CN116862420A - Intelligent agricultural management platform - Google Patents

Abstract

The invention discloses an intelligent agricultural management platform, and belongs to the technical field of agricultural management. The intelligent agricultural management platform comprises a real-time data monitoring module, a control module and a control module, wherein the real-time data monitoring module is used for monitoring the state of crops in real time and acquiring agricultural real-time data; the data processing and calculating module is used for preprocessing the acquired agricultural real-time data; the agricultural analysis and evaluation module is used for analyzing and evaluating the agricultural summary data and preparing a corresponding analysis and evaluation report; the remote agricultural management and control module is used for remotely managing and controlling crops; and the agricultural data storage module is used for storing various agricultural standard data in the growth cycle of crops. The invention solves the problem that the existing agricultural management cannot be effectively pre-warned and controlled based on the abnormal condition of the agricultural management, so that the agricultural management effect is poor.

Description

Intelligent agricultural management platform

Technical Field

The invention relates to the technical field of agricultural management, in particular to an intelligent agricultural management platform.

Background

The agricultural Internet of things, namely the Internet of things which is displayed in real time through various instruments and meters or is used as a parameter of automatic control and participates in the automatic control, can provide scientific basis for precise regulation and control of a greenhouse, achieves the purposes of increasing yield, improving quality, regulating growth cycle and improving economic benefit, is generally provided with a controller, and can automatically control various instruments and meters through a controller program, so that various instruments and meters do not need to be manually controlled.

The chinese patent with publication number CN217425963U discloses a wisdom agriculture thing networking controller, relates to agriculture thing networking technical field, through at mounting panel front surface mounting first guide rail and second guide rail, is favorable to protecting the display screen, reduces the influence of moisture and impurity to the display screen, through at controller main part bottom installation hollow tube and support piece to save the big-arch shelter space, the installation controller main part of being convenient for, it is more convenient to use. The above patent has the following drawbacks during actual use:

during agricultural management, early warning management and control cannot be effectively performed based on abnormal conditions of agricultural management, so that the agricultural management effect is poor.

Disclosure of Invention

The invention aims to provide an intelligent agricultural management platform which can effectively perform early warning management and control based on abnormal conditions of agricultural management, improve the agricultural management effect and solve the problems in the background technology.

In order to achieve the above purpose, the present invention provides the following technical solutions:

intelligent agricultural management platform comprising

The real-time data monitoring module is used for monitoring the state of crops in real time and acquiring agricultural real-time data, wherein the agricultural real-time data comprises, but is not limited to, air temperature and humidity, soil temperature and humidity, carbon dioxide concentration, illumination intensity and crop video image information;

The data processing and calculating module is used for preprocessing the acquired agricultural real-time data, completely extracting agricultural characterization data from the acquired agricultural real-time data according to intelligent agricultural management requirements, searching, grouping and calculating the extracted agricultural characterization data, and determining agricultural summary data based on intelligent agricultural management;

the agricultural analysis evaluation module is used for analyzing and evaluating the agricultural summary data, acquiring the agricultural summary data based on intelligent agricultural management, analyzing and evaluating the acquired agricultural summary data by referring to stored agricultural standard data based on an online data analysis method, analyzing whether the acquired agricultural summary data accords with the agricultural standard data range, determining an evaluation result according to the analysis condition, and making a corresponding analysis and evaluation report;

the remote agricultural management and control module is used for carrying out remote management and control on crops, determining a remote management and control strategy based on the analysis and evaluation report according to the formulated analysis and evaluation report, and carrying out remote management and control on the crops according to an agricultural management and control method provided on the remote management and control strategy;

the agricultural data storage module is used for storing various agricultural standard data in the growth cycle of crops and providing reference basis for analysis and evaluation of the crops.

Preferably, the real-time data monitoring module comprises

The air temperature and humidity sensor is used for monitoring the air temperature and humidity of the surrounding environment of the crops in real time, adopts a humidity sensitive element and a heat sensitive element, collects the air humidity and temperature signals of the surrounding environment of the crops in real time, and converts the signals into current signals or voltage signals which are in linear relation with the humidity and the temperature and output the current signals or the voltage signals after being processed by circuits such as voltage stabilizing filtering, operational amplification, nonlinear correction, V/I conversion, constant current and reverse protection and the like, so as to obtain the air temperature and humidity information of the surrounding environment of the crops;

the soil temperature and humidity sensor is used for monitoring the temperature and humidity of the soil where the crops are planted in real time, and the inserted temperature and humidity sensor is inserted into the soil where the crops are planted, so that the temperature and humidity of the soil where the crops are planted are monitored in real time, and the soil temperature and humidity information of the crops are obtained;

the carbon dioxide sensor is used for monitoring the carbon dioxide concentration of the surrounding environment of crops in real time, adopts an infrared carbon dioxide sensor and utilizes the non-dispersive infrared principle to detect the CO existing in the air ₂ Detecting to obtain carbon dioxide concentration information of the surrounding environment of the crops in a growing state;

The illumination sensor is used for monitoring illumination intensity of the surrounding environment of the crops in real time, an advanced photoelectric conversion module is adopted to convert an illumination intensity value into a voltage value, and then the voltage value is converted into 0-2V or 4-20mA through the conditioning circuit to obtain illumination intensity information of the surrounding environment of the crops in a growing state;

the agricultural remote sensing unmanned aerial vehicle is used for monitoring crop video images of crops in a growing state in real time, acquiring the space remote sensing information of the crops by utilizing advanced unmanned aerial vehicle technology, remote sensing sensor technology, remote sensing and remote control technology, communication technology, GPS differential positioning technology and remote sensing application technology, and acquiring the crop video images of the crops in the growing state by completing remote sensing data processing, modeling and application analysis application technology.

