CN115719284A - Intelligent pest prevention and control method - Google Patents
Intelligent pest prevention and control method Download PDFInfo
- Publication number
- CN115719284A CN115719284A CN202110969553.8A CN202110969553A CN115719284A CN 115719284 A CN115719284 A CN 115719284A CN 202110969553 A CN202110969553 A CN 202110969553A CN 115719284 A CN115719284 A CN 115719284A
- Authority
- CN
- China
- Prior art keywords
- data
- model
- intelligent
- cloud platform
- control method
- 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.)
- Pending
Links
- 241000607479 Yersinia pestis Species 0.000 title claims abstract description 39
- 230000002265 prevention Effects 0.000 title claims abstract description 28
- 238000000034 method Methods 0.000 title claims abstract description 23
- 238000012544 monitoring process Methods 0.000 claims abstract description 59
- 238000012545 processing Methods 0.000 claims abstract description 25
- 238000004458 analytical method Methods 0.000 claims abstract description 17
- 238000005516 engineering process Methods 0.000 claims abstract description 14
- 230000005540 biological transmission Effects 0.000 claims abstract description 13
- 230000010485 coping Effects 0.000 claims abstract description 13
- 238000013528 artificial neural network Methods 0.000 claims abstract description 9
- 238000007405 data analysis Methods 0.000 claims abstract description 7
- 238000013499 data model Methods 0.000 claims abstract description 7
- 241000238631 Hexapoda Species 0.000 claims description 23
- 230000033228 biological regulation Effects 0.000 claims description 12
- 201000010099 disease Diseases 0.000 claims description 11
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 11
- 230000000694 effects Effects 0.000 claims description 10
- 230000008859 change Effects 0.000 claims description 7
- 238000004891 communication Methods 0.000 claims description 7
- 238000004364 calculation method Methods 0.000 claims description 5
- 238000007418 data mining Methods 0.000 claims description 5
- 238000012423 maintenance Methods 0.000 claims description 5
- 238000013079 data visualisation Methods 0.000 claims description 4
- 230000006870 function Effects 0.000 claims description 4
- 238000007689 inspection Methods 0.000 claims description 4
- 230000009545 invasion Effects 0.000 claims description 4
- 238000004088 simulation Methods 0.000 claims description 4
- 241000894007 species Species 0.000 claims description 4
- 238000013473 artificial intelligence Methods 0.000 claims description 3
- 238000003745 diagnosis Methods 0.000 claims description 3
- 238000007726 management method Methods 0.000 claims description 3
- 238000013486 operation strategy Methods 0.000 claims description 3
- 239000013307 optical fiber Substances 0.000 claims description 3
- 238000012800 visualization Methods 0.000 claims description 3
- 230000002452 interceptive effect Effects 0.000 claims 1
- 230000008569 process Effects 0.000 description 5
- 239000002689 soil Substances 0.000 description 5
- 230000009286 beneficial effect Effects 0.000 description 4
- 238000004422 calculation algorithm Methods 0.000 description 4
- 230000007613 environmental effect Effects 0.000 description 4
- 238000005286 illumination Methods 0.000 description 4
- 238000003860 storage Methods 0.000 description 4
- 238000011282 treatment Methods 0.000 description 4
- 238000012271 agricultural production Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 230000012010 growth Effects 0.000 description 3
- 238000012937 correction Methods 0.000 description 2
- 239000003344 environmental pollutant Substances 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 230000006855 networking Effects 0.000 description 2
- 231100000719 pollutant Toxicity 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- 241000243771 Bursaphelenchus xylophilus Species 0.000 description 1
- 241000196324 Embryophyta Species 0.000 description 1
- 241000233866 Fungi Species 0.000 description 1
- 241001465754 Metazoa Species 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 238000009395 breeding Methods 0.000 description 1
- 230000001488 breeding effect Effects 0.000 description 1
- 238000004140 cleaning Methods 0.000 description 1
- 238000007621 cluster analysis Methods 0.000 description 1
- 238000010835 comparative analysis Methods 0.000 description 1
- 238000013527 convolutional neural network Methods 0.000 description 1
- 238000013500 data storage Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001514 detection method Methods 0.000 description 1
- 230000006866 deterioration Effects 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 229940079593 drug Drugs 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 238000003912 environmental pollution Methods 0.000 description 1
- 238000000605 extraction Methods 0.000 description 1
- 230000000749 insecticidal effect Effects 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000003973 irrigation Methods 0.000 description 1
