CN113344524A - Intelligent agricultural crop planting management method and system based on remote data acquisition and analysis technology and storage medium - Google Patents
Intelligent agricultural crop planting management method and system based on remote data acquisition and analysis technology and storage medium Download PDFInfo
- Publication number
- CN113344524A CN113344524A CN202110614102.2A CN202110614102A CN113344524A CN 113344524 A CN113344524 A CN 113344524A CN 202110614102 A CN202110614102 A CN 202110614102A CN 113344524 A CN113344524 A CN 113344524A
- Authority
- CN
- China
- Prior art keywords
- insect
- insect pest
- pest
- unmanned aerial
- aerial vehicle
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
- 238000007726 management method Methods 0.000 title claims abstract description 76
- 238000005516 engineering process Methods 0.000 title claims abstract description 34
- 238000004458 analytical method Methods 0.000 title claims abstract description 19
- 238000003860 storage Methods 0.000 title claims abstract description 14
- 241000607479 Yersinia pestis Species 0.000 claims abstract description 313
- 239000000575 pesticide Substances 0.000 claims abstract description 186
- 238000005507 spraying Methods 0.000 claims abstract description 124
- 238000000034 method Methods 0.000 claims abstract description 33
- 238000000605 extraction Methods 0.000 claims abstract description 14
- 238000002360 preparation method Methods 0.000 claims abstract description 10
- 241000238631 Hexapoda Species 0.000 claims description 307
- 239000007921 spray Substances 0.000 claims description 74
- 244000038559 crop plants Species 0.000 claims description 40
- 201000010099 disease Diseases 0.000 claims description 27
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 27
- 238000007405 data analysis Methods 0.000 claims description 9
- 238000013480 data collection Methods 0.000 claims description 9
- 230000001276 controlling effect Effects 0.000 claims description 8
- 238000004590 computer program Methods 0.000 claims description 6
- 238000003709 image segmentation Methods 0.000 claims description 3
- 230000001105 regulatory effect Effects 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims description 3
- 238000005192 partition Methods 0.000 claims 2
- -1 reas Species 0.000 claims 1
- 230000000694 effects Effects 0.000 abstract description 6
- 230000007547 defect Effects 0.000 description 2
- 239000000284 extract Substances 0.000 description 2
- 230000006870 function Effects 0.000 description 2
- 238000011065 in-situ storage Methods 0.000 description 2
- 238000007792 addition Methods 0.000 description 1
- 238000012271 agricultural production Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 239000007788 liquid Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/10—Office automation; Time management
- G06Q10/103—Workflow collaboration or project management
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01M—CATCHING, TRAPPING OR SCARING OF ANIMALS; APPARATUS FOR THE DESTRUCTION OF NOXIOUS ANIMALS OR NOXIOUS PLANTS
- A01M7/00—Special adaptations or arrangements of liquid-spraying apparatus for purposes covered by this subclass
- A01M7/0025—Mechanical sprayers
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01M—CATCHING, TRAPPING OR SCARING OF ANIMALS; APPARATUS FOR THE DESTRUCTION OF NOXIOUS ANIMALS OR NOXIOUS PLANTS
- A01M7/00—Special adaptations or arrangements of liquid-spraying apparatus for purposes covered by this subclass
- A01M7/0089—Regulating or controlling systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/24—Classification techniques
- G06F18/241—Classification techniques relating to the classification model, e.g. parametric or non-parametric approaches
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/02—Agriculture; Fishing; Forestry; Mining
Landscapes
- Engineering & Computer Science (AREA)
- Life Sciences & Earth Sciences (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- Strategic Management (AREA)
- Human Resources & Organizations (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Evolutionary Computation (AREA)
- Evolutionary Biology (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Bioinformatics & Computational Biology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Entrepreneurship & Innovation (AREA)
- Economics (AREA)
- Artificial Intelligence (AREA)
- Environmental Sciences (AREA)
- Zoology (AREA)
- Tourism & Hospitality (AREA)
- General Engineering & Computer Science (AREA)
- Wood Science & Technology (AREA)
- Insects & Arthropods (AREA)
- Pest Control & Pesticides (AREA)
- Mechanical Engineering (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Agronomy & Crop Science (AREA)
- Animal Husbandry (AREA)
- Marine Sciences & Fisheries (AREA)
- Mining & Mineral Resources (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Catching Or Destruction (AREA)
Abstract
The invention discloses an intelligent agricultural crop planting management method, system and storage medium based on remote data acquisition and analysis technology, which comprises the steps of carrying out remote pest plant extraction on a farmland to be sprayed with pesticides by an unmanned aerial vehicle, carrying out pest parameter acquisition, further respectively analyzing according to pest parameters to obtain the types of pesticides to be sprayed and the total spraying amount corresponding to various pesticides corresponding to crops in the farmland, carrying out preparation work before pesticide spraying on the unmanned aerial vehicle, positioning the geographical position of the pest plant, and intelligently controlling the start and stop of the unmanned aerial vehicle, the types of sprayed pesticides and the pesticide spraying amount in real time during the pesticide spraying process of the unmanned aerial vehicle on the farmland, thereby realizing intelligent management on the pesticide spraying technology of crops, perfecting the function of the pesticide spraying management technology of the unmanned aerial vehicle, and improving the flexibility and the accuracy of the pesticide spraying management of the unmanned aerial vehicle, thereby improving the spraying effect and better ensuring the safety of crops.
Description
Technical Field
The invention belongs to the technical field of crop planting management, particularly relates to a crop pesticide spraying management technology, and particularly relates to an intelligent agricultural crop planting management method, system and storage medium based on a remote data acquisition and analysis technology.
Background
In recent years, with the continuous development of science and technology and the increasing demand of agricultural production on safe and efficient planting, the crop planting management technology is also improved from the traditional manual extensive planting management technology to the intelligent fine planting management technology. Taking the management technology of spraying pesticides as an example, the current pesticide spraying technology of our country has been changed from traditional manual pesticide spraying into spraying pesticides through unmanned aerial vehicles, effectively remedies the defects of time and labor waste and low spraying efficiency of manual pesticide spraying, can better prevent crop diseases and insect pests from occurring, and improves the economic benefit of farmers.
