CN116824380A - Wisdom agricultural cloud platform monitored control system - Google Patents

Abstract

The invention relates to an intelligent agricultural cloud platform monitoring system, in particular to the technical field of agriculture, which comprises an acquisition module, a soil analysis module, a first adjustment module, a planting density analysis module, a second adjustment module, a target image and a pest analysis module, wherein the acquisition module is used for acquiring soil information, environment information, pesticide application area information and crop information, the soil analysis module is used for analyzing soil conditions, the first adjustment module is used for adjusting the process of analyzing the soil conditions, the planting density analysis module is used for analyzing the standard planting density of crops, the second adjustment module is used for adjusting the process of analyzing the standard planting density, the acquisition module is used for acquiring the target image in a crop image, the pest analysis module is used for analyzing the acquired target image, the pesticide application mode control module is used for controlling the pesticide application mode, and the optimization module is used for optimizing the control process of the pesticide application mode according to the yield of the crops in one production period.

Description

Wisdom agricultural cloud platform monitored control system

Technical Field

The invention relates to the technical field of agriculture, in particular to an intelligent agriculture cloud platform monitoring system.

Background

The intelligent agricultural cloud platform is an intelligent cloud computing platform specially designed and constructed for the agricultural field. The method applies the modern information technology, the Internet of things, the data analysis, the artificial intelligence and other technologies to agricultural production and management, and aims to improve the agricultural production efficiency, the resource utilization efficiency and the agricultural product quality and reduce the environmental impact.

The intelligent agricultural cloud platform monitoring system analyzes three layers of mountain soil conditions, planting density and influence degree of crops by insect attack, adjusts an analysis process according to factors such as salinization of soil set according to soil characteristics of mountain lands, analyzes an adjusted result and sets a corresponding application mode, so that monitoring efficiency of the crops is improved.

Chinese patent publication No.: CN110688989B discloses an intelligent agricultural monitoring management system and method based on ecological environmental protection, the monitoring management system comprises a pest statistics module, a pest database and a pest killing module, the pest statistics module is used for counting the severity of pests suffered by the current crops in a certain time interval, the pest database is used for storing the pest characteristics of various pests and the threat level of the pests, the pest killing module uses different pest killing tools to kill the pests according to the comprehensive condition of the pests suffered by the crops, the pest statistics module comprises a crop image statistics module, a pest sticking plate pest statistics module and a pest degree comprehensive analysis module, the crop image statistics module comprises a crop image acquisition module, a crop image processing module and a crop image evaluation module, and the crop image acquisition module is used for acquiring the image information of the crops; therefore, the scheme only aims at pests in the setting of the pest killing tool, does not analyze the growth environment and the growth result of crops, and has the problem of low monitoring efficiency of crops.

Disclosure of Invention

Therefore, the invention provides an intelligent agricultural cloud platform monitoring system which is used for solving the problem of low monitoring efficiency on crops in the prior art.

To achieve the above object, the present invention provides an intelligent agricultural cloud platform monitoring system, the system comprising,

the acquisition module is used for acquiring soil information, environment information, pesticide application area information and crop information;

the system comprises a soil analysis module, a soil humidity analysis module and a soil fertility analysis unit, wherein the soil analysis module is used for analyzing soil according to the ion concentration, the soil temperature and the soil humidity in collected soil, the soil analysis module is provided with a soil temperature analysis unit used for analyzing soil conditions according to the collected soil temperature, the soil analysis module is also provided with a soil humidity analysis unit used for performing secondary analysis on the soil conditions according to the collected soil humidity, and the soil analysis module is also provided with a soil fertility analysis unit used for performing tertiary analysis on the soil conditions according to the ion concentration in the collected soil;

the first adjusting module is used for adjusting the soil analysis process according to the collected environmental information;

the planting density analysis module is used for analyzing the standard planting density of crops according to the collected information of the application area;

The second adjustment module is used for adjusting the analysis process of the standard planting density according to the collected conductivity and the acid-base property of the soil, is provided with a second adjustment unit used for adjusting the analysis process of the planting density according to the collected conductivity of the soil, and is also provided with a second correction unit used for correcting the adjustment process of the analysis process of the planting density according to the collected acid-base property of the soil;

the acquisition module is used for acquiring a target image in the crop image;

the insect pest analysis module is used for analyzing insect pests according to the acquired target images;

the pesticide application mode control module is used for controlling the pesticide application mode according to the analysis result of the soil condition, the analysis result of the standard planting density of crops and the analysis result of insect pests;

and the optimizing module is used for optimizing the control process of the application mode according to the yield of crops in one growth period.

Further, the soil temperature analysis unit calculates an average temperature w0 in the collection period, compares the average temperature w0 with each preset soil temperature, and analyzes the soil according to the comparison result, wherein:

When w0 is less than w1, the soil temperature analysis unit judges that the soil temperature is unsuitable for pest growth;

when w1 is more than or equal to w0 and less than or equal to w2, the soil analysis unit judges that the soil temperature is suitable for pest growth;

when w1 is more than w2, the soil analysis unit judges that the soil temperature is very suitable for pest growth;

wherein w0= (w1+w2+) +wn/n.

Further, when the soil temperature is suitable for pest growth or the soil temperature is very suitable for pest growth, the soil humidity analysis unit calculates the average humidity s0 in the collection period, compares the average humidity s0 with each preset humidity, and analyzes the soil condition according to the comparison result, wherein:

when the soil temperature is suitable for pest growth, if s0 is less than s1, the soil humidity analysis unit judges that the soil humidity is unsuitable for pest growth in the collection period; if s1 is less than or equal to s0 and less than or equal to s2, the soil humidity analysis unit judges that the soil humidity in the collection period is suitable for pest growth; if s0 is more than s2, the soil humidity analysis unit judges that the soil humidity in the collection period is very suitable for pest growth;

when the soil temperature is very suitable for pest growth, if s0 is less than s3, the soil humidity analysis unit judges that the soil humidity is not suitable for pest growth in the collection period; if s3 is less than or equal to s0 and less than or equal to s4, the soil humidity analysis unit judges that the soil humidity in the collection period is suitable for pest growth; if s0 is more than s4, the soil humidity analysis unit judges that the soil humidity in the collection period is very suitable for pest growth;

Wherein s0= (s1+s2+) +sn)/n, n is the number of collection nodes.

Further, the soil fertility analysis unit calculates the average ion concentration in the collection period, compares the average ion concentration with each preset ion concentration, and analyzes the soil condition for three times according to the comparison result, wherein:

when the soil temperature is not suitable for the growth of pests or the soil humidity is not suitable for the growth of pests, the soil fertility analysis unit judges that the dangerous grade of the soil condition is dangerous; when the soil humidity is suitable for the growth of pests, if a0 is less than a1 and b0 is less than b1 or a1 is less than or equal to a0 and b0 is less than b1 or b1 is less than or equal to b0 and a0 is less than a1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is low; the soil fertility analysis unit judges that the dangerous grade of the soil condition is low; if a0 is more than a1 and b0 is more than b1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is medium;

when the soil humidity is very suitable for the growth of pests, if a0 is less than a1 and b0 is less than b1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is low; if a1 is less than or equal to a0 and b0 is less than or equal to b1 or b1 is less than or equal to b0 and a0 is less than a1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is medium; if a0 is more than a1 and b0 is more than b1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is high;

Wherein a0= (a1+a2+) +an)/n, b0= (b1+b2+) +bn)/n.