- 230000002262 irrigation Effects 0.000 description 1
- 230000004807 localization Effects 0.000 description 1
- 230000000813 microbial effect Effects 0.000 description 1
- 230000035764 nutrition Effects 0.000 description 1
- 235000016709 nutrition Nutrition 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000004321 preservation Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000033764 rhythmic process Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 239000007921 spray Substances 0.000 description 1
- 238000007619 statistical method Methods 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 230000007306 turnover Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses a pest intelligent prevention and control method which comprises a product central monitoring station, a cloud platform and an information ecological chain, wherein the central monitoring station comprises a data acquisition layer and a data transmission layer, the cloud platform comprises a display layer, a business application layer, a data analysis layer, a data model, a data lake and a technical assembly, and the information ecological chain comprises an intelligent coping strategy, an intelligent operation mode, intelligent prevention and control equipment and a basic monitoring point. The pest intelligent prevention and control method takes a central monitoring station as a core, N monitoring sites are attached, collected information is transmitted to a cloud platform through 5G signals, picture recognition, counting analysis and corresponding coping combination strategies are generated through a neural network and transmitted to each Internet of things device for coping processing, processing results are fed back to the cloud platform in real time for secondary decision making, closed loop of information is achieved, manual intervention is completely separated, and more scientific, reasonable and comprehensive intelligence of green control technology is promoted.
Description
Technical Field
The invention relates to the technical field of pest prevention and control, in particular to an intelligent pest prevention and control method.
Background
Harmful organisms are organisms which are harmful to human life, production and agricultural planting under certain conditions, most of the organisms are organisms which are seriously damaged by a large number of animals in captivity, cultivated crops, flowers and seedlings, at present, harmful organisms such as insect pests, rat pests and the like are still serious threats in the processes of planting, breeding, processing, storing and transporting in the global scope, more troubles are brought to the agricultural production of people, china is a country with a large population and rare cultivated land per capita, the cultivated land area available for people is further reduced along with the gradual deterioration of the natural ecological environment and the gradual acceleration of the urbanization process, and the traditional agricultural production has many problems.
The existing pest intelligent prevention and control method has certain defects, the preliminary application of the Internet of things requires too much manual participation and has low intelligent degree, the pest control system based on the Internet of things needs manual intervention, the cost of attached facility equipment is high, the problem that the nutrition supplement of agricultural crop growth can be solved only, and the pest can not be radically controlled is concretely reflected in that after the front end of the pest control system collects data, the scheme formed by the system automatically only adjusts illumination, moisture and the like to be automatically operated, the rest of the pest control system needs manual operation, the illumination and moisture are automatically adjusted, facilities such as a diversion canal, pressure irrigation equipment, a shading greenhouse and the like need to be built, the high facility cost and the electricity consumption cost determine that the measure can not be popularized and applied in a large range.
Disclosure of Invention
The invention aims to provide an intelligent pest prevention and control method to solve the problems in the background technology.
In order to achieve the purpose, the invention provides the following technical scheme:
a pest intelligent prevention and control method comprises a product center monitoring station, a cloud platform and an information ecological chain, wherein the center monitoring station comprises a data acquisition layer and a data transmission layer, the cloud platform comprises a display layer, a service application layer, a data analysis layer, a data model, a data lake and a technical assembly, and the information ecological chain comprises an intelligent coping strategy, an intelligent operation mode, intelligent prevention and control equipment and a basic monitoring point.
