CN113379769A - Intelligent defense platform for crop diseases and insect pests - Google Patents
Intelligent defense platform for crop diseases and insect pests Download PDFInfo
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Abstract
The invention discloses an intelligent defense platform for crop diseases and insect pests, which comprises a user terminal, a central server and a field detection defense unit, wherein the user terminal is in signal connection with the central server through an internet module, the central server is in signal connection with the field detection defense unit through the internet module, the central server comprises an information transceiving unit, a prevention analysis unit, an application server, a pest image database, a pest big data analysis library and a mode identification unit, and the field detection defense unit comprises a terminal controller, a data acquisition module and a pest defense module. According to the invention, technologies such as the Internet, the Internet of things, image recognition, a spectrum technology and big data analysis are adopted, and a set of crop disease and insect pest intelligent defense platform is established by combining the crop disease and insect pest defense technology, so that large-information-amount disease and insect pest images and data can be established, deep mining analysis is carried out, and quick information push and disease and insect pest early warning are realized.
Description
Technical Field
The invention relates to the technical field of crop pest and disease defense, in particular to an intelligent defense platform for crop pests.
Background
With the continuous increase of population and the reduction of per capita cultivated land, the pressure of food production is getting bigger and bigger, statistics shows that the loss of food crops in the world caused by diseases, pests and weeds is up to more than 30 percent every year, therefore, scientific and effective measures are taken to reduce the diseases, pests and pests, and the method has important significance for the improvement of food yield and the survival and development of human beings. With the advancement of the urbanization process of China, the population of people engaged in agriculture is less and less, and the demand of agricultural production is greater and greater, so the requirement on the production efficiency of agriculture is raised. In recent years, the yield increasing speed of food in China is in a descending trend, wherein the pest and disease damage is one of the main reasons for reducing the yield capability of the food. Because most farmers do not know the occurrence and development rules of plant diseases and insect pests, and cannot grasp the key period of plant disease and insect pest control, the method not only causes medicament waste, environmental pollution and aggravation of economic burden, but also cannot achieve the expected control effect. Because crop diseases and insect pests are frequent, professional technicians are few in production, and the existing disease and insect pest chart data are limited, the real-time performance of disease and insect pest information acquisition is insufficient, the personnel requirements are very high, the diseases and insect pests of crops are often misdiagnosed, and the improvement of the crop yield is seriously influenced. There is a need to establish a rapid and accurate diagnostic defense system.
At present, the technology of the Internet of things is mature at home, especially, the intelligent home is in the world leading level, and a plurality of wonderful schemes are provided in the field of smart cities. At present, agricultural breeding and pest defense technologies become mature day by day, and internet of things technologies and image recognition technologies are developed at a high speed, but the integration of agricultural pest defense with internet technologies, internet of things technologies and image recognition technologies is still in the exploration starting stage, and the market potential is huge.
Disclosure of Invention
In order to overcome the defects in the prior art, the embodiment of the invention provides an intelligent defense platform for crop diseases and insect pests, and the invention aims to solve the technical problems that: how to utilize thing networking and image recognition technology to carry out intelligent defense to crops, improve the output of crops.
In order to achieve the purpose, the invention provides the following technical scheme: the utility model provides a crops plant diseases and insect pests intelligence defense platform, includes user terminal, central server and field detection defense unit, user terminal passes through internet module and central server signal connection, central server passes through internet module and field detection defense unit signal connection, central server includes information transceiver unit, prevention analysis unit, application server, sick worm picture database, sick worm big data analysis storehouse and mode identification unit, field detection defense unit includes terminal controller, data acquisition module and sick worm defense module.
In a preferred embodiment, the user terminal is a mobile phone, a tablet computer or a PC terminal, and the internet module is a wired network, WIFI, 3G/4G mobile network, bluetooth or RFID radio frequency identification communication technology.
In a preferred embodiment, the central server is in signal connection with the user terminal and a terminal controller in the field detection defense unit through an information transceiving unit, and the prevention analysis unit comprises an image preprocessing module, an image feature extraction module and a pattern recognition modeling module.
In a preferred embodiment, the image preprocessing module comprises image smoothing and image segmentation, the image smoothing is used for reducing and eliminating noise in the image, the data after the image smoothing is transmitted to the image segmentation, the image segmentation is used for extracting leaf spots, insect spots and pests in the image, the image feature extraction module is used for extracting and classifying texture, color, shape and edge contour features of the image, and the pattern recognition modeling module is used for constructing a classifier model by using image feature parameters.