Further, the first adjustment module is provided with a first adjustment unit, the first adjustment unit is used for comparing the collected precipitation j0 with a preset precipitation j1, and calculating a first adjustment coefficient according to a comparison result to adjust the analysis process of the soil, wherein:

when j0 is less than or equal to j1, the first adjusting unit judges that the precipitation amount is normal and does not adjust;

when j0 > j1, the first adjusting unit determines that the precipitation is excessive, sets a first adjusting coefficient alpha to adjust the preset humidity s1, sets s1=1+ (j 1-j 0)/(j 1+ j 0), sets s1 after adjustment as s1', and sets s1' =s1×α;

the first adjustment module is further provided with a first correction unit, the first correction unit compares the collected ambient temperature t0 with a preset ambient temperature, and calculates a first correction coefficient according to a comparison result to correct an adjustment process of the soil analysis process, wherein:

when t0 is less than t1 or t0 is more than t2, the first correction unit judges that the temperature is not suitable for pest growth and does not correct;

when t1 is less than or equal to t0 and less than or equal to t2, the first correction unit judges that the temperature is suitable for pest growth, sets a first correction coefficient beta to correct a first adjustment coefficient alpha, sets beta= | (t2+t1)/2-t0|/[ (t2+t1)/2 ], sets the corrected first adjustment coefficient alpha as alpha 1, and sets alpha 1 = alpha x beta;

Wherein t1 is a preset minimum temperature, and t2 is a preset maximum temperature.

Further, the planting density analysis module calculates a standard planting density m0 of the crops according to the collected pesticide application area information, compares the standard planting density with a collected planting density m1 of the crops, and analyzes the planting density of the crops according to a comparison result, wherein:

m0= [ (x 0/x1+1) × (y0/y1+1) ]/(x0×y0), wherein x0 is the length of the application area, x1 is the preset planting pitch of the length of the application area, y0 is the width of the application area, and y1 is the preset planting pitch of the width of the application area;

when m1 is less than or equal to m0, the planting density analysis module judges that the planting density is proper;

and when m1 is more than m0, the planting density analysis module judges that the planting density is overlarge.

Further, the second adjusting unit compares the collected conductivity k0 of the soil with each preset conductivity, calculates a second adjusting coefficient according to the comparison result, and adjusts the analysis process of the planting density, wherein:

when k0 is less than k1, the second adjusting unit judges that salinization of the soil is low, sets a second adjusting coefficient gamma 1 to adjust the preset density m1, and sets gamma 1 = 1+ (k 1-k 0)/(k 1+ k 0);

When k1 is less than or equal to k0 and less than or equal to k2, the second regulating unit judges that salinization of the soil is normal and does not regulate;

when k0 is more than k2, the second adjusting unit judges that salinization of the soil is high, sets a second adjusting coefficient gamma 2 to adjust the preset density m1, and sets gamma 2 = 1- (k 2-k 0)/(k 2+ k 0);

the second adjusting unit adjusts the coefficient gamma according to a second _F Adjusting the preset density m1, setting the adjusted preset density m1 as m2, and setting m2=m1×γ _F ，F=1,2；

Wherein k1 is a preset minimum conductivity, and k2 is a preset maximum conductivity;

the second correction unit compares the acid-base property h0 of the collected soil with each preset acid-base property, calculates a second correction coefficient according to the comparison result, and corrects the second adjustment coefficient, wherein:

when H0 is less than H1 or H0 is more than H2, the second correction unit judges that the PH of the soil is low, sets a second correction coefficient H1 to correct the adjustment coefficient gamma, and sets H1=1+ (H1-H0)/(h1+h0);

when h1 is less than or equal to h0 and less than or equal to h2, the second correction unit judges that the PH of the soil is normal, and no correction is performed;

when H0 > H2, the second correction unit determines that the PH of the soil is high, sets a second correction coefficient H2 to correct the adjustment coefficient gamma, and sets H2+ (k2-k0)/(k2+k0);

The second correction unit corrects the first correction coefficient according to the second correction coefficient H _v For the second adjustment coefficient gamma _F Correcting and adding the corrected second adjustment coefficient gamma _F Let gamma be _F 'gamma' is set _F ’=H _v ×γ _F ,v=1,2；

Wherein h1 is a preset minimum pH, and h2 is a preset maximum pH.

Further, the pest analysis module performs region division on the obtained target image according to a preset gray value, calculates the threat degree of the pest according to a region division result, compares the threat degree of the pest with the preset threat degree, and analyzes the severity of the pest according to a comparison result, wherein:

when D1 is less than or equal to DO is less than or equal to D2, the insect pest analysis module takes the area with the gray value of D0 as a leaf area;

when D0 is more than D2 or D0 is less than D1, the insect pest analysis module takes the area with the gray value of D0 as a damaged area;

the pest analysis module sets the damage degree of each target image leaf as Nu, sets nu=e1/(e1+e2), sets the pest threat degree as N, sets n= (n1+n2+ & gtnu)/u, and 0 < u is less than or equal to z, wherein:

when N is less than or equal to N1, the pest analysis module judges that the pest severity is mild;

when N1 is more than or equal to N2, the pest analysis module judges that the pest severity is moderate;

when N is more than N2, the pest analysis unit judges that the pest severity is severe;

Wherein A1 is a preset minimum gray value, A2 is a preset maximum gray value, B1 is the damaged area in the target image, B2 is the leaf sub-area in the target image, z is the number of preset shooting areas, N1 is the leaf damage degree of the first target image, N2 is the leaf damage degree of the second target image, and Nu is the leaf damage degree of the u-th target image.

Further, the pesticide application mode control module controls the pesticide application mode according to the analysis result of the soil condition, the analysis result of the standard planting density of the crops and the analysis result of the insect pest, wherein:

when the pest severity is mild, no application mode is set;

when the pest severity is moderate, if i1/i is more than or equal to e1 and i2/i is less than e1, the pesticide spraying mode control module sets the unmanned aerial vehicle to spray pesticide to kill pests, and the dosage is set as R1; if i2/i is more than or equal to e1 and the planting density is too high, the pesticide spraying mode control module sets the unmanned aerial vehicle to spray pesticide to kill pests, and the dosage is set as R2;

when the severity of the insect pest is severe, if i3/i0 is more than or equal to e1 and i4/i0 is less than e1, the pesticide spraying mode control module sets the unmanned aerial vehicle to spray pesticide to kill the insect pest, and the dosage is set as R3; if i4/i0 is more than or equal to e1 and the planting density is too high, the pesticide spraying mode control module sets the unmanned aerial vehicle to spray pesticides to kill pests, and the pesticide consumption is set as R4, wherein R1 is more than R2 and less than R3 is more than R4.