Furthermore, the central monitoring station can cover integrated information acquisition equipment with various types and various factors, acquired information is remotely transmitted to the cloud platform through the central control system, a user utilizes the remote login cloud platform to check data of the central monitoring station in real time, and relevant equipment monitoring parameters are changed through cloud operation.
Further, the cloud platform adopts latest processing technologies such as big data, a neural network, artificial intelligence and 5G, so that the functions of data on-line management, on-line visualization, on-line calculation, on-line diagnosis and the like are realized from the acquisition to the accurate identification, model processing, strategy generation, feedback information tracking, secondary analysis, data mining and the like, and a big data visualization interaction system is formed.
Further, the data transmission layer comprises 5G communication, an Internet of things communication card, broadband transmission and video optical fiber transmission, the data lake comprises a data relation and a data mart, big data are processed, the data relation and the data mart are built into a data lake form by adopting a Hadoop technology, the relevance of the data is enhanced, and the using effect of the data is improved.
Further, the data analysis layer comprises image processing, image recognition, data modeling, data inspection and data tracing, and the data model comprises a data driving model, an environment simulation model, a dynamic regulation and control model, an operation strategy model, an emergency plan model, a biological diversity regulation and control model, a prediction model, an early warning model, a decision model, a regional strategy model and a combined strategy model.
Further, the display layer comprises trend analysis and prediction of insect conditions, disease conditions and mouse conditions, comparison analysis of year-round comparison data and year-round comparison data, and early warning prompt of differential data; filing insect conditions, illness conditions and disasters; tracking a decision disposal scheme, evaluating a processing result and the like, wherein the application places of the business application layer comprise forestry, agriculture and operation and maintenance.
Furthermore, the intelligent coping strategy comprises disaster outbreak and foreign species invasion, the intelligent operation mode comprises environment change regulation and control, biological diversity maintenance, theft loss and faults, and the intelligent prevention and control equipment comprises monitoring and prevention and control.
Compared with the prior art, the invention has the beneficial effects that: the pest intelligent prevention and control method takes a central monitoring station as a core, N monitoring sites are attached, acquired information is transmitted to a cloud platform through 5G signals, picture recognition is carried out through a neural network, counting analysis is carried out, corresponding coping combination strategies are generated through an artificial intelligent model and then transmitted to each Internet of things device for coping processing, meanwhile, each Internet of things device feeds processing results back to the cloud platform in real time for secondary decision making, closed loop of information is achieved, manual intervention is completely separated, and more scientific and reasonable comprehensive intelligence of a green control technology is promoted.
Drawings
FIG. 1 is a schematic diagram of the system configuration of a central monitoring station according to the present invention;
FIG. 2 is a cloud platform system flow composition diagram of the present invention;
FIG. 3 is a schematic diagram of the information ecological chain system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "upper", "lower", "inner", "outer", "front", "rear", "both ends", "one end", "the other end", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless explicitly stated or limited otherwise, the terms "mounted," "disposed," "connected," and the like are to be construed broadly, such as "connected," which may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Example 1
Referring to fig. 1, an embodiment of the present invention: the central monitoring station comprises a data acquisition layer and a data transmission layer, the cloud platform comprises a display layer, a business application layer, a data analysis layer, a data model, a data lake and a technical assembly, the information ecological chain comprises an intelligent coping strategy, an intelligent operation mode, intelligent prevention and control equipment and a basic monitoring point, acquired information is transmitted to the cloud platform through a 5G signal, a neural network is used for picture identification and counting analysis, a corresponding coping combination strategy is generated through an artificial intelligent model and then transmitted to each Internet of things equipment for coping processing, each Internet of things equipment can feed processing results back to the cloud platform in real time for secondary decision making, closed loop of information is achieved, manual intervention is completely separated, and the comprehensive intelligence of green control technology is promoted to be more scientific and reasonable.
