CN107711762A - Intelligent Insect infestation monitoring method and intelligent Insect infestation monitoring device - Google Patents
Intelligent Insect infestation monitoring method and intelligent Insect infestation monitoring device Download PDFInfo
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- CN107711762A CN107711762A CN201710975947.8A CN201710975947A CN107711762A CN 107711762 A CN107711762 A CN 107711762A CN 201710975947 A CN201710975947 A CN 201710975947A CN 107711762 A CN107711762 A CN 107711762A
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- 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
- A01M1/00—Stationary means for catching or killing insects
- A01M1/02—Stationary means for catching or killing insects with devices or substances, e.g. food, pheronones attracting the insects
- A01M1/04—Attracting insects by using illumination or colours
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- 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
- A01M1/00—Stationary means for catching or killing insects
- A01M1/10—Catching insects by using Traps
- A01M1/106—Catching insects by using Traps for flying insects
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- 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
- A01M1/00—Stationary means for catching or killing insects
- A01M1/20—Poisoning, narcotising, or burning insects
- A01M1/2094—Poisoning, narcotising, or burning insects killing insects by using temperature, e.g. flames, steam or freezing
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
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- Life Sciences & Earth Sciences (AREA)
- Pest Control & Pesticides (AREA)
- Environmental Sciences (AREA)
- Engineering & Computer Science (AREA)
- Insects & Arthropods (AREA)
- Wood Science & Technology (AREA)
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- General Health & Medical Sciences (AREA)
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Abstract
Intelligent Insect infestation monitoring method provided by the invention and intelligent Insect infestation monitoring device, are related to Insect infestation monitoring technical field.The intelligent Insect infestation monitoring method includes capture insect, insect IMAQ, insect image transmitting, insect image procossing and establishes insect pest Early-warning Model step.It is caught pests by trapper, video camera is shot to insect corpse, obtains insect corpse picture, and insect corpse picture is transferred in the image processing module of detecting and reporting pest information instrument and is identified, statistics and analysis.The intelligent Insect infestation monitoring method can grasp the species, quantity and growing state of insect in real time, successfully manage and administer insect pest, and automaticity is high, and intelligence degree is high, and monitor set and improvement insect pest are integrated, and insect-pest effect is good.Present invention also offers a kind of intelligent Insect infestation monitoring device, including casing, video camera, Electric brush of bristles, controller, image processing module and trapper, and monitoring is timely and effective, and recognition result is accurate.
Description
Technical field
The present invention relates to Insect infestation monitoring technical field, in particular to a kind of intelligent Insect infestation monitoring method and intelligent worm
Feelings monitoring device.
Background technology
In agricultural planting production process, the monitoring and prediction of insect pest are the key points of pest and disease damage prevention and control.Traditional monitoring
Wasted time and energy with Forecasting Methodology, actual effect is poor and the degree of accuracy is low.China scientist utilizes remote sensing technology, GIS-Geographic Information System
(GIS) and global positioning system technology establishes the monitoring and warning system of a variety of agriculture and forestry injurious insects, considerably improves monitoring and warning
Horizontal and ability.Solve to a certain extent and observe and predict the problems such as labor intensity is big and efficiency is low.
But in actual application, due to the limitation of technical conditions, the pest forecast lamp of present practical application is still
Need detecting and reporting pest information personnel periodically to field, the type and quantity of manually recorded insect.This pattern is on the one hand in time not
Real-time can be accomplished, waste the optimal prevention time of insect pest to a certain extent；On the other hand it is not solve worm fundamentally
Feelings observe and predict the problem of labor intensity is big and efficiency is low.
In view of this, design and manufacture a kind of intelligent Insect infestation monitoring method, can be used in analyzing in plant growing process
The real-time condition of insect, automation and intelligence degree are high, and insect-pest effect is good, is truly realized and knows in advance, prevents agriculture in advance
Evil, new thinking is brought for the development of farmland damage control technology, there is directive significance to production estimation, be current anti-agriculture
It is badly in need of improved technical problem in evil technical field.
The content of the invention
It is an object of the invention to provide a kind of intelligent Insect infestation monitoring method, including capture insect, insect IMAQ, evil
Worm image transmitting, insect image procossing and establish insect pest Early-warning Model step.It is caught pests by trapper, video camera is to insect
Corpse is shot, and obtains insect corpse picture, and insect corpse picture is transferred in the image processing module of detecting and reporting pest information instrument
Row identification, statistics and analysis.The intelligent Insect infestation monitoring method can grasp the species, quantity and growing state of insect in real time, effectively
Reply and improvement insect pest, automaticity is high, and intelligence degree is high, and monitor set is integrated with insect pest is administered, and insect-pest effect is good,
With great application value.
