CN117968757A

CN117968757A - Autonomous navigation inspection field crop growth management system and method

Info

Publication number: CN117968757A
Application number: CN202311777807.1A
Authority: CN
Inventors: 颜爱忠; 宋成法; 刘金宝
Original assignee: Sinoso Science And Technology Inc
Current assignee: Sinoso Science And Technology Inc
Priority date: 2023-12-22
Filing date: 2023-12-22
Publication date: 2024-05-03

Abstract

The invention relates to the technical field of field crop growth management inspection equipment, and discloses an autonomous navigation inspection field crop growth management system and method. This autonomous navigation inspection field crop growth management system gathers growth management dataset through data acquisition module, environmental assessment unit calculation environmental index Hjzs, real-time supervision crop growth environment, the quality factor Zlxs is calculated to the growth evaluation unit, real-time supervision crop's growth state, in time discover the problem, replace manual inspection be difficult for leaking the mistake, control processing module calculates management and control data group Gksjz, the operating personnel of being convenient for judges fast, it is easy and simple to handle to patrol and examine management operation, management and control data group Gksjz contrast reference dataset, judge hierarchical aassessment crop growth state, generate the processing signal, accurate control operation intensity is more manpower-saving.

Description

Autonomous navigation inspection field crop growth management system and method

Technical Field

The invention relates to the technical field of field crop growth management inspection equipment, in particular to an autonomous navigation inspection field crop growth management system and method.

Background

With the continuous development of technology, agricultural inspection equipment is continuously innovated and upgraded, so that the agricultural production efficiency and the agricultural product quality are continuously improved, and richer and safer agricultural products are provided for people in China. The inspection field crop growth management is an indispensable link in agricultural production, and relates to observation, recording and analysis of crop growth conditions so as to discover problems in time and take corresponding measures. The autonomous navigation inspection field crop growth management system is an intelligent management system for monitoring, data acquisition, analysis and processing the field crop growth environment in real time by means of modern information technology, unmanned plane technology, agricultural Internet of things technology and the like. By monitoring the growth environment of the field crops in real time, scientific basis is provided for agricultural production, and the agricultural production efficiency and economic benefit are improved.

The autonomous navigation inspection field crop growth management system mainly comprises intelligent inspection equipment, a sensor, a data acquisition module, a data analysis processing module, a user side and the like. The intelligent inspection equipment is used as a carrier of the autonomous navigation inspection system and is responsible for cruising in the field and collecting crop growth environment data. The sensor comprises a soil humidity sensor, a temperature sensor, an illumination sensor, a meteorological sensor and other sensors, and is used for monitoring various parameters of the growth environment of crops in the field in real time. The data acquisition module is responsible for acquiring, processing and transmitting the data acquired by the sensor, so that the real-time updating and remote access of the data are realized. The data analysis processing module analyzes and processes the acquired data to generate a crop growth status report, provides a basis for agricultural production decision, and regulates and controls the field crop growth environment, such as irrigation, fertilization, pest control and the like. The user side provides a friendly operation interface for agricultural producers, and realizes real-time monitoring and remote management of the field crop growth environment. When the autonomous navigation inspection field crop growth management system is applied to modern agricultural production, the autonomous navigation inspection field crop growth management system has wide application value in multiple aspects such as agricultural production efficiency, production cost, industrial structure adjustment, informatization level and the like. The method provides scientific basis for agricultural production and improves the agricultural production efficiency through real-time monitoring and regulation of the field crop growth environment. Measures such as accurate fertilization, water-saving irrigation and the like reduce the agricultural production cost and improve the economic benefit. The method can accurately control the input of pesticides, fertilizers and the like, and reduce the environmental pollution in agricultural production. Modern information technology, unmanned plane technology and other means are introduced, the agricultural informatization level is improved, and the agricultural modernization process is effectively promoted.

At present, the traditional inspection field crop growth management system needs to be connected with various sensors and intelligent equipment through a wireless communication technology, a complicated networking and remote monitoring user end needs professional technicians to install and operate, the professional requirement is high, traditional agricultural personnel learn to master and master more forcefully, and in addition, the traditional agricultural personnel also need to input corresponding labor force to assist in field operation, and operations such as spraying, weeding, fertilizing and the like cannot be controlled accurately.

Disclosure of Invention

(One) solving the technical problems

Aiming at the defects of the prior art, the invention provides an autonomous navigation inspection field crop growth management system and an autonomous navigation inspection field crop growth management method, which have the advantages of simple and convenient inspection management operation, more labor-saving operation intensity precise control and the like, and solve the problems of high operation professional requirements of the inspection management system, relatively laborious learning and mastering, incapability of precisely controlling the operation degree, and high labor intensity of personnel.

