CN207560210U - Home farm's Environmental security prior-warning device - Google Patents
Home farm's Environmental security prior-warning device Download PDFInfo
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- CN207560210U CN207560210U CN201721511388.7U CN201721511388U CN207560210U CN 207560210 U CN207560210 U CN 207560210U CN 201721511388 U CN201721511388 U CN 201721511388U CN 207560210 U CN207560210 U CN 207560210U
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- wireless network
- wireless
- deep learning
- facility
- quadrotor
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Abstract
Home farm's Environmental security prior-warning device, including wireless camera, wireless network covering facility, deep learning application work station, quadrotor, smart mobile phone, wireless camera covers facility with wireless network, passes through wireless network connection between wireless network covering facility and deep learning application work station, quadrotor, smart mobile phone.Can the combination that monitored with quadrotor to wide range be monitored by the small range of fixed position wireless camera, give full play to respective advantage, reach monitoring illegal invasion person in real time and timely and effectively be handled.Make less farm management person that can just complete to large range of real time monitoring, there is higher pre-alerting ability.The safe early warning of the surrounding enviroment such as farm, zoo, forest zone, construction site, parking lot or judicial supervision place is can be widely used in, has the characteristics that simple in structure, reasonable design, at low cost, easy to install and use, application mode is flexible, accuracy is high, wide adaptability.
Description
Technical field
The utility model is related to the improvement of safety early warning device structure, specifically a kind of home farm's Environmental security early warning
Device belongs to safe early warning field.
Background technology
In order to monitor wide range place（Such as：Station square, park, forest zone, farm, school, construction site, the administration of justice
Supervision place etc.）Personnel and other activity conditions, way conventional at present be mostly certain places setting around place
The image information monitored is transmitted to by wire transmission line in monitoring room by several cameras, by relevant staff day
Night is stood fast at before monitoring display screen, and reinforming other staff after found the abnormal situation is disposed.Intensity of workers is big,
Monitoring effect is poor, disposes not in time, often since the error of staff causes the accidents such as missing inspection.It was found that there are some remote monitorings
The report of monitor and alarm system, but mostly there is integration degree is low, accuracy is high for detection, the degree of automation is not strong,
The defects of cost is higher, adaptability is not wide.
Invention content
The purpose of the utility model is to overcome the deficiencies in the prior art, provide a kind of simple in structure, at low cost, automation
Degree is strong, detection accuracy is high, application mode is flexible, wide adaptability home farm's Environmental security prior-warning device.
Realizing the technical solution of the utility model aim is：This home farm's Environmental security prior-warning device, including at least
One wireless camera, wireless network covering facility, deep learning application work station, quadrotor, at least one intelligence
Mobile phone, wireless camera cover facility, wireless network covering facility and deep learning application work station, quadrotor with wireless network
Pass through wireless network connection between aircraft, smart mobile phone.
The wireless camera, by solar powered control circuit, micromachine, lens bodies, radio communication mold
Block forms, and control circuit controls transmission mechanism that lens bodies edge is made both horizontally and vertically to move by micromachine, camera lens master
The image information of body acquisition covers facility network connection, wireless camera through control circuit, wireless communication module and wireless network
It is equipped with rain cover.
The wireless network covering facility, it is wireless using independent 802.11n agreements according to the needs of different monitoring range
Router or AC combine the wireless network covering of allocation plan with AP.
The deep learning application work station, by the computer master of application deep learning field convolutional neural networks technology
Machine, display composition, are responsible for analysis and identification and control device and run, realize deep learning application work station to invader's type and
The identification of quantity.
The quadrotor is in the aircraft body with camera, equipped with by master controller, flight control
Unit processed, battery monitoring unit, GPS, magnetic induction sensor, acceleration transducer, gyroscope composite module and radio communication mold
The flight control of block composition and signal processing system.
Commercially available general high configuration computer and related peripherals and wireless can be selected in the utility model uniqueness simple in structure
The components such as network coverage facility, wireless camera, quadrotor are completed, and are easily implemented.