The present invention also aims to provide a kind of intelligent Insect infestation monitoring device, including casing, video camera, Electric brush of bristles,
Controller, image processing module and trapper.After video camera shooting insect picture, trigger controller, controller controls electronic hair
Brush cleans insect corpse, and insect corpse is cleared up away from going out in insect population for casing.Picture after video camera shooting is transferred to figure
As in processing module, being identified, statistics and analysis, and insect pest Early-warning Model is finally established, provide Pest control scheme.The intelligence
Energy Insect infestation monitoring method automates and intelligence degree is high, and use range is wide, has and monitors and pre- insect-pest function, vermins-proof effect
It is good, there is great application value.
The present invention, which improves its technical problem, to be realized using following technical scheme.
A kind of intelligent Insect infestation monitoring method provided by the invention, the intelligent Insect infestation monitoring method comprise the following steps：
Insect is captured, insect is caught and by the insect stunning or lethal.
Insect IMAQ, gather stunning or lethal insect picture.
Insect image transmitting, by the insect picture transfer to image processing module.
Insect image procossing, first carries out the pretreatment of the insect picture, then carries out convolutional neural networks identification, obtains institute
State the type and quantity of insect and preserve to memory cell.
Insect pest Early-warning Model is established, according to the type and quantity of the insect, is compared with the insect data in database
It is right, establish insect pest Early-warning Model and provide and instruct measure accordingly.
Further, in the capture insect step, the insect is captured using trapper, the trapper includes luring
Lamp and stunning plate are caught, the trapping lamp is used to attract the insect, and the insect is in the trapping lamp way is flown to, described in shock
Stunning plate stunning.
Further, the trapper also includes temperature storehouse, and the temperature storehouse is controlled using infrared temperature, stunning it is described
It is lethal that insect falls into the temperature storehouse.
Further, in the insect image acquisition step, using insect picture described in camera acquisition and by the evil
Worm picture is transferred in described image processing module.
Further, the convolutional neural networks use YOLO convolutional neural networks, and the insect picture is identified
And analysis.
Further, in the insect image processing step, in addition to the insect positioning, to the insect classification and
Count, and the data of the insect are preserved.
Further, the intelligent Insect infestation monitoring method also includes collection weather information, is examined using weather information sensor
Thermometric humidity information, wind direction and wind velocity information, light radiation information, and by the humiture information, the wind direction and wind velocity information, described
Light radiation information and the data of the insect preserve in the lump, and establish database.
Further, after the insect IMAQ, also need to carry out insect corpse processing；The insect corpse processing step
In, using drive device, transmission component and Electric brush of bristles, the transmission component includes gear and rack, the drive device with
The gear connection, drives the pinion rotation, the gear engages with the rack, the pinion rotation, drives the tooth
Bar is moved, and the rack is connected with the Electric brush of bristles, and the rack movement drives the Electric brush of bristles movement.
Further, established described in insect pest Early-warning Model, the species of the insect monitored in real time, quantity and described
Weather information obtains the insect pest Early-warning Model compared with the corresponding data in the database, and with reference to the database
The reasoning of middle deposit and experience, provide corresponding counter-measure.
A kind of intelligent Insect infestation monitoring device provided by the invention, using above-mentioned intelligent Insect infestation monitoring method, for real-time
Monitoring Insect Pest insect pest situation；The intelligent Insect infestation monitoring device includes casing, video camera, Electric brush of bristles, controller, image processing module
And trapper.
Insect leakage port is offered at the top of the casing, the bottom of the casing offers out insect population；It is provided with the casing
Worm platform is carried, the Electric brush of bristles is connected with the Electric brush of bristles, is used for located at the top of the load worm platform, the controller
The Electric brush of bristles is controlled to move.
The trapper is located at the top of the casing, for catching pests and allowing the insect lethal；Insect corpse passes through
The insect leakage port is fallen on the load worm platform, and the Electric brush of bristles is used for the insect corpse on the load worm platform
Cleaning to it is described go out insect population.
The video camera is arranged on the top of the casing, and the controller is connected with the video camera, for controlling
State the shooting time of video camera.The video camera is connected with described image processing module, is put down for shooting and recording the load worm
The quantity and species of insect on platform, and the insect picture transfer of shooting to described image processing module, described image are handled
Module is used to position, classify, count, analyze the insect.
After the video camera shoots the insect picture, the controller is triggered, the controller controls the electronic hair
Brush cleans the insect corpse, by the insect corpse from it is described go out insect population in clear up away.
Intelligent Insect infestation monitoring method provided by the invention and intelligent Insect infestation monitoring device have the beneficial of the following aspects
Effect：
A kind of intelligent Insect infestation monitoring method provided by the invention, including capture insect, insect IMAQ, insect image pass
Defeated, insect image procossing and establish insect pest Early-warning Model step.It is caught pests by trapper, video camera is clapped insect corpse
Take the photograph, obtain insect corpse picture, and insect corpse picture is transferred in the image processing module of detecting and reporting pest information instrument and is identified,
Statistics and analysis.The intelligent Insect infestation monitoring method can grasp the species, quantity and growing state of insect in real time, successfully manage and control
Insect pest is managed, automaticity is high, and intelligence degree is high, and monitor set and improvement insect pest are integrated, and insect-pest effect is good, are had very big
Application value.