Further, the optimization module compares the yield p0 of the crops in the growth period with the preset yield p1, and optimizes the control process of the application mode of the next growth period according to the comparison result, wherein:

when p0 is less than p1, the optimization module sets an optimization coefficient G1 to optimize a preset abnormal coefficient e1, and sets G1=1+ (p 1-p 0)/(p1+p0);

when p1 is more than or equal to p0 and less than or equal to p2, the optimization module does not perform optimization;

when p0 is more than p2, the optimization module sets an optimization coefficient G2 to optimize a preset abnormal coefficient e1, and sets G2=1- (p 2-p 0)/(p2+p0);

the optimization module is used for optimizing the coefficient G according to the optimization coefficient _J For preset exception systemThe number e1 is optimized, and the optimized preset density e1 is set as e1', and e1' =e1×g is set _J ,j=1,2;

Wherein, p1 is the preset minimum yield, and p2 is the preset maximum yield.

Compared with the prior art, the invention has the beneficial effects that the soil temperature analysis unit analyzes the soil temperature to analyze the suitability of insect attack at the soil temperature, compares the average temperature with the preset temperature value to improve the accuracy of soil temperature analysis, thereby improving the accuracy of the control application mode, and finally improving the monitoring efficiency of crops, the soil humidity analysis unit analyzes the soil humidity according to the analysis result of the soil temperature to analyze the suitability of insect attack at the soil humidity, compares the average humidity with the preset humidity value to improve the accuracy of soil humidity analysis, thereby improving the accuracy of controlling the application mode, and finally improving the monitoring efficiency of crops, the soil fertility analysis unit analyzes the ion concentration in soil to analyze the dangerous grade of soil conditions by calculating the average ion concentration and the preset ion concentrations, thereby improving the accuracy of the dangerous grade analysis of soil conditions, and finally improving the monitoring efficiency of crops, the first regulation unit sets the accuracy of controlling the first regulation mode, thereby improving the accuracy of the dangerous grade of crops, and finally improving the accuracy of the dangerous grade of crops, the plant density analysis module improves accuracy of standard plant density by setting various preset inter-plant distances so as to improve accuracy of plant density analysis, and further improves accuracy of control of pesticide application mode, and finally improves monitoring efficiency of crops, the second adjusting unit improves accuracy of control of pesticide application mode by setting preset conductivity so as to improve accuracy of analysis result of plant density, and further improves accuracy of control of pesticide application mode, and finally improves monitoring efficiency of crops, the second correcting unit improves accuracy of analysis result of plant density by setting preset PH so as to improve accuracy of control of pesticide application mode, and finally improves monitoring efficiency of crops by setting preset gray threshold so as to improve accuracy of dividing area, and further improves accuracy of severity judgment, and further improves monitoring efficiency of crops by setting control of pesticide application mode, and the pest control module improves efficiency of control of pesticide application mode by setting preset analysis result of pesticide application mode by analyzing soil condition, and finally improves accuracy of pesticide application mode so as to improve efficiency of control of pesticide application mode, and improve efficiency of control of pesticide application mode by setting the pesticide application mode.

Drawings

Fig. 1 is a schematic structural diagram of a smart agricultural cloud platform monitoring system according to the present embodiment;

FIG. 2 is a schematic view of the soil analysis module according to the present embodiment;

fig. 3 is a schematic structural diagram of a first adjustment module according to the present embodiment;

fig. 4 is a schematic structural diagram of a second adjustment module according to the present embodiment.

Detailed Description

In order that the objects and advantages of the invention will become more apparent, the invention will be further described with reference to the following examples; it should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.

Preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are merely for explaining the technical principles of the present invention, and are not intended to limit the scope of the present invention.

It should be noted that, in the description of the present invention, unless explicitly specified and limited otherwise, the terms "mounted," "connected," and "connected" are to be construed broadly, and may be, for example, fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; can be directly connected or indirectly connected through an intermediate medium, and can be communication between two elements. The specific meaning of the above terms in the present invention can be understood by those skilled in the art according to the specific circumstances.

Referring to fig. 1, a schematic structural diagram of a smart agricultural cloud platform monitoring system according to the present embodiment is shown, which includes,

the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring soil information, environment information, application area information and crop information, the soil information comprises ion concentration in soil, soil temperature, soil humidity, soil conductivity and acid-base property of the soil, the ion concentration comprises nitrogen ions and phosphorus ions, the environment information comprises environment temperature and precipitation amount, the application area information comprises application area length and application area width, the application area is circumscribed rectangular of a farmland, the length of the application area is circumscribed rectangular, the width of the application area is circumscribed rectangular, the crop information comprises planting density of crops and yield of the crops in a growth period, and the growth period is time from sowing to harvesting of the crops; in this embodiment, the method for collecting soil information, environmental information, information of a pesticide application area and yield of crops in a growth period is not specifically limited, and can be freely set by a person skilled in the art, and only needs to meet the requirements for collecting the soil information, the environmental information, the information of the pesticide application area and the yield of crops in the growth period, for example, the crop information can be collected interactively, the ion concentration in the soil can be collected according to a preset time node in the collection period through an electrochemical sensor, the soil temperature and the soil humidity can be collected according to a preset time node in the collection period through a temperature sensor and a humidity sensor, the conductivity of the soil can be collected in the middle period of the conductivity collection period through a conductivity sensor, the acid-base property of the soil can be collected in the middle period of the acid-base property collection period through a soil PH sensor, and the environmental temperature and the precipitation amount can be obtained through a network; in the implementation, the acquisition period and the preset time node are not particularly limited, and can be freely set by a person skilled in the art, and the acquisition period and the preset time node can be set only by meeting the setting requirements of the acquisition period and the preset time node, for example, the acquisition period can be set to be 12h, 24h and the like, the preset time node can be set to be a preset time node every 1h or 2h in the acquisition period and the like, and environmental information and planting information can be acquired through various intelligent sensors; in this embodiment, the conductivity collection period and the acid-base collection period are not specifically limited, and can be freely set by a person skilled in the art, and only the setting requirements of the conductivity collection period and the acid-base collection period are met, for example, the conductivity collection period can be set to 10 days, 15 days, etc., and the acid-base collection period can be set to 10 days, 15 days, etc.;

The soil analysis module is used for analyzing the soil according to the ion concentration, the soil temperature and the soil humidity in the collected soil, and is connected with the collected module;

the first adjusting module is used for adjusting the soil analysis process according to the collected environmental information and is connected with the soil analysis module;

the planting density analysis module is used for analyzing the standard planting density of crops according to the collected information of the application area;

the second adjusting module is used for adjusting the analysis process of the standard planting density according to the collected conductivity and acid-base property of the soil;

the acquisition module is used for acquiring a target image in the crop image, and the acquisition module is connected with the second adjustment module, and in the embodiment, the crop image is acquired by shooting a shooting area in a shooting period through a camera of the unmanned aerial vehicle, and the target image is an image of leaves of the crop; in this embodiment, the method for acquiring the target image is not limited, and a person skilled in the art can freely set the method, for example, the method includes dividing the acquired crop image into regions according to the gray values, and dividing the regions with the same gray valuesThe area is used as the same area, the contour curve of each area is used as the shape of the area, the area with the shape the same as the shape of the leaves is used as the target image, and other target image acquisition modes can be set, so that the acquisition requirement of the target image in the crop image is met; in this embodiment, the setting of the shooting period and the shooting area is not particularly limited, and a person skilled in the art can freely set the shooting period and the shooting area only by meeting the setting requirement of the shooting period and the shooting area, for example, the shooting period is set to 5 days, 7 days, 10 days, etc., for example, when the shot crops are corn, the application area can be equally divided into 9 rectangular areas, and the central area of each rectangular area is 1m ² Is set as a shooting area;

the insect pest analysis module is used for analyzing insect pests according to the acquired target images and is connected with the acquisition module;

the pesticide application mode control module is used for controlling the pesticide application mode according to the analysis result of the soil condition, the analysis result of the standard planting density of crops and the analysis result of insect pests;

and the optimizing module is used for optimizing the control process of the pesticide application mode according to the yield of crops in one growth period and is connected with the pesticide application mode control module.