However, the current pesticide spraying management technology of the unmanned aerial vehicle is still imperfect, and the management flexibility and accuracy are insufficient, which is embodied in the following aspects:
1. in the current pesticide spraying operation process of crops through the unmanned aerial vehicle, most of pesticide types sprayed by the unmanned aerial vehicle to the same farmland area are fixed and invariable, the condition that the insect pest types of the crops suffering from insect pests are different in the same farmland is not considered, and the pesticide types sprayed by different insect pest types are definitely different, so that the condition that the crops are simply sprayed by the fixed and invariable pesticide types is obviously unreasonable, and the crops are possibly damaged;
2. at present spray the pesticide operation in-process to crops through unmanned aerial vehicle, the pesticide volume that unmanned aerial vehicle sprayed in same farmland region is unified control, do not consider that the crops of same kind of insect pest type may have the condition that the insect spot area is different, different insect spot areas, its pesticide that corresponds sprays the volume and exists the difference, consequently spray all crops in the farmland with unified pesticide spray volume alone and be not conform to crops actual spray demand obviously, lead to spraying the effect poor.
Disclosure of Invention
In view of the above problems, the present invention provides a method, a system and a storage medium for intelligent agricultural crop planting management based on a remote data collection and analysis technology, which can effectively solve the problems mentioned in the background art.
The purpose of the invention can be realized by the following technical scheme:
the invention provides an intelligent agricultural crop planting management method based on a remote data acquisition and analysis technology, which comprises the following steps:
s1, dividing farmland sub-regions: counting the number of rows of crop planting in a farmland to be sprayed with pesticides by a farmland subregion dividing module, and dividing the farmland into subregions according to the number of rows of crop planting;
s2, remotely extracting insect pest plants: carrying out remote image acquisition on crops in each sub-area through an unmanned aerial vehicle according to a pest plant remote extraction module to obtain crop images corresponding to each sub-area, and extracting pest plants in each sub-area from the crop images;
s3, collecting insect pest parameters corresponding to insect pest plants: insect pest parameters of insect pest plants corresponding to the sub-areas are collected through an insect pest parameter collecting module of the insect pest plants;
s4, statistics of types of the diseases: summarizing all the insect pest plants in all sub-regions of the farmland through a farmland insect pest type summarizing and counting module, extracting insect pest types from insect pest parameters corresponding to all the insect pest plants, comparing the insect pest types corresponding to all the insect pest plants with each other, judging whether the same insect pest types exist or not, classifying the insect pest plants corresponding to the same insect pest types, and counting all the insect pest types of crops in the farmland;
s5, analyzing the types of pesticides sprayed on the farmland: matching all the pest types of the crops in the farmland with pesticide types corresponding to various pest types in a management database through a management cloud platform to obtain pesticide types corresponding to various pest types of the crops in the farmland;
s6, total pesticide spraying amount analysis: extracting the area of the insect spot from insect pest parameters of insect pest plants corresponding to various types of insect pests in the farmland through a management cloud platform, and analyzing the total spraying amount corresponding to various pesticides in the farmland according to the area;
s7, positioning the geographical position of the insect plant: positioning the geographical positions of the insect pest plants corresponding to the types of the various diseases in the farmland through an insect pest plant geographical position positioning module;
s8, intelligent control of pesticide spraying of the unmanned aerial vehicle: the intelligent control terminal carries out the preparation work before pesticide spraying on the unmanned aerial vehicle according to the pesticide types corresponding to various pest types and the total spraying amount corresponding to various pesticides of crops in the farmland, and the geographical position of the unmanned aerial vehicle is acquired in real time during the pesticide spraying process of the unmanned aerial vehicle on the farmland, and matching the geographical position of the plant with the geographical position of each insect pest corresponding to each insect pest type, if the matching fails, continuing flying, if matching is successful, controlling the unmanned aerial vehicle to stop flying, simultaneously opening the pesticide spraying head corresponding to the unmanned aerial vehicle, connecting the pesticide spraying head corresponding to the unmanned aerial vehicle to the pesticide type storage tank corresponding to the pest type according to the pest type corresponding to the successfully matched pest plant, meanwhile, the pesticide spraying amount of the pesticide spraying head is controlled according to the area of the insect spot corresponding to the successfully matched insect pest plant.
According to a preferred embodiment of the first aspect of the present invention, in S2, the pest plants in each sub-region are extracted from the crop image corresponding to each sub-region, and the specific extraction process performs the following steps:
d1, extracting the outline of each crop plant from the crop image corresponding to each subregion, and counting the number of the extracted outline of each crop plant, wherein the number of the outline is the number of the crop plants corresponding to each subregion;
d2, carrying out image segmentation on the crop image corresponding to each subregion according to the extracted outline of the single crop plant to obtain each segmented subimage, wherein each subimage corresponds to the single crop plant respectively;
d3, focusing the divided sub-images on the leaves, stems and root parts of the crop plants respectively, extracting insect spots, if the insect spots cannot be extracted from the leaves, stems and root parts of the crop plants corresponding to a certain sub-image, indicating that the crop plants corresponding to the sub-image have no insect pests, and if the insect spots can be extracted from at least one part of the leaves, stems and root parts of the crop plants corresponding to a certain sub-image, indicating that the crop plants corresponding to the sub-image have insect pests, and recording the crop plants as insect pest plants, thereby obtaining the insect pest plants in each sub-area.
According to a preferred embodiment of the first aspect of the invention, the pest parameters include a pest type and a pest patch area.