A kind of intelligent Insect infestation monitoring device provided by the invention, including casing, video camera, Electric brush of bristles, controller, image
Processing module and trapper.After video camera shooting insect picture, trigger controller, controller control Electric brush of bristles cleans insect corpse
Body, insect corpse is cleared up away from going out in insect population for casing.Picture after video camera shooting is transferred in image processing module,
It is identified, statistics and analysis, and finally establishes insect pest Early-warning Model, provides Pest control scheme.The intelligent Insect infestation monitoring side
Method automates and intelligence degree is high, and use range is wide, has monitoring and pre- insect-pest function, and vermins-proof effect is good, has very big
Application value.
Brief description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below by embodiment it is required use it is attached
Figure is briefly described, it will be appreciated that the following drawings illustrate only certain embodiments of the present invention, therefore be not construed as pair
The restriction of scope, for those of ordinary skill in the art, on the premise of not paying creative work, can also be according to this
A little accompanying drawings obtain other related accompanying drawings.
Fig. 1 is the operational flowchart for the intelligent Insect infestation monitoring method that the specific embodiment of the invention provides；
Fig. 2 is the concrete operations flow chart for the intelligent Insect infestation monitoring method that the specific embodiment of the invention provides；
Fig. 3 is the structural representation of polypide processing unit in the intelligent Insect infestation monitoring method that the specific embodiment of the invention provides
Figure；
Fig. 4 is the composition frame chart for the intelligent Insect infestation monitoring device that the specific embodiment of the invention provides.
Icon：10- polypide processing units；110- casings；111- insect leakage ports；113- goes out insect population；114- carries worm platform；120-
Drive device；121- Electric brush of bristles；123- slide rails；125- transmission components；130- controllers；150- trappers；151- stunning plates；
153- video cameras；155- light compensating lamps；210- image processing modules；211- pretreatment units；213- figure cutting units；215- schemes
Shape integral unit；220- memory cell；230- display units；240- prewarning units.
Embodiment
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is
Part of the embodiment of the present invention, rather than whole embodiments.The present invention implementation being generally described and illustrated herein in the accompanying drawings
The component of example can be configured to arrange and design with a variety of.
Therefore, below the detailed description of the embodiments of the invention to providing in the accompanying drawings be not intended to limit it is claimed
The scope of the present invention, but be merely representative of the present invention selected embodiment.It is common based on the embodiment in the present invention, this area
The every other embodiment that technical staff is obtained under the premise of creative work is not made, belong to the model that the present invention protects
Enclose.
In the description of the invention, it is to be understood that the orientation or position relationship of the instruction such as term " on ", " under " are base
In orientation shown in the drawings or position relationship, or product of the present invention using when the orientation usually put or position relationship, or
Person is the orientation or position relationship that those skilled in the art usually understand, is for only for ease of the description present invention and simplifies description,
Rather than instruction or imply signified equipment or element must have specific orientation, with specific azimuth configuration and operation, because
This is not considered as limiting the invention.
" first ", " second " etc. of the present invention, is used only for being distinguish between in description, not special implication.
In the description of the invention, it is also necessary to explanation, unless otherwise clearly defined and limited, term " setting ",
" installation " should be interpreted broadly, for example, it may be being fixedly connected or being detachably connected, or be integrally connected；Can be
It is joined directly together, can also be indirectly connected by intermediary.For the ordinary skill in the art, can be with concrete condition
Understand the concrete meaning of above-mentioned term in the present invention.
Fig. 1 is the operational flowchart for the intelligent Insect infestation monitoring method that the specific embodiment of the invention provides, and refer to Fig. 1.
A kind of intelligent Insect infestation monitoring method that the present embodiment provides, intelligent Insect infestation monitoring method comprise the following steps：
S1：Insect is captured, insect is caught and by insect stunning or lethal.
S2：Insect IMAQ, gather stunning or lethal insect picture.
S3：Insect image transmitting, by insect picture transfer to image processing module.
S4：Insect image procossing, first carries out the pretreatment of insect picture, then carries out convolutional neural networks identification, is done harm to
The type and quantity of worm are simultaneously preserved to memory cell 220.
S5：Insect pest Early-warning Model is established, according to the type and quantity of insect, is compared with the insect data in database
It is right, establish insect pest Early-warning Model and provide and instruct measure accordingly.
Specifically, in insect step is captured, insect is captured using trapper 150, trapper 150 includes trapping lamp and cause
Confused plate 151, trapping lamp are used to attract insect, and insect hits the stunning of stunning plate 151 in trapping lamp way is flown to.Alternatively, trap
Lamp may be mounted on stunning plate 151 or be set close to stunning plate 151, and trapping lamp uses LED frequency conversion trapping lamps.Stunning plate 151
It can be made of glass material, or sound wave or light wave of special frequency channel etc. can also be used by insect stunning or lethal.