Preferably, the data processing calculation module comprises

The agricultural data extraction unit is used for extracting the acquired agricultural real-time data and completely extracting agricultural characterization data for intelligent agricultural management from the acquired agricultural real-time data according to intelligent agricultural management requirements;

the agricultural data retrieval unit is used for retrieving the extracted agricultural characterization data, retrieving the extracted agricultural characterization data according to a sequential retrieval method, filtering out the agricultural characterization data which are useless for intelligent agricultural management, and retaining the agricultural characterization data which are useful for intelligent agricultural management;

The agricultural data grouping unit is used for grouping the retrieved agricultural characterization data, and effectively grouping the reserved agricultural characterization data which are useful for intelligent agricultural management according to the mutual exclusivity principle based on the distribution characteristics of the agricultural characterization data so as to divide the agricultural characterization data into different groups;

the agricultural data calculation unit is used for calculating the grouped agricultural characterization data, obtaining the agricultural characterization data of each group after division, carrying out arithmetic and logic operation on the agricultural characterization data, and determining the agricultural summary data based on intelligent agricultural management.

Preferably, the agricultural data calculation unit includes:

the data analysis unit is used for acquiring the data characteristic values of the agricultural characterization data, acquiring the summarization rule of the agricultural characterization data and determining the summarization characteristic values of the agricultural characterization data under the summarization rule;

the system comprises a mode acquisition unit, a data processing unit and a data processing unit, wherein the mode acquisition unit is used for acquiring a data relationship between historical agricultural summary data and historical characterization data, obtaining a data processing rule based on the data relationship, determining a first fusion mode of data characteristic values based on the data processing rule, and determining a second fusion mode of the summary characteristic values based on the data processing rule;

The coefficient determining unit is used for determining a first selection coefficient of a first fusion mode based on the data attribute and the numerical value corresponding to the data characteristic value, and determining a second selection coefficient of a second fusion mode based on the summarized attribute and the summarized numerical value of the summarized characteristic value;

the data fusion unit is used for carrying out data fusion on the agricultural representation data corresponding to the first selection coefficient which is larger than the second selection coefficient according to the first fusion mode to obtain agricultural fusion data, and carrying out data fusion on the agricultural representation data corresponding to the first selection coefficient which is not larger than the second selection coefficient according to the second fusion mode to obtain agricultural fusion data;

the model building unit is used for acquiring summary dimensions, dividing agricultural fusion data into a plurality of fusion data in different dimensions, and building an operation logic network model based on the summary dimensions and corresponding summary rules;

the data summarizing unit is used for inputting the fusion data into the operation logic network model to realize arithmetic and logic operation on the fusion data so as to obtain initial summarized data;

the summarizing verification unit is used for carrying out numerical verification on the initial summarizing data according to the numerical range of the summarizing data, and extracting abnormal summarizing data which does not meet the numerical range of the summarizing data;

The data correction unit is used for acquiring fusion data corresponding to the abnormal summary data, and manually summarizing the fusion data to obtain normal summary data;

and the data determining unit is used for taking the normal summary data as final agricultural summary data based on intelligent agricultural management.

Preferably, the agricultural analysis and evaluation module comprises

The data comparison analysis unit is used for carrying out comparison analysis on the processed agricultural summary data to obtain agricultural summary data based on intelligent agricultural management, carrying out comparison analysis on the obtained agricultural summary data by referring to stored agricultural standard data based on an online data analysis method, judging whether the obtained agricultural summary data is in the range of the agricultural standard data, and determining a comparison analysis result according to the judgment condition;

and the data evaluation measurement unit is used for evaluating and measuring the agricultural summary data after the comparison analysis, correspondingly evaluating and measuring the agricultural summary data based on the determined comparison analysis result, and determining a corresponding analysis and evaluation report according to the evaluation and measurement condition.

Preferably, the agricultural summary data is analyzed and evaluated, and the following operations are performed:

acquiring agricultural summary data based on intelligent agricultural management;

Comparing and analyzing the obtained agricultural summary data by referring to the stored agricultural standard data, and determining a comparison and analysis result;

based on the comparison analysis result, carrying out corresponding evaluation and measurement on the agricultural summary data, and determining a corresponding analysis and evaluation report according to the evaluation and measurement condition;

aiming at the condition that the agricultural summary data is in the range of the agricultural standard data according to the analysis result, the determined analysis and evaluation report is that the intelligent agriculture management is normal;

and aiming at the condition that the analysis result is that the agricultural summarized data is not in the range of the agricultural standard data, reporting the determined analysis and evaluation as the intelligent agricultural management abnormality.

Preferably, the remote agricultural management module comprises

The remote agricultural management and control unit is used for remotely managing and controlling the intelligent agriculture and determining a remote management and control strategy based on the analysis and evaluation report according to the formulated analysis and evaluation report;

the remote agricultural execution unit is used for executing a remote management and control strategy and carrying out remote management and control on crops according to an agricultural management and control method provided by the remote management and control strategy;

the remote agricultural early warning unit is used for carrying out management early warning on the intelligent agriculture, acquiring intelligent agricultural management abnormal conditions and carrying out intelligent agricultural management early warning on the basis of the intelligent agricultural management abnormal conditions;

The management and control strategy storage unit is used for storing agricultural management and control strategies based on intelligent agricultural management, each intelligent agricultural management abnormal situation corresponds to the corresponding agricultural management and control strategy, and the intelligent agricultural management abnormal situation is solved based on the agricultural management and control strategy;

the strategy index calling unit is used for indexing and calling the agricultural management and control strategy, acquiring the agricultural management and control strategy to be executed, indexing the agricultural management and control strategy meeting the requirements from a plurality of stored agricultural management and control strategies based on the agricultural management and control strategy to be executed, and calling the indexed agricultural management and control strategy.