In a preferred embodiment, the application server is used for displaying and controlling data of the central server and inputting and repairing information, the pest image database adopts a national professional crop pest database as information docking for judging pests on field crops, the pest big data analysis database is a Hadoop database, and the pattern recognition unit is used for calculating and analyzing a classifier model.
In a preferred embodiment, the data acquisition module comprises an intelligent camera, a spectrum measuring instrument and a soil sensor which are arranged in the field, the data acquisition module is in signal connection with the central server through a terminal controller, and the pest defense module comprises a drug spraying machine and an ultraviolet pest trapping and killing lamp which are arranged in the field.
In a preferred embodiment, the intelligent camera is used for monitoring crop scab images and crop pest images, the spectrum analyzer is used for monitoring crop spectral characteristics, crop growth, crop water and fertilizer condition diagnosis, crop yield estimation and crop quality detection, the soil sensor is used for monitoring moisture content, soil temperature and soil salt total content of crop soil, the drug spraying machine is used for automatic pesticide spraying and pest removal of crops, the ultraviolet pest trapping and killing lamp is used for trapping and killing pests, and the ultraviolet pest trapping and killing lamp adopts an ultraviolet pest trapping lamp with a wavelength of 330-.
In a preferred embodiment, the pattern recognition modeling module adopts a classifier model in the field of statistics and data mining when constructing the classifier model, the classifier model adopts open source statistical analysis software R to realize algorithm modeling, and the image segmentation method comprises threshold-based segmentation, edge-based segmentation and region-based segmentation.
In a preferred embodiment, the pest picture database comprises the entry of pest information in a national professional crop pest database and the entry of new species of pests collected by the data collection module by using the application server.
Compared with the prior art, the invention has the technical effects and advantages that:
according to the invention, technologies such as the Internet, the Internet of things, image recognition, a spectrum technology and big data analysis are adopted, a set of crop disease and pest intelligent defense platform is established by combining crop disease and pest defense technologies, and the crop disease and pest images can be transmitted to the platform in real time through the application of the Internet and the Internet of things; through an image identification technology, the collected image is identified, and the plant diseases and insect pests of crops can be diagnosed quickly and accurately, so that measures can be taken at the first time to prevent and treat the plant diseases and insect pests of the crops; meanwhile, a spectrum tester is used for analyzing the spectral characteristics of the crops for plant diseases and insect pests, so that double insurance of monitoring is achieved; by the big data technology, pest and disease images and data with large information amount can be established, deep mining analysis is carried out, and quick information push and pest and disease early warning are realized; and the expert consultation function is provided, and a grower can submit the problems of crop diseases and insect pests to the experts in real time or quasi-real time on line and ask the corresponding experts to answer.
Drawings
FIG. 1 is a schematic diagram of the system of the present invention.
Fig. 2 is a schematic structural diagram of the central server of the present invention.
FIG. 3 is a schematic diagram of the operation of the image prevention analysis unit according to the present invention.
FIG. 4 is a schematic diagram of an image recognition process according to the present invention.
FIG. 5 is a diagram illustrating an example of image smoothing processing according to the present invention.
FIG. 6 is a diagram illustrating an example of image segmentation processing according to the present invention.
The reference signs are: 1, a user terminal; 2, a central server; 3, detecting and defending units in the field; 4, an internet module; 5 an information transmitting and receiving unit; 6 a preventive analysis unit; 7 an application server; 8 database of pictures of diseases and pests; 9, a disease and insect big data analysis library; 10 a pattern recognition unit; 11 a terminal controller; 12 a data acquisition module; 13 a pest defense module; 14 an image preprocessing module; 15 an image feature extraction module; 16 a pattern recognition modeling module; 17 an intelligent camera; 18 a spectrometer; 19 a soil sensor; 20 a drug spraying machine; 21 ultraviolet pest trapping lamp.
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.
As shown in fig. 1-6, a crops plant diseases and insect pests intelligence defense platform, includes user terminal 1, central server 2 and field detection defense unit 3, user terminal 1 passes through internet module 4 and central server 2 signal connection, central server 2 passes through internet module 4 and field detection defense unit 3 signal connection, central server 2 includes information transceiver unit 5, prevention analysis unit 6, application server 7, sick worm picture database 8, sick worm big data analysis storehouse 9 and mode identification unit 10, field detection defense unit 3 includes terminal controller 11, data acquisition module 12 and sick worm defense module 13.