Preferably, trapper 150 also includes temperature storehouse, temperature storehouse is controlled using infrared temperature, and the insect of stunning falls into
Temperature storehouse is lethal.Temperature storehouse can select high temperature storehouse that insect heat is dead, or insect is freezed to death from low temperature bin.Preferably, this
Infrared heat storehouse is used in embodiment, insect is lethal.
In insect image acquisition step, insect picture is gathered using video camera 153 and insect picture is transferred at image
Manage in module 210.Specifically, image processing module 210 can include pretreatment unit 211, figure cutting unit 213 and figure
Integral unit 215, pretreatment unit 211 first pre-process to insect picture, and figure cutting unit 213 is by insect picture segmentation
Into more parts of view data, figure integral unit 215 is identified, counts and added up to every part of view data, finally obtains insect
Type and quantity information.
The pattern analysis of insect picture is to identify to complete by convolutional neural networks, preferably, being adopted in the present embodiment
With YOLO convolutional neural networks, insect picture is identified and analyzed.For example gray proces first are carried out to insect picture, returned
One change processing etc., then by the insect picture segmentation after processing be 15 parts of view data, split number and be not limited to that, can also
For other numerical value.Every part of image content is identified and counted respectively, finally does cumulative, the final species sum for obtaining insect
Measure information.The type and quantity information of the insect got is shown or early warning by detecting and reporting pest information instrument to operator.
Fig. 2 is the concrete operations flow chart for the intelligent Insect infestation monitoring method that the specific embodiment of the invention provides, and Fig. 3 is this hair
The structural representation of polypide processing unit 10, refer to Fig. 2 and figure in the intelligent Insect infestation monitoring method that bright specific embodiment provides
3。
Intelligent Insect infestation monitoring method also includes：
S21：The processing of insect corpse.
After insect IMAQ, also need to carry out insect corpse processing.In insect corpse processing step, handled and filled using polypide
10 are put, polypide processing unit 10 includes casing 110, drive device 120, transmission component 125 and Electric brush of bristles 121, transmission component
125 include gear and rack, and drive device 120 is connected with gear, and drive gear rotates, wheel and rack engagement, pinion rotation,
Band carry-over bar is moved, and rack is connected with Electric brush of bristles 121, and rack movement drives Electric brush of bristles 121 to move.Preferably, casing
Slide rail 123 is provided with 110, Electric brush of bristles 121 moves back and forth along slide rail 123.Certainly, it is not limited to that, transmission component 125 is also
Can be the kinds of drive such as belt wheel transmission, Chain conveyer or lead screw pair.
Video camera 153 is arranged on casing 110, is provided with casing 110 and is carried worm platform 114, the top of casing 110 offers
Insect leakage port 111, the end for carrying worm platform 114 offer out insect population 113, and Electric brush of bristles 121 moves on worm platform 114 is carried, energy
It is enough to clean insect corpse to going out at insect population 113.Light compensating lamp 155 is installed on casing 110, is the coverage of video camera 153
Enough illuminations are provided, strengthen shooting effect.Alternatively, casing 110 and load worm platform 114 are made of PVC material.
Preferably, in insect image processing step, the identification and statistics of image specifically also include：
S41：Insect positions.Insect in insect picture is positioned, and by the evil in the insect and database of positioning
Worm is compared.
S42：Insect is classified and counted.After insect fixation and recognition, insect is classified and counted, and by the number of insect
According to being preserved.
S43：Weather information is gathered, humiture information, wind direction and wind velocity information, light radiation are detected using weather information sensor
Information etc., and humiture information, wind direction and wind velocity information, light radiation information and the data of insect are preserved in the lump, and establish data
Storehouse.
In insect pest Early-warning Model is established, in species, quantity and the weather information and database of the insect monitored in real time
Corresponding data compares, and obtains insect pest Early-warning Model, and combines the reasoning laid in database and experience, provides corresponding reply
Measure, prevention and improvement insect pest.Data message in database is through test of many times, is furtherd investigate by theory and combines agriculture
Industry expert for many years empirical, and constantly updating and perfect, to ensure insect pest situation precision of analysis.
Fig. 4 is the composition frame chart for the intelligent Insect infestation monitoring device that the specific embodiment of the invention provides, and refer to Fig. 4.
A kind of intelligent Insect infestation monitoring device that the present embodiment provides, using above-mentioned intelligent Insect infestation monitoring method, for reality
When Monitoring Insect Pest insect pest situation.Intelligent Insect infestation monitoring device includes casing 110, video camera 153, Electric brush of bristles 121, controller 130, figure
As processing module 210 and trapper 150.