(II) technical scheme

In order to achieve the above purpose, the present invention provides the following technical solutions: an autonomous navigation inspection field crop growth management system comprises a data acquisition module, an analysis and evaluation module and a control processing module;

The data acquisition module comprises a growth environment unit, a growth progress unit and a navigation inspection unit, wherein the growth environment unit acquires a field data set in real time through a thermometer, a hygrometer, an anemometer, a barometer and an illuminance sensor and transmits the field data set to the analysis and evaluation module through a network, the growth progress unit acquires a crop data set through a database and transmits the crop data set to the analysis and evaluation module through the network, the navigation inspection unit acquires an inspection data set through a navigation inspection device setting inspection period and transmits the inspection data set to the analysis and evaluation module through the network, the growth management data set consists of the field data set, the crop data set and the inspection data set, and the data acquisition module is connected with the analysis and evaluation module through the network;

The analysis evaluation module numbers a field dataset, a crop dataset and a patrol dataset according to the characteristics of the growth management dataset, establishes a reference dataset through a network connection database, numbers the reference dataset, wherein the reference dataset comprises a reference temperature, a reference humidity, a growth tolerance reference wind speed and direction, a reference air pressure value, a reference illumination level, a qualified standard crop reference growth characteristic, a reference environment index, a reference quality coefficient and a reference management dataset, the reference dataset corresponds to the growth management dataset in a one-to-one mode, the analysis evaluation module comprises an environment evaluation unit and a growth evaluation unit, the environment evaluation unit calculates an environment index Hjzs according to the growth management dataset and the reference dataset, and transmits the environment index Hjzs to the control processing module through a network, and the growth evaluation unit calculates a quality coefficient Zlxs according to the growth management dataset and the reference dataset and transmits the growth tolerance reference wind speed and direction, the reference air pressure value, the reference illumination level, the qualified standard crop reference growth characteristic, the reference environment index, the reference quality coefficient and the reference management dataset to the control processing module through the network, and the analysis evaluation module controls the processing module through the network connection;

The control processing module calculates a management and control data set Gksjz according to an environment index Hjzs, a quality coefficient Zlxs and a reference data set, and stores the management and control data set Gksjz in a database, the control processing module judges and evaluates the growth state of crops in a grading manner according to the management and control data set Gksjz by comparing the reference data set, and generates corresponding processing signals, the control processing module comprises an fertigation unit and a weeding and pest control unit, the fertigation unit is connected and controls a spraying device according to the processing signals, and the weeding and pest control unit is connected and controls the removing device according to the processing signals.

Preferably, the analysis and evaluation module numbers the field data set, the crop data set and the inspection data set according to the characteristics of the growth management data set, wherein the field data set numbers are TJ _wd、TJ_sd、TJf_sx、TJ_qy and TJ _gz, the crop data set numbers are ZW ₁、ZW₂、ZW₃、...ZW_n, and the inspection data set numbers are XJ ₁、XJ₂、XJ₃、...XJ_n.

Preferably, the analysis and evaluation module numbers the reference dataset features according to their features, the reference data being CK _wd、CK_sd、CK_fsx、CK_qy、CK_gz、CK_zw、CK_Hjzs、CK_Zlxs and CK _gk.

Preferably, the environment assessment unit calculates the environment index Hjzs according to the growth management data set and the reference data set, and the calculation formula is as follows:

In the formula, hjzs represents an environmental index, TJ _wd-CK_wd represents a difference value between an actual temperature of a field crop growth environment and a growth reference temperature, TJ _sd-CK_sd represents a difference value between an actual humidity of the field crop growth environment and a growth reference humidity, TJ _fsx-TJ_fsx∩CK_fsx represents residual data obtained by subtracting an intersection part of an actual wind speed and a wind direction of the field crop growth environment and a growth tolerance reference wind speed and wind direction, TJ _qy-CK_qy represents a difference value between an actual air pressure value of the field crop growth environment and a growth reference air pressure value, and TJ _gz-TJ_gz∩CK_gz represents residual data obtained by subtracting an intersection part of an actual light level of the field crop growth environment and a growth reference light level.

Preferably, the growth evaluation unit calculates the quality coefficient Zlxs according to the growth management data set and the reference data set, and the calculation formula is as follows:

In the formula, zlxs represents a quality coefficient, CK _zw-ZW_n represents the number of field crops with actual growth characteristics reaching standards under the condition of normal growth and having the qualification standard of reference growth characteristics, and Z _xj represents the total planting amount of the field crops for autonomous navigation inspection.