The security threat that the utility model effectively solves to monitor fairly large home farm's plantation, culturing area is faced is asked
Topic can find the information such as the images of illegal invasions such as people, animal, wild beast in first time by some wireless camera first,
Wireless network covering facility, deep learning application work station are transmitted to through wireless network, deep learning application work station passes through master
Invader's type and quantity identification software module in machine, parse image, form the spy substantially of invasion people, animal or wild beast
Sign, timely automated identification people, animal, the type of wild beast, quantity, geographical location, shows corresponding recognition result in the display, and
These information by wireless network are transmitted to the intelligent mobile phone terminal of home farm manager in time, manager is allowed to grasp in time
Potential security risk, takes measures as early as possible.At the same time, deep learning application work station is passed these information by wireless network
Quadrotor is sent to, starts the invasion place that quadrotor flies to people, animal or wild beast, acquires invader on a large scale
Image information, and the image collected information is transmitted to deep learning application work station in time by wireless network.Through depth
After degree study further identifies essential characteristic, type and quantity of invader etc. using work station, then it is transmitted to family
The intelligent mobile phone terminal of farm management person makes manager further correct taken measures, timely and effectively solve and
The invasion of people, animal or wild beast etc. is handled, ensures being perfectly safe for home farm.
It is few that the utility model can alleviate home farm administrative staff, especially to close on mountain area home farm security risk big
Practical problem, realize individual and the group of the invasions such as the people, animal to different densities degree and different scales, wild beast, carry out class
The measurements such as type identification, counting statistics, population distribution density make less farm management person that can just complete to large range of prison
Control.Realize the broad applicability to invading population analysis under home farm's different background environment；Group is invaded to different scales degree
The flexibility of body distribution density and individual amount statistics；Real-time anti-is counted to invasion population distribution density and individual sum
Ying Xing；Effectively home farm's group intrusion event can be analyzed and early warning, there is higher pre-alerting ability.Except for
Outside monitoring to planting, cultivating the illegal invasions such as relevant home farm's people, animal or wild beast, this home farm's Environmental security is pre-
Alarm device also can be widely used in the safety of the surrounding enviroment such as zoo, forest zone, construction site, parking lot or judicial supervision place
Early warning, the organic knot monitored by the small range monitoring of fixed position wireless camera with quadrotor to wide range
It closes, gives full play to respective advantage, achieve the effect that most preferably to monitor illegal invasion person and carry out timely and effective processing.With structure letter
List, reasonable design, the features such as at low cost, easy to install and use, application mode is flexible, accuracy is high, wide adaptability.
Description of the drawings
Fig. 1 is a kind of structure diagram of embodiment of the utility model.
Fig. 2 is the workflow schematic diagram of the utility model embodiment.
Fig. 3 is the workflow schematic diagram of wireless camera in embodiment.
Fig. 4 is the workflow schematic diagram of quadrotor in embodiment.
Specific embodiment
The utility model is further described with the embodiment provided below in conjunction with the accompanying drawings.
The structure of this home farm's Environmental security prior-warning device is as shown in Figure 1, by several wireless cameras 1, wirelessly
Network coverage facility 2, deep learning application work station 3, quadrotor 4 and several smart mobile phones 5 form.Wireless camera
Between head and wireless network cover facility, wireless network covering facility and deep learning application work station, quadrotor and
Realize that mutual information connects by wireless network between smart mobile phone.Wireless camera, by solar powered control
Circuit processed, micromachine, lens bodies, wireless communication module composition, control circuit control transmission mechanism to make by micromachine
Lens bodies along both horizontally and vertically moving, the image information of lens bodies acquisition through control circuit, wireless communication module with
Wireless network covers facility network connection, and wireless camera is equipped with rain cover.Wireless network covers facility, according to different monitoring
The needs of range combine the wireless network covering of allocation plan using independent 802.11n agreements wireless router or AC with AP.It is deep
Degree study is made of host computer, the display of application deep learning field convolutional neural networks technology, is responsible for using work station
Analysis and identification is run with control device, and deep learning application work station includes invader's type and quantity identification module.Four rotations
Rotor aircraft is in the aircraft body with camera, equipped with by master controller, flight control units, battery cell monitoring list
Member, GPS, magnetic induction sensor, acceleration transducer, gyroscope composite module and wireless communication module composition flight control and
Signal processing system.