Referring to fig. 2, a schematic structural diagram of a soil analysis module according to the present embodiment is shown, where the soil analysis module includes,

the soil temperature analysis unit is used for analyzing soil conditions according to the collected soil temperature;

the soil humidity analysis unit is used for carrying out secondary analysis on soil conditions according to the collected soil humidity, and is connected with the soil temperature analysis unit;

the soil fertility analysis unit is used for carrying out three-time analysis on the soil condition according to the ion concentration in the collected soil and is connected with the soil temperature analysis unit;

Fig. 3 is a schematic structural diagram of a first adjustment module according to the present embodiment, where the first adjustment module includes,

the first adjusting unit is used for adjusting the analysis process of the soil according to the collected precipitation;

the first correction unit is used for correcting the adjustment process of the analysis process of the soil according to the collected ambient temperature and is connected with the first adjustment unit;

fig. 4 is a schematic structural diagram of a second adjusting module according to the present embodiment, where the second adjusting module includes,

the second adjusting unit is used for adjusting the analysis process of the planting density according to the collected conductivity of the soil;

the second correction unit is used for correcting the adjustment process of the analysis process of the planting density according to the acidity and alkalinity of the collected soil, and is connected with the second adjustment unit.

Specifically, the agricultural monitoring system is applied to monitoring of mountain farmland pest control, and is used for analyzing three layers of mountain soil conditions, planting density and influence degree of pests on crops, adjusting analysis processes according to factors such as salinization of soil set according to soil characteristics of mountain lands, analyzing adjusted results and setting different application modes so as to improve monitoring efficiency of the crops.

Specifically, the soil temperature analysis unit analyzes the soil temperature to analyze the suitability of insect pest at the soil temperature, compares the average temperature with preset temperature values to improve the accuracy of soil temperature analysis, thereby improving the accuracy of controlling the pesticide application mode, and finally improving the monitoring efficiency of crops, the soil humidity analysis unit analyzes the soil humidity according to the analysis result of the soil temperature to analyze the suitability of insect pest at the soil humidity, compares the average humidity with the preset humidity values to improve the accuracy of soil humidity analysis, thereby improving the accuracy of controlling the pesticide application mode, and finally improving the monitoring efficiency of crops, the soil fertility analysis unit analyzes the ion concentration in soil to analyze the dangerous grade of soil conditions, compares the average ion concentration with each preset ion concentration to improve the accuracy of dangerous grade analysis of soil conditions, thereby improving the accuracy of controlling the pesticide application mode, and finally improving the monitoring efficiency of crops, the first regulation unit sets a preset precipitation to improve the accuracy of controlling the pesticide application mode, thereby improving the accuracy of dangerous grade of crops, and finally improving the accuracy of dangerous grade analysis results by setting the first regulation factor to improve the accuracy of controlling the soil conditions, the plant density analysis module improves accuracy of standard plant density by setting various preset inter-plant distances so as to improve accuracy of plant density analysis, and further improves accuracy of control of pesticide application mode, and finally improves monitoring efficiency of crops, the second adjusting unit improves accuracy of control of pesticide application mode by setting preset conductivity so as to improve accuracy of analysis result of plant density, and further improves accuracy of control of pesticide application mode, and finally improves monitoring efficiency of crops, the second correcting unit improves accuracy of analysis result of plant density by setting preset PH so as to improve accuracy of control of pesticide application mode, and finally improves monitoring efficiency of crops by setting preset gray threshold so as to improve accuracy of dividing area, and further improves accuracy of severity judgment, and further improves monitoring efficiency of crops by setting control of pesticide application mode, and the pest control module improves efficiency of control of pesticide application mode by setting preset analysis result of pesticide application mode by analyzing soil condition, and finally improves accuracy of pesticide application mode so as to improve efficiency of control of pesticide application mode, and improve efficiency of control of pesticide application mode by setting the pesticide application mode.

Specifically, the soil temperature analysis unit calculates an average temperature w0 in a collection period, compares the average temperature w0 with each preset soil temperature, and analyzes the soil according to a comparison result, wherein:

when w0 is less than w1, the soil temperature analysis unit judges that the soil temperature is unsuitable for pest growth;

when w1 is more than or equal to w0 and less than or equal to w2, the soil analysis unit judges that the soil temperature is suitable for pest growth;

when w1 is more than w2, the soil analysis unit judges that the soil temperature is very suitable for pest growth;

wherein w0= (w1+w2+ & gt/n, W1 is a preset minimum soil temperature, W2 is a preset maximum soil temperature, W1 is a soil temperature collected by a first preset time node, W2 is a soil temperature collected by a second preset time node.

Specifically, the soil temperature analysis unit analyzes the soil temperature to analyze the suitability of insect pests at the soil temperature, and compares the average temperature with a preset temperature value to improve the accuracy of soil temperature analysis, so that the accuracy of controlling the pesticide application mode is improved, and finally the monitoring efficiency of crops is improved; in this embodiment, the setting of the preset minimum soil temperature w1, the preset maximum soil temperature w2 and the number of preset time nodes is not specifically limited, and a person skilled in the art can freely set the setting of the preset minimum soil temperature w1, the preset maximum soil temperature w2 and the number of preset time nodes n only needs to be satisfied, if the pest is aphid, the optimal value of w1 is 18 °, the optimal value of w2 is 28 °, and the optimal value of n is 8.

Specifically, when the soil temperature is suitable for pest growth or the soil temperature is very suitable for pest growth, the soil humidity analysis unit calculates the average humidity s0 in the acquisition period, compares the average humidity s0 with each preset humidity, and analyzes the soil condition according to the comparison result, wherein:

when the soil temperature is suitable for pest growth, if s0 is less than s1, the soil humidity analysis unit judges that the soil humidity is unsuitable for pest growth in the collection period; if s1 is less than or equal to s0 and less than or equal to s2, the soil humidity analysis unit judges that the soil humidity in the collection period is suitable for pest growth; if s0 is more than s2, the soil humidity analysis unit judges that the soil humidity in the collection period is very suitable for pest growth;

when the soil temperature is very suitable for pest growth, if s0 is less than s3, the soil humidity analysis unit judges that the soil humidity is not suitable for pest growth in the collection period; if s3 is less than or equal to s0 and less than or equal to s4, the soil humidity analysis unit judges that the soil humidity in the collection period is suitable for pest growth; if s0 is more than s4, the soil humidity analysis unit judges that the soil humidity in the collection period is very suitable for pest growth;

wherein s0= (s1+s2+ & gt Sn)/n, n is the number of collection nodes, S1 is preset first humidity, S2 is preset second humidity, S3 is preset third humidity, S4 is preset fourth humidity, S1 < S3 < S2 < S4, S1 is the soil humidity collected by the first preset time node, S2 is the soil humidity collected by the second preset time node.