Preferably, the control processing module calculates the management data set Gksjz according to the environmental index Hjzs, the quality coefficient Zlxs and the reference data set, and the calculation formula is as follows:

In the formula, gksjz represents a management and control data set, CK _Hjzs -Hjz represents a difference value between an actual environment index of a field crop and a reference environment index, and CK _Zlxs -Zlxs represents a difference value between an actual quality coefficient of the field crop and a reference quality coefficient.

Preferably, the control processing module determines to evaluate the growth status of the crop in a graded manner according to the control data set Gksjz, by comparing the reference data set, wherein the control data set Gksjz generates the fertigation processing signal when one of the environmental index differences is lower than the reference control data set CK _gk, and the control data set Gksjz generates the pest-killing processing signal when one of the quality coefficients is lower than the reference control data set CK _gk.

Preferably, the fertigation unit is connected with and controls the spraying device according to the fertigation processing signal and is used for spraying the liquid manure at fixed time, fixed quantity and fixed point.

Preferably, the weeding insect pest unit is connected with and controls the removing device according to the pest removal processing signal and is used for removing harmful substances quantitatively at fixed points.

Preferably, the autonomous navigation inspection field crop growth management method comprises the following steps:

the method comprises the steps that firstly, a data acquisition module acquires a field data set in real time through a growth environment unit, a crop data set is acquired through a growth progress unit, and a patrol data set is acquired through a navigation patrol unit to form a growth management data set, and the growth management data set is transmitted to an analysis and evaluation module;

Step two, the analysis and evaluation module numbers the growth management data set according to the characteristics of the growth management data set, establishes a reference data set, numbers the reference data set, calculates an environment index Hjzs and a quality coefficient Zlxs, and transmits the environment index Hjzs and the quality coefficient Zlxs to the control processing module;

Step three, a control processing module calculates a management and control data set Gksjz according to the environment index Hjzs, the quality coefficient Zlxs and the reference data set, compares the reference data set, judges and evaluates the growth state of crops in a grading manner, and generates corresponding processing signals;

and fourthly, the fertigation unit is connected with and controls the spraying device according to the processing signal, and the weeding and pest killing unit is connected with and controls the removing device according to the processing signal.

Compared with the prior art, the invention provides an autonomous navigation inspection field crop growth management system and method, which have the following beneficial effects:

1. According to the invention, a growth environment unit, a growth progress unit and a navigation inspection unit are arranged through a data acquisition module to acquire a growth management data set, an analysis and evaluation module numbers the growth management data set according to the characteristics of the growth management data set, the analysis and evaluation module establishes a reference data set and numbers the reference data set, the environment evaluation unit calculates an environment index Hjzs, normalizes various influencing variables, monitors the growth environment of field crops in real time, calculates a quality coefficient Zlxs, monitors the growth state of the crops in real time, timely finds and processes the growth problem, replaces manual inspection, is not easy to leak error, and controls a processing module to calculate a management and data set Gksjz according to the environment index Hjzs, the quality coefficient Zlxs and the reference data set, so that operators can conveniently and quickly know whether external environment factors reach the standard of normal growth, quickly know whether the growth state of the crops is healthy, and inspection management operation is simple and easy to understand.

2. According to the invention, the control processing module calculates the management and control data set Gksjz according to the environmental index Hjzs, the quality coefficient Zlxs and the reference data set, compares the reference data set, judges and evaluates the growth state of crops in a grading manner, controls the data set Gksjz, when one of the environmental index differences is lower than the reference management and control data set CK _gt, the environmental soil is water deficient and drought, generates an irrigation and fertilization processing signal, controls the data set Gksjz, when one of the quality coefficients is lower than the reference management and control data set CK _gk, the crop growth state is poor and short, generates a pest elimination processing signal, the irrigation and fertilization unit is connected with and controls the spraying device according to the irrigation and fertilization processing signal, is used for timing, quantitative and fixed-point spraying of water and fertilizer, the weeding and pest elimination unit is connected with and controls the removing device according to the pest elimination processing signal, is used for fixed-point and quantitative removal of harmful substances, and the operation strength is more labor-saving.

Drawings

FIG. 1 is a schematic diagram of a structural system of the present invention;

FIG. 2 is a schematic diagram of the structural method of the present invention.

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.