Furthermore, the central monitoring station can cover integrated information acquisition equipment with various types and various factors, the acquired information is remotely transmitted to the cloud platform through the central control system, a user utilizes the remote login cloud platform to check the data of the central monitoring station in real time, related equipment monitoring parameters are changed by operating at the cloud end, the central monitoring station comprises data acquisition and monitoring functions and biological monitoring and environmental monitoring, the biological monitoring comprises an intelligent pest situation monitoring lamp, a target pest automatic monitoring and reporting system, a pulse cloud spore automatic monitoring and reporting system and a mouse situation automatic monitoring system, the intelligent pest situation monitoring and reporting lamp can be used for monitoring the adult in a general way, acquiring remote images and automatically identifying and marking, the insect pest is accurately monitored by the target insect pest automatic monitoring and reporting system, the activity rhythm of the target insect pest is counted by using an infrared sensing mode aiming at single key insect pests, disease universality monitoring is carried out through a pulse cloud spore automatic detection and reporting system, remote image acquisition is carried out, automatic identification and marking are carried out to grasp the change of the number of target spores, disease early warning is realized, the automatic monitoring system for the mouse condition utilizes infrared and industrial camera technology to monitor the activity rule of the mouse damage in real time, the environment monitoring system comprises a microclimate information acquisition system, a soil moisture content and an ecological real-time monitoring system, the data change of meteorological factors such as air temperature and humidity, wind speed and direction, rainfall and the like is monitored by a microclimate information acquisition system, the service and pest and disease damage forecast and the agricultural production are carried out, the multilayer soil humidity is monitored through the soil moisture content, the occurrence of plant diseases and insect pests and the optimal required soil humidity are related according to the difference of the root depths of crops in different growth periods, and the ecological real-time monitoring system is used for remotely monitoring and predicting the disease and insect pest occurrence condition and the crop growth condition of the point.
Furthermore, the cloud platform adopts the latest processing technologies such as big data, a neural network, artificial intelligence and 5G, so that the functions of online management, online visualization, online calculation, online diagnosis and the like of data are realized from the acquisition to the accurate identification, model processing, strategy generation, feedback information tracking, secondary analysis, data mining and the like, a big data visualization interaction system is formed, a uniform cloud platform system can be built, multi-channel information acquisition is realized, and a big data warehouse is built.
Further, the data transmission layer comprises 5G communication, an Internet of things communication card, broadband transmission and video optical fiber transmission, the data lake comprises a data relation and a data mart, big data are processed, the data relation and the data mart are established into a data lake form by adopting a Hadoop technology, the relevance of the data is enhanced, the use effect of the data is improved, edge calculation and data screening are carried out on the equipment end through original data, the effective data are finally transmitted to the server database for gathering and analyzing, and data storage is finally carried out through a server distributed file system in the modes of graphs, data tables, characters, audios and videos and the like.
Further, the data analysis layer comprises image processing, image recognition, data modeling, data inspection and data tracing, the data model comprises a data driving model, an environment simulation model, a dynamic regulation and control model, an operation strategy model, an emergency plan model, a biodiversity regulation and control model, a prediction model, an early warning model, a decision model, a regional strategy model and a combined strategy model, the image processing is an image obtained by sampling and digitalizing devices such as a digital video camera, a scanner, a digital camera and the like, the image is analyzed by a computer to achieve a required result, the image recognition adopts a convolution neural network technology, namely, on the basis of neural network image recognition, the characteristic comparison processing is added, a target object is segmented by adopting a target monitoring algorithm, namely foreground extraction, and the segmented images are recognized and classified by adopting a deep neural network, obtaining the category of a target object, so that image recognition is more accurate, data modeling is used for defining and analyzing a process of supporting data requirements needed by a business process within the range of an organized information system, a data set + a business target + an algorithm + optimization iteration = data modeling, each part is indispensable, data inspection is a verification operation for ensuring the integrity of data, a designated algorithm is used for calculating a check value of original data, a receiver calculates the check value once by using the same algorithm, if the check values obtained by two times of calculation are the same, the data is complete, data tracing service data is transmitted to other systems according to integration requirements after being generated in a production library, the data needs to span a plurality of systems from generation to final use, undergo a plurality of processing treatments and pass through data tracing, the user can accurately know each link of data processing, and the correct use of the data is ensured.