Specifically, the soil humidity analysis unit analyzes the soil humidity according to the analysis result of the soil temperature to analyze the suitability of insect damage under the soil humidity, and compares the average humidity with a preset humidity value to improve the accuracy of soil humidity analysis, thereby improving the accuracy of controlling the pesticide application mode and finally improving the monitoring efficiency of crops; in this embodiment, the setting of the preset first humidity s1, the preset second humidity s2, the preset third humidity s3 and the preset fourth humidity s4 is not specifically limited, and a person skilled in the art can freely set the setting of the preset first humidity s1, the preset second humidity s2, the preset third humidity s3 and the preset fourth humidity s4 only needs to be satisfied, for example, when the pest is an underground aphid, the optimal value of s1 is 40%, the optimal value of s2 is 65%, the optimal value of s3 is 45%, and the optimal value of s4 is 60%.

Specifically, the soil fertility analysis unit calculates the average ion concentration in the acquisition period, compares the average ion concentration with each preset ion concentration, and analyzes the soil condition for three times according to the comparison result, wherein:

when the soil temperature is not suitable for the growth of pests or the soil humidity is not suitable for the growth of pests, the soil fertility analysis unit judges that the dangerous grade of the soil condition is dangerous; when the soil humidity is suitable for the growth of pests, if a0 is less than a1 and b0 is less than b1 or a1 is less than or equal to a0 and b0 is less than b1 or b1 is less than or equal to b0 and a0 is less than a1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is low; the soil fertility analysis unit judges that the dangerous grade of the soil condition is low; if a0 is more than a1 and b0 is more than b1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is medium;

When the soil humidity is very suitable for the growth of pests, if a0 is less than a1 and b0 is less than b1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is low; if a1 is less than or equal to a0 and b0 is less than or equal to b1 or b1 is less than or equal to b0 and a0 is less than a1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is medium; if a0 is more than a1 and b0 is more than b1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is high;

wherein a0= (a1+a2+ & An)/n, b0= (b1+b2+ & Bn)/n, a0 is the average nitrogen ion concentration in the collection period, B0 is the average phosphorus ion concentration in the collection period, A1 is the preset nitrogen ion concentration, B1 is the preset phosphorus ion concentration, A1 is the nitrogen ion concentration collected by the first preset time node, A2 is the nitrogen ion concentration collected by the second preset time node.

Specifically, the soil fertility analysis unit analyzes the ion concentration in the soil to analyze the dangerous grade of the soil condition, and compares the average ion concentration with each preset ion concentration to improve the accuracy of the analysis of the dangerous grade of the soil condition, thereby improving the accuracy of the control of the pesticide application mode and finally improving the monitoring efficiency of crops; in this embodiment, the setting of the preset nitrogen ion concentration a1 and the preset phosphorus ion concentration b1 is not specifically limited, and a person skilled in the art can freely set the setting of the preset nitrogen ion concentration a1 and the preset phosphorus ion concentration b1 only needs to meet the setting requirement, for example, when the pest is an underground aphid, the optimal value of a1 is 55mg/L, and the optimal value of b1 is 28mg/L.

Specifically, the first adjusting unit is configured to compare the collected precipitation j0 with a preset precipitation j1, and calculate a first adjusting coefficient according to a comparison result to adjust an analysis process of the soil, where:

when j0 is less than or equal to j1, the first adjusting unit judges that the precipitation amount is normal and does not adjust;

when j0 > j1, the first adjusting unit determines that the precipitation is excessive, sets a first adjusting coefficient α to adjust the preset humidity s1, sets s1=1+ (j 1-j 0)/(j 1+j 0), sets s1 after the adjustment as s1', and sets s1' =s1×α.

Specifically, the first adjusting unit improves the accuracy of the first adjusting coefficient by setting the preset precipitation amount, so that the accuracy of an analysis result of the soil condition dangerous level is improved, the accuracy of controlling the pesticide application mode is improved, and finally the monitoring efficiency of crops is improved; in this embodiment, the setting of the preset precipitation amount j1 is not specifically limited, and a person skilled in the art can freely set the setting of the preset precipitation amount j1 only by meeting the value requirement of j1, wherein the optimal value of j1 is 200mm.

Specifically, the first correction unit compares the collected environmental temperature t0 with a preset environmental temperature, calculates a first correction coefficient according to a comparison result, and corrects an adjustment process of the soil analysis process, wherein:

When t0 is less than t1 or t0 is more than t2, the first correction unit judges that the temperature is not suitable for pest growth and does not correct;

when t1 is less than or equal to t0 and less than or equal to t2, the first correction unit judges that the temperature is suitable for pest growth, sets a first correction coefficient beta to correct a first adjustment coefficient alpha, sets beta= | (t2+t1)/2-t0|/[ (t2+t1)/2 ], sets the corrected first adjustment coefficient alpha as alpha 1, and sets alpha 1 = alpha x beta;

wherein t1 is a preset minimum temperature, and t2 is a preset maximum temperature.

Specifically, the first correction unit improves the accuracy of the first correction coefficient by setting the preset temperature, so that the accuracy of an analysis result of the soil condition dangerous level is improved, the accuracy of a control application mode is improved, and finally the monitoring efficiency of crops is improved; in this embodiment, the setting of t1 and t2 is not specifically limited, and a person skilled in the art can freely set the setting of t1 and t2 only by meeting the value requirement of t1 and t2, wherein, for example, in summer, the optimal value of t1 is 20 ° and the optimal value of t1 is 30 °.

Specifically, the planting density analysis module calculates a standard planting density m0 of crops according to the collected pesticide application area information, compares the standard planting density with the collected planting density m1 of the crops, and analyzes the planting density of the crops according to a comparison result, wherein:

m0= [ (x 0/x1+1) × (y0/y1+1) ]/(x0×y0), wherein x0 is the length of the application area, x1 is the preset planting pitch of the length of the application area, y0 is the width of the application area, and y1 is the preset planting pitch of the width of the application area;

when m1 is less than or equal to m0, the planting density analysis module judges that the planting density is proper;

and when m1 is more than m0, the planting density analysis module judges that the planting density is overlarge.

Specifically, the planting density analysis module improves the accuracy of standard planting density by setting various preset planting distances, so that the accuracy of planting density analysis is improved, the accuracy of controlling the pesticide application mode is further improved, and finally the monitoring efficiency of crops is improved; in this embodiment, the setting of x1 and y1 is not specifically limited, and a person skilled in the art can freely set the setting of x1 and y1 only by meeting the value requirement of x1 and y1, wherein the optimal value of x1 is 35cm, and the optimal value of y1 is 25 °.