In a preferred embodiment, the user terminal 1 is a mobile phone, a tablet computer or a PC terminal, the internet module 4 is a wired network, WIFI, 3G/4G mobile network, bluetooth or RFID radio frequency identification communication technology, and in the present application, the 4G mobile network and the RFID radio frequency identification communication technology are preferably used, and the RFID radio frequency identification communication technology can identify a specific target through a radio signal and read and write related data without establishing mechanical or optical contact between an identification system and the specific target.
In a preferred embodiment, the central server 2 is in signal connection with the user terminal 1 and the terminal controller 11 in the field detection defense unit 3 through the information transceiver unit 5, and the prevention analysis unit 6 comprises an image preprocessing module 14, an image feature extraction module 15 and a pattern recognition modeling module 16.
In a preferred embodiment, the image preprocessing module 14 includes image smoothing and image segmentation, the image smoothing is used for reducing and eliminating noise in the image, the data after the image smoothing is transmitted to the image segmentation, the image segmentation is used for extracting leaf spots, insect spots and pests in the image, the image feature extraction module 15 is used for extracting and classifying texture, color, shape and edge contour features of the image, and the pattern recognition modeling module 16 is used for constructing a classifier model by using image feature parameters.
In a preferred embodiment, the application server 7 is used for displaying and controlling data of the central server 2 and inputting and repairing information, the pest image database 8 adopts a national professional crop pest database as information docking for judging pests on field crops, the pest big data analysis database 9 is a Hadoop database, the pattern recognition unit 10 is used for calculating and analyzing a classifier model, and the Hadoop database is a highly extensible storage platform because it can store and distribute hundreds of cheap server data clusters which are operated in parallel.
In a preferred embodiment, the data acquisition module 12 comprises an intelligent camera 17, a spectrum measuring instrument 18 and a soil sensor 19 which are arranged in the field, the data acquisition module 12 is in signal connection with the central server 2 through the terminal controller 11, and the pest defense module 13 comprises a drug spraying machine 20 and an ultraviolet pest trapping and killing lamp 21 which are arranged in the field.
In a preferred embodiment, the intelligent camera 17 is used for monitoring crop scab images and crop pest images, the spectrum analyzer 18 is used for monitoring crop spectral characteristics, crop growth, crop water and fertilizer condition diagnosis, crop yield estimation and crop quality detection, the soil sensor 19 is used for monitoring crop soil moisture content, soil temperature and humidity and total soil salt content, the drug spraying machine 20 is used for automatic pesticide spraying and pest removal of crops, the ultraviolet pest trapping and killing lamp 21 is used for trapping and killing pests, the ultraviolet pest trapping and killing lamp 21 adopts an ultraviolet pest trapping lamp with a wavelength of 330 and 400 nanometers, crops are irregular natural ash bodies, solar radiation generates specific spectra through reflection, penetration, absorption and the like, and the spectral characteristics are the comprehensive result of interaction between the crop growth process and environmental factors, the crop growth condition and health condition are closely related to biophysical and morphological characteristics, certain stress factors may cause changes of spectral characteristics, and by utilizing the principle, spectral characteristics of crops can be analyzed and distinguished, the growth vigor of the crops can be monitored, the water and fertilizer conditions can be diagnosed, the yield can be estimated, the quality can be detected and the like.
In a preferred embodiment, the pattern recognition modeling module 16 constructs a classifier model using a classifier model in the field of statistics and data mining, the classifier model is modeled using an open source statistical analysis software R, and the image segmentation method includes a threshold-based segmentation, an edge-based segmentation and a region-based segmentation.
In a preferred embodiment, the pest picture database 8 includes the entry of pest information in a national professional crop pest database and the entry of new species of pests collected by the data collection module 12 by using the application server 7.