Present utility model application people is implemented a set of for 8000 square metres of home farms of monitoring area by above-described embodiment
Environmental security prior-warning device.This set home farm Environmental security prior-warning device selects 6 wireless cameras, 1 set of wireless network to cover
Lid facility, 1 deep learning application work station, 1 quadrotor and 4 smart mobile phone compositions.Wireless camera and nothing
Between line network coverage facility, wireless network covering facility and deep learning application work station, quadrotor and intelligent hand
Realize that mutual information connects by wireless network between machine.
Wireless camera selects solar powered Raspberry Pi control circuits, two lofty ambition
2208-80T micromachines, RPi IR-CUT Camera lens bodies, control circuit control general day to regard 326 by micromachine
Transmission mechanism makes lens bodies along both horizontally and vertically moving, and the image information of lens bodies acquisition is through control circuit, wireless
Communication module 802.11n agreement USB wireless network cards cover facility network connection with wireless network, and wireless camera is equipped with DL-
1012 rain covers, the influence for running and working to avoid sleety weather to wireless camera.
Wireless network covers facility, selects Ai Tai WX100AC+AP integrated modes（One small-sized independent AC controller, 4
Outdoor version AP）Form wireless network covering.
Deep learning application work station, by the association day ease 510pro of application deep learning field convolutional neural networks technology
Desktop computer, display and related peripherals composition are responsible for analysis and identification and are run with control device, in deep learning application work station
Including invader's type and quantity identification software module.
The aircraft body that quadrotor is selected is 450 rack of carbon fibre material, and rack is equipped with bright space 2212
1000KV brushless motors 4,1045 positive and negative slurry 4,2200mAh 11.1V 30C charged lithium cells 1, aircraft body
Mei Jiaxin C4015 cameras are carried on self-balancing holder.Equipped with by STM32F103ZE master controllers in aircraft body（Together
When be responsible for battery cell monitoring）, BZ-8223R flight control units, NEO-M8N u-blox NEO-M8N-0-01GPS modules, magnetic strength
The flight that inductive sensing device, acceleration transducer, MPU-9250 gyroscopes composite module and NRF24L01 wireless communication modules form
Control and signal processing system.
The workflow of this home farm's Environmental security prior-warning device is as shown in Figure 2.
Mounted on 6 of home farm periphery critical positions based on solar powered wireless camera in control circuit
Under Raspberry Pi effects, the general day of transmission mechanism is controlled to make depending on 326 by micromachine lofty ambition 2208-80T
Lens bodies RPi IR-CUT Camera acquire the scene of different location in real time along appropriate angle is both horizontally and vertically turned round
Image information.The image information being collected into is incident upon on the photosensitive element in lens bodies by lens bodies, and photosensitive element is light
Signal is converted to electric signal, and electric signal is converted into digital signal and after compression under control circuit effect through wireless communication module
802.11n agreement USB wireless network cards are wirelessly transmitted to wireless network covering facility, with reference to Fig. 3.
If encountering has people, animal, wild beast when illegal invasion persons, some wireless camera can will be seen that at the first time
The information such as the image of illegal invasion person be transmitted to wireless network covering facility, wireless network covering facility transmission through wireless network
To deep learning application work station, deep learning application work station is identified soft by the invader's type and quantity that are run in host
Part module, parses image, forms the essential characteristic of invader's people, animal or wild beast, timely automated identification people, animal or wild beast
Type, quantity, geographical location etc., show corresponding recognition result in the display, and these information are passed through into wireless network
It is transmitted to the intelligent mobile phone terminal of each home farm manager in time, manager is made to understand the safety wind grasped and occurred in time
Danger, the area controlled as early as possible to the wireless camera takes measures.