According to a preferred embodiment of the first aspect of the present invention, in S3, pest parameters of pest plants corresponding to each sub-area are collected, where the method specifically includes:
e1, counting the number of the insect pest plants in each subregion, and positioning the region position of the insect spot corresponding to each insect pest plant;
e2, focusing the sub-images corresponding to the insect pest plants in the insect pest regions according to the positions of the located insect pests, further extracting the insect pest features, comparing the extracted insect pest features with the insect pest features corresponding to various insect pest types in the management database, and if the comparison between the extracted insect pest features of a certain insect pest region and the insect pest features corresponding to a certain insect pest type is successful, determining the insect pest type corresponding to the insect pest region as the insect pest type;
e3, extracting the shape and contour of the insect spot area corresponding to each insect pest plant to obtain the area of the insect spot corresponding to each insect pest plant.
According to a preferred embodiment of the first aspect of the present invention, the total amount of the pesticide sprays in the farmland is analyzed in S6, and the specific analysis method is as follows:
f1, overlapping the insect spot areas of the insect plants corresponding to the various types of the diseases in the farmland to obtain the total insect spot area of the insect plants corresponding to the various types of the diseases in the farmland;
f2, comparing the total insect spot area of the insect pest plants corresponding to the various insect disease types in the farmland with the pesticide spraying amount corresponding to the various insect spot areas of the pesticide types belonging to the insect disease types in the management database, and screening out the total spraying amount corresponding to various pesticides in the farmland.
According to a preferred embodiment of the first aspect of the present invention, in S8, the preparation work before pesticide spraying is performed on the unmanned aerial vehicle according to the pesticide types corresponding to the various types of diseases and the total amount of pesticide spraying on the crops in the farmland, the specific operation process is to prepare the pesticide types carried by the unmanned aerial vehicle according to the pesticide types corresponding to the various types of diseases and the total amount of pesticide spraying on the crops in the farmland, and prepare the pesticide amounts corresponding to the various pesticides carried by the unmanned aerial vehicle according to the total amount of pesticide spraying on the crops in the farmland.
According to a preferred embodiment of the first aspect of the present invention, in S8, the method for controlling the pesticide spraying amount of the pesticide spraying head according to the area of the pest spot corresponding to the successfully matched pest plant includes the following steps:
h1, comparing the spot area corresponding to the successfully matched insect pest plant with the pesticide spraying amount corresponding to each spot area of the pesticide type to which the insect pest type belongs in the successfully matched insect pest plant in the management database to obtain the pesticide spraying amount corresponding to the spot area of the successfully matched insect pest plant;
h2, arranging a flow meter in the pesticide spray head corresponding to the unmanned aerial vehicle, collecting the actual pesticide spray amount sprayed out from the pesticide spray head in real time, comparing the actual pesticide spray amount with the pesticide spray amount corresponding to the pest spot area of the successfully matched pest plant, continuing spraying if the actual pesticide spray amount is less than the pesticide spray amount corresponding to the pest spot area of the successfully matched pest plant, and controlling the pesticide spray head corresponding to the unmanned aerial vehicle to close and stop spraying if the actual pesticide spray amount is more than or equal to the pesticide spray amount corresponding to the pest spot area of the successfully matched pest plant.
According to a preferred embodiment of the first aspect of the present invention, in the step S8, during the pesticide spraying process on the successfully matched pest plants, the current spraying height of the unmanned aerial vehicle is further controlled, and the specific control process is as follows:
k1, judging the parts of the crop plants corresponding to the spot areas of the successfully matched insect pest plants, and recording the parts of the crop plants in the spot areas as spot parts;
k2, acquiring the height of the insect pest plant matched successfully corresponding to the insect spot part;
k3, comparing the height of the spot part corresponding to the successfully matched insect pest plant with the suitable spraying height of the unmanned aerial vehicle corresponding to the height of each spot part in the management database to obtain the suitable spraying height of the unmanned aerial vehicle corresponding to the spot part of the successfully matched insect pest plant;
k4, obtain unmanned aerial vehicle and spray the height at present, and spray the height with the unmanned aerial vehicle that should match the insect spot position correspondence of successful insect pest plant and contrast, if unmanned aerial vehicle sprays the height at present and equals the suitable height that sprays of the unmanned aerial vehicle that should match the insect spot position correspondence of successful insect pest plant, then not regulate and control this unmanned aerial vehicle's the height that sprays, if unmanned aerial vehicle sprays the height at present and is less than the suitable height that sprays of the unmanned aerial vehicle that should match the insect spot position correspondence of successful insect pest plant, then spray the height and increase to unmanned aerial vehicle's current, if unmanned aerial vehicle sprays the height at present and is greater than the suitable height that sprays of the unmanned aerial vehicle that should match the insect spot position correspondence of successful insect pest plant, then spray the.
The invention provides a remote data acquisition and analysis technology-based intelligent agricultural crop planting management system, which comprises a farmland subregion dividing module, a pest plant remote extraction module, a pest plant pest parameter acquisition module, a farmland pest type summarizing and counting module, a management database, a management cloud platform, a pest plant geographic position positioning module and an intelligent control terminal, the farmland subregion division module is connected with the insect pest plant remote extraction module, the insect pest plant remote extraction module is connected with the insect pest plant insect pest parameter acquisition module, the insect pest plant insect pest parameter acquisition module is respectively connected with the farmland disease type gathering and counting module and the management cloud platform, the farmland disease type gathering and counting module is connected with the management cloud platform, and the management cloud platform and the insect pest plant geographic position positioning module are connected with the intelligent control terminal.
The third aspect of the invention provides a storage medium, wherein a computer program is burnt on the storage medium, and when the computer program runs in a memory of a server, the intelligent agricultural crop planting management method based on the remote data acquisition and analysis technology is realized.