The top of casing 110 offers insect leakage port 111, and the bottom of casing 110 offers out insect population 113；Set in casing 110
Have and carry worm platform 114, Electric brush of bristles 121 is connected located at the top for carrying worm platform 114, controller 130 with Electric brush of bristles 121, is used
Moved in control Electric brush of bristles 121.Trapper 150 is located at the top of casing 110, for catching pests and allowing insect lethal.Evil
Worm corpse falls to through insect leakage port 111 and carried on worm platform 114, and Electric brush of bristles 121 is used for the insect corpse that will be carried on worm platform 114
Cleaning is to going out insect population 113.
Video camera 153 is arranged on the top of casing 110, and controller 130 is connected with video camera 153, for controlling video camera
153 shooting time.Video camera 153 is connected with image processing module 210, for shooting and recording the evil carried on worm platform 114
The quantity and species of worm, and by the insect picture transfer of shooting to image processing module 210.Video camera 153 can be continuously shot,
Can also certain interval of time shooting once, the filming frequency of video camera 153 and the cleaning frequency of Electric brush of bristles 121 are according to reality
Depending on situation, control is made overall plans and coordinate by controller 130.Picture transfer after shooting can be real-time Transmission or every
A period of time transmission primaries, such as, one hour, two hours or four hours transmission primaries.Image processing module 210 be used for position,
Classification, statistics, analysis insect, and preserve into memory cell 220.The insect data and weather information and number that will be monitored in real time
It is analyzed according to the data in storehouse, user is presented to by display unit 230 and prewarning unit 240.Display unit 230 can
To show the currently monitored information, Insect infestation monitoring report and suggestion and measure.
After video camera 153 shoots insect picture, trigger controller 130, controller 130 controls Electric brush of bristles 121 to clean evil
Worm corpse, by insect corpse from going out in insect population 113 to clear up away.Controller 130 is connected with drive device 120, is driven for controlling
Dynamic device 120.It is easily understood that controller 130 and drive device 120 can be electrically connected or wireless connection, can
Realize remote control etc..Drive device 120 can use stepper motor, preferably, in the present embodiment, drive device 120 is adopted
With MAXON brushless electric machines.Electric brush of bristles 121 uses nylon bristle.
In summary, intelligent Insect infestation monitoring method provided by the invention and intelligent Insect infestation monitoring device have following side
The beneficial effect in face：
Intelligent Insect infestation monitoring method provided by the invention, by the trapping pests of polypide processing unit 10 and evil can be killed
Worm, insect corpse fall to from insect leakage port 111 and carried on worm platform 114, and video camera 153 is to carrying the insect corpse on worm platform 114
Shooting, insect corpse picture is obtained, and insect corpse picture is transferred in the image processing module 210 of detecting and reporting pest information instrument, schemed
Picture processing module 210 analyzes the insect corpse picture, the final kind for grasping insect by convolutional neural networks recognition methods
Class, quantity and growing state, successfully manage and administer insect pest.After video camera 153 shoots picture, trigger controller 130, controller
130 control stepper motors, are moved by the driving electric hairbrush 121 of transmission component 125, clean the insect corpse carried on worm platform 114
Body.The intelligent Insect infestation monitoring method automaticity is high, and intelligence degree is high, and monitor set and improvement insect pest are integrated, insect-pest
Effect is good, brings new thinking for the development of farmland damage control technology, has directive significance to production estimation, have pole
Big application value.
Intelligent Insect infestation monitoring device provided by the invention, including casing 110, video camera 153, Electric brush of bristles 121, controller
130th, image processing module 210 and trapper 150.After video camera 153 shoots insect picture, trigger controller 130, controller
130 control Electric brush of bristles 121 clean insect corpse, and insect corpse is cleared up away from going out in insect population 113 for casing 110.Shooting
Picture after machine 153 is shot is transferred in image processing module 210, is identified, statistics and analysis, and it is pre- finally to establish insect pest
Alert model, provides Pest control scheme.The intelligent Insect infestation monitoring method automation and intelligence degree are high, and use range is wide, tool
There are monitoring and pre- insect-pest function, vermins-proof effect is good, has great application value.
The preferred embodiments of the present invention are the foregoing is only, are not intended to limit the invention, for the skill of this area
For art personnel, the present invention can have various changes, combination and change.Within the spirit and principles of the invention, made
Any modification, equivalent substitution and improvements etc., should be included in the scope of the protection.
Claims (10)
- A kind of 1. intelligent Insect infestation monitoring method, it is characterised in that the intelligent Insect infestation monitoring method comprises the following steps：Insect is captured, insect is caught and by the insect stunning or lethal；Insect IMAQ, gather stunning or lethal insect picture；Insect image transmitting, by the insect picture transfer to image processing module；Insect image procossing, first carries out the pretreatment of the insect picture, then carries out convolutional neural networks identification, obtains the evil The type and quantity of worm are simultaneously preserved to memory cell；Insect pest Early-warning Model is established, according to the type and quantity of the insect, is compared, builds with the insect data in database Found insect pest Early-warning Model and provide and instruct measure accordingly.