Preferably, the remote agricultural management and control unit comprises:

the report analysis unit is used for acquiring abnormal agricultural summary data corresponding to the intelligent agricultural management abnormality and a data standard range corresponding to the abnormal agricultural summary data from the analysis and evaluation report;

the first determining unit is used for selecting a first agricultural management and control strategy which is corresponding to the abnormal agricultural summary data from the stored multiple agricultural management and control strategies;

calculating an abnormal characteristic value of the abnormal agricultural summary data according to the following formula;

K＝α∑a+β∑b+γ∑c

wherein K represents an abnormal characteristic value of the abnormal agricultural summary data, α represents an attribute coefficient of the first attribute, Σa represents an abnormal agricultural summary data amount under the first attribute, β represents an attribute coefficient of the second attribute, Σb represents an abnormal agricultural summary data amount under the second attribute, γ represents an attribute coefficient of the third attribute, Σc represents an abnormal agricultural summary data amount under the third attribute;

Taking the industry control strategy corresponding to the abnormal characteristic value as a first agricultural control strategy;

the second determining unit is used for determining a matching value of the intelligent agriculture management abnormality and the first agriculture management strategy based on the abnormal agriculture summary data, the data standard range corresponding to the abnormal agriculture summary data, the strategy characteristics and the strategy values of the first agriculture management strategy;

wherein P represents a matching value of the intelligent agriculture management exception and the current first agriculture management policy, delta A represents a numerical value difference between the exception agriculture summarized data under the first attribute and a data standard range corresponding to the exception agriculture summarized data, and alpha ₀ Representing a policy characteristic value of the current first agricultural control policy under a first attribute, wherein delta B represents a numerical value difference between abnormal agricultural summary data under a second attribute and a data standard range corresponding to the abnormal agricultural summary data, and beta ₀ Representing a policy characteristic value of the current first agricultural control policy under the second attribute, wherein delta C represents a numerical value difference between abnormal agricultural summary data under the third attribute and a data standard range corresponding to the abnormal agricultural summary data, and gamma ₀ Representing a policy characteristic value of the current first agricultural management and control policy under a third attribute, wherein R represents a policy value of the current first agricultural management and control policy under a first attribute, Q represents a policy value of the current first agricultural management and control policy under a second attribute, and G represents a policy value of the current first agricultural management and control policy under the third attribute;

And the strategy determining unit is used for selecting the first agricultural management and control strategy with the largest matching value as a final remote management and control strategy.

Preferably, the remote management and control are carried out on crops, and the following operations are carried out:

acquiring an analysis and evaluation report based on intelligent agricultural management;

determining a remote control strategy based on the analysis evaluation report according to the analysis evaluation report;

according to the determined remote control strategy, retrieving an agricultural control strategy which is consistent with the determined remote control strategy and meets the requirements from a plurality of stored agricultural control strategies;

acquiring an indexed agricultural control strategy, and calling the indexed agricultural control strategy;

and carrying out remote management and control on crops according to the agricultural management and control method provided on the called agricultural management and control strategy.

Preferably, the agricultural management and control policies are indexed and invoked, performing the following operations:

acquiring a determined remote control strategy based on an analysis evaluation report, and extracting key word characteristics of the remote control strategy;

based on the keyword characteristics of the remote management and control strategies, retrieving the agricultural management and control strategies which are consistent with the keyword characteristics and meet the requirements from a plurality of stored agricultural management and control strategies;

Aiming at the condition that the index agricultural control strategy is consistent with the key word characteristic of the remote control strategy, the index agricultural control strategy is called out;

and continuing to index the agricultural management and control strategy until the indexed agricultural management and control strategy is consistent with the remote management and control strategy keyword feature aiming at the condition that the indexed agricultural management and control strategy is inconsistent with the remote management and control strategy keyword feature.

Compared with the prior art, the invention has the beneficial effects that:

according to the intelligent agricultural management system, the states of crops are monitored in real time, the agricultural real-time data are acquired, the acquired agricultural real-time data are preprocessed, the agricultural summary data based on intelligent agricultural management are determined, the acquired agricultural summary data are analyzed and evaluated by referring to stored agricultural standard data based on an online data analysis method, a corresponding analysis and evaluation report is determined, a remote management and control strategy based on the analysis and evaluation report is determined according to the formulated analysis and evaluation report, the crops are subjected to remote management and control according to the agricultural management and control method provided on the remote management and control strategy, the abnormal conditions based on agricultural management can be effectively warned and controlled, and the agricultural management effect is improved.

Drawings

FIG. 1 is a block diagram of a smart agricultural management platform according to the present invention;

FIG. 2 is a block diagram of the intelligent agricultural management platform of the present invention;

fig. 3 is an algorithm diagram of the present invention for remote management and control of crops.

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.

In order to solve the problem that the existing agricultural management cannot be effectively pre-warned and controlled based on the abnormal condition of the agricultural management, resulting in poor agricultural management effect, referring to fig. 1-3, the present embodiment provides the following technical scheme:

intelligent agricultural management platform comprising

The real-time data monitoring module monitors the state of crops in real time and acquires agricultural real-time data based on an air temperature and humidity sensor, a soil temperature and humidity sensor, a carbon dioxide sensor, an illumination sensor and an agricultural remote sensing unmanned aerial vehicle, wherein the agricultural real-time data comprises but is not limited to air temperature and humidity, soil temperature and humidity, carbon dioxide concentration, illumination intensity and crop video image information;

The air temperature and humidity sensor is used for monitoring the air temperature and humidity of the surrounding environment of the crops in real time, the humidity sensitive element and the thermosensitive element are used for collecting the air humidity and temperature signals of the surrounding environment of the crops in real time, and the air temperature and humidity information of the surrounding environment of the crops is obtained after the air temperature and humidity signals are converted into current signals or voltage signals which are in linear relation with the humidity and the temperature and output after being processed by circuits such as voltage stabilizing filtering, operational amplification, nonlinear correction, V/I conversion, constant current and reverse protection and the like;

the method comprises the steps of monitoring the temperature and the humidity of soil for planting crops in real time by using a soil temperature and humidity sensor, inserting the inserted temperature and humidity sensor into the soil for planting crops, monitoring the temperature and the humidity of the soil for planting crops in real time, and obtaining the temperature and humidity information of the soil for planting crops;

the carbon dioxide concentration of the surrounding environment of crops is monitored in real time by using a carbon dioxide sensor, and CO existing in the air is detected by using an infrared carbon dioxide sensor and a non-dispersive infrared principle ₂ Detecting to obtain carbon dioxide concentration information of the surrounding environment of the crops in a growing state;

The illumination intensity of the surrounding environment of the crops is monitored in real time by utilizing an illumination sensor, an advanced photoelectric conversion module is adopted to convert the illumination intensity value into a voltage value, and then the voltage value is converted into 0-2V or 4-20mA by a conditioning circuit to obtain the illumination intensity information of the surrounding environment of the crops in a growing state;

the method comprises the steps of monitoring crop video images of crops in a growing state in real time by utilizing an agricultural remote sensing unmanned aerial vehicle, acquiring space remote sensing information of the crops by utilizing an advanced unmanned aerial vehicle technology, a remote sensing sensor technology, a remote sensing and remote control technology, a communication technology, a GPS differential positioning technology and a remote sensing application technology, and acquiring the crop video images of the crops in the growing state by completing remote sensing data processing, modeling and application analysis application technologies.