Specifically, the second adjusting unit compares the collected conductivity k0 of the soil with each preset conductivity, calculates a second adjusting coefficient according to the comparison result, and adjusts the analysis process of the planting density, wherein:

when k0 is less than k1, the second adjusting unit judges that salinization of the soil is low, sets a second adjusting coefficient gamma 1 to adjust the preset density m1, and sets gamma 1 = 1+ (k 1-k 0)/(k 1+ k 0);

When k1 is less than or equal to k0 and less than or equal to k2, the second regulating unit judges that salinization of the soil is normal and does not regulate;

when k0 is more than k2, the second adjusting unit judges that salinization of the soil is high, sets a second adjusting coefficient gamma 2 to adjust the preset density m1, and sets gamma 2 = 1- (k 2-k 0)/(k 2+ k 0);

the second adjusting unit adjusts the coefficient gamma according to a second _F Adjusting the preset density m1, setting the adjusted preset density m1 as m2, and setting m2=m1×γ _F ，F=1,2；

Wherein k1 is a preset minimum conductivity, and k2 is a preset maximum conductivity.

Specifically, the second adjusting unit improves the accuracy of the second adjusting coefficient by setting preset conductivity, so that the accuracy of an analysis result of the planting density is improved, the accuracy of controlling the application mode is improved, and finally the monitoring efficiency of crops is improved; in this embodiment, the setting of the preset k1 and k2 is not specifically limited, and a person skilled in the art can freely set the setting of the preset k1 and k2 only by meeting the value requirement of k1 and k2, wherein the optimal value of k1 is 2 mS/cm, and the optimal value of k2 is 4mS/cm.

Specifically, the second correction unit compares the acid-base property h0 of the collected soil with each preset acid-base property, calculates a second correction coefficient according to the comparison result, and corrects the second adjustment coefficient, wherein:

When H0 is less than H1 or H0 is more than H2, the second correction unit judges that the PH of the soil is low, sets a second correction coefficient H1 to correct the adjustment coefficient gamma, and sets H1=1+ (H1-H0)/(h1+h0);

when h1 is less than or equal to h0 and less than or equal to h2, the second correction unit judges that the PH of the soil is normal, and no correction is performed;

when H0 > H2, the second correction unit determines that the PH of the soil is high, sets a second correction coefficient H2 to correct the adjustment coefficient gamma, and sets H2+ (k2-k0)/(k2+k0);

the second correction unit corrects the first correction coefficient according to the second correction coefficient H _v For the second adjustment coefficient gamma _F Correcting and adding the corrected second adjustment coefficient gamma _F Let gamma be _F 'gamma' is set _F ’=H _v ×γ _F ,v=1,2；

Wherein h1 is a preset minimum pH, and h2 is a preset maximum pH.

Specifically, the second correction unit improves the accuracy of the second correction coefficient by setting the preset PH, so that the accuracy of the analysis result of the planting density is improved, the accuracy of the control application mode is improved, and finally the monitoring efficiency of crops is improved; in this embodiment, the setting of the preset values h1 and h2 is not specifically limited, and a person skilled in the art can freely set the setting of the preset values only by meeting the value requirements of h1 and h2, wherein the optimal value of h1 is 4.5, and the optimal value of h2 is 7.

Specifically, the pest analysis module performs region division on the obtained target image according to a preset gray value, calculates the threat degree of the pest according to a region division result, compares the threat degree of the pest with the preset threat degree, and analyzes the severity of the pest according to a comparison result, wherein:

when D1 is less than or equal to DO is less than or equal to D2, the insect pest analysis module takes the area with the gray value of D0 as a leaf area;

when D0 is more than D2 or D0 is less than D1, the insect pest analysis module takes the area with the gray value of D0 as a damaged area;

the pest analysis module sets the leaf damage degree of each target image to Nu, sets nu=e1/(e1+e2), sets the pest threat degree to N, sets n= (n1+n2+ & gtnu)/u, and 0 < u.ltoreq.z, wherein:

when N is less than or equal to N1, the pest analysis module judges that the pest severity is mild;

when N1 is more than or equal to N2, the pest analysis module judges that the pest severity is moderate;

when N is more than N2, the pest analysis unit judges that the pest severity is severe;

wherein A1 is a preset minimum gray value, A2 is a preset maximum gray value, B1 is the damaged area in the target image, B2 is the leaf sub-area in the target image, z is the number of preset shooting areas, N1 is the leaf damage degree of the first target image, N2 is the leaf damage degree of the second target image, and Nu is the leaf damage degree of the u-th target image.

Specifically, the pest analysis module improves accuracy of dividing areas by setting a preset gray threshold value, further improves accuracy of judging the severity of the pest, further improves accuracy of controlling a pesticide application mode, and finally improves monitoring efficiency of crops; in this embodiment, the value of the preset gray value is not specifically limited, and a person skilled in the art can freely set the value of the preset gray value only by meeting the value requirement of the preset gray value, wherein the optimal value of D1 is 98.2 and the optimal value of D2 is 192.8 under the condition of sufficient illumination.

Specifically, the pesticide application mode control module controls the pesticide application mode according to the analysis result of soil conditions, the analysis result of standard planting density of crops and the analysis result of insect pests, wherein:

when the pest severity is mild, no application mode is set;

when the pest severity is moderate, if i1/i is more than or equal to e1 and i2/i is less than e1, the pesticide spraying mode control module sets the unmanned aerial vehicle to spray pesticide to kill pests, and the dosage is set as R1; if i2/i is more than or equal to e1 and the planting density is too high, the pesticide spraying mode control module sets the unmanned aerial vehicle to spray pesticide to kill pests, and the dosage is set as R2;

When the severity of the insect pest is severe, if i3/i0 is more than or equal to e1 and i4/i0 is less than e1, the pesticide spraying mode control module sets the unmanned aerial vehicle to spray pesticide to kill the insect pest, and the dosage is set as R3; if i4/i0 is more than or equal to e1 and the planting density is too high, the pesticide spraying mode control module sets the unmanned aerial vehicle to spray pesticide to kill pests, and the pesticide consumption is set as R4, R1 is more than R2 and less than R3 and less than R4;

wherein i1 is the number of acquisition cycles in the judging soil condition risk level between the shooting cycle in which the pest severity is judged to be moderate and the last time of application, i2 is the number of acquisition cycles in the judging soil condition risk level between the shooting cycle in which the pest severity is judged to be moderate and the last time of application, e1 is a preset anomaly coefficient, i is the number of acquisition cycles between the shooting cycle in which the pest severity is judged to be moderate and the last time of application, i3 is the number of acquisition cycles in the judging soil condition risk level between the shooting cycle in which the pest severity is judged to be severe and the last time of application, i4 is the number of acquisition cycles in which the judging soil condition risk level is high between the shooting cycle in which the pest severity is judged to be severe and the last time of application, i0 is the number of acquisition cycles in the judging soil condition risk level between the shooting cycle in which the pest severity is judged to be moderate and the last time of application, R1 is a first preset drug amount, R2 is a second preset drug amount, R3 is a third preset drug amount, and R4 is a fourth preset drug amount.