Further, the show layer includes visual PC end, large-size screen show, remove end APP, can be to the pest situation, the state of an illness, trend analysis of mouse situation, the prediction, compare with the ring of the past year, the comparative analysis of data with comparing, to the early warning suggestion of differentiation data, to the pest situation, the state of an illness, the archives of calamity, the tracking of decision-making treatment scheme, the processing result aassessment etc. business application layer application place includes wisdom forest control, wisdom agriculture, thing networking fortune dimension, wisdom forest control carries out target pest survey and report, harmful organism information, pine wood nematode monitoring early warning, wisdom agriculture carries out mouse situation monitoring, the pest situation monitoring, seedling condition monitoring, soil moisture monitoring, the disaster condition monitoring, thing networking fortune dimension is various equipment, including the pest situation lamp, lure accuse equipment etc.
Further, the intelligent coping strategy comprises disaster outbreak and foreign species invasion, the intelligent operation mode comprises environmental change regulation and control, biological diversity maintenance, theft and failure, the intelligent prevention and control equipment comprises monitoring and control, the disaster outbreak comprises biological prevention and control, physical prevention and control and chemical prevention and control, the biological prevention and control adopts measures of throwing natural enemies, the physical prevention and control adopts facilities such as insecticidal lamps and traps, the chemical prevention and control adopts an unmanned aerial vehicle to automatically mix medicines, the crawler-type robot sprays and places baits, the foreign species invasion adopts equipment such as video and sound control to collect biological information, biological characteristic analysis is carried out by analyzing activity time and activity environment, sample preservation is carried out by biological capture, hazard early warning is carried out by utilizing a PC end, an aPP end and short messages, the environmental change regulation and control adopts monitoring illumination, normal day night illumination changes the scene, when monitoring light is the evening, open automatically, monitoring self-closing when dawn, through monitoring battery power, continuous plum rainy day is sunless, when battery power content is low, automatically, reduce the opening frequency/time length of high power consumption equipment, frequency is changed and adjustment insect catching dish turnover frequency to adjustment microbial disease fungus spore splicing, it passes through intelligent monitoring pest to maintain biodiversity, the relationship of beneficial insect activity period quantity, when beneficial insect catches the volume and reaches certain proportion, self-closing equipment, the beneficial insect is protected, stolen and trouble includes the alarm of whistling, monitoring camera catches, GPS localization tracking, carry out equipment restart according to trouble information, fault alarm, long-range sending information passes through the SMS, cell-phone APP, PC end, the mail, instant messaging software etc., establish journey fortune dimension information communication.
Example 2
The data processing mode carries out pretreatment on received data by the edge terminal equipment, completes operations such as distinguishing, analyzing, extracting and cleaning, and sends the data to the cloud service platform after the data is converted into trustable data, the flat service platform processor carries out data pretreatment on the data extracted and integrated from the data source, data mining, statistical analysis and other technologies, and due to the characteristics of large analysis data volume of big data, complex query and analysis and the like, the analysis data mainly aims at the whole data population to be analyzed, a multi-mode mixed architecture is adopted, and the key technology of data processing comprises the following steps: distributed server file systems, artificial intelligence-data mining, cluster analysis, association rule analysis, convolutional neural networks, non-relational databases, data visualization techniques, and the like.
After the data-driven model obtains a set of data, if a certain effect is desired and some operation is performed on the data, the model is allowed to fit the data, so that the model is changed to achieve the effect.
The environment simulation model applies a system analysis principle, establishes a theoretical or solid model of the environment system, observes the response of the model by changing specific parameters under the condition of artificial control, and predicts the behavior and characteristics of the actual system.