Specifically, the air temperature and humidity information of the surrounding environment of the crops, the soil temperature and humidity information of the planted crops, the carbon dioxide concentration information of the surrounding environment of the crops, the illumination intensity information of the surrounding environment of the crops and the crop video image of the crops in a growing state are acquired in real time by utilizing an air temperature and humidity sensor, a soil temperature and humidity sensor, a carbon dioxide sensor, an illumination sensor and an agricultural remote sensing unmanned aerial vehicle.

The data processing calculation module is used for preprocessing the acquired agricultural real-time data, completely extracting agricultural characterization data for intelligent agricultural management from the acquired agricultural real-time data according to intelligent agricultural management requirements, searching the extracted agricultural characterization data according to a sequential searching method, filtering out the agricultural characterization data useless for intelligent agricultural management, reserving the agricultural characterization data useful for intelligent agricultural management, effectively grouping the reserved agricultural characterization data useful for intelligent agricultural management according to a mutual exclusivity principle, dividing the agricultural characterization data into different groups, performing arithmetic and logic operation on the agricultural characterization data, and determining the agricultural summary data based on intelligent agricultural management;

it should be noted that the data processing calculation module includes

The agricultural data extraction unit is used for extracting the acquired agricultural real-time data and completely extracting agricultural characterization data for intelligent agricultural management from the acquired agricultural real-time data according to intelligent agricultural management requirements;

the agricultural data retrieval unit is used for retrieving the extracted agricultural characterization data, retrieving the extracted agricultural characterization data according to a sequential retrieval method, filtering out the agricultural characterization data which are useless for intelligent agricultural management, and retaining the agricultural characterization data which are useful for intelligent agricultural management;

The agricultural data grouping unit is used for grouping the retrieved agricultural characterization data, and effectively grouping the reserved agricultural characterization data which are useful for intelligent agricultural management according to the mutual exclusivity principle based on the distribution characteristics of the agricultural characterization data so as to divide the agricultural characterization data into different groups;

the agricultural data calculation unit is used for calculating the grouped agricultural characterization data, obtaining the agricultural characterization data of each group after division, carrying out arithmetic and logic operation on the agricultural characterization data, and determining the agricultural summary data based on intelligent agricultural management.

In one embodiment, the agricultural data calculation unit includes:

the data analysis unit is used for acquiring the data characteristic values of the agricultural characterization data, acquiring the summarization rule of the agricultural characterization data and determining the summarization characteristic values of the agricultural characterization data under the summarization rule;

the system comprises a mode acquisition unit, a data processing unit and a data processing unit, wherein the mode acquisition unit is used for acquiring a data relationship between historical agricultural summary data and historical characterization data, obtaining a data processing rule based on the data relationship, determining a first fusion mode of data characteristic values based on the data processing rule, and determining a second fusion mode of the summary characteristic values based on the data processing rule;

The coefficient determining unit is used for determining a first selection coefficient of a first fusion mode based on the data attribute and the numerical value corresponding to the data characteristic value, and determining a second selection coefficient of a second fusion mode based on the summarized attribute and the summarized numerical value of the summarized characteristic value;

the data fusion unit is used for carrying out data fusion on the agricultural representation data corresponding to the first selection coefficient which is larger than the second selection coefficient according to the first fusion mode to obtain agricultural fusion data, and carrying out data fusion on the agricultural representation data corresponding to the first selection coefficient which is not larger than the second selection coefficient according to the second fusion mode to obtain agricultural fusion data;

the model building unit is used for acquiring summary dimensions, dividing agricultural fusion data into a plurality of fusion data in different dimensions, and building an operation logic network model based on the summary dimensions and corresponding summary rules;

the data summarizing unit is used for inputting the fusion data into the operation logic network model to realize arithmetic and logic operation on the fusion data so as to obtain initial summarized data;

the summarizing verification unit is used for carrying out numerical verification on the initial summarizing data according to the numerical range of the summarizing data, and extracting abnormal summarizing data which does not meet the numerical range of the summarizing data;

The data correction unit is used for acquiring fusion data corresponding to the abnormal summary data, and manually summarizing the fusion data to obtain normal summary data;

and the data determining unit is used for taking the normal summary data as final agricultural summary data based on intelligent agricultural management.

In this embodiment, the data feature value is determined according to the attribute value of the data, the summary feature value is determined according to the attribute value of the data summary, and different feature values correspond to different data attributes or summary attributes.

In this embodiment, the fusion of the agricultural characterization data is to combine, correlate and combine the data and information of the multi-sensor information sources to obtain more accurate agricultural characterization data.

In this embodiment, the first fusion mode is biased to achieve fusion of data based on the data itself, such as longitudinal fusion of carbon dioxide concentrations acquired at different times, and the second fusion mode is biased to achieve fusion of data based on data summary, such as lateral fusion of illumination intensities at different environmental locations.

In this embodiment, the more important and the larger or smaller the value of the data attribute corresponding to the data characteristic value is in agriculture, the larger the first selection coefficient of the corresponding first fusion mode is, and the same is true for the second selection coefficient.

In this embodiment, the aggregated dimension is, for example, an attribute dimension. Numerical dimensions, etc.