Based on any one of the above aspects, the invention has the following beneficial effects:
1. the invention remotely extracts the insect pest plants through the unmanned aerial vehicle in the farmland to be sprayed with pesticide, collects the insect pest parameters of the extracted insect pest plants, further analyzes the types of pesticide corresponding to various types of diseases existing in crops in the farmland according to the types of the diseases in the insect pest parameters, analyzes the total spraying amount corresponding to various pesticides in the farmland according to the area of insect spots in the insect pest parameters, thereby carrying out preparation work before spraying pesticide on the unmanned aerial vehicle, simultaneously positions the geographical positions of the insect pest plants, and intelligently controls the starting and stopping of the unmanned aerial vehicle, the types of sprayed pesticide and the pesticide spraying amount in real time in the pesticide spraying process of the unmanned aerial vehicle on the farmland, thereby realizing intelligent management on the pesticide spraying technology of crops, and fully overcoming the defects of insufficient management flexibility and accuracy existing in the current pesticide spraying management technology of the unmanned aerial vehicle, perfects the function of unmanned aerial vehicle pesticide spraying management technology, has improved unmanned aerial vehicle pesticide spraying management's flexibility ratio and precision, and then has promoted the effect of spraying, has ensured the safety of crops better.
2. According to the invention, in the pesticide spraying process of successfully matched insect pest plants, the height of the insect spot part of the insect pest plant is obtained, and the current spraying height of the unmanned aerial vehicle is regulated and controlled, so that the pesticide sprayed from the spraying height of the regulated and controlled unmanned aerial vehicle can be accurately aligned to the insect spot part, the accurate spraying of the unmanned aerial vehicle is further deeply optimized, and the spraying effect is enhanced.
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 steps of a method of the present invention;
fig. 2 is a schematic diagram of the system module connection according to 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, a first aspect of the present invention provides an intelligent agricultural crop planting management method based on a remote data collection and analysis technology, including the following steps:
s1, dividing farmland sub-regions: counting the number of rows of crop planting in a farmland to be sprayed with pesticides by a farmland subregion dividing module, and dividing the farmland into subregions according to the number of rows of crop planting;
s2, remotely extracting insect pest plants: according to the long-range module of drawing of insect pest plant to installing the appearance of making a video recording on unmanned aerial vehicle and carrying out long-range image acquisition through unmanned aerial vehicle to the crops of each subregion, obtain the crops image that each subregion corresponds to extract the insect pest plant in each subregion from it, its specific extraction process carries out following step:
d1, extracting the outline of each crop plant from the crop image corresponding to each subregion, and counting the number of the extracted outline of each crop plant, wherein the number of the outline is the number of the crop plants corresponding to each subregion;
d2, carrying out image segmentation on the crop image corresponding to each subregion according to the extracted outline of the single crop plant to obtain each segmented subimage, wherein each subimage corresponds to the single crop plant respectively;
d3, focusing the divided sub-images on the leaves, stems and root parts of the crop plants respectively, extracting insect spots, if the leaves, stems and root parts of the crop plants corresponding to a certain sub-image can not be extracted with insect spots, indicating that the crop plants corresponding to the sub-image have no insect pests, and if at least one part of the leaves, stems and root parts of the crop plants corresponding to a certain sub-image can be extracted with insect spots, indicating that the crop plants corresponding to the sub-image have insect pests, and recording the crop plants as insect pest plants, thereby obtaining the insect pest plants in each sub-area;
in the embodiment, the unmanned aerial vehicle is used for remotely acquiring data of a farmland to be sprayed with pesticide currently, and extracting pest plants from the data, so that a spraying target is provided for targeted pesticide spraying of the pest plants in the later period, and compared with in-situ acquisition, the remote acquisition mode is more convenient, so that the acquisition efficiency is improved, and the in-situ acquisition cost is reduced;
s3, collecting insect pest parameters corresponding to insect pest plants: insect pest parameters are collected on the insect pest plants corresponding to the sub-regions through an insect pest parameter collecting module, wherein the insect pest parameters comprise insect pest types and insect pest areas, and the specific collecting method of the insect pest parameters comprises the following steps:
e1, counting the number of the insect pest plants in each subregion, and positioning the region position of the insect spot corresponding to each insect pest plant;
e2, focusing the sub-images corresponding to the insect pest plants in the insect pest regions according to the positions of the located insect pests, further extracting the insect pest characteristics, wherein the insect pest characteristics comprise insect pest shapes, insect pest colors, insect pest textures and the like, comparing the extracted insect pest characteristics with the insect pest characteristics corresponding to various insect pest types in the management database, and if the comparison between the extracted insect pest characteristics of a certain insect pest region and the insect pest characteristics corresponding to a certain insect pest type is successful, determining the insect pest type corresponding to the insect pest region as the insect pest type;
e3, extracting the shape contour of the insect spot area corresponding to each insect pest plant, wherein the extracted shape contour of the insect spot separates the insect spot area from the non-insect spot area, and the insect spot area of the insect spot area corresponding to each insect pest plant is obtained by a seed point filling method;
the pest parameters collected by the embodiment of the invention provide analysis basis for analyzing the types of pesticides to be sprayed on crops in the farmland on one hand, and provide analysis basis for analyzing the total spraying amount corresponding to various pesticides to be sprayed on crops in the farmland on the other hand;
s4, statistics of types of the diseases: summarizing all the insect pest plants in all sub-regions of the farmland through a farmland insect pest type summarizing and counting module, extracting insect pest types from insect pest parameters corresponding to all the insect pest plants, comparing the insect pest types corresponding to all the insect pest plants with each other, judging whether the same insect pest types exist or not, classifying the insect pest plants corresponding to the same insect pest types, and counting all the insect pest types of crops in the farmland;
s5, analyzing the types of pesticides sprayed on the farmland: matching all the pest types of the crops in the farmland with pesticide types corresponding to various pest types in a management database through a management cloud platform to obtain pesticide types corresponding to various pest types of the crops in the farmland;
s6, total pesticide spraying amount analysis: the method comprises the following steps of extracting the insect spot area from insect pest parameters of insect pest plants corresponding to various insect pest types in the farmland through a management cloud platform, and analyzing the total spraying amount corresponding to various pesticides in the farmland according to the insect pest area, wherein the specific analysis method comprises the following steps:
f1, overlapping the insect spot areas of the insect plants corresponding to the various types of the diseases in the farmland to obtain the total insect spot area of the insect plants corresponding to the various types of the diseases in the farmland;
f2, comparing the total insect spot area of the insect pest plants corresponding to the various insect disease types in the farmland with the pesticide spraying amount corresponding to the various insect spot areas of the pesticide types belonging to the insect disease types in the management database, and screening out the total spraying amount corresponding to various pesticides in the farmland;
s7, positioning the geographical position of the insect plant: positioning the geographical positions of the insect pest plants corresponding to the types of the various diseases in the farmland through an insect pest plant geographical position positioning module;
s8, intelligent control of pesticide spraying of the unmanned aerial vehicle: the preparation work before pesticide spraying is carried out on the unmanned aerial vehicle through the intelligent control terminal according to the pesticide types corresponding to various pest types of crops in the farmland and the spraying total amount corresponding to various pesticides, the preparation work is used for preparing the pesticide types carried by the unmanned aerial vehicle according to the pesticide types corresponding to various pest types of crops in the farmland, and the pesticide amount corresponding to various pesticides carried by the unmanned aerial vehicle is prepared according to the spraying total amount corresponding to various pesticides;
in the pesticide amount preparation process corresponding to various pesticides carried by the unmanned aerial vehicle, the prepared pesticide amount is slightly larger than the total spraying amount corresponding to various pesticides in the spraying process, considering that the unmanned aerial vehicle is likely to have liquid leakage in the spraying process and excessive spraying caused by the condition that the spraying amount is not fine enough, and the condition that the pesticide amount is not enough in the spraying process is avoided;
and in the pesticide spraying process of the unmanned aerial vehicle on the farmland, installing a GPS (global positioning system) locator on the unmanned aerial vehicle, acquiring the geographical position of the unmanned aerial vehicle in real time, matching the geographical position of the unmanned aerial vehicle with the geographical positions of all pest plants corresponding to various pest types, if the geographical position of the unmanned aerial vehicle is different from the geographical positions of all pest plants corresponding to any pest type, indicating that the matching fails, continuing to fly, if the geographical position of the unmanned aerial vehicle is the same as the geographical position of a certain pest plant corresponding to a certain pest type, indicating that the matching succeeds, controlling the unmanned aerial vehicle to stop flying, simultaneously opening a pesticide spraying head corresponding to the unmanned aerial vehicle, connecting the pesticide spraying head corresponding to the unmanned aerial vehicle to a pesticide storage tank corresponding to the pest type according to the pest type corresponding to the pest plant successfully matched, and simultaneously controlling the pesticide spraying head according to the pest spot area corresponding to the pest plant successfully matched The specific control method of the medicine spraying amount comprises the following steps:
h1, comparing the spot area corresponding to the successfully matched insect pest plant with the pesticide spraying amount corresponding to each spot area of the pesticide type to which the insect pest type belongs in the successfully matched insect pest plant in the management database to obtain the pesticide spraying amount corresponding to the spot area of the successfully matched insect pest plant;
h2, arranging a flow meter in the pesticide spray head corresponding to the unmanned aerial vehicle, collecting the actual pesticide spray amount sprayed out from the pesticide spray head in real time, comparing the actual pesticide spray amount with the pesticide spray amount corresponding to the pest spot area of the successfully matched pest plant, continuing spraying if the actual pesticide spray amount is less than the pesticide spray amount corresponding to the pest spot area of the successfully matched pest plant, and controlling the pesticide spray head corresponding to the unmanned aerial vehicle to close and stop spraying if the actual pesticide spray amount is more than or equal to the pesticide spray amount corresponding to the pest spot area of the successfully matched pest plant.
In the embodiment, the unmanned aerial vehicle remotely extracts pest plants of a farmland to be sprayed with pesticides, collects pest parameters, analyzes and obtains the types of pesticides to be sprayed and the total spraying amount of various pesticides corresponding to crops in the farmland according to the pest parameters, and simultaneously positions the geographical positions of the pest plants, intelligently controls the start and stop of the unmanned aerial vehicle in real time and the types and the amount of the sprayed pesticides during the pesticide spraying process of the unmanned aerial vehicle on the farmland, realizes the intelligent management of the pesticide spraying technology of crops, embodies the characteristics of high intelligent degree and strong practicability, perfects the function of the pesticide spraying management technology of the unmanned aerial vehicle, improves the flexibility and the accuracy of the pesticide spraying management of the unmanned aerial vehicle, and further improves the spraying effect, the safety of crops is better guaranteed.
And unmanned aerial vehicle carries out the pesticide to the insect pest plant that matches successfully and sprays the in-process, still adjusts and controls the current height of spraying of unmanned aerial vehicle, and its specific regulation and control process is as follows:
k1, judging the parts of the crop plants corresponding to the spot areas of the successfully matched insect pest plants, and recording the parts of the crop plants in the spot areas as spot parts;
k2, acquiring the height of the insect pest plant matched successfully corresponding to the insect spot part;
k3, comparing the height of the spot part corresponding to the successfully matched insect pest plant with the suitable spraying height of the unmanned aerial vehicle corresponding to the height of each spot part in the management database to obtain the suitable spraying height of the unmanned aerial vehicle corresponding to the spot part of the successfully matched insect pest plant;
k4, obtain unmanned aerial vehicle and spray the height at present, and spray the height with the unmanned aerial vehicle that should match the insect spot position correspondence of successful insect pest plant and contrast, if unmanned aerial vehicle sprays the height at present and equals the suitable height that sprays of the unmanned aerial vehicle that should match the insect spot position correspondence of successful insect pest plant, then not regulate and control this unmanned aerial vehicle's the height that sprays, if unmanned aerial vehicle sprays the height at present and is less than the suitable height that sprays of the unmanned aerial vehicle that should match the insect spot position correspondence of successful insect pest plant, then spray the height to unmanned aerial vehicle at present and increase, and regulate and control to the suitable height that sprays of unmanned aerial vehicle, if unmanned aerial vehicle sprays the height that highly is greater than this unmanned aerial vehicle that matches the insect spot position correspondence of successful insect pest plant and suitably sprays the height, then spray the height to unmanned aerial vehicle at present and reduce, and regulate and control to the suitable unmanned aerial vehicle of spraying the height.