The implementation mode is specifically as follows:
a preparation stage: (1) firstly, acquiring picture information by using a mobile phone APP, uploading the acquired information to a central server 2, carrying out information butt joint on a pest picture database in the central server 2 and a national professional crop disease and pest database to acquire basic data and perfect a central database;
(2) an intelligent camera 17, a spectrum determinator 18, a soil sensor 19, a drug spraying machine 20 and an ultraviolet pest trapping lamp 21 are deployed in the field, a 4G mobile network card (special for the Internet of things) provided by a China telecom operator is used as equipment, the equipment transmits image data and a determination result into the central server 2 at regular time, and related image information can be displayed on the user terminal 1;
the use stage is as follows: the method comprises the steps of monitoring the growth condition of crops in real time by using an intelligent camera 17, a spectrum measuring instrument 18 and a soil sensor 19 which are deployed in the field, collecting disease spot images and pest images of the crops by using the intelligent camera 17, detecting specific spectrums generated on the crops by solar radiation through reflection, penetration, absorption and the like by using the spectrum measuring instrument 18, collecting information such as moisture, temperature and humidity, soil salinity and the like in the soil of the crops by using the soil sensor 19, transmitting the collected data to an information transceiving unit 5 in a central server 2 through a terminal controller 11 by using the spectrum measuring instrument 18 and the soil sensor 19, checking the spectral characteristics of the crops, such as the growth vigor, the water and fertilizer condition, the estimated yield, the detected quality and the soil condition of the crops by using an agricultural user through a user terminal 1, directly sending doubts to the central server 2 by using the user terminal 1 according to the data checked by the user terminal 1, the agricultural experts solve the problems proposed by the users through the central server 2, and interactive question answering between the users and the agricultural experts is realized; the image collected by the intelligent camera 17 is transmitted to the information transceiver unit 5 in the central server 2 through the terminal controller 11, the information transceiver unit 5 transmits the image information to the prevention analysis unit 6, the image preprocessing module 14 in the prevention analysis unit 6 performs smoothing and segmentation processing on the collected image, the smoothing of the image can reduce and eliminate noise in the image, improve the image quality and facilitate the extraction and analysis of image characteristics, the image segmentation is to extract leaf scabs, insect spots and pests in the image, the image characteristics extraction module 15 is used for extracting and classifying the texture, color, shape and edge contour of the image after the image segmentation is completed, then the pattern recognition modeling module 16 is used for modeling the processed image by open source statistical analysis software R, the pattern recognition unit 10 is used for finding out specific recognition models and parameters of different types of crop pests according to the built model analysis, agricultural user can utilize user terminal 1 to look over the pest condition of crops, when needing to clear up the pest, the user can utilize user terminal 1 to send the insecticidal instruction, and the instruction that user terminal 1 sent transmits for terminal controller 11 through central server 2, and terminal controller 11 control medicine sprinkler 20 and ultraviolet ray pest trap lamp 21 are opened, utilize medicine sprinkler 20 and ultraviolet ray pest trap lamp 21 to handle the pest on the crops.
The points to be finally explained are: first, in the description of the present application, it should be noted that, unless otherwise specified and limited, the terms "mounted," "connected," and "connected" should be understood broadly, and may be a mechanical connection or an electrical connection, or a communication between two elements, and may be a direct connection, and "upper," "lower," "left," and "right" are only used to indicate a relative positional relationship, and when the absolute position of the object to be described is changed, the relative positional relationship may be changed;
secondly, the method comprises the following steps: in the drawings of the disclosed embodiments of the invention, only the structures related to the disclosed embodiments are referred to, other structures can refer to common designs, and the same embodiment and different embodiments of the invention can be combined with each other without conflict;
and finally: the above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that are within the spirit and principle of the present invention are intended to be included in the scope of the present invention.
Claims (9)
1. The utility model provides a crops plant diseases and insect pests intelligence defense platform which characterized in that: including user terminal (1), central server (2) and field detection defense unit (3), user terminal (1) is through internet module (4) and central server (2) signal connection, central server (2) are through internet module (4) and field detection defense unit (3) signal connection, central server (2) are including information transceiver unit (5), prevention analysis unit (6), application server (7), sick worm picture database (8), big data analysis storehouse of sick worm (9) and mode identification unit (10), field detection defense unit (3) are including terminal controller (11), data acquisition module (12) and sick worm defense module (13).
2. The intelligent defense platform for crop diseases and insect pests according to claim 1, characterized in that: the user terminal (1) is a mobile phone, a tablet personal computer or a PC terminal, and the internet module (4) is a wired network, WIFI, 3G/4G mobile network, Bluetooth or RFID radio frequency identification communication technology.
3. The intelligent defense platform for crop diseases and insect pests according to claim 1, characterized in that: the central server (2) is in signal connection with a user terminal (1) and a terminal controller (11) in the field detection defense unit (3) through an information transceiving unit (5), and the prevention analysis unit (6) comprises an image preprocessing module (14), an image feature extraction module (15) and a mode identification modeling module (16).
4. The intelligent defense platform for crop diseases and insect pests according to claim 3, characterized in that: the image preprocessing module (14) comprises image smoothing and image segmentation, the image smoothing is used for reducing and eliminating noise in an image, data after the image smoothing is transmitted to the image segmentation, the image segmentation is used for extracting leaf scabs, insect plaques and pests in the image, the image feature extraction module (15) is used for extracting and classifying image texture, color, shape and edge contour features, and the pattern recognition modeling module (16) is used for constructing a classifier model for image feature parameters.