In this embodiment, the operation logic network model belongs to an artificial network model, and implements intelligent summarization of data, for example, adding, subtracting, multiplying, dividing and the like, to obtain summarized data.

In this embodiment, the aggregate data value range is derived from historical agricultural experience.

The beneficial effects of above-mentioned design scheme are: according to the method, data fusion is carried out on the agricultural characterization data according to the data characteristics and the summary characteristic values of the agricultural characterization data in a proper fusion mode, the data quantity for data summarization is reduced, and further, the efficiency and accuracy of data summarization are improved.

The agricultural analysis evaluation module is used for analyzing and evaluating the agricultural summary data, acquiring the agricultural summary data based on intelligent agricultural management, analyzing and evaluating the acquired agricultural summary data by referring to stored agricultural standard data based on an online data analysis method, analyzing whether the acquired agricultural summary data accords with the agricultural standard data range, determining an evaluation result according to the analysis condition, and making a corresponding analysis and evaluation report;

it should be noted that the agricultural analysis and evaluation module comprises

The data comparison analysis unit is used for carrying out comparison analysis on the processed agricultural summary data to obtain agricultural summary data based on intelligent agricultural management, carrying out comparison analysis on the obtained agricultural summary data by referring to stored agricultural standard data based on an online data analysis method, judging whether the obtained agricultural summary data is in the range of the agricultural standard data, and determining a comparison analysis result according to the judgment condition;

and the data evaluation measurement unit is used for evaluating and measuring the agricultural summary data after the comparison analysis, correspondingly evaluating and measuring the agricultural summary data based on the determined comparison analysis result, and determining a corresponding analysis and evaluation report according to the evaluation and measurement condition.

Analyzing and evaluating the agricultural summary data, and executing the following operations:

acquiring agricultural summary data based on intelligent agricultural management;

comparing and analyzing the obtained agricultural summary data by referring to the stored agricultural standard data, and determining a comparison and analysis result;

based on the comparison analysis result, carrying out corresponding evaluation and measurement on the agricultural summary data, and determining a corresponding analysis and evaluation report according to the evaluation and measurement condition;

aiming at the condition that the agricultural summary data is in the range of the agricultural standard data according to the analysis result, the determined analysis and evaluation report is that the intelligent agriculture management is normal;

and aiming at the condition that the analysis result is that the agricultural summarized data is not in the range of the agricultural standard data, reporting the determined analysis and evaluation as the intelligent agricultural management abnormality.

The remote agricultural management and control module is used for carrying out remote management and control on crops, determining a remote management and control strategy based on the analysis and evaluation report according to the formulated analysis and evaluation report, and carrying out remote management and control on the crops according to an agricultural management and control method provided on the remote management and control strategy;

it should be noted that the remote agricultural management and control module includes

The remote agricultural management and control unit is used for remotely managing and controlling the intelligent agriculture and determining a remote management and control strategy based on the analysis and evaluation report according to the formulated analysis and evaluation report;

The remote agricultural execution unit is used for executing a remote management and control strategy and carrying out remote management and control on crops according to an agricultural management and control method provided by the remote management and control strategy;

the remote agricultural early warning unit is used for carrying out management early warning on the intelligent agriculture, acquiring intelligent agricultural management abnormal conditions and carrying out intelligent agricultural management early warning on the basis of the intelligent agricultural management abnormal conditions;

the management and control strategy storage unit is used for storing agricultural management and control strategies based on intelligent agricultural management, each intelligent agricultural management abnormal situation corresponds to the corresponding agricultural management and control strategy, and the intelligent agricultural management abnormal situation is solved based on the agricultural management and control strategy;

the strategy index calling unit is used for indexing and calling the agricultural management and control strategy, acquiring the agricultural management and control strategy to be executed, indexing the agricultural management and control strategy meeting the requirements from a plurality of stored agricultural management and control strategies based on the agricultural management and control strategy to be executed, and calling the indexed agricultural management and control strategy.

In one embodiment, the remote agricultural management unit comprises:

the report analysis unit is used for acquiring abnormal agricultural summary data corresponding to the intelligent agricultural management abnormality and a data standard range corresponding to the abnormal agricultural summary data from the analysis and evaluation report;

The first determining unit is used for selecting a first agricultural management and control strategy which is corresponding to the abnormal agricultural summary data from the stored multiple agricultural management and control strategies;

calculating an abnormal characteristic value of the abnormal agricultural summary data according to the following formula;

K＝α∑a+β∑b+γ∑c

wherein K represents an abnormal characteristic value of the abnormal agricultural summary data, α represents an attribute coefficient of the first attribute, Σa represents an abnormal agricultural summary data amount under the first attribute, β represents an attribute coefficient of the second attribute, Σb represents an abnormal agricultural summary data amount under the second attribute, γ represents an attribute coefficient of the third attribute, Σc represents an abnormal agricultural summary data amount under the third attribute;

taking the industry control strategy corresponding to the abnormal characteristic value as a first agricultural control strategy;

the second determining unit is used for determining a matching value of the intelligent agriculture management abnormality and the first agriculture management strategy based on the abnormal agriculture summary data, the data standard range corresponding to the abnormal agriculture summary data, the strategy characteristics and the strategy values of the first agriculture management strategy;

wherein P represents a matching value of the intelligent agriculture management exception and the current first agriculture management policy, delta A represents a numerical value difference between the exception agriculture summarized data under the first attribute and a data standard range corresponding to the exception agriculture summarized data, and alpha ₀ Representing a policy characteristic value of the current first agricultural control policy under a first attribute, wherein delta B represents a numerical value difference between abnormal agricultural summary data under a second attribute and a data standard range corresponding to the abnormal agricultural summary data, and beta ₀ Representing a policy characteristic value of the current first agricultural control policy under the second attribute, wherein delta C represents a numerical value difference between abnormal agricultural summary data under the third attribute and a data standard range corresponding to the abnormal agricultural summary data, and gamma ₀ Representing a policy characteristic value of the current first agricultural management and control policy under a third attribute, wherein R represents a policy value of the current first agricultural management and control policy under a first attribute, Q represents a policy value of the current first agricultural management and control policy under a second attribute, and G represents a policy value of the current first agricultural management and control policy under the third attribute;

and the strategy determining unit is used for selecting the first agricultural management and control strategy with the largest matching value as a final remote management and control strategy.