This embodiment is carrying out the pesticide to the successful insect pest plant of matching and spraying the in-process, through the height that acquires insect pest plant insect spot position, and then highly regulates and control spraying unmanned aerial vehicle is current in view of the above for the unmanned aerial vehicle place of regulation and control sprays the pesticide that highly sprays out and can accurately aim at the insect spot position, and the accurate of having optimized unmanned aerial vehicle more deeply sprays, has reinforceed the spraying effect.
Referring to fig. 2, a second aspect of the invention provides an intelligent agricultural crop planting management system based on a remote data acquisition and analysis technology, which comprises a farmland subregion dividing module, a pest plant remote extraction module, a pest plant pest parameter acquisition module, a farmland pest type summarizing and counting module, a management database, a management cloud platform, a pest plant geographic position positioning module and an intelligent control terminal, wherein the management database is used for storing pesticide varieties corresponding to various pest types, storing pest spot characteristics corresponding to various pest types, pesticide spraying amounts corresponding to various pest areas of the pesticide varieties to which the various pest types belong, and storing an unmanned aerial vehicle appropriate spraying height corresponding to the heights of the various pest parts.
The farmland subregion division module is connected with the insect pest plant remote extraction module, the insect pest plant remote extraction module is connected with the insect pest plant insect pest parameter acquisition module, the insect pest plant insect pest parameter acquisition module is respectively connected with the farmland disease type gathering and counting module and the management cloud platform, the farmland disease type gathering and counting module is connected with the management cloud platform, and the management cloud platform and the insect pest plant geographic position positioning module are connected with the intelligent control terminal.
The third aspect of the invention provides a storage medium, wherein a computer program is burnt on the storage medium, and when the computer program runs in a memory of a server, the intelligent agricultural crop planting management method based on the remote data acquisition and analysis technology is realized.
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 (10)
1. An intelligent agricultural crop planting management method based on a remote data acquisition and analysis technology is characterized by comprising the following steps:
s1, dividing farmland sub-regions: counting the number of rows of crop planting in a farmland to be sprayed with pesticides by a farmland subregion dividing module, and dividing the farmland into subregions according to the number of rows of crop planting;
s2, remotely extracting insect pest plants: carrying out remote image acquisition on crops in each sub-area through an unmanned aerial vehicle according to a pest plant remote extraction module to obtain crop images corresponding to each sub-area, and extracting pest plants in each sub-area from the crop images;
s3, collecting insect pest parameters corresponding to insect pest plants: insect pest parameters of insect pest plants corresponding to the sub-areas are collected through an insect pest parameter collecting module of the insect pest plants;
s4, statistics of types of the diseases: summarizing all the insect pest plants in all sub-regions of the farmland through a farmland insect pest type summarizing and counting module, extracting insect pest types from insect pest parameters corresponding to all the insect pest plants, comparing the insect pest types corresponding to all the insect pest plants with each other, judging whether the same insect pest types exist or not, classifying the insect pest plants corresponding to the same insect pest types, and counting all the insect pest types of crops in the farmland;
s5, analyzing the types of pesticides sprayed on the farmland: matching all the pest types of the crops in the farmland with pesticide types corresponding to various pest types in a management database through a management cloud platform to obtain pesticide types corresponding to various pest types of the crops in the farmland;
s6, total pesticide spraying amount analysis: extracting the area of the insect spot from insect pest parameters of insect pest plants corresponding to various types of insect pests in the farmland through a management cloud platform, and analyzing the total spraying amount corresponding to various pesticides in the farmland according to the area;
s7, positioning the geographical position of the insect plant: positioning the geographical positions of the insect pest plants corresponding to the types of the various diseases in the farmland through an insect pest plant geographical position positioning module;
s8, intelligent control of pesticide spraying of the unmanned aerial vehicle: the intelligent control terminal carries out the preparation work before pesticide spraying on the unmanned aerial vehicle according to the pesticide types corresponding to various pest types and the total spraying amount corresponding to various pesticides of crops in the farmland, and the geographical position of the unmanned aerial vehicle is acquired in real time during the pesticide spraying process of the unmanned aerial vehicle on the farmland, and matching the geographical position of the plant with the geographical position of each insect pest corresponding to each insect pest type, if the matching fails, continuing flying, if matching is successful, controlling the unmanned aerial vehicle to stop flying, simultaneously opening the pesticide spraying head corresponding to the unmanned aerial vehicle, connecting the pesticide spraying head corresponding to the unmanned aerial vehicle to the pesticide type storage tank corresponding to the pest type according to the pest type corresponding to the successfully matched pest plant, meanwhile, the pesticide spraying amount of the pesticide spraying head is controlled according to the area of the insect spot corresponding to the successfully matched insect pest plant.
2. The intelligent agricultural crop planting management method based on the remote data collection and analysis technology as claimed in claim 1, wherein: in the step S2, pest plants in each sub-region are extracted from the crop image corresponding to each sub-region, and the specific extraction process includes the following steps:
d1, extracting the outline of each crop plant from the crop image corresponding to each subregion, and counting the number of the extracted outline of each crop plant, wherein the number of the outline is the number of the crop plants corresponding to each subregion;
d2, carrying out image segmentation on the crop image corresponding to each subregion according to the extracted outline of the single crop plant to obtain each segmented subimage, wherein each subimage corresponds to the single crop plant respectively;
d3, focusing the divided sub-images on the leaves, stems and root parts of the crop plants respectively, extracting insect spots, if the insect spots cannot be extracted from the leaves, stems and root parts of the crop plants corresponding to a certain sub-image, indicating that the crop plants corresponding to the sub-image have no insect pests, and if the insect spots can be extracted from at least one part of the leaves, stems and root parts of the crop plants corresponding to a certain sub-image, indicating that the crop plants corresponding to the sub-image have insect pests, and recording the crop plants as insect pest plants, thereby obtaining the insect pest plants in each sub-area.