- 2. intelligent Insect infestation monitoring method according to claim 1, it is characterised in that in the capture insect step, adopt The insect is captured with trapper, the trapper includes trapping lamp and stunning plate, and the trapping lamp is used to attract the insect, The insect hits the stunning plate stunning in the trapping lamp way is flown to.
- 3. intelligent Insect infestation monitoring method according to claim 2, it is characterised in that the trapper also includes temperature storehouse, The temperature storehouse is controlled using infrared temperature, and it is lethal that the insect of stunning falls into the temperature storehouse.
- 4. intelligent Insect infestation monitoring method according to claim 1, it is characterised in that in the insect image acquisition step, It is transferred to using insect picture described in camera acquisition and by the insect picture in described image processing module.
- 5. intelligent Insect infestation monitoring method according to claim 1, it is characterised in that the convolutional neural networks use YOLO Convolutional neural networks, the insect picture is identified and analyzed.
- 6. intelligent Insect infestation monitoring method according to claim 5, it is characterised in that in the insect image processing step, Also include classifying and counting to insect positioning, to the insect, and the data of the insect are preserved.
- 7. intelligent Insect infestation monitoring method according to claim 6, it is characterised in that the intelligent Insect infestation monitoring method is also wrapped Collection weather information is included, humiture information, wind direction and wind velocity information, light radiation information are detected using weather information sensor, and will The humiture information, the wind direction and wind velocity information, the light radiation information and the data of the insect preserve in the lump, and establish Database.
- 8. intelligent Insect infestation monitoring method according to claim 1, it is characterised in that after the insect IMAQ, also need Carry out insect corpse processing；It is described using drive device, transmission component and Electric brush of bristles in the insect corpse processing step Transmission component includes gear and rack, and the drive device is connected with the gear, drives the pinion rotation, the gear with The rack engagement, the pinion rotation, drives the rack to move, the rack is connected with the Electric brush of bristles, the tooth Bar movement drives the Electric brush of bristles movement.
- 9. intelligent Insect infestation monitoring method according to claim 7, it is characterised in that establish insect pest Early-warning Model described In, species, quantity and the weather information of the insect monitored in real time compared with the corresponding data in the database, The insect pest Early-warning Model is obtained, and with reference to the reasoning and experience laid in the database, provides corresponding counter-measure.
- 10. a kind of intelligent Insect infestation monitoring device, it is characterised in that using the intelligent insect pest situation any one of claim 1 to 9 Monitoring method, for real-time Monitoring Insect Pest insect pest situation；The intelligent Insect infestation monitoring device includes casing, video camera, Electric brush of bristles, control Device, image processing module and trapper processed；Insect leakage port is offered at the top of the casing, the bottom of the casing offers out insect population；It is provided with the casing and carries worm Platform, the Electric brush of bristles is located at the top of the load worm platform, and the controller is connected with the Electric brush of bristles, for controlling The Electric brush of bristles movement；The trapper is located at the top of the casing, for catching pests and allowing the insect lethal；Described in insect corpse warp Insect leakage port is fallen on the load worm platform, and the Electric brush of bristles is used to clear up the insect corpse on the load worm platform Go out insect population described in；The video camera is arranged on the top of the casing, and the controller is connected with the video camera, for controlling described take the photograph The shooting time of camera；The video camera is connected with described image processing module, for shooting and recording the load worm platform Insect quantity and species, and by the insect picture transfer of shooting to described image processing module, described image processing module For positioning, classifying, counting, analyzing the insect；After the video camera shoots the insect picture, the controller is triggered, the controller controls the Electric brush of bristles clear Sweep the insect corpse, by the insect corpse from it is described go out insect population in clear up away.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710975947.8A CN107711762A (en) | 2017-10-19 | 2017-10-19 | Intelligent Insect infestation monitoring method and intelligent Insect infestation monitoring device |