In this embodiment, the anomaly characteristic value is used to represent an anomaly attribute of the anomalous agricultural summary data, such as one or more combinations of carbon dioxide anomalies and air temperature and humidity anomalies, and there may be at most 3 major anomalies.

In this embodiment, the first agricultural control strategy is multiple, the control modes are the same, and the individual operand value adjustment values are different.

In this embodiment, the policy value is used to represent the magnitude of the control effort, and the value is (0, 1).

In this embodiment, the policy feature value of the first agricultural management policy under the first attribute is related to the policy content related to the first attribute in the policy, and the more important the content, the larger the corresponding policy feature value.

In this embodiment, the first attribute is most important, the second attribute and the third attribute are sequentially the same, and alpha > beta > gamma, the values are all in (0, 1), alpha ₀ ，β ₀ ，γ ₀ As well as the same.

The beneficial effects of above-mentioned design scheme are: according to the method, the attribute condition of the abnormal agricultural summary data is calculated to match the first agricultural control strategy corresponding to the abnormal agricultural summary data, the control direction is determined, then the numerical condition of the abnormal agricultural summary data and the matching value of the strategy information of the first agricultural control strategy are utilized to select the optimal strategy as the final remote control strategy, the control intensity in the control strategy can be determined according to the abnormal numerical value, different coefficients or strategy characteristic values are set according to the influence of different attributes such as air, soil and the like on agriculture in two calculation processes, the rationality and the practicability of a calculation result are guaranteed, the accurate control on agriculture is realized, and the agricultural management effect is improved.

The agricultural data storage module is used for storing various agricultural standard data in the growth cycle of crops and providing reference basis for analysis and evaluation of the crops.

The intelligent agriculture management method is as follows: the method comprises the steps of monitoring the state of crops in real time, acquiring agricultural real-time data, preprocessing the acquired agricultural real-time data, determining agricultural summary data based on intelligent agricultural management, analyzing and evaluating the acquired agricultural summary data based on an online data analysis method, referring to stored agricultural standard data, determining a corresponding analysis and evaluation report, determining a remote management and control strategy based on the analysis and evaluation report according to the formulated analysis and evaluation report, performing remote management and control on the crops according to an agricultural management and control method provided on the remote management and control strategy, and effectively performing early warning management and control based on abnormal conditions of agricultural management, so that the agricultural management effect is improved.

Remote management and control are carried out on crops, and the following operations are executed:

acquiring an analysis and evaluation report based on intelligent agricultural management;

determining a remote control strategy based on the analysis evaluation report according to the analysis evaluation report;

according to the determined remote control strategy, retrieving an agricultural control strategy which is consistent with the determined remote control strategy and meets the requirements from a plurality of stored agricultural control strategies;

Acquiring an indexed agricultural control strategy, and calling the indexed agricultural control strategy;

and carrying out remote management and control on crops according to the agricultural management and control method provided on the called agricultural management and control strategy.

Indexing and calling the agricultural management and control strategy, and executing the following operations:

acquiring a determined remote control strategy based on an analysis evaluation report, and extracting key word characteristics of the remote control strategy;

based on the keyword characteristics of the remote management and control strategies, retrieving the agricultural management and control strategies which are consistent with the keyword characteristics and meet the requirements from a plurality of stored agricultural management and control strategies;

aiming at the condition that the index agricultural control strategy is consistent with the key word characteristic of the remote control strategy, the index agricultural control strategy is called out;

and continuing to index the agricultural management and control strategy until the indexed agricultural management and control strategy is consistent with the remote management and control strategy keyword feature aiming at the condition that the indexed agricultural management and control strategy is inconsistent with the remote management and control strategy keyword feature.

In summary, the intelligent agricultural management platform monitors the state of crops in real time, acquires agricultural real-time data, preprocesses the acquired agricultural real-time data, determines agricultural summary data based on intelligent agricultural management, analyzes and evaluates the acquired agricultural summary data based on an online data analysis method, refers to stored agricultural standard data, determines a corresponding analysis and evaluation report, determines a remote management and control strategy based on the analysis and evaluation report according to the formulated analysis and evaluation report, performs remote management and control on the crops according to the agricultural management and control method provided on the remote management and control strategy, and can effectively perform early warning and control based on abnormal conditions of agricultural management and improve the agricultural management effect.

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

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 (10)

1. Intelligent agriculture management platform, its characterized in that includes

The real-time data monitoring module is used for monitoring the state of crops in real time and acquiring agricultural real-time data, wherein the agricultural real-time data comprises, but is not limited to, air temperature and humidity, soil temperature and humidity, carbon dioxide concentration, illumination intensity and crop video image information;

The data processing and calculating module is used for preprocessing the acquired agricultural real-time data, completely extracting agricultural characterization data from the acquired agricultural real-time data according to intelligent agricultural management requirements, searching, grouping and calculating the extracted agricultural characterization data, and determining agricultural summary data based on intelligent agricultural management;

the agricultural analysis evaluation module is used for analyzing and evaluating the agricultural summary data, acquiring the agricultural summary data based on intelligent agricultural management, analyzing and evaluating the acquired agricultural summary data by referring to stored agricultural standard data based on an online data analysis method, analyzing whether the acquired agricultural summary data accords with the agricultural standard data range, determining an evaluation result according to the analysis condition, and making a corresponding analysis and evaluation report;

the remote agricultural management and control module is used for carrying out remote management and control on crops, determining a remote management and control strategy based on the analysis and evaluation report according to the formulated analysis and evaluation report, and carrying out remote management and control on the crops according to an agricultural management and control method provided on the remote management and control strategy;

the agricultural data storage module is used for storing various agricultural standard data in the growth period of crops and providing reference basis for analysis and evaluation of the crops;

