KR20220112321A - System and method for preventing invasion of wild animal using drones - Google Patents

Abstract

A wild animal invasion preventing and managing system using a drone and a method thereof are disclosed. The present invention comprises: a drone for obtaining first image data of a first region; and a server detecting a wild animal invading the first region based on the first image data. The server may control the drone to prevent invasion of the wild animal.

Description

SYSTEM AND METHOD FOR PREVENTING INVASION OF WILD ANIMAL USING DRONES

The present invention relates to a system and method for preventing and managing wild animals using drones. More particularly, it relates to a system and method for preventing and managing wildlife invasion through vision recognition technology.

In the era of the Fourth Industrial Revolution, the drone-related industry, which refers to unmanned aerial vehicles (UVA), is emerging as a new industry that will lead the future.

Drones were developed for military use in the early 20th century and have performed military missions such as reconnaissance, surveillance, and bombing. Utilization is becoming common in a wide variety of fields such as collecting information by being put into difficult points (regions) or dangerous areas, shooting dramas and movies, and logistics and delivery.

In recent years, drones are not only used to overcome the limitations of existing surveying device methods for land, river, and facility inspection and surveying, but also use drones for various purposes by utilizing the mobility of drones. Recently, technologies for using image data captured by a drone's camera in various ways by grafting vision recognition technology have been proposed.

In particular, drones may be suitable for industries that perform various tasks on a large land, such as agriculture and livestock. Recently, as the number of wild animals increases, there is a problem that destroys agricultural products and damages the livestock industry.

Accordingly, there is an increasing need to use drones to prevent invasion of wild animals and to manage habitats by observing wild animals.

Republic of Korea Patent Publication No. 10-2200679 (Title of Invention: Distance Surveying Drone)

It is an object of the present invention to prevent the invasion of wild animals by utilizing the drone's maneuverability and vision recognition technology.

In addition, it is an object of the present invention to propose a system for easily detecting an abnormal state of a fence enclosing a large land by utilizing the drone's mobility and vision recognition technology.

Another object of the present invention is to propose a system for easily detecting whether a fire has occurred in a large area by utilizing the maneuverability of a drone.

In addition, an object of the present invention is to obtain clearer image data by protecting a lens due to the characteristics of a camera of a drone used outdoors.

Another object of the present invention is to propose a system capable of efficiently managing wild animals by easily acquiring habitat information of wild animals by utilizing drone mobility and vision recognition technology.

In order to solve the above problem, the present invention includes a drone for acquiring first image data of a first area and a server for detecting wild animals invading the first area based on the first image data, The server may control the drone to prevent invasion of the wild animal.

In addition, in the present invention, the drone may further include a warning generating device for generating a noise, and the drone may prevent invasion of the wild animal by using the noise.

In addition, at least a portion of the first area is surrounded by a fence, the drone further includes a lidar sensor that generates second image data for