3. The intelligent agricultural crop planting management method based on the remote data collection and analysis technology as claimed in claim 1, wherein: the insect pest parameters comprise types of insect pests and areas of insect spots.
4. The intelligent agricultural crop planting management method based on the remote data collection and analysis technology as claimed in claim 2, wherein: and in the S3, insect pest parameter acquisition is carried out on the insect pest plants corresponding to the sub-regions, and the specific acquisition method comprises the following steps:
e1, counting the number of the insect pest plants in each subregion, and positioning the region position of the insect spot corresponding to each insect pest plant;
e2, focusing the sub-images corresponding to the insect pest plants in the insect pest regions according to the positions of the located insect pests, further extracting the insect pest features, comparing the extracted insect pest features with the insect pest features corresponding to various insect pest types in the management database, and if the comparison between the extracted insect pest features of a certain insect pest region and the insect pest features corresponding to a certain insect pest type is successful, determining the insect pest type corresponding to the insect pest region as the insect pest type;
e3, extracting the shape and contour of the insect spot area corresponding to each insect pest plant to obtain the area of the insect spot corresponding to each insect pest plant.
5. The intelligent agricultural crop planting management method based on the remote data collection and analysis technology as claimed in claim 1, wherein: and S6, analyzing the total spraying amount corresponding to each pesticide in the farmland, wherein the specific analysis method comprises the following steps:
f1, overlapping the insect spot areas of the insect plants corresponding to the various types of the diseases in the farmland to obtain the total insect spot area of the insect plants corresponding to the various types of the diseases in the farmland;
f2, comparing the total insect spot area of the insect pest plants corresponding to the various insect disease types in the farmland with the pesticide spraying amount corresponding to the various insect spot areas of the pesticide types belonging to the insect disease types in the management database, and screening out the total spraying amount corresponding to various pesticides in the farmland.
6. The intelligent agricultural crop planting management method based on the remote data collection and analysis technology as claimed in claim 1, wherein: the preparation work before the pesticide is sprayed to the unmanned aerial vehicle is carried out according to the pesticide types corresponding to the various pest types and the spraying total amount corresponding to the various pesticides of the crops in the farmland in S8, the specific operation process of the preparation method is to prepare the pesticide types carried by the unmanned aerial vehicle according to the pesticide types corresponding to the various pest types of the crops in the farmland, and prepare the pesticide amount corresponding to the various pesticides carried by the unmanned aerial vehicle according to the spraying total amount corresponding to the various pesticides.
7. The intelligent agricultural crop planting management method based on the remote data collection and analysis technology as claimed in claim 1, wherein: in the step S8, the pesticide spraying amount of the pesticide spraying head is controlled according to the area of the insect spot corresponding to the successfully matched insect pest plant, and the specific control method comprises the following steps:
h1, comparing the spot area corresponding to the successfully matched insect pest plant with the pesticide spraying amount corresponding to each spot area of the pesticide type to which the insect pest type belongs in the successfully matched insect pest plant in the management database to obtain the pesticide spraying amount corresponding to the spot area of the successfully matched insect pest plant;
h2, arranging a flow meter in the pesticide spray head corresponding to the unmanned aerial vehicle, collecting the actual pesticide spray amount sprayed out from the pesticide spray head in real time, comparing the actual pesticide spray amount with the pesticide spray amount corresponding to the pest spot area of the successfully matched pest plant, continuing spraying if the actual pesticide spray amount is less than the pesticide spray amount corresponding to the pest spot area of the successfully matched pest plant, and controlling the pesticide spray head corresponding to the unmanned aerial vehicle to close and stop spraying if the actual pesticide spray amount is more than or equal to the pesticide spray amount corresponding to the pest spot area of the successfully matched pest plant.
8. The intelligent agricultural crop planting management method based on the remote data collection and analysis technology as claimed in claim 1, wherein: in S8, in the pesticide spraying process of successfully matched insect plants, the current spraying height of the unmanned aerial vehicle is regulated and controlled, and the specific regulation and control process is as follows:
k1, judging the parts of the crop plants corresponding to the spot areas of the successfully matched insect pest plants, and recording the parts of the crop plants in the spot areas as spot parts;
k2, acquiring the height of the insect pest plant matched successfully corresponding to the insect spot part;
k3, comparing the height of the spot part corresponding to the successfully matched insect pest plant with the suitable spraying height of the unmanned aerial vehicle corresponding to the height of each spot part in the management database to obtain the suitable spraying height of the unmanned aerial vehicle corresponding to the spot part of the successfully matched insect pest plant;
k4, obtain unmanned aerial vehicle and spray the height at present, and spray the height with the unmanned aerial vehicle that should match the insect spot position correspondence of successful insect pest plant and contrast, if unmanned aerial vehicle sprays the height at present and equals the suitable height that sprays of the unmanned aerial vehicle that should match the insect spot position correspondence of successful insect pest plant, then not regulate and control this unmanned aerial vehicle's the height that sprays, if unmanned aerial vehicle sprays the height at present and is less than the suitable height that sprays of the unmanned aerial vehicle that should match the insect spot position correspondence of successful insect pest plant, then spray the height and increase to unmanned aerial vehicle's current, if unmanned aerial vehicle sprays the height at present and is greater than the suitable height that sprays of the unmanned aerial vehicle that should match the insect spot position correspondence of successful insect pest plant, then spray the height to unmanned aerial vehicle at present and reduce.