The data processing calculation module comprises

The agricultural data extraction unit is used for extracting the acquired agricultural real-time data and completely extracting agricultural characterization data for intelligent agricultural management from the acquired agricultural real-time data according to intelligent agricultural management requirements;

the agricultural data retrieval unit is used for retrieving the extracted agricultural characterization data, retrieving the extracted agricultural characterization data according to a sequential retrieval method, filtering out the agricultural characterization data which are useless for intelligent agricultural management, and retaining the agricultural characterization data which are useful for intelligent agricultural management;

the agricultural data grouping unit is used for grouping the retrieved agricultural characterization data, and effectively grouping the reserved agricultural characterization data which are useful for intelligent agricultural management according to the mutual exclusivity principle based on the distribution characteristics of the agricultural characterization data so as to divide the agricultural characterization data into different groups;

the agricultural data calculation unit is used for calculating the grouped agricultural characterization data, obtaining the agricultural characterization data of each group after division, carrying out arithmetic and logic operation on the agricultural characterization data, and determining agricultural summary data based on intelligent agricultural management;

The agricultural data calculation unit includes:

the data analysis unit is used for acquiring the data characteristic values of the agricultural characterization data, acquiring the summarization rule of the agricultural characterization data and determining the summarization characteristic values of the agricultural characterization data under the summarization rule;

the system comprises a mode acquisition unit, a data processing unit and a data processing unit, wherein the mode acquisition unit is used for acquiring a data relationship between historical agricultural summary data and historical characterization data, obtaining a data processing rule based on the data relationship, determining a first fusion mode of data characteristic values based on the data processing rule, and determining a second fusion mode of the summary characteristic values based on the data processing rule;

the coefficient determining unit is used for determining a first selection coefficient of a first fusion mode based on the data attribute and the numerical value corresponding to the data characteristic value, and determining a second selection coefficient of a second fusion mode based on the summarized attribute and the summarized numerical value of the summarized characteristic value;

the data fusion unit is used for carrying out data fusion on the agricultural representation data corresponding to the first selection coefficient which is larger than the second selection coefficient according to the first fusion mode to obtain agricultural fusion data, and carrying out data fusion on the agricultural representation data corresponding to the first selection coefficient which is not larger than the second selection coefficient according to the second fusion mode to obtain agricultural fusion data;

The model building unit is used for acquiring summary dimensions, dividing agricultural fusion data into a plurality of fusion data in different dimensions, and building an operation logic network model based on the summary dimensions and corresponding summary rules;

the data summarizing unit is used for inputting the fusion data into the operation logic network model to realize arithmetic and logic operation on the fusion data so as to obtain initial summarized data;

the summarizing verification unit is used for carrying out numerical verification on the initial summarizing data according to the numerical range of the summarizing data, and extracting abnormal summarizing data which does not meet the numerical range of the summarizing data;

the data correction unit is used for acquiring fusion data corresponding to the abnormal summary data, and manually summarizing the fusion data to obtain normal summary data;

and the data determining unit is used for taking the normal summary data as final agricultural summary data based on intelligent agricultural management.

2. The intelligent agricultural management platform of claim 1, wherein: the real-time data monitoring module comprises

The air temperature and humidity sensor is used for monitoring the air temperature and humidity of the surrounding environment of the crops in real time, adopts a humidity sensitive element and a heat sensitive element, collects the air humidity and temperature signals of the surrounding environment of the crops in real time, and converts the signals into current signals or voltage signals which are in linear relation with the humidity and the temperature and outputs the current signals or the voltage signals after voltage stabilizing filtering, operational amplification, nonlinear correction, V/I conversion, constant current and reverse protection treatment to obtain the air temperature and humidity information of the surrounding environment of the crops;

The soil temperature and humidity sensor is used for monitoring the temperature and humidity of the soil where the crops are planted in real time, and the inserted temperature and humidity sensor is inserted into the soil where the crops are planted, so that the temperature and humidity of the soil where the crops are planted are monitored in real time, and the soil temperature and humidity information of the crops are obtained;

the carbon dioxide sensor is used for monitoring the carbon dioxide concentration of the surrounding environment of crops in real time, adopts an infrared carbon dioxide sensor and utilizes non-dispersive infrared sourcesManaging CO present in air ₂ And detecting to obtain the carbon dioxide concentration information of the surrounding environment of the crops in the growing state.

3. The intelligent agricultural management platform of claim 2, wherein: the real-time data monitoring module further comprises

The illumination sensor is used for monitoring illumination intensity of the surrounding environment of the crops in real time, an advanced photoelectric conversion module is adopted to convert an illumination intensity value into a voltage value, and then the voltage value is converted into 0-2V or 4-20mA through the conditioning circuit to obtain illumination intensity information of the surrounding environment of the crops in a growing state;

the agricultural remote sensing unmanned aerial vehicle is used for monitoring crop video images of crops in a growing state in real time, acquiring the space remote sensing information of the crops by utilizing advanced unmanned aerial vehicle technology, remote sensing sensor technology, remote sensing and remote control technology, communication technology, GPS differential positioning technology and remote sensing application technology, and acquiring the crop video images of the crops in the growing state by completing remote sensing data processing, modeling and application analysis application technology.

4. A smart agriculture management platform as claimed in claim 3, wherein: the agricultural analysis and evaluation module comprises

The data comparison analysis unit is used for carrying out comparison analysis on the processed agricultural summary data to obtain agricultural summary data based on intelligent agricultural management, carrying out comparison analysis on the obtained agricultural summary data by referring to stored agricultural standard data based on an online data analysis method, judging whether the obtained agricultural summary data is in the range of the agricultural standard data, and determining a comparison analysis result according to the judgment condition;

and the data evaluation measurement unit is used for evaluating and measuring the agricultural summary data after the comparison analysis, correspondingly evaluating and measuring the agricultural summary data based on the determined comparison analysis result, and determining a corresponding analysis and evaluation report according to the evaluation and measurement condition.