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| CN108782492A (en) * | 2018-05-18 | 2018-11-13 | 仲恺农业工程学院 | A kind of pest control method based on pest control equipment |
| CN108812575A (en) * | 2018-05-18 | 2018-11-16 | 仲恺农业工程学院 | A kind of pest control method based on learning-oriented pest control equipment |
| CN109147282A (en) * | 2018-07-03 | 2019-01-04 | 华南农业大学 | A kind of intelligence rice field insect pest graded forecast system and forecasting procedure |
| CN109588391A (en) * | 2018-11-26 | 2019-04-09 | 盐城吉大智能终端产业研究院有限公司 | A kind of insect pest intelligent detection device |
| CN109845547A (en) * | 2018-12-12 | 2019-06-07 | 安徽玉野建设工程有限公司 | A kind of garden pest insects monitoring method and large-scale vertical garden pest insects monitoring device |
| CN109964896A (en) * | 2019-05-10 | 2019-07-05 | 福建师范大学福清分校 | A kind of Internet of Things monitoring analysis system luring worm identification sorting equipment and pest and disease damage |
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| CN110782435A (en) * | 2019-10-17 | 2020-02-11 | 浙江中烟工业有限责任公司 | Tobacco worm detection method based on deep learning model |
| CN111179266A (en) * | 2020-01-15 | 2020-05-19 | 河北润宜机电科技有限公司 | Artificial intelligence analysis system for tobacco insects |
| CN111445062A (en) * | 2020-03-17 | 2020-07-24 | 深圳数联天下智能科技有限公司 | Insect pest position prediction method and device, computer equipment and storage medium |
| CN111460990A (en) * | 2020-03-31 | 2020-07-28 | 青海省草原总站 | Big data-based alpine pastoral area grassland insect pest monitoring and early warning system and method |
| CN111768044A (en) * | 2020-07-01 | 2020-10-13 | 石河子大学 | Method and system for monitoring cotton aphid number in seedling stage of cotton |
| CN111838103A (en) * | 2020-07-27 | 2020-10-30 | 广州大学 | Agricultural pest intelligent monitoring prevention and control system |
| CN112015117A (en) * | 2020-08-28 | 2020-12-01 | 重庆法尔物联网科技有限公司 | Intelligent cloud control insect trapping and monitoring working circuit |
| CN112106747A (en) * | 2020-08-11 | 2020-12-22 | 上海有间建筑科技有限公司 | Intelligent agricultural insect pest remote automatic monitoring system |
| CN112655682A (en) * | 2020-12-21 | 2021-04-16 | 浙江农林大学暨阳学院 | Method for intelligently monitoring and treating agricultural pests |
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| CN108812575A (en) * | 2018-05-18 | 2018-11-16 | 仲恺农业工程学院 | A kind of pest control method based on learning-oriented pest control equipment |
| CN108812575B (en) * | 2018-05-18 | 2021-08-31 | 仲恺农业工程学院 | Pest control method based on learning type pest control equipment |
| CN108782492B (en) * | 2018-05-18 | 2021-03-02 | 仲恺农业工程学院 | Pest control method based on pest control equipment |
| CN108782492A (en) * | 2018-05-18 | 2018-11-13 | 仲恺农业工程学院 | A kind of pest control method based on pest control equipment |
| CN109147282A (en) * | 2018-07-03 | 2019-01-04 | 华南农业大学 | A kind of intelligence rice field insect pest graded forecast system and forecasting procedure |
| CN112911931B (en) * | 2018-09-21 | 2022-11-04 | 拜耳公司 | Imaging device for detecting arthropods and system for detecting arthropods |
| CN112911931A (en) * | 2018-09-21 | 2021-06-04 | 拜耳公司 | Detection of arthropods |
| CN109588391A (en) * | 2018-11-26 | 2019-04-09 | 盐城吉大智能终端产业研究院有限公司 | A kind of insect pest intelligent detection device |
| CN109588391B (en) * | 2018-11-26 | 2021-06-01 | 盐城吉大智能终端产业研究院有限公司 | Insect pest intelligent detection device |
| CN109845547A (en) * | 2018-12-12 | 2019-06-07 | 安徽玉野建设工程有限公司 | A kind of garden pest insects monitoring method and large-scale vertical garden pest insects monitoring device |
| CN109964896A (en) * | 2019-05-10 | 2019-07-05 | 福建师范大学福清分校 | A kind of Internet of Things monitoring analysis system luring worm identification sorting equipment and pest and disease damage |
| CN109964896B (en) * | 2019-05-10 | 2024-03-12 | 福建技术师范学院 | Insect attracting, identifying and sorting device and pest and disease monitoring and analyzing system based on Internet of things |
| CN110235873B (en) * | 2019-06-26 | 2021-11-26 | 北京农业智能装备技术研究中心 | Automatic monitoring and forecasting system for insect pest situation of agricultural and forestry harmful insects |