Referring to fig. 1, an autonomous navigation inspection field crop growth management system includes a data acquisition module, an analysis evaluation module and a control processing module;

The data acquisition module comprises a growth environment unit, a growth progress unit and a navigation inspection unit, wherein the growth environment unit acquires a field data set in real time through a thermometer, a hygrometer, an anemometer, a barometer and an illuminance sensor and transmits the field data set to the analysis and evaluation module through a network, the important focus is that the growth environment of crops is a basic condition for guaranteeing healthy growth and development of crops, the growth progress unit acquires the crop data set through a database and transmits the crop data set to the analysis and evaluation module through the network, the crop data set comprises data of crop types, growth characteristics, growth period and the like, the navigation inspection unit acquires an inspection data set through a navigation inspection device, and transmits the inspection data set to the analysis and evaluation module through the network, the navigation inspection device is provided with a camera, the inspection period is set according to different growth stages of different types of crops, the management operation is simple and easy to understand, the growth management data set comprises the field data set, the crop data set and the inspection data set, the data set is more comprehensive, the subsequent analysis and growth management is more accurate, and the data acquisition module is connected with the analysis and evaluation module through the network;

The analysis and evaluation module numbers a field dataset, a crop dataset and a patrol dataset according to the characteristics of the growth management dataset, wherein the field dataset numbers are TJ _wd、TJ_sd、TJ_fsx、TJ_qy and TJ _gz, the numbers correspond to the field temperature, humidity, wind direction, air pressure and illumination level, the crop dataset numbers are ZW ₁、ZW₂、ZW₃、...ZW_n, the numbers correspond to different types of crops and different growth periods, the patrol dataset numbers are XJ ₁、XJ₂、XJ₃、...XJ_n, the numbers correspond to actual growth images of different crops, the analysis and evaluation module establishes a reference dataset through a network connection database and numbers the reference dataset, the reference dataset comprises a reference temperature, a reference humidity, a growth tolerance reference wind speed and wind direction, a reference air pressure value, a reference illumination level, a qualified standard crop reference growth characteristic, a reference environment index, a reference quality coefficient and a reference management dataset number one by one, the reference dataset is CK _wd、CK_sd、CK_fsx、CK_qy、CK_qz、CK_zw、CK_Hjzs、CK_Zlxs and CK _gk, the analysis and evaluation module comprises an environment evaluation unit and a growth evaluation unit, the environment evaluation unit calculates an environment index Hjzs according to the growth management dataset and the reference dataset and transmits the environment index to the control processing module through the network, and the calculation formula is as follows:

In the formula, hjzs represents an environment index, TJ _wd-CK_wd represents a difference value between the actual temperature of the growth environment of the field crops and the growth reference temperature, TJ _sd-CK_sd represents a difference value between the actual humidity of the growth environment of the field crops and the growth reference humidity, TJ _fsx-TJ_fsx∩CK_fsx represents residual data obtained by subtracting the intersection part of the actual wind speed and the wind direction of the growth environment of the field crops and the growth tolerance reference wind speed, TJ _qy-CK_qy represents a difference value between the actual air pressure value of the growth environment of the field crops and the growth reference air pressure value, TJ _gz-TJ_gz∩CK_gz represents residual data obtained by subtracting the intersection part of the actual light level of the growth environment of the field crops and the growth reference light level, and various influencing variables are normalized according to the environment index Hjzs, so that the growth environment of the field crops is monitored in real time, and the operation intensity is convenient to follow-up accurate control;

the growth evaluation unit calculates a quality coefficient Zlxs according to the growth management data set and the reference data set, and transmits the quality coefficient Zlxs to the control processing module through a network, wherein the calculation formula is as follows:

In the formula, zlxs represents a quality coefficient, CK _zw-ZW_n represents the number of field crops with standard actual growth characteristics under the qualification standard with reference growth characteristics under the normal growth condition, Z _xj represents the total planting amount of the field crops which are independently navigated and inspected, the growth state of the crops is monitored in real time according to the quality coefficient Zlxs, and the growth problem is found and processed in time to replace manual inspection so as to avoid error leakage;

the analysis and evaluation module is connected with the control processing module through a network and transmits the environment index Hjzs, the quality coefficient Zlxs and the reference data set to the control processing module;

the control processing module calculates a management and control data set Gksjz according to the environment index Hjzs, the quality coefficient Zlxs and the reference data set, and stores the management and control data set Gksjz in a database, wherein the calculation formula is as follows:

in the formula, gksjz represents a management and control data set, CK _Hjzs -Hjz represents the difference value between the actual environmental index of the field crops and the reference environmental index, CK _Zlxs -Zlxs represents the difference value between the actual quality coefficient of the field crops and the reference quality coefficient, whether the external environmental factors reach the standard of normal growth can be quickly known according to the environmental index difference value in the management and control data set Gksjz, whether the internal growth state of the crops is healthy and grows can be quickly known according to the quality coefficient difference value in the management and control data set Gksjz, and the conclusion analysis is simple and easy to understand;