At the same time, this information is transmitted to quadrotor by wireless network and opened by deep learning application work station
Dynamic quadrotor takes off.STM32F103ZE master controllers in quadrotor are responsible for realizing BZ-8223R flight controls
The co-ordination of unit and NRF24L01 wireless communication module processed.Flight control units are controlled to adjust in aircraft body rack
The rotating speed of four brushless motors changes positive and negative slurry rotor rotating speed, controls the lift of flight；And in GPS module, magnetic induction sensor
（Determine the direction of quadrotor）, acceleration transducer（Determine aircraft acceleration）, gyroscope composite module（Judge to fly
Row device pose）Cooperation under, control and adjustment aircraft posture and position.Quadrotor flight is made wirelessly to be taken the photograph to some
As head monitors the region of covering, acquired on a large scale by Mei Jiaxin C4015 cameras and image acquisition and processing module therein
The image information at scene, and the image information of acquisition is returned in time through wireless communication module NRF24L01 by wireless network
Deep learning application work station, with reference to Fig. 4.Deep learning application work station is to essential characteristic, type and quantity of invader etc.
After making further identification, the intelligent mobile phone terminal of home farm manager is re-send to, manager is made to further appreciate that invader
More accurately situation corrects the measures initially taken, and so as to more accurately handle the invasion of people, animal or wild beast etc., protects
Card home farm is perfectly safe.
Through inside this Environmental security prior-warning device of display on probation is simple in structure, reasonable design, those skilled in the art is all
Commercially available universal component can be selected to be completed by technical solutions of the utility model, it is easy to install and use, easily implement；Pole can be used
Few administrative staff monitor large range of illegal invasion person in real time in the case where not influencing normal work, time saving and energy saving, then
Without fixed Security Personnel is arranged day and night to stand fast at before monitoring display screen；The small range of fixed position wireless camera can be passed through
It monitors to monitor wide range with quadrotor and organically combine, give full play to respective advantage, alarm is timely, accuracy is high,
Wide adaptability, by the favorable comment of trier.
Claims (1)
1. a kind of home farm's Environmental security prior-warning device, it is characterised in that：Including at least one wireless camera, wireless network
Cover facility, deep learning application work station, quadrotor, at least one smart mobile phone, wireless camera and wireless network
Network covers facility, passes through between wireless network covering facility and deep learning application work station, quadrotor, smart mobile phone
Wireless network connection；The wireless camera, by solar powered control circuit, micromachine, lens bodies, channel radio
Believe module composition, control circuit controls transmission mechanism that lens bodies edge is made both horizontally and vertically to move by micromachine, mirror
The image information of head main body acquisition covers facility network connection through control circuit, wireless communication module and wireless network, wirelessly takes the photograph
As head is equipped with rain cover；The wireless network covering facility, according to the needs of different monitoring range, using independent
802.11n agreements wireless router or AC combine the wireless network covering of allocation plan with AP；The deep learning application work
It stands, is made of host computer, the display of application deep learning field convolutional neural networks technology, is responsible for analysis and identification and control
Device operation processed, realizes identification of the deep learning application work station to invader's type and quantity；The quadrotor,
It is in the aircraft body with camera, equipped with by master controller, flight control units, battery monitoring unit, GPS, magnetic
The flight control and signal processing that inductive pick-up, acceleration transducer, gyroscope composite module and wireless communication module form
System.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201721511388.7U CN207560210U (en) | 2017-11-14 | 2017-11-14 | Home farm's Environmental security prior-warning device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201721511388.7U CN207560210U (en) | 2017-11-14 | 2017-11-14 | Home farm's Environmental security prior-warning device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN207560210U true CN207560210U (en) | 2018-06-29 |
Family
ID=62681491
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201721511388.7U Active CN207560210U (en) | 2017-11-14 | 2017-11-14 | Home farm's Environmental security prior-warning device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN207560210U (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109341763A (en) * | 2018-10-10 | 2019-02-15 | 广东长盈科技股份有限公司 | A kind of transportation data collection system and method based on Internet of Things |
| US11620895B2 (en) | 2020-08-05 | 2023-04-04 | Allstate Insurance Company | Systems and methods for disturbance detection and identification based on disturbance analysis |
-
2017
- 2017-11-14 CN CN201721511388.7U patent/CN207560210U/en active Active
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109341763A (en) * | 2018-10-10 | 2019-02-15 | 广东长盈科技股份有限公司 | A kind of transportation data collection system and method based on Internet of Things |
| US11620895B2 (en) | 2020-08-05 | 2023-04-04 | Allstate Insurance Company | Systems and methods for disturbance detection and identification based on disturbance analysis |
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