5. The intelligent defense platform for crop diseases and insect pests as claimed in claim 4, wherein: the application server (7) is used for displaying and controlling data of the central server (2) and inputting and repairing information, the pest picture database (8) adopts a national professional crop pest database as information butt joint and is used for judging pests on field crops, the pest big data analysis database (9) is a Hadoop database, and the pattern recognition unit (10) is used for calculating and analyzing a classifier model.
6. The intelligent defense platform for crop diseases and insect pests according to claim 1, characterized in that: data acquisition module (12) is including setting up in intelligent camera (17), spectral measurement appearance (18) and soil sensor (19) in the field, data acquisition module (12) are through terminal control ware (11) and central server (2) signal connection, sick worm defense module (13) are including setting up in medicine spraying machine (20) and ultraviolet ray pest trap lamp (21) in the field.
7. The intelligent defense platform for crop diseases and insect pests according to claim 6, characterized in that: the intelligent camera (17) is used for monitoring crop scab images and crop pest images, the spectrum determinator (18) is used for monitoring crop spectral characteristics, crop growth, crop water and fertilizer condition diagnosis, crop yield estimation and crop quality detection, the soil sensor (19) is used for monitoring moisture content, soil temperature and humidity and total soil salt content of crop soil, the drug spraying machine (20) is used for automatically spraying pesticide on crops to remove pests, the ultraviolet pest trapping and killing lamp (21) is used for trapping and killing the pests, and the ultraviolet pest trapping and killing lamp (21) adopts an ultraviolet pest trapping lamp with the wavelength of 330 and 400 nanometers.
8. The intelligent defense platform for crop diseases and insect pests as claimed in claim 4, wherein: the pattern recognition modeling module (16) adopts a classifier model in the fields of statistics and data mining when constructing the classifier model, the classifier model adopts open source statistical analysis software R to realize algorithm modeling, and the image segmentation method comprises threshold-based segmentation, edge-based segmentation and region-based segmentation.
9. The intelligent defense platform for crop diseases and insect pests according to claim 5, characterized in that: the pest picture database (8) comprises the input of pest information in a national professional crop pest database by using an application server (7) and the input of new species of pests acquired by a data acquisition module (12).
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| CN113925039A (en) * | 2021-10-12 | 2022-01-14 | 一鼎(福建)生态园林建设有限公司 | Internet of things-based garden pest and disease intelligent protection system and prevention and control method |
| CN114419429A (en) * | 2021-12-08 | 2022-04-29 | 慧之安信息技术股份有限公司 | Intelligent recommendation method based on crop leaf pathology |
| CN114460080A (en) * | 2022-02-09 | 2022-05-10 | 安徽大学 | Rice disease and pest intelligent monitoring system |
| CN114511476A (en) * | 2021-12-21 | 2022-05-17 | 中科环森智慧科技(苏州)有限公司 | Intelligent analysis application system for image data |
| CN114550848A (en) * | 2022-02-21 | 2022-05-27 | 北京京东尚科信息技术有限公司 | Crop disease treatment method and device, electronic equipment and computer readable medium |
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2021
- 2021-06-30 CN CN202110739646.1A patent/CN113379769A/en not_active Withdrawn
Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113925039A (en) * | 2021-10-12 | 2022-01-14 | 一鼎(福建)生态园林建设有限公司 | Internet of things-based garden pest and disease intelligent protection system and prevention and control method |
| CN113925039B (en) * | 2021-10-12 | 2022-10-11 | 一鼎(福建)生态园林建设有限公司 | Internet of things-based garden pest and disease intelligent protection system and prevention and control method |
| CN113900451A (en) * | 2021-11-17 | 2022-01-07 | 湖南精飞智能科技有限公司 | Unmanned aerial vehicle digital agriculture application system based on 5G Beidou technology |
| CN114419429A (en) * | 2021-12-08 | 2022-04-29 | 慧之安信息技术股份有限公司 | Intelligent recommendation method based on crop leaf pathology |
| CN114511476A (en) * | 2021-12-21 | 2022-05-17 | 中科环森智慧科技(苏州)有限公司 | Intelligent analysis application system for image data |
| CN114460080A (en) * | 2022-02-09 | 2022-05-10 | 安徽大学 | Rice disease and pest intelligent monitoring system |
| CN114550848A (en) * | 2022-02-21 | 2022-05-27 | 北京京东尚科信息技术有限公司 | Crop disease treatment method and device, electronic equipment and computer readable medium |
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