Specifically, the pesticide application mode control module analyzes the soil conditions, the planting density and the insect pest analysis result, and sets a preset abnormal coefficient to improve the accuracy of the control process, improve the pesticide utilization efficiency and improve the monitoring efficiency of crops; in this embodiment, the values of e1, R2 and R3 are not specifically limited, and can be freely set by those skilled in the art, so long as the values of e1, R2 and R3 are satisfied, for example, when the crop is corn, the optimal value of e1 is 0.3 and the optimal value of R1 is 15ml/m ² The optimal value of R2 is 35ml/m ² The optimal value of R3 is 60ml/m ² The optimal value of R4 is 80ml/m ² 。

Specifically, the optimization module compares the yield p0 of crops in a growth period with a preset yield p1, and optimizes a control process of a next growth period application mode according to a comparison result, wherein:

when p0 is less than p1, the optimization module sets an optimization coefficient G1 to optimize a preset abnormal coefficient e1, and sets G1=1+ (p 1-p 0)/(p1+p0);

when p1 is more than or equal to p0 and less than or equal to p2, the optimization module does not perform optimization;

when p0 is more than p2, the optimization module sets an optimization coefficient G2 to optimize a preset abnormal coefficient e1, and sets G2=1- (p 2-p 0)/(p2+p0);

The optimization module is based onOptimizing coefficient G _J Optimizing the preset anomaly coefficient e1, setting the optimized preset density e1 as e1', and setting e1' =e1×g _J ,j=1,2;

Wherein, p1 is the preset minimum yield, and p2 is the preset maximum yield.

Specifically, the optimization module improves the accuracy of the optimization coefficient by setting the preset yield, and improves the accuracy of the pesticide application mode control by analyzing the yield of crops, so that the monitoring efficiency of the crops is improved; in this embodiment, the setting of the preset yield p1 is not specifically limited, and a person skilled in the art can freely set the preset yield p1 only by meeting the value requirement of p1, wherein the optimal value of p1 is 0.23/m when the crop is corn ² 。

Thus far, the technical solution of the present invention has been described in connection with the preferred embodiments shown in the drawings, but it is easily understood by those skilled in the art that the scope of protection of the present invention is not limited to these specific embodiments. Equivalent modifications and substitutions for related technical features may be made by those skilled in the art without departing from the principles of the present invention, and such modifications and substitutions will be within the scope of the present invention.

Claims (10)

1. An intelligent agricultural cloud platform monitoring system is characterized by comprising,

the acquisition module is used for acquiring soil information, environment information, pesticide application area information and crop information;

the system comprises a soil analysis module, a soil humidity analysis module and a soil fertility analysis unit, wherein the soil analysis module is used for analyzing soil according to the ion concentration, the soil temperature and the soil humidity in collected soil, the soil analysis module is provided with a soil temperature analysis unit used for analyzing soil conditions according to the collected soil temperature, the soil analysis module is also provided with a soil humidity analysis unit used for performing secondary analysis on the soil conditions according to the collected soil humidity, and the soil analysis module is also provided with a soil fertility analysis unit used for performing tertiary analysis on the soil conditions according to the ion concentration in the collected soil;

the first adjusting module is used for adjusting the soil analysis process according to the collected environmental information;

the planting density analysis module is used for analyzing the standard planting density of crops according to the collected information of the application area;

the second adjustment module is used for adjusting the analysis process of the standard planting density according to the collected conductivity and the acid-base property of the soil, is provided with a second adjustment unit used for adjusting the analysis process of the planting density according to the collected conductivity of the soil, and is also provided with a second correction unit used for correcting the adjustment process of the analysis process of the planting density according to the collected acid-base property of the soil;

The acquisition module is used for acquiring a target image in the crop image;

the insect pest analysis module is used for analyzing insect pests according to the acquired target images;

the pesticide application mode control module is used for controlling the pesticide application mode according to the analysis result of the soil condition, the analysis result of the standard planting density of crops and the analysis result of insect pests;

and the optimizing module is used for optimizing the control process of the application mode according to the yield of crops in one growth period.

2. The intelligent agricultural cloud platform monitoring system according to claim 1, wherein the soil temperature analysis unit calculates an average temperature w0 in a collection period, compares the average temperature w0 with each preset soil temperature, and analyzes the soil according to a comparison result, wherein:

when w0 is less than w1, the soil temperature analysis unit judges that the soil temperature is unsuitable for pest growth;

when w1 is more than or equal to w0 and less than or equal to w2, the soil analysis unit judges that the soil temperature is suitable for pest growth;

when w1 is more than w2, the soil analysis unit judges that the soil temperature is very suitable for pest growth;

wherein w0= (w1+w2+) +wn/n.

3. The intelligent agricultural cloud platform monitoring system according to claim 2, wherein when the soil temperature is suitable for pest growth or the soil temperature is very suitable for pest growth, the soil humidity analysis unit calculates an average humidity s0 in a collection period, compares the average humidity s0 with each preset humidity, and analyzes the soil condition according to the comparison result, wherein:

When the soil temperature is suitable for pest growth, if s0 is less than s1, the soil humidity analysis unit judges that the soil humidity is unsuitable for pest growth in the collection period; if s1 is less than or equal to s0 and less than or equal to s2, the soil humidity analysis unit judges that the soil humidity in the collection period is suitable for pest growth; if s0 is more than s2, the soil humidity analysis unit judges that the soil humidity in the collection period is very suitable for pest growth;

when the soil temperature is very suitable for pest growth, if s0 is less than s3, the soil humidity analysis unit judges that the soil humidity is not suitable for pest growth in the collection period; if s3 is less than or equal to s0 and less than or equal to s4, the soil humidity analysis unit judges that the soil humidity in the collection period is suitable for pest growth; if s0 is more than s4, the soil humidity analysis unit judges that the soil humidity in the collection period is very suitable for pest growth;

wherein s0= (s1+s2+) +sn)/n, n is the number of collection nodes.

4. The intelligent agricultural cloud platform monitoring system according to claim 3, wherein the soil fertility analysis unit calculates an average ion concentration in a collection period, compares the average ion concentration with each preset ion concentration, and performs three analyses on soil conditions according to a comparison result, wherein:

When the soil temperature is not suitable for the growth of pests or the soil humidity is not suitable for the growth of pests, the soil fertility analysis unit judges that the dangerous grade of the soil condition is dangerous;

when the soil humidity is suitable for the growth of pests, if a0 is less than a1 and b0 is less than b1 or a1 is less than or equal to a0 and b0 is less than b1 or b1 is less than or equal to b0 and a0 is less than a1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is low; if a0 is more than a1 and b0 is more than b1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is medium;

when the soil humidity is very suitable for the growth of pests, if a0 is less than a1 and b0 is less than b1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is low; if a1 is less than or equal to a0 and b0 is less than or equal to b1 or b1 is less than or equal to b0 and a0 is less than a1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is medium; if a0 is more than a1 and b0 is more than b1, the soil fertility analysis unit judges that the dangerous grade of the soil condition is high;

wherein a0= (a1+a2+) +an)/n, b0= (b1+b2+) +bn)/n.