| CN110235873A (en) * | 2019-06-26 | 2019-09-17 | 北京农业智能装备技术研究中心 | A kind of agricultural harmful insect insect pest situation automatic monitoring forecast system |
| CN110472784A (en) * | 2019-08-08 | 2019-11-19 | 黑龙江农垦垦通信息通信有限公司 | A kind of insect pests forecasting based on artificial intelligence and diagnostic system and method |
| CN110782435A (en) * | 2019-10-17 | 2020-02-11 | 浙江中烟工业有限责任公司 | Tobacco worm detection method based on deep learning model |
| CN111179266A (en) * | 2020-01-15 | 2020-05-19 | 河北润宜机电科技有限公司 | Artificial intelligence analysis system for tobacco insects |
| CN111445062B (en) * | 2020-03-17 | 2023-08-29 | 深圳数联天下智能科技有限公司 | Pest location prediction method, device, computer equipment and storage medium |
| CN111445062A (en) * | 2020-03-17 | 2020-07-24 | 深圳数联天下智能科技有限公司 | Insect pest position prediction method and device, computer equipment and storage medium |
| CN111460990A (en) * | 2020-03-31 | 2020-07-28 | 青海省草原总站 | Big data-based alpine pastoral area grassland insect pest monitoring and early warning system and method |
| CN111768044B (en) * | 2020-07-01 | 2022-07-08 | 石河子大学 | Method and system for monitoring cotton aphid number in seedling stage of cotton |
| CN111768044A (en) * | 2020-07-01 | 2020-10-13 | 石河子大学 | Method and system for monitoring cotton aphid number in seedling stage of cotton |
| CN111838103A (en) * | 2020-07-27 | 2020-10-30 | 广州大学 | Agricultural pest intelligent monitoring prevention and control system |
| CN112106747A (en) * | 2020-08-11 | 2020-12-22 | 上海有间建筑科技有限公司 | Intelligent agricultural insect pest remote automatic monitoring system |
| CN112015117A (en) * | 2020-08-28 | 2020-12-01 | 重庆法尔物联网科技有限公司 | Intelligent cloud control insect trapping and monitoring working circuit |
| CN112655682A (en) * | 2020-12-21 | 2021-04-16 | 浙江农林大学暨阳学院 | Method for intelligently monitoring and treating agricultural pests |
| CN112825832A (en) * | 2021-01-08 | 2021-05-25 | 江苏久智环境科技服务有限公司 | Early warning system for preventing and treating diseases and pests of ancient and famous trees |
| CN112862054A (en) * | 2021-02-26 | 2021-05-28 | 北京农业智能装备技术研究中心 | Real-time pest detecting and counting system |
| CN112862054B (en) * | 2021-02-26 | 2024-05-14 | 北京农业智能装备技术研究中心 | Real-time pest detecting and counting system |
| CN112931456B (en) * | 2021-04-13 | 2024-03-29 | 山东农业大学 | Device for collecting insects of field crops and insect pest monitoring and early warning method |
| CN112931456A (en) * | 2021-04-13 | 2021-06-11 | 山东农业大学 | Insect collecting device for field crops and insect pest monitoring and early warning method |
| CN113204584A (en) * | 2021-04-26 | 2021-08-03 | 红云红河烟草(集团)有限责任公司 | Insect condition monitoring and early warning method, device and equipment applied to tobacco industry |
| CN113273555A (en) * | 2021-06-15 | 2021-08-20 | 米恩基(浙江)传感科技有限公司 | Artificial intelligence insect situation prediction system and prediction method |
| CN113273555B (en) * | 2021-06-15 | 2023-07-04 | 米恩基(浙江)传感科技有限公司 | Artificial intelligence insect condition prediction system and prediction method |
| CN113749077A (en) * | 2021-09-06 | 2021-12-07 | 江苏中烟工业有限责任公司 | Tobacco beetle population density investigation method for tobacco storage warehouse |
| CN113749077B (en) * | 2021-09-06 | 2022-08-12 | 江苏中烟工业有限责任公司 | Tobacco beetle population density investigation method for tobacco storage warehouse |
| CN113925034A (en) * | 2021-10-18 | 2022-01-14 | 山东农业大学 | Apple orchard pest orientation monitoring and early warning device and method based on machine vision |
| CN114063179B (en) * | 2021-10-27 | 2023-10-27 | 福建省农业科学院植物保护研究所 | Intelligent monitoring equipment for invasion organism cross-border |
| CN114063179A (en) * | 2021-10-27 | 2022-02-18 | 福建省农业科学院植物保护研究所 | Biological cross-border intelligent monitoring equipment of invasion |
| CN114208565A (en) * | 2021-12-13 | 2022-03-22 | 青海省草原总站 | Image type grassland insect pest information acquisition device |
| CN114342717A (en) * | 2021-12-27 | 2022-04-15 | 深圳市金阳盛城市服务集团有限公司 | Insect pest detecting and reporting method, device, equipment and storage medium |
| CN114304097B (en) * | 2021-12-31 | 2023-08-18 | 广西真典科技有限公司 | Intelligent insect condition observation and report equipment and insect pest monitoring method thereof |
| CN114304097A (en) * | 2021-12-31 | 2022-04-12 | 广西真典科技有限公司 | Intelligent insect condition forecasting device and insect pest monitoring method thereof |
| CN115136827A (en) * | 2022-05-25 | 2022-10-04 | 深圳华云信息系统有限公司 | Insect pest situation monitoring method and device, electronic equipment and storage medium |
| CN115443960A (en) * | 2022-09-30 | 2022-12-09 | 河南云飞科技发展有限公司 | Method and device based on live insect photographing identification |
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