5. The intelligent agricultural management platform of claim 4, wherein: analyzing and evaluating the agricultural summary data, and executing the following operations:

acquiring agricultural summary data based on intelligent agricultural management;

comparing and analyzing the obtained agricultural summary data by referring to the stored agricultural standard data, and determining a comparison and analysis result;

Based on the comparison analysis result, carrying out corresponding evaluation and measurement on the agricultural summary data, and determining a corresponding analysis and evaluation report according to the evaluation and measurement condition;

aiming at the condition that the agricultural summary data is in the range of the agricultural standard data according to the analysis result, the determined analysis and evaluation report is that the intelligent agriculture management is normal;

and aiming at the condition that the analysis result is that the agricultural summarized data is not in the range of the agricultural standard data, reporting the determined analysis and evaluation as the intelligent agricultural management abnormality.

6. The intelligent agricultural management platform of claim 5, wherein: the remote agricultural management and control module comprises

The remote agricultural management and control unit is used for remotely managing and controlling the intelligent agriculture and determining a remote management and control strategy based on the analysis and evaluation report according to the formulated analysis and evaluation report;

the remote agricultural execution unit is used for executing a remote management and control strategy and carrying out remote management and control on crops according to an agricultural management and control method provided by the remote management and control strategy;

and the remote agricultural early warning unit is used for carrying out management early warning on the intelligent agriculture, acquiring abnormal intelligent agricultural management conditions and carrying out intelligent agricultural management early warning on the basis of abnormal intelligent agricultural management.

7. The intelligent agricultural management platform of claim 6, wherein: the remote agricultural management and control module further comprises

The management and control strategy storage unit is used for storing agricultural management and control strategies based on intelligent agricultural management, each intelligent agricultural management abnormal situation corresponds to the corresponding agricultural management and control strategy, and the intelligent agricultural management abnormal situation is solved based on the agricultural management and control strategy;

the strategy index calling unit is used for indexing and calling the agricultural management and control strategy, acquiring the agricultural management and control strategy to be executed, indexing the agricultural management and control strategy meeting the requirements from a plurality of stored agricultural management and control strategies based on the agricultural management and control strategy to be executed, and calling the indexed agricultural management and control strategy.

8. The intelligent agricultural management platform of claim 7, wherein: the remote agricultural management and control unit includes:

the report analysis unit is used for acquiring abnormal agricultural summary data corresponding to the intelligent agricultural management abnormality and a data standard range corresponding to the abnormal agricultural summary data from the analysis and evaluation report;

the first determining unit is used for selecting a first agricultural management and control strategy which is corresponding to the abnormal agricultural summary data from the stored multiple agricultural management and control strategies;

Calculating an abnormal characteristic value of the abnormal agricultural summary data according to the following formula;

wherein K represents an abnormal characteristic value of the abnormal agricultural summary data, α represents an attribute coefficient of the first attribute, Σa represents an abnormal agricultural summary data amount under the first attribute, β represents an attribute coefficient of the second attribute, Σb represents an abnormal agricultural summary data amount under the second attribute, γ represents an attribute coefficient of the third attribute, Σc represents an abnormal agricultural summary data amount under the third attribute;

taking the industry control strategy corresponding to the abnormal characteristic value as a first agricultural control strategy;

the second determining unit is used for determining a matching value of the intelligent agriculture management abnormality and the first agriculture management strategy based on the abnormal agriculture summary data, the data standard range corresponding to the abnormal agriculture summary data, the strategy characteristics and the strategy values of the first agriculture management strategy;

wherein P represents a matching value of the intelligent agriculture management exception and the current first agriculture management policy, delta A represents a numerical value difference between the exception agriculture summarized data under the first attribute and a data standard range corresponding to the exception agriculture summarized data, and alpha ₀ Representing a policy characteristic value of the current first agricultural control policy under a first attribute, wherein delta B represents a numerical value difference between abnormal agricultural summary data under a second attribute and a data standard range corresponding to the abnormal agricultural summary data, and beta ₀ Representing a policy characteristic value of the current first agricultural control policy under the second attribute, wherein delta C represents a numerical value difference between abnormal agricultural summary data under the third attribute and a data standard range corresponding to the abnormal agricultural summary data, and gamma ₀ Representing a policy characteristic value of the current first agricultural management and control policy under a third attribute, wherein R represents a policy value of the current first agricultural management and control policy under a first attribute, Q represents a policy value of the current first agricultural management and control policy under a second attribute, and G represents a policy value of the current first agricultural management and control policy under the third attribute;

and the strategy determining unit is used for selecting the first agricultural management and control strategy with the largest matching value as a final remote management and control strategy.

9. The intelligent agricultural management platform of claim 7, wherein: remote management and control are carried out on crops, and the following operations are executed:

acquiring an analysis and evaluation report based on intelligent agricultural management;

determining a remote control strategy based on the analysis evaluation report according to the analysis evaluation report;

according to the determined remote control strategy, retrieving an agricultural control strategy which is consistent with the determined remote control strategy and meets the requirements from a plurality of stored agricultural control strategies;

Acquiring an indexed agricultural control strategy, and calling the indexed agricultural control strategy;

and carrying out remote management and control on crops according to the agricultural management and control method provided on the called agricultural management and control strategy.

10. The intelligent agricultural management platform of claim 9, wherein: indexing and calling the agricultural management and control strategy, and executing the following operations:

acquiring a determined remote control strategy based on an analysis evaluation report, and extracting key word characteristics of the remote control strategy;

based on the keyword characteristics of the remote management and control strategies, retrieving the agricultural management and control strategies which are consistent with the keyword characteristics and meet the requirements from a plurality of stored agricultural management and control strategies;

aiming at the condition that the index agricultural control strategy is consistent with the key word characteristic of the remote control strategy, the index agricultural control strategy is called out;

and continuing to index the agricultural management and control strategy until the indexed agricultural management and control strategy is consistent with the remote management and control strategy keyword feature aiming at the condition that the indexed agricultural management and control strategy is inconsistent with the remote management and control strategy keyword feature.