The control processing module judges and evaluates the growth state of crops in a grading manner according to the control data set Gksjz and compares the reference data set to generate corresponding processing signals, the control data set Gksjz is used for generating irrigation and fertilization processing signals when the environmental index difference is lower than the reference control data set CK _gk and the environmental soil is lack of water and drought, the control data set GKsjz is used for generating pest removal processing signals when the quality coefficient is lower than the reference control data set CK _gk and the crop growth state is poor and short, the control processing module comprises an irrigation and fertilization unit and a weeding and pest removal unit, the irrigation and fertilization unit is connected and controls a spraying device according to the irrigation and fertilization processing signals and is used for spraying water and fertilizer at fixed time and fixed time, and the weeding and pest removal unit is connected and controls a removal device according to the pest removal processing signals and is used for removing harmful substances at fixed point and fixed quantity.

An autonomous navigation inspection field crop growth management method comprises the following steps:

Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.

Claims

1. An autonomous navigation inspection field crop growth management system is characterized in that: the system comprises a data acquisition module, an analysis and evaluation module and a control processing module;

2. An autonomous navigational routing field crop growth management system as defined in claim 1, wherein: the analysis and evaluation module numbers a field data set, a crop data set and a patrol data set according to the characteristics of the growth management data set, wherein the field data set numbers are TJ _wd、TJ_sd、TJ_fsx、TJ_qy and TJ _gz, the crop data set number is ZW ₁、ZW₂、ZW₃、...ZW_n, and the patrol data set number is XJ ₁、XJ₂、XJ₃、...XJ_n.

3. An autonomous navigational routing field crop growth management system as defined in claim 2, wherein: the analysis and evaluation module numbers the reference dataset features according to their features, the reference data being CK _wd、CK_sd、CK_fsx、CK_qy、CK_gz、CK_zw、CK_Hjzs、CK_Zlxs and CK _gk.

4. An autonomous navigational routing field crop growth management system as defined in claim 3, wherein: the environment assessment unit calculates an environment index Hjzs according to the growth management data set and the reference data set, and the calculation formula is as follows:

In the formula, hjzs represents an environmental index, TJ _wd—CK_wd represents a difference value between an actual temperature of a field crop growth environment and a growth reference temperature, TJ _sd—CK_sd represents a difference value between an actual humidity of the field crop growth environment and a growth reference humidity, TJ _fsx-TJ_fsx∩ CK_fsx represents residual data obtained by subtracting an intersection part of an actual wind speed and a wind direction of the field crop growth environment and a growth tolerance reference wind speed and wind direction, TJ _qy—CK_qy represents a difference value between an actual air pressure value of the field crop growth environment and a growth reference air pressure value, and TJ _gz-TJ_gz∩CK_gz represents residual data obtained by subtracting an intersection part of an actual light level of the field crop growth environment and a growth reference light level.

5. An autonomous navigational routing field crop growth management system as defined in claim 3, wherein: the growth evaluation unit calculates a quality coefficient Zlxs according to the growth management data set and the reference data set, and the calculation formula is as follows:

6. An autonomous navigational routing field crop growth management system as defined in claim 3, wherein: the control processing module calculates a management and control data set Gksjz according to the environment index Hjzs, the quality coefficient Zlxs and the reference data set, and the calculation formula is as follows:

7. An autonomous navigational routing field crop growth management system as defined in claim 6, wherein: the control processing module judges and evaluates the growth state of crops in a grading manner according to the control data set Gksjz and the reference data set, when one of the environmental index differences in the control data set Gksjz is lower than the reference control data set CK _gk, the control processing module generates an irrigation and fertilization processing signal, and when one of the quality coefficients in the control data set Gksjz is lower than the reference control data set CK _gk, the control processing module generates a pest-killing processing signal.

8. An autonomous navigational routing field crop growth management system as defined in claim 7, wherein: the fertigation unit is connected with and controls the spraying device according to the fertigation processing signal and is used for spraying the liquid manure at fixed time, fixed quantity and fixed point.

9. An autonomous navigational routing field crop growth management system as defined in claim 7, wherein: the weeding insect pest unit is connected with and controls the removing device according to the pest removal processing signal and is used for quantitatively removing harmful substances at fixed points.

10. An autonomous navigation inspection field crop growth management method is characterized by comprising the following steps of: the method comprises the following steps: