CN112896520A - Agricultural unmanned aerial vehicle operation remote control method based on big data analysis - Google Patents
Agricultural unmanned aerial vehicle operation remote control method based on big data analysis Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 35
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Abstract
The invention discloses an agricultural unmanned aerial vehicle operation remote control method based on big data analysis, which divides a rice field area into sub-areas, acquires the area of each rice field sub-area, simultaneously acquires the rice plant growth parameters of each rice field sub-area, thereby counting the average comprehensive growth coefficient of rice corresponding to each rice field sub-area, analyzes the total pesticide spraying amount corresponding to each rice field sub-area according to the area of each rice field sub-area, simultaneously acquires the average height of rice plants corresponding to each rice field sub-area from the rice plant growth parameters of each rice field sub-area, further acquires the standard spraying height of the unmanned aerial vehicle corresponding to each sub-area, overcomes the defect that the actual spraying requirement of crops is not met in the current pesticide spraying operation process of the crops by the unmanned aerial vehicle, improves the spraying effect, greatly reduces the crop damage caused by the fact that the actual spraying requirement of the crops is not met, the requirement of accurate plant protection on crops is met.
Description
Technical Field
The invention belongs to the technical field of agricultural unmanned aerial vehicle remote control, and particularly relates to an agricultural unmanned aerial vehicle operation remote control method based on big data analysis.
Background
In recent years, with the continuous improvement of the modernization level of agriculture, the demand for safe and efficient plant protection technology in agricultural production is more and more large, and by taking pesticide spraying as an example, the traditional manual pesticide spraying technology in China is time-consuming and labor-consuming, the plant protection effect is also not good, and crops cannot be effectively protected. And modern unmanned aerial vehicle sprays pesticide technique compares traditional artifical machinery and sprays, has advantages such as safe, high-efficient, save medicament use amount, not only can reduce the plant protection cost, still can promote work efficiency by a wide margin to better prevent that the plant diseases and insect pests from appearing in crops, improve the planting family economic benefits.
However, in the current pesticide spraying operation process of crops through the unmanned aerial vehicle, the spraying height and the spraying dosage of the unmanned aerial vehicle in the crop planting area are uniformly controlled, and the influences of different plant heights of the crops in the crop planting area on the spraying height and the influences of different growth conditions of the crops on the spraying dosage are not considered. To same kind of crops, different plant height, the spraying height of its actual demand is different, different growing situation, the spraying dose of its actual demand is also different, it sprays to carry out the pesticide with unified spraying height and spraying dose to all crops in the crops planting region simply, obviously not conform to the actual demand of spraying of crops, and then make some crops in the crops planting region can not reach predetermined effect of spraying, cause the damage of crops even, can not fine guarantee crops's safety, be difficult to satisfy the accurate plant protection demand to crops.
Disclosure of Invention
In order to solve the problems, the invention provides an agricultural unmanned aerial vehicle operation remote control method based on big data analysis by taking pesticide spraying on rice as an example, by dividing a rice field region into subareas and analyzing the growth condition of the rice in each rice field subarea, the total pesticide spraying amount and the unmanned aerial vehicle spraying height corresponding to each rice field subarea are counted, the spraying parameters of the unmanned aerial vehicle corresponding to each rice field subarea are regulated and controlled in real time, and the requirement of precise plant protection on crops is met.
The purpose of the invention can be realized by the following technical scheme:
a big data analysis-based agricultural unmanned aerial vehicle operation remote control method comprises the following steps;
s1, rice field subregion division: acquiring a boundary outline of a rice field area corresponding to a rice field to be sprayed with pesticides, and counting the area of the rice field area according to the acquired boundary outline of the rice field area, so that the rice field area is divided into a plurality of rice field sub-areas according to a method for uniformly and equally dividing the rice field area, the divided rice field sub-areas are numbered according to a predefined sequence and respectively marked as 1,2.. i.. n, and meanwhile, the area corresponding to each rice field sub-area is counted according to the number of the divided rice field sub-areas;
s2, acquiring rice field image in the rice field subregion: acquiring rice field images in each rice field subregion to obtain a rice field image of each rice field subregion, acquiring the number of rice plants from the obtained rice field image of each rice field subregion, numbering the rice plants corresponding to each acquired rice field subregion, and sequentially marking the rice plants as A, B.i.n.;
s3, constructing a rice plant growth parameter set in the rice field sub-region: sequentially focusing the rice field images of the rice field subareas in each rice field area according to the numbering sequence of each rice plant in each rice field subarea, further acquiring the height of each rice plant and the length of the rice ear corresponding to each rice plant, simultaneously sequentially focusing the rice field images of the rice field subareas on the rice ear areas corresponding to each rice plant, and extracting the maximum outline and the minimum outline of the rice grains on the rice ears corresponding to each rice plant and the color characteristics of the rice grains, so as to obtain the maximum volume, the minimum volume and the color chromaticity of the rice grains corresponding to each rice plant in each rice field subregion, at the moment, the average volume of the rice grains corresponding to each rice plant in each rice field subregion is calculated according to the maximum volume and the minimum volume of the rice grains corresponding to each rice plant in each rice field subregion, therefore, the obtained rice plant height, rice ear length, average rice grain volume and rice grain color degree corresponding to each rice plant in each rice field subregion constitute a rice plant growth parameter set Q of the rice field subregion.w i(qw iA,qw iB,...,qw iI,...,qw iN)，qw iI is a numerical value corresponding to the growth parameter of the I-th rice plant in the I-th rice field subregion, w is the growth parameter, and w is r1, r2, r3 and r4 which are respectively expressed as the height of the rice plant, the length of the rice ear, the average volume of the rice grain and the color chromaticity of the rice grain;
s4, carrying out comprehensive growth coefficient statistics on each rice plant in the rice field subregion: sequentially extracting the heights of the rice plants corresponding to the rice plants in each rice field subregion from the rice plant growth parameter set in the rice field subregion, comparing the heights with the plant height growth coefficients corresponding to the heights of the rice plants in the growth parameter database, screening the plant height growth coefficients corresponding to the rice plants in each rice field subregion from the rice plant growth parameter set in the rice field subregion, sequentially extracting the lengths of the rice ears corresponding to the rice plants in each rice field subregion from the rice plant growth parameter set in the rice field subregion, comparing the lengths with the ear length growth coefficients corresponding to the lengths of the rice ears in the growth parameter database, screening the ear length growth coefficients corresponding to the rice plants in each rice field subregion from the rice plant growth parameter set in the rice field subregion, sequentially extracting the average volume of the rice grains corresponding to the rice plants in each rice field subregion from the rice plant growth parameter set in the rice field subregion, and comparing the average volume of the rice grains with the saturation growth coefficients corresponding to the average volume of the rice grains in the growth parameter database, screening out plumpness vigor coefficients corresponding to all rice plants in all the rice field subregions from the rice field subregion rice plant vigor parameter sets, sequentially extracting the rice grain color chroma corresponding to all the rice plants in all the rice field subregions from the rice field subregion rice plant vigor parameter sets, comparing the rice grain color chroma and the color degree vigor coefficients corresponding to all the rice grain color chroma in the vigor parameter database, and screening out the color degree vigor coefficients corresponding to all the rice plants in all the rice field subregions from the rice grain color vigor coefficients, so that the comprehensive vigor coefficients corresponding to all the rice plants in all the rice field subregions are counted according to the plant height vigor coefficients, the spike length vigor coefficients, the plumpness vigor coefficients and the color degree vigor coefficients corresponding to all the rice plant subregions in all the;
s5, total pesticide spraying amount statistics of the rice field subareas: carrying out mean value processing on the comprehensive growth coefficients corresponding to the rice plants in each rice field subregion to obtain the average comprehensive growth coefficient of the rice corresponding to each rice field subregion, wherein the calculation formula is
Expressed as the average integrated growth coefficient of the rice corresponding to the ith rice field subregion, and the obtained average integrated growth coefficient of the rice corresponding to each rice field subregion and various rice in the pesticide spraying databaseComparing the pesticide spraying amount of the unit rice field area corresponding to the average comprehensive growth factor, screening out the pesticide spraying amount of the unit rice field area corresponding to each rice field sub-area, and meanwhile, counting the total pesticide spraying amount corresponding to each rice field sub-area according to the area corresponding to each rice field sub-area;
s6, standard spraying height analysis of unmanned aerial vehicles in the rice field subareas: extracting the rice plant height corresponding to each rice plant in each rice field subregion from the rice plant growth parameter set of each rice field subregion, and carrying out mean value processing on the rice plant height to obtain the average rice plant height corresponding to each rice field subregion, wherein the calculation formula is
The average height of the rice plants corresponding to the ith rice field subregion is expressed, so that the average height of the rice plants corresponding to each rice field subregion is compared with the standard unmanned aerial vehicle spraying height corresponding to the average height of each rice plant in the pesticide spraying database, and the standard unmanned aerial vehicle spraying height corresponding to each rice field subregion is obtained;
s7, detecting the wind speed of the rice field subregion: installing anemorumbometers in the rice field subregions respectively, wherein the anemorumeters are used for acquiring the wind speeds of the rice field subregions;
s8, actual spraying height statistics of unmanned aerial vehicles in the rice field subareas: comparing the wind speed of each rice field subregion with the spraying height influence coefficients corresponding to various wind speeds in the pesticide spraying database, screening the spraying height influence coefficients corresponding to each rice field subregion, and counting the actual spraying height of the unmanned aerial vehicle corresponding to each rice field subregion according to the standard spraying height of the unmanned aerial vehicle corresponding to each rice field subregion and the spraying height influence coefficients;
s9, acquiring the geographical position of the actual boundary spraying area of the rice field subregion: extracting boundary contour lines corresponding to the rice field sub-regions, namely standard boundary spraying region contours corresponding to the rice field sub-regions by the unmanned aerial vehicle, comparing the wind speed of the rice field sub-regions with the boundary spraying region offset distance corresponding to various wind speeds in the pesticide spraying database, thereby obtaining the boundary spraying region offset distance corresponding to the unmanned aerial vehicle in each rice field sub-region, meanwhile, obtaining the geographic position corresponding to the standard boundary spraying region corresponding to the rice field sub-region by the unmanned aerial vehicle, and further obtaining the actual boundary spraying region geographic position corresponding to the rice field sub-region by the unmanned aerial vehicle according to the boundary spraying region offset distance corresponding to the rice field sub-region by the unmanned aerial vehicle;
s10, unmanned aerial vehicle spraying parameter real-time regulation and control: when the unmanned aerial vehicle flies to each rice field subregion, the pesticide spraying of each rice field subregion is carried out according to the total pesticide spraying amount corresponding to each rice field subregion, the actual spraying height of the unmanned aerial vehicle and the geographical position of the actual boundary spraying region, by regulating and controlling the total pesticide spraying amount, the spraying height and the geographical position of the boundary spraying region sprayed by the unmanned aerial vehicle in real time.
As a preferred technical solution, in the step S1, the area of the rice field area is counted according to the obtained boundary contour line of the rice field area, and the specific counting method performs the following steps:
g1, acquiring longitude and latitude coordinates of the boundary contour line of the rice field area by using a GPS land surveying instrument;
g2, converting the longitude and latitude coordinates of the obtained contour line end points of the rice field area boundary into plane coordinates, and establishing a plane coordinate system
G3, connecting each end point of the boundary of the rice field area with the origin of coordinates, so that each side of the rice field area and the origin form a triangle, thereby dividing the rice field area into a plurality of triangles, and respectively calculating the area of each triangle;
and G4, summing the calculated areas of the triangles to obtain the area of the rice field area.
As a preferred technical scheme, the calculation formula of the area corresponding to each rice field subregion is
S represents an area corresponding to each paddy field subregion, and S represents a paddy field region area.
As a preferred technical solution, in S2, the method for obtaining the number of rice plants from the obtained rice field image of each rice field subregion specifically comprises the following steps:
d1, extracting the outline of each individual rice plant from the obtained rice field image of each rice field subregion;
and D2, counting the number of the outlines of the extracted individual rice plants, namely the number of the rice plants corresponding to each rice field subregion.
Preferably, in S3, the maximum contour and the minimum contour of the rice grains on the ear corresponding to each rice plant are extracted, and the specific extraction process includes obtaining the number of the rice grains on the ear corresponding to each rice plant, extracting the contour corresponding to each rice grain, comparing the extracted contours of the rice grains with each other, and selecting the rice grains with the maximum contour and the rice grains with the minimum contour from the extracted contours.
As a preferred technical scheme, the calculation formula of the average volume of the rice grains corresponding to each rice plant in each rice field subregion is
Expressed as the average volume of rice grains, V, corresponding to the I-th rice plant in the I-th rice field sub-regioniImax、ViIminExpressed as the maximum volume and the minimum volume of rice grains corresponding to the I-th rice plant in the I-th rice field sub-area, respectively.
As a preferred technical scheme, the calculation formula of the comprehensive growth coefficient corresponding to each rice plant in each rice field subregion is
δiI is expressed as the comprehensive growth coefficient, alpha, corresponding to the I rice plant in the I rice field subregioniI、βiI、γiI、λiAnd I is respectively expressed as a plant height growth coefficient, a panicle length growth coefficient, a plumpness growth coefficient and a color and luster growth coefficient corresponding to the I rice plant in the I rice field subregion.
As a preferred technical scheme, the calculation formula of the total pesticide spraying amount corresponding to each rice field subregion is Ki＝ki*s，KiExpressed as the total sprayed pesticide, k, corresponding to the ith rice field subregioniExpressed as the amount of pesticide sprayed on the unit paddy field area corresponding to the ith paddy field area.
As a preferred technical scheme, the calculation formula of the actual spraying height of the unmanned aerial vehicle corresponding to each rice field subregion is Hi′＝Hi*ηiH' represents the actual spraying height of the unmanned aerial vehicle corresponding to the ith rice field subregion, HiExpressed as the standard spraying height, eta of the unmanned aerial vehicle corresponding to the ith rice field subregioniExpressed as spray height impact coefficient corresponding to the ith paddy field area.
The invention has the following beneficial effects:
(1) the invention divides the rice field area into sub-areas, acquires the area of each rice field sub-area, and simultaneously acquires the rice plant growth parameters of each rice field sub-area, thereby counting the average comprehensive growth coefficient of rice corresponding to each rice field sub-area, analyzes the total pesticide spraying amount corresponding to each rice field sub-area according to the area of each rice field sub-area, and simultaneously acquires the average height of rice corresponding to each rice field sub-area from the rice plant growth parameters of each rice field sub-area, further acquires the standard spraying height of the unmanned aerial vehicle corresponding to each rice field sub-area, overcomes the defect that the actual spraying requirement of crops is not met in the current pesticide spraying process of crops by the unmanned aerial vehicle, improves the spraying effect, greatly reduces the crop damage caused by the fact that the actual spraying requirement of crops is not met, and well ensures the safety of the crops, the requirement of accurate plant protection on crops is met, and the economic benefit of farmers is further improved.
(2) According to the invention, the wind speed detection is carried out on each rice field subregion, so that the spraying height influence coefficient corresponding to each rice field subregion is obtained, and the actual spraying height of the unmanned aerial vehicle corresponding to each rice field subregion is counted by combining the standard spraying height of the unmanned aerial vehicle corresponding to each rice field subregion, so that the influence analysis of the wind speed on the actual spraying height of the unmanned aerial vehicle is realized, the actual situation is well fitted, the situation that the unmanned aerial vehicle cannot be sprayed to a target rice region due to the fact that the unmanned aerial vehicle is only sprayed according to the standard spraying height is avoided, the spraying accuracy is reduced, and the spraying effect is further reduced.
(3) According to the method, the deviation distance of the boundary spraying area corresponding to each rice field subregion of the unmanned aerial vehicle is obtained according to the wind speed of each rice field subregion, so that the geographic position of the actual boundary spraying area corresponding to each rice field subregion of the unmanned aerial vehicle is obtained, the influence of the wind speed on the actual boundary spraying area of the unmanned aerial vehicle is analyzed, the out-of-range spraying condition caused by spraying only according to the standard boundary spraying area corresponding to each rice field subregion of the unmanned aerial vehicle is avoided, and the rice in other rice field subregions is greatly reduced from being subjected to phytotoxicity due to out-of-range spraying.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
FIG. 1 is a flow chart of the method steps of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the agricultural unmanned aerial vehicle operation remote control method based on big data analysis comprises the following steps;
s1, rice field subregion division: acquiring a rice field region boundary outline corresponding to a rice field to be sprayed with pesticides, and counting the rice field region area according to the acquired rice field region boundary outline, wherein the specific counting method comprises the following steps:
g1, acquiring longitude and latitude coordinates of the boundary contour line of the rice field area by using a GPS land surveying instrument;
g2, converting the longitude and latitude coordinates of the obtained contour line end points of the rice field area boundary into plane coordinates, and establishing a plane coordinate system
G3, connecting each end point of the boundary of the rice field area with the origin of coordinates, so that each side of the rice field area and the origin form a triangle, thereby dividing the rice field area into a plurality of triangles, and respectively calculating the area of each triangle;
g4, summing the calculated areas of the triangles to obtain the area of the rice field area;
dividing the rice field area into a plurality of rice field sub-areas according to a method for evenly dividing the rice field area, numbering the divided rice field sub-areas according to a predefined sequence, marking the divided rice field sub-areas as 1,2
S represents the area corresponding to each rice field subregion, and S represents the rice field region area;
according to the embodiment, by dividing the rice field to be sprayed with the pesticide into sub-regions, a basis is provided for the subsequent analysis of the spraying parameters of the unmanned aerial vehicle in each rice field sub-region;
s2, acquiring rice field image in the rice field subregion: the method comprises the following steps of acquiring rice field images in each rice field subregion to obtain a rice field image of each rice field subregion, and acquiring the number of rice plants from the obtained rice field image of each rice field subregion, wherein the specific acquisition method comprises the following steps:
d1, extracting the outline of each individual rice plant from the obtained rice field image of each rice field subregion;
d2, counting the number of the outlines of the extracted individual rice plants, namely the number of the rice plants corresponding to each rice field subregion;
numbering the rice plants corresponding to the obtained rice field subregions, and sequentially marking the rice plants as A, B.
S3, constructing a rice plant growth parameter set in the rice field sub-region: according to the numbering sequence of each rice plant in each rice field subregion, the rice field subregions are numberedSequentially focusing rice field images in each rice plant area to further obtain the rice plant height and the rice ear length corresponding to each rice plant, simultaneously sequentially focusing the rice field images in each rice field area in each rice plant area in each rice ear area corresponding to each rice plant, extracting the maximum outline, the minimum outline and the rice grain color characteristics of the rice grains on the rice ears corresponding to each rice plant, wherein the specific extraction process of the maximum outline and the minimum outline of the rice grains on the rice ears comprises the steps of obtaining the number of the rice grains on the rice ears corresponding to each rice plant, extracting the outline corresponding to each rice grain, further comparing the extracted outlines of each rice grain with each other, screening the rice grains with the maximum outline and the rice grains with the minimum outline from the obtained, thus obtaining the maximum volume, the minimum volume and the rice grain color chromaticity corresponding to each rice plant in each rice field area, and then obtaining the maximum volume, the minimum volume and the rice grain color chromaticity corresponding to each rice plant in each rice field area according to the maximum volume, the rice grains corresponding to each rice plant in each rice field, Calculating the average volume of rice grains corresponding to each rice plant in each rice field subregion by using the minimum volume
Expressed as the average volume of rice grains, V, corresponding to the I-th rice plant in the I-th rice field sub-regioniImax、ViIminRespectively representing the maximum volume and the minimum volume of the rice grains corresponding to the I-th rice plant in the ith rice field subregion, and forming a rice plant growth parameter set Q of the rice field subregion by the rice plant height, the rice ear length, the average volume of the rice grains and the color chromaticity of the rice grains corresponding to each rice plant in each rice field subregionw i(qw iA,qw iB,...,qw iI,...,qw iN)，qw iI is a numerical value corresponding to the growth parameter of the I-th rice plant in the I-th rice field subregion, w is the growth parameter, and w is r1, r2, r3 and r4 which are respectively expressed as the height of the rice plant, the length of the rice ear, the average volume of the rice grain and the color chromaticity of the rice grain;
s4, carrying out comprehensive growth coefficient statistics on each rice plant in the rice field subregion: from the rice plant growth parameter set in the rice field subareasExtracting the height of each rice plant in each rice field subregion, comparing the height with the plant height and vigor coefficient corresponding to each rice plant height in the vigor parameter database, screening the plant height and vigor coefficient corresponding to each rice plant in each rice field subregion, sequentially extracting the length of the rice ear corresponding to each rice plant in each rice field subregion from the rice plant vigor parameter set of the rice field subregions, comparing the length of the rice ear with the ear length and vigor coefficient corresponding to each rice ear length in the vigor parameter database, screening the ear length and vigor coefficient corresponding to each rice plant in each rice field subregion, sequentially extracting the average volume of the rice grains corresponding to each rice plant in each rice field subregion from the rice plant vigor parameter set of the rice field subregions, comparing the average volume of the rice grains with the plumpness and vigor coefficient corresponding to the average volume of each rice grain in the vigor parameter database, screening the plumpness and vigor coefficient corresponding to each rice plant in each rice field subregion, finally, the rice grain color chroma corresponding to each rice plant in each rice field subregion is sequentially extracted from the rice plant growth parameter set in each rice field subregion, and is compared with the color degree growth coefficient corresponding to each rice grain color chroma in the growth parameter database, the color degree growth coefficient corresponding to each rice plant in each rice field subregion is screened out, and therefore the comprehensive growth coefficient corresponding to each rice plant in each rice field subregion is counted according to the plant height growth coefficient, the ear growth coefficient, the plumpness growth coefficient and the color degree growth coefficient corresponding to each rice plant in each rice field subregion
δiI is expressed as the comprehensive growth coefficient, alpha, corresponding to the I rice plant in the I rice field subregioniI、βiI、γiI、λiI is respectively expressed as a plant height growth coefficient, a panicle length growth coefficient, a plumpness growth coefficient and a color and luster growth coefficient corresponding to the I rice plant in the I rice field subregion;
the comprehensive growth factor of the rice plants counted in the embodiment is combined with parameters of plant height growth, ear growth, plumpness growth of rice grains and color and luster growth of the rice grains of the rice plants, so that the quantitative display of the comprehensive growth condition of the rice plants is realized, and the analysis one-sidedness problem caused by analyzing the comprehensive growth condition only according to a single growth parameter is avoided, and the accuracy of counting the total pesticide spraying amount of the sub-area of the rice field at the back is influenced;
s5, total pesticide spraying amount statistics of the rice field subareas: carrying out mean value processing on the comprehensive growth coefficients corresponding to the rice plants in each rice field subregion to obtain the average comprehensive growth coefficient of the rice corresponding to each rice field subregion, wherein the calculation formula is
Expressed as the average integrated growth coefficient of the rice corresponding to the ith rice field subregion, the obtained average integrated growth coefficient of the rice corresponding to each rice field subregion is compared with the pesticide spraying amount of the unit rice field region area corresponding to the average integrated growth coefficient of each rice in the pesticide spraying database, the pesticide spraying amount of the unit rice field region area corresponding to each rice field subregion is screened out, and meanwhile, the total pesticide spraying amount K corresponding to each rice field subregion is counted according to the area corresponding to each rice field subregioni＝ki*s，KiExpressed as the total sprayed pesticide, k, corresponding to the ith rice field subregioniThe pesticide amount sprayed on the unit rice field area corresponding to the ith rice field sub-area is expressed;
s6, standard spraying height analysis of unmanned aerial vehicles in the rice field subareas: extracting the rice plant height corresponding to each rice plant in each rice field subregion from the rice plant growth parameter set of each rice field subregion, and carrying out mean value processing on the rice plant height to obtain the average rice plant height corresponding to each rice field subregion, wherein the calculation formula is
Expressed as the average height of rice plants corresponding to the ith rice field area, so as to lead the average height of the rice plants corresponding to each rice field area to be in accordance with the unmanned aerial vehicle standard corresponding to the average height of various rice plants in the pesticide spraying databaseComparing the spraying heights to obtain the standard spraying heights of the unmanned aerial vehicles corresponding to the rice field subregions;
s7, detecting the wind speed of the rice field subregion: installing anemorumbometers in the rice field subregions respectively, wherein the anemorumeters are used for acquiring the wind speeds of the rice field subregions;
s8, actual spraying height statistics of unmanned aerial vehicles in the rice field subareas: comparing the wind speed of each rice field subregion with the spraying height influence coefficient corresponding to each wind speed in the pesticide spraying database, screening the spraying height influence coefficient corresponding to each rice field subregion, and counting the actual spraying height H 'of the unmanned aerial vehicle corresponding to each rice field subregion according to the standard spraying height of the unmanned aerial vehicle corresponding to each rice field subregion and the spraying height influence coefficient'i＝Hi*ηiH' represents the actual spraying height of the unmanned aerial vehicle corresponding to the ith rice field subregion, HiExpressed as the standard spraying height, eta of the unmanned aerial vehicle corresponding to the ith rice field subregioniExpressed as the spray height influence coefficient corresponding to the ith rice field subregion;
in the embodiment, the wind speed detection is carried out on each rice field subregion, so that the spraying height influence coefficient corresponding to each rice field subregion is obtained, the actual spraying height of the unmanned aerial vehicle corresponding to each rice field subregion is counted by combining the standard spraying heights of the unmanned aerial vehicles corresponding to each rice field subregion, the influence analysis of the wind speed on the actual spraying height of the unmanned aerial vehicle is realized, the actual situation is well fitted, the situation that the target rice region cannot be sprayed due to the fact that spraying is carried out only according to the standard spraying height of the unmanned aerial vehicle is avoided, the spraying accuracy is reduced, and the spraying effect is further reduced;
s9, acquiring the geographical position of the actual boundary spraying area of the rice field subregion: extracting boundary contour lines corresponding to the rice field sub-regions, namely standard boundary spraying region contours corresponding to the rice field sub-regions by the unmanned aerial vehicle, comparing the wind speed of the rice field sub-regions with the boundary spraying region offset distance corresponding to various wind speeds in the pesticide spraying database, thereby obtaining the boundary spraying region offset distance corresponding to the unmanned aerial vehicle in each rice field sub-region, meanwhile, obtaining the geographic position corresponding to the standard boundary spraying region corresponding to the rice field sub-region by the unmanned aerial vehicle, and further obtaining the actual boundary spraying region geographic position corresponding to the rice field sub-region by the unmanned aerial vehicle according to the boundary spraying region offset distance corresponding to the rice field sub-region by the unmanned aerial vehicle;
according to the method, the deviation distance of the boundary spraying area corresponding to each rice field sub-area of the unmanned aerial vehicle is obtained according to the wind speed of each rice field sub-area, so that the geographical position of the actual boundary spraying area corresponding to each rice field sub-area of the unmanned aerial vehicle is obtained, the influence of the wind speed on the actual boundary spraying area of the unmanned aerial vehicle is analyzed, the boundary-crossing spraying condition caused by spraying only according to the standard boundary spraying area corresponding to each rice field sub-area of the unmanned aerial vehicle is avoided, and the occurrence of the condition that rice in other rice field sub-areas is subjected to phytotoxicity due to boundary-crossing spraying is greatly reduced;
s10, unmanned aerial vehicle spraying parameter real-time regulation and control: when unmanned aerial vehicle flies each paddy field subregion, according to the total pesticide volume that sprays that each paddy field subregion corresponds, unmanned aerial vehicle actually sprays height and actual border and sprays regional geographical position, the total pesticide volume that real-time regulation and control unmanned aerial vehicle sprayed, spray height and border and spray regional geographical position, the pesticide that carries out each paddy field subregion sprays, compensate at present to spray the not enough that the operation in-process of pesticide is not conform to the crops actual demand that sprays that exists through unmanned aerial vehicle, the spraying effect has been improved, the emergence of the crop damage condition is caused because of not conforming to the crops actual demand that sprays that has significantly reduced, the safety of fine guarantee crops, the accurate plant protection demand to crops has been satisfied, and then the economic benefits of grower has been improved.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (9)
1. A big data analysis-based agricultural unmanned aerial vehicle operation remote control method is characterized by comprising the following steps: comprises the following steps;
s1, rice field subregion division: acquiring a boundary outline of a rice field area corresponding to a rice field to be sprayed with pesticides, and counting the area of the rice field area according to the acquired boundary outline of the rice field area, so that the rice field area is divided into a plurality of rice field sub-areas according to a method for uniformly and equally dividing the rice field area, the divided rice field sub-areas are numbered according to a predefined sequence and respectively marked as 1,2.. i.. n, and meanwhile, the area corresponding to each rice field sub-area is counted according to the number of the divided rice field sub-areas;
s2, acquiring rice field image in the rice field subregion: acquiring rice field images in each rice field subregion to obtain a rice field image of each rice field subregion, acquiring the number of rice plants from the obtained rice field image of each rice field subregion, numbering the rice plants corresponding to each acquired rice field subregion, and sequentially marking the rice plants as A, B.i.n.;
s3, constructing a rice plant growth parameter set in the rice field sub-region: sequentially focusing the rice field images of the rice field subareas in each rice field area according to the numbering sequence of each rice plant in each rice field subarea, further acquiring the height of each rice plant and the length of the rice ear corresponding to each rice plant, simultaneously sequentially focusing the rice field images of the rice field subareas on the rice ear areas corresponding to each rice plant, and extracting the maximum outline and the minimum outline of the rice grains on the rice ears corresponding to each rice plant and the color characteristics of the rice grains, so as to obtain the maximum volume, the minimum volume and the color chromaticity of the rice grains corresponding to each rice plant in each rice field subregion, at the moment, the average volume of the rice grains corresponding to each rice plant in each rice field subregion is calculated according to the maximum volume and the minimum volume of the rice grains corresponding to each rice plant in each rice field subregion, therefore, the obtained rice plant height, rice ear length, average rice grain volume and rice grain color degree corresponding to each rice plant in each rice field subregion constitute a rice plant growth parameter set Q of the rice field subregion.w i(qw iA,qw iB,...,qw iI,...,qw iN)，qw iI is a numerical value corresponding to the growth parameter of the I-th rice plant in the I-th rice field subregion, w is a growth parameter, and w is r1, r2, r3 and r4 respectivelyThe height of rice plant, the length of rice ear, the average volume of rice grain and the color and chroma of rice grain;
s4, carrying out comprehensive growth coefficient statistics on each rice plant in the rice field subregion: sequentially extracting the heights of the rice plants corresponding to the rice plants in each rice field subregion from the rice plant growth parameter set in the rice field subregion, comparing the heights with the plant height growth coefficients corresponding to the heights of the rice plants in the growth parameter database, screening the plant height growth coefficients corresponding to the rice plants in each rice field subregion from the rice plant growth parameter set in the rice field subregion, sequentially extracting the lengths of the rice ears corresponding to the rice plants in each rice field subregion from the rice plant growth parameter set in the rice field subregion, comparing the lengths with the ear length growth coefficients corresponding to the lengths of the rice ears in the growth parameter database, screening the ear length growth coefficients corresponding to the rice plants in each rice field subregion from the rice plant growth parameter set in the rice field subregion, sequentially extracting the average volume of the rice grains corresponding to the rice plants in each rice field subregion from the rice plant growth parameter set in the rice field subregion, and comparing the average volume of the rice grains with the saturation growth coefficients corresponding to the average volume of the rice grains in the growth parameter database, screening out plumpness vigor coefficients corresponding to all rice plants in all the rice field subregions from the rice field subregion rice plant vigor parameter sets, sequentially extracting the rice grain color chroma corresponding to all the rice plants in all the rice field subregions from the rice field subregion rice plant vigor parameter sets, comparing the rice grain color chroma and the color degree vigor coefficients corresponding to all the rice grain color chroma in the vigor parameter database, and screening out the color degree vigor coefficients corresponding to all the rice plants in all the rice field subregions from the rice grain color vigor coefficients, so that the comprehensive vigor coefficients corresponding to all the rice plants in all the rice field subregions are counted according to the plant height vigor coefficients, the spike length vigor coefficients, the plumpness vigor coefficients and the color degree vigor coefficients corresponding to all the rice plant subregions in all the;
s5, total pesticide spraying amount statistics of the rice field subareas: carrying out mean value processing on the comprehensive growth coefficients corresponding to the rice plants in each rice field subregion to obtain the average comprehensive growth coefficient of the rice corresponding to each rice field subregion, wherein the calculation formula is
Expressing the average integrated growth coefficient of the rice corresponding to the ith rice field subregion, comparing the obtained average integrated growth coefficient of the rice corresponding to each rice field subregion with the pesticide spraying amount of the unit rice field region area corresponding to the average integrated growth coefficient of each rice in the pesticide spraying database, screening out the pesticide spraying amount of the unit rice field region area corresponding to each rice field subregion, and meanwhile, counting the total pesticide spraying amount of each rice field subregion according to the area corresponding to each rice field subregion;
s6, standard spraying height analysis of unmanned aerial vehicles in the rice field subareas: extracting the rice plant height corresponding to each rice plant in each rice field subregion from the rice plant growth parameter set of each rice field subregion, and carrying out mean value processing on the rice plant height to obtain the average rice plant height corresponding to each rice field subregion, wherein the calculation formula is
The average height of the rice plants corresponding to the ith rice field subregion is expressed, so that the average height of the rice plants corresponding to each rice field subregion is compared with the standard unmanned aerial vehicle spraying height corresponding to the average height of each rice plant in the pesticide spraying database, and the standard unmanned aerial vehicle spraying height corresponding to each rice field subregion is obtained;
s7, detecting the wind speed of the rice field subregion: installing anemorumbometers in the rice field subregions respectively, wherein the anemorumeters are used for acquiring the wind speeds of the rice field subregions;
s8, actual spraying height statistics of unmanned aerial vehicles in the rice field subareas: comparing the wind speed of each rice field subregion with the spraying height influence coefficients corresponding to various wind speeds in the pesticide spraying database, screening the spraying height influence coefficients corresponding to each rice field subregion, and counting the actual spraying height of the unmanned aerial vehicle corresponding to each rice field subregion according to the standard spraying height of the unmanned aerial vehicle corresponding to each rice field subregion and the spraying height influence coefficients;
s9, acquiring the geographical position of the actual boundary spraying area of the rice field subregion: extracting boundary contour lines corresponding to the rice field sub-regions, namely standard boundary spraying region contours corresponding to the rice field sub-regions by the unmanned aerial vehicle, comparing the wind speed of the rice field sub-regions with the boundary spraying region offset distance corresponding to various wind speeds in the pesticide spraying database, thereby obtaining the boundary spraying region offset distance corresponding to the unmanned aerial vehicle in each rice field sub-region, meanwhile, obtaining the geographic position corresponding to the standard boundary spraying region corresponding to the rice field sub-region by the unmanned aerial vehicle, and further obtaining the actual boundary spraying region geographic position corresponding to the rice field sub-region by the unmanned aerial vehicle according to the boundary spraying region offset distance corresponding to the rice field sub-region by the unmanned aerial vehicle;
s10, unmanned aerial vehicle spraying parameter real-time regulation and control: when the unmanned aerial vehicle flies to each rice field subregion, the pesticide spraying of each rice field subregion is carried out according to the total pesticide spraying amount corresponding to each rice field subregion, the actual spraying height of the unmanned aerial vehicle and the geographical position of the actual boundary spraying region, by regulating and controlling the total pesticide spraying amount, the spraying height and the geographical position of the boundary spraying region sprayed by the unmanned aerial vehicle in real time.
2. The agricultural unmanned aerial vehicle operation remote control method based on big data analysis according to claim 1, characterized in that: in the step S1, the area of the rice field area is counted according to the obtained boundary contour line of the rice field area, and the specific counting method performs the following steps:
g1, acquiring longitude and latitude coordinates of the boundary contour line of the rice field area by using a GPS land surveying instrument;
g2, converting the longitude and latitude coordinates of the obtained contour line end points of the rice field area boundary into plane coordinates, and establishing a plane coordinate system
G3, connecting each end point of the boundary of the rice field area with the origin of coordinates, so that each side of the rice field area and the origin form a triangle, thereby dividing the rice field area into a plurality of triangles, and respectively calculating the area of each triangle;
and G4, summing the calculated areas of the triangles to obtain the area of the rice field area.
3. The method of claim 1A big data analysis-based agricultural unmanned aerial vehicle operation remote control method is characterized by comprising the following steps: the calculation formula of the area corresponding to each rice field subregion is
S represents an area corresponding to each paddy field subregion, and S represents a paddy field region area.
4. The agricultural unmanned aerial vehicle operation remote control method based on big data analysis according to claim 1, characterized in that: in S2, the method for obtaining the number of rice plants from the obtained rice field image of each rice field sub-area includes the following steps:
d1, extracting the outline of each individual rice plant from the obtained rice field image of each rice field subregion;
and D2, counting the number of the outlines of the extracted individual rice plants, namely the number of the rice plants corresponding to each rice field subregion.
5. The agricultural unmanned aerial vehicle operation remote control method based on big data analysis according to claim 1, characterized in that: the specific extraction process of S3 includes obtaining the number of rice grains on the ear corresponding to each rice plant, extracting the corresponding contours of each rice grain, comparing the extracted contours of each rice grain, and selecting the rice grain with the largest contour and the rice grain with the smallest contour from the extracted contours.
6. The agricultural unmanned aerial vehicle operation remote control method based on big data analysis according to claim 1, wherein: the calculation formula of the average volume of the rice grains corresponding to each rice plant in each rice field subregion is
Expressed as the average volume of rice grains, V, corresponding to the I-th rice plant in the I-th rice field sub-regioniImax、ViIminExpressed as the maximum volume and the minimum volume of rice grains corresponding to the I-th rice plant in the I-th rice field sub-area, respectively.
7. The agricultural unmanned aerial vehicle operation remote control method based on big data analysis according to claim 1, wherein: the calculation formula of the comprehensive growth coefficient corresponding to each rice plant in each rice field subregion is
δiI is expressed as the comprehensive growth coefficient, alpha, corresponding to the I rice plant in the I rice field subregioniI、βiI、γiI、λiAnd I is respectively expressed as a plant height growth coefficient, a panicle length growth coefficient, a plumpness growth coefficient and a color and luster growth coefficient corresponding to the I rice plant in the I rice field subregion.
8. The agricultural unmanned aerial vehicle operation remote control method based on big data analysis according to claim 1, wherein: the calculation formula of the total pesticide spraying amount corresponding to each rice field subregion is Ki＝ki*s，KiExpressed as the total sprayed pesticide, k, corresponding to the ith rice field subregioniExpressed as the amount of pesticide sprayed on the unit paddy field area corresponding to the ith paddy field area.
9. The agricultural unmanned aerial vehicle operation remote control method based on big data analysis according to claim 1, wherein: the calculation formula of the actual spraying height of the unmanned aerial vehicle corresponding to each rice field subregion is H'i＝Hi*ηiH' represents the actual spraying height of the unmanned aerial vehicle corresponding to the ith rice field subregion, HiExpressed as the standard spraying height, eta of the unmanned aerial vehicle corresponding to the ith rice field subregioniExpressed as the spray height influence coefficient corresponding to the ith rice field subregion。
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