9. The utility model provides an wisdom agricultural crop plants management system based on remote data acquisition analysis technique which characterized in that: including farmland subregion partition module, the long-range module of drawing of insect pest plant, insect pest plant insect pest parameter acquisition module, farmland pest type statistics module that gathers, the management database, the management cloud platform, insect pest plant geographical position orientation module and intelligent control terminal, wherein farmland subregion partition module is connected with insect pest plant long-range extraction module, insect pest plant long-range extraction module is connected with insect pest plant insect pest parameter acquisition module, insect pest plant insect pest parameter acquisition module gathers statistics module and management cloud platform with farmland pest type respectively and is connected, farmland pest type statistics module that gathers is connected with management cloud platform, management cloud platform and insect pest plant geographical position orientation module all are connected with intelligent control terminal.
10. A storage medium, characterized by: the storage medium is burned with a computer program, and the computer program realizes the method of any one of the above claims 1-8 when running in the memory of the server.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110614102.2A CN113344524A (en) | 2021-06-02 | 2021-06-02 | Intelligent agricultural crop planting management method and system based on remote data acquisition and analysis technology and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110614102.2A CN113344524A (en) | 2021-06-02 | 2021-06-02 | Intelligent agricultural crop planting management method and system based on remote data acquisition and analysis technology and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113344524A true CN113344524A (en) | 2021-09-03 |
Family
ID=77473062
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110614102.2A Withdrawn CN113344524A (en) | 2021-06-02 | 2021-06-02 | Intelligent agricultural crop planting management method and system based on remote data acquisition and analysis technology and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113344524A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113973793A (en) * | 2021-09-09 | 2022-01-28 | 常州希米智能科技有限公司 | Unmanned aerial vehicle spraying treatment method and system for pest and disease damage area |
| CN114332461A (en) * | 2021-12-29 | 2022-04-12 | 江苏业派生物科技有限公司 | Intelligent agricultural insect pest remote detection system and method |
| CN117078456A (en) * | 2023-10-13 | 2023-11-17 | 杨凌职业技术学院 | Agriculture and forestry plant diseases and insect pests monitoring management system |
| CN117389310A (en) * | 2023-12-07 | 2024-01-12 | 临沂大学 | Agricultural unmanned aerial vehicle sprays operation control system |
-
2021
- 2021-06-02 CN CN202110614102.2A patent/CN113344524A/en not_active Withdrawn
Cited By (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113973793A (en) * | 2021-09-09 | 2022-01-28 | 常州希米智能科技有限公司 | Unmanned aerial vehicle spraying treatment method and system for pest and disease damage area |
| CN113973793B (en) * | 2021-09-09 | 2023-08-04 | 常州希米智能科技有限公司 | Unmanned aerial vehicle spraying treatment method and system for pest and disease areas |
| CN114332461A (en) * | 2021-12-29 | 2022-04-12 | 江苏业派生物科技有限公司 | Intelligent agricultural insect pest remote detection system and method |
| CN114332461B (en) * | 2021-12-29 | 2023-03-24 | 江苏业派生物科技有限公司 | Intelligent agricultural insect pest remote detection system and method |
| CN117078456A (en) * | 2023-10-13 | 2023-11-17 | 杨凌职业技术学院 | Agriculture and forestry plant diseases and insect pests monitoring management system |
| CN117078456B (en) * | 2023-10-13 | 2023-12-15 | 杨凌职业技术学院 | Agriculture and forestry plant diseases and insect pests monitoring management system |
| CN117389310A (en) * | 2023-12-07 | 2024-01-12 | 临沂大学 | Agricultural unmanned aerial vehicle sprays operation control system |
| CN117389310B (en) * | 2023-12-07 | 2024-02-23 | 临沂大学 | Agricultural unmanned aerial vehicle sprays operation control system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113344524A (en) | Intelligent agricultural crop planting management method and system based on remote data acquisition and analysis technology and storage medium | |
| CN111596689B (en) | Intelligent agricultural plant protection operation control system based on big data Internet of things | |
| CN109197278B (en) | Method and device for determining operation strategy and method for determining drug spraying strategy | |
| Genovese et al. | A methodology for a combined use of normalised difference vegetation index and CORINE land cover data for crop yield monitoring and forecasting. A case study on Spain | |
| CN112197819A (en) | Plant growth accurate control method based on production base | |
| CN205819567U (en) | A kind of unmanned plane plant protection system | |
| CN104764533A (en) | Intelligent agricultural system based on unmanned aerial vehicle image collecting and thermal infrared imager | |
| CN116391690A (en) | Intelligent agricultural planting monitoring system based on big data of Internet of things | |
| CN114868504A (en) | Method and device for monitoring growth state of landscape plants | |
| CN111982097A (en) | Method and device for generating target route of unmanned operation equipment and plant protection system | |
| CN111985724B (en) | Crop yield estimation method, device, equipment and storage medium | |
| CN113325873A (en) | Unmanned aerial vehicle plant protection operation data acquisition and analysis method, system and computer storage medium | |
| CN108668606A (en) | A kind of municipal administration intelligence greening cutting machine | |
| CN114568265A (en) | Afforestation maintenance intelligent monitoring management system based on artificial intelligence | |
| CN104865935A (en) | Intelligent agricultural system based on unmanned-aerial-vehicle image collection | |
| CN111506097A (en) | Application system and method of unmanned aerial vehicle remote sensing technology in precision agriculture | |
| CN113469112A (en) | Crop growth condition image identification method and system | |
| CN117575835A (en) | Tea garden growth monitoring system and method based on unmanned aerial vehicle aerial photography | |
| CN113435345A (en) | Growth stage determination method and device, agricultural system, equipment and storage medium | |
| CN115424151A (en) | Agricultural intelligent platform based on image processing | |
| CN110326602A (en) | A kind of unmanned unmanned plane plant protection system based on Internet of Things | |
| CN109343533A (en) | A kind of robot system and its control method of golf course lawn maintenance | |
| CN113361377A (en) | Plant growth control model construction method, electronic device and storage medium | |
| CN114158537A (en) | Automatic pesticide spraying system and application method thereof | |
| CN113342036A (en) | Accurate management and control system and method for crops |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20210903 |
|
| WW01 | Invention patent application withdrawn after publication |