In the process of urban atmospheric environmental pollution treatment, the dynamic regulation model needs to take treatment measures on the pollutant emission source to realize standard emission, and needs to control the total pollutant emission amount in an atmospheric environmental system within the bearing capacity range of natural environment, and establishes a pollution source allowable emission dynamic regulation model according to the change of meteorological conditions.
When the prediction model adopts a quantitative prediction method to predict, the quantity relation among objects described by a mathematical language or a formula reveals the internal regularity among the objects to a certain extent, and the quantity relation is used as a direct basis for calculating a predicted value during prediction.
The data relationship comprises an association factor library, a difference information library, a scene library, an ecological environment factor library, a biological characteristic library and a binding relationship, wherein the association factor library is used for storing id of factors which are associated with each other, establishing the binding relationship, and associating through foreign keys of different tables, the difference information library is used for storing data types, formats and storage logic, the scene library is used for storing data types, formats and storage logic, the ecological environment factor library is used for storing data types, formats and storage logic, and the biological characteristic library is used for storing data types, formats and storage logic.
The data mart comprises a video database for storing basic information such as the source, size, uploader and front-end access path of video in the database, video files are stored in a server end in folders according to year and time, and can be accessed by returning to a front-end access address, the picture library user database stores basic information such as the source, the size, the uploader, the front-end access path and the like of the picture, the picture files are stored in the server end according to the year and time in folders, and can be accessed by returning to the front access address, the insect state library is used for storing information such as insect state names, general introductions and the like in the database, the information is stored in a character string format, the server side stores insect state comparison pictures to facilitate manual correction and comparison, the ill-state database is used for storing information such as ill-state names, general introduction and the like in the database, the information is stored in a character string format, the server side stores the ill-condition comparison picture, manual correction is convenient for comparison, the knowledge base is used for storing introduction information such as the ill condition, the insect condition and the like in the database, uploading to a database in a front-end markdown form, storing in a character string and html format, using an insect condition file to store information such as insect conditions in the database, recording in a first insect file and a second insect file, uploading to a database in a front-end markdown form, storing in a character string and html format, and storing the related picture data to the server, the disease condition file is used for storing information such as disease conditions and the like in the database, one record of disease conditions is provided, uploading to a database in a front-end markdown form, storing in a character string and html format, and storing the related picture data to the server, the environment file is used for storing the information such as the environment and the like in the database, one record is in one environment scene, uploading the image data to a database in a front-end markdown form, storing the image data in a character string and html format, and storing the related image data to a server.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (7)
1. A pest intelligent prevention and control method comprises a product central monitoring station, a cloud platform and an information ecological chain, wherein the central monitoring station comprises a data acquisition layer and a data transmission layer, the cloud platform comprises a display layer, a service application layer, a data analysis layer, a data model, a data lake and a technical assembly, and the information ecological chain comprises an intelligent coping strategy, an intelligent operation mode, intelligent prevention and control equipment and a basic monitoring point.
2. A pest intelligent control method according to claim 1, wherein: the central monitoring station can cover integrated information acquisition equipment with various types of multiple factors, the acquired information is remotely transmitted to the cloud platform through the central control system, a user utilizes the remote login cloud platform to check the data of the central monitoring station in real time, and relevant equipment monitoring parameters are changed in cloud operation.
3. A pest intelligent control method according to claim 1, wherein: the cloud platform adopts the latest processing technologies such as big data, a neural network, artificial intelligence and 5G, so that the functions of data on-line management, on-line visualization, on-line calculation, on-line diagnosis and the like are realized from the acquisition to the accurate identification, model processing, strategy generation, feedback information tracking, secondary analysis, data mining and the like, and a big data visualization interactive system is formed.
