farmland area, various visual data of the imaging picture corresponding to the target farmland area, and the total number of each component pixel point of the imaging picture corresponding to the target farmland area includes: synchronously inputting multiple regional information of the target farmland area, various visual data of the imaging picture corresponding to the target farmland area, and the total number of each component pixel point of the imaging picture corresponding to the target farmland area into the AI ​​analysis model; Among them, using the AI ​​analysis model to intelligently analyze the overall soil moisture value of the target farmland area according to multiple regional information of the target farmland area, various visual data of the imaging picture corresponding to the target farmland area, and the total number of each component pixel point of the imaging picture corresponding to the target farmland area also includes: using MATLAB toolbox to realize simulation and testing of the AI ​​analysis model.

3. The smart agricultural management system according to claim 2, characterized in that: The system further comprises: The SOC control chip is connected to the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism respectively, and is used to provide configuration operations of working parameters for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in a time-sharing manner; Among them, the SOC control chip is respectively connected to the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism, and is used to provide the configuration operations of working parameters for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in time sharing, including: the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism share the same working parameter configuration interface.

4. The smart agricultural management system according to claim 3, characterized in that: The soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data collection mechanism use different configuration address data.

5. The smart agricultural management system according to claim 3, characterized in that: Establishing parallel connections of communication data links between the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism, and the data acquisition mechanism through parallel data buses; Among them, the parallel connection of the communication data link established between each of the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism through a parallel data bus includes: the parallel data bus is one of an 8-bit parallel data bus, a 16-bit parallel data bus and a 32-bit parallel data bus.

6. The smart agricultural management system according to claim 2, characterized in that: The system further comprises: An electric power support device is respectively connected to the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism, and is used to provide power distribution support of different working voltages for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in a time-sharing manner; Among them, the power support device is respectively connected to the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism, and is used to provide power distribution support with different working voltages for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in a time-sharing manner, including: among the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism, two or more devices with the same working voltage requirements use the same power supply line.

7. The smart agricultural management system according to claim 6, characterized in that: The power support device is respectively connected to the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism, and is used to provide power distribution support with different working voltages for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in a time-sharing manner, and also includes: the power support device is an uninterruptible power supply device.

8. The smart agricultural management system according to claim 7, characterized in that: The power support device is respectively connected to the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism, and is used to provide power distribution support with different working voltages for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in a time-sharing manner, and also includes: providing different working voltages including 3.3V working voltage for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in a time-sharing manner.

9. The smart agricultural management system according to claim 8, characterized in that: The power support device is respectively connected to the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism, and is used to provide power distribution support with different working voltages for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in a time-sharing manner, and also includes: providing different working voltages including 5V working voltage for the soil moisture analysis device, the farmland capture mechanism, the multiple training mechanism and the data acquisition mechanism in a time-sharing manner.