5. The intelligent agricultural cloud platform monitoring system according to claim 4, wherein the first adjustment module is provided with a first adjustment unit, the first adjustment unit is configured to compare the collected precipitation amount j0 with a preset precipitation amount j1, and calculate a first adjustment coefficient according to a comparison result to adjust an analysis process of the soil, wherein:

When j0 is less than or equal to j1, the first adjusting unit judges that the precipitation amount is normal and does not adjust;

when j0 > j1, the first adjusting unit determines that the precipitation is excessive, sets a first adjusting coefficient alpha to adjust the preset humidity s1, sets s1=1+ (j 1-j 0)/(j 1+ j 0), sets s1 after adjustment as s1', and sets s1' =s1×α;

the first adjustment module is further provided with a first correction unit, the first correction unit compares the collected ambient temperature t0 with a preset ambient temperature, and calculates a first correction coefficient according to a comparison result to correct an adjustment process of the soil analysis process, wherein:

when t0 is less than t1 or t0 is more than t2, the first correction unit judges that the temperature is not suitable for pest growth and does not correct;

when t1 is less than or equal to t0 and less than or equal to t2, the first correction unit judges that the temperature is suitable for pest growth, sets a first correction coefficient beta to correct a first adjustment coefficient alpha, sets beta= | (t2+t1)/2-t0|/[ (t2+t1)/2 ], sets the corrected first adjustment coefficient alpha as alpha 1, and sets alpha 1 = alpha x beta;

wherein t1 is a preset minimum temperature, and t2 is a preset maximum temperature.

6. The intelligent agricultural cloud platform monitoring system of claim 1, wherein the planting density analysis module calculates a standard planting density m0 of the crop according to the collected pesticide application area information, compares the standard planting density with a collected planting density m1 of the crop, and analyzes the planting density of the crop according to a comparison result, wherein:

m0= [ (x 0/x1+1) × (y0/y1+1) ]/(x0×y0), wherein x0 is the length of the application area, x1 is the preset planting pitch of the length of the application area, y0 is the width of the application area, and y1 is the preset planting pitch of the width of the application area;

when m1 is less than or equal to m0, the planting density analysis module judges that the planting density is proper;

and when m1 is more than m0, the planting density analysis module judges that the planting density is overlarge.

7. The intelligent agricultural cloud platform monitoring system according to claim 6, wherein the second adjusting unit compares the collected conductivity k0 of the soil with each preset conductivity, calculates a second adjusting coefficient according to the comparison result, and adjusts an analysis process of the planting density, wherein:

when k0 is less than k1, the second adjusting unit judges that salinization of the soil is low, sets a second adjusting coefficient gamma 1 to adjust the preset density m1, and sets gamma 1 = 1+ (k 1-k 0)/(k 1+ k 0);

when k1 is less than or equal to k0 and less than or equal to k2, the second regulating unit judges that salinization of the soil is normal and does not regulate;

when k0 is more than k2, the second adjusting unit judges that salinization of the soil is high, sets a second adjusting coefficient gamma 2 to adjust the preset density m1, and sets gamma 2 = 1- (k 2-k 0)/(k 2+ k 0);

The second adjusting unit adjusts the coefficient gamma according to a second _F Adjusting the preset density m1, setting the adjusted preset density m1 as m2, and setting m2=m1×γ _F ，F=1,2；

Wherein k1 is a preset minimum conductivity, and k2 is a preset maximum conductivity;

the second correction unit compares the acid-base property h0 of the collected soil with each preset acid-base property, calculates a second correction coefficient according to the comparison result, and corrects the second adjustment coefficient, wherein:

when H0 is less than H1 or H0 is more than H2, the second correction unit judges that the PH of the soil is low, sets a second correction coefficient H1 to correct the adjustment coefficient gamma, and sets H1=1+ (H1-H0)/(h1+h0);

when h1 is less than or equal to h0 and less than or equal to h2, the second correction unit judges that the PH of the soil is normal, and no correction is performed;

when H0 > H2, the second correction unit determines that the PH of the soil is high, sets a second correction coefficient H2 to correct the adjustment coefficient gamma, and sets H2+ (k2-k0)/(k2+k0);

the second correction unit corrects the first correction coefficient according to the second correction coefficient H _v For the second adjustment coefficient gamma _F Correcting and adding the corrected second adjustment coefficient gamma _F Let gamma be _F 'gamma' is set _F ’=H _v ×γ _F ,v=1,2；

Wherein h1 is a preset minimum pH, and h2 is a preset maximum pH.

8. The intelligent agricultural cloud platform monitoring system according to claim 1, wherein the pest analysis module performs region division on the obtained target image according to a preset gray value, calculates a pest threat level according to a region division result, compares the pest threat level with the preset threat level, and analyzes the pest severity according to a comparison result, wherein:

When D1 is less than or equal to DO is less than or equal to D2, the insect pest analysis module takes the area with the gray value of D0 as a leaf area;

when D0 is more than D2 or D0 is less than D1, the insect pest analysis module takes the area with the gray value of D0 as a damaged area;

the pest analysis module sets the damage degree of each target image leaf as Nu, sets nu=e1/(e1+e2), sets the pest threat degree as N, sets n= (n1+n2+ & gtnu)/u, and 0 < u is less than or equal to z, wherein:

when N is less than or equal to N1, the pest analysis module judges that the pest severity is mild;

when N1 is more than or equal to N2, the pest analysis module judges that the pest severity is moderate;

when N is more than N2, the pest analysis unit judges that the pest severity is severe;

wherein A1 is a preset minimum gray value, A2 is a preset maximum gray value, B1 is the damaged area in the target image, B2 is the leaf sub-area in the target image, z is the number of preset shooting areas, N1 is the leaf damage degree of the first target image, N2 is the leaf damage degree of the second target image, and Nu is the leaf damage degree of the u-th target image.

9. The intelligent agricultural cloud platform monitoring system of claim 8, wherein the pesticide application mode control module controls the pesticide application mode according to an analysis result of soil conditions, an analysis result of standard planting density of crops, and an analysis result of insect pests, wherein:

When the pest severity is mild, no application mode is set;

when the pest severity is moderate, if i1/i is more than or equal to e1 and i2/i is less than e1, the pesticide spraying mode control module sets the unmanned aerial vehicle to spray pesticide to kill pests, and the dosage is set as R1; if i2/i is more than or equal to e1 and the planting density is too high, the pesticide spraying mode control module sets the unmanned aerial vehicle to spray pesticide to kill pests, and the dosage is set as R2;

when the severity of the insect pest is severe, if i3/i0 is more than or equal to e1 and i4/i0 is less than e1, the pesticide spraying mode control module sets the unmanned aerial vehicle to spray pesticide to kill the insect pest, and the dosage is set as R3; if i4/i0 is more than or equal to e1 and the planting density is too high, the pesticide spraying mode control module sets the unmanned aerial vehicle to spray pesticides to kill pests, and the pesticide consumption is set as R4, wherein R1 is more than R2 and less than R3 is more than R4.

10. The intelligent agricultural cloud platform monitoring system of claim 9, wherein the optimization module compares a yield p0 of the crop in the growth cycle with a preset yield p1, and optimizes a control process of the next growth cycle application mode according to a comparison result, wherein:

when p0 is less than p1, the optimization module sets an optimization coefficient G1 to optimize a preset abnormal coefficient e1, and sets G1=1+ (p 1-p 0)/(p1+p0);

When p1 is more than or equal to p0 and less than or equal to p2, the optimization module does not perform optimization;

when p0 is more than p2, the optimization module sets an optimization coefficient G2 to optimize a preset abnormal coefficient e1, and sets G2=1- (p 2-p 0)/(p2+p0);

the optimization module is used for optimizing the coefficient G according to the optimization coefficient _J Optimizing the preset anomaly coefficient e1, setting the optimized preset density e1 as e1', and setting e1' =e1×g _J ,j=1,2;

Wherein, p1 is the preset minimum yield, and p2 is the preset maximum yield.