4. A pest intelligent prevention and control method according to claim 1, wherein: the data transmission layer comprises 5G communication, an Internet of things communication card, broadband transmission and video optical fiber transmission, the data lake comprises a data relation and a data mart, big data are processed, the data relation and the data mart are established into a data lake form by adopting a Hadoop technology, the relevance of the data is enhanced, and the use effect of the data is improved.
5. A pest intelligent prevention and control method according to claim 1, wherein: the data analysis layer comprises image processing, image recognition, data modeling, data inspection and data tracing, and the data model comprises a data driving model, an environment simulation model, a dynamic regulation and control model, an operation strategy model, an emergency plan model, a biological diversity regulation and control model, a prediction model, an early warning model, a decision model, a regional strategy model and a combined strategy model.
6. A pest intelligent control method according to claim 1, wherein: the display layer comprises trend analysis and prediction of insect conditions, disease conditions and mouse conditions, comparison analysis of year-round comparison data and year-round comparison data, and early warning prompt of differentiated data; filing insect conditions, illness conditions and disasters; tracking a decision disposal scheme, evaluating a processing result and the like, wherein the application places of the business application layer comprise forestry, agriculture and operation and maintenance.
7. A pest intelligent control method according to claim 1, wherein: the intelligent coping strategy comprises disaster outbreak and foreign species invasion, the intelligent operation mode comprises environment change regulation and control, biological diversity maintenance, theft loss and faults, and the intelligent prevention and control equipment comprises monitoring and prevention and control.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110969553.8A CN115719284A (en) | 2021-08-23 | 2021-08-23 | Intelligent pest prevention and control method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110969553.8A CN115719284A (en) | 2021-08-23 | 2021-08-23 | Intelligent pest prevention and control method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN115719284A true CN115719284A (en) | 2023-02-28 |
Family
ID=85253312
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110969553.8A Pending CN115719284A (en) | 2021-08-23 | 2021-08-23 | Intelligent pest prevention and control method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115719284A (en) |
-
2021
- 2021-08-23 CN CN202110969553.8A patent/CN115719284A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN113095555B (en) | Crop pest monitoring method, system and storage medium based on Internet of things | |
| US20200117897A1 (en) | Adaptive Artificial Intelligence Training Data Acquisition and Plant Monitoring System | |
| CN113409023A (en) | Wisdom gardens integrated service management platform | |
| CN110347127A (en) | Crop planting mandatory system and method based on cloud service | |
| CN109781963A (en) | A kind of field planting environmental monitoring system | |
| BR112021002477A2 (en) | sensor assisted image | |
| CN111767802A (en) | Method and device for detecting abnormal state of object | |
| CN104991459A (en) | Organic vegetable greenhouse monitoring system and method | |
| CN113920288A (en) | Greenhouse cucumber planting management system based on Internet of things | |
| CN108776874A (en) | A kind of modern agriculture regulatory analysis system | |
| CN114460080A (en) | Rice disease and pest intelligent monitoring system | |
| CN115759643A (en) | Blueberry QACCP production management system based on Internet of things | |
| CN113867243A (en) | Digital and intelligent landscaping and maintenance integrated management system | |
| CN112465109A (en) | Green house controlling means based on cloud limit is in coordination | |
| CN112561367A (en) | Intelligent planting decision control system | |
| CN114723667A (en) | Agricultural fine planting and disaster prevention control system | |
| CN112116206A (en) | Intelligent agricultural system based on big data | |
| CN116300608A (en) | Intelligent agriculture remote monitoring system based on big data | |
| CN114298615A (en) | Crop planting risk prevention method and device, storage medium and equipment | |
| CN116645232A (en) | Intelligent management system for agricultural cultivation | |
| CN116543347A (en) | Intelligent insect condition on-line monitoring system, method, device and medium | |
| CN113947344A (en) | Ecological cycle agriculture whole industry chain management system and method | |
| CN112907061A (en) | Potato whole industry chain management system | |
| CN113377141A (en) | Artificial intelligence agricultural automatic management system | |
| CN114543869A (en) | Agricultural braced system based on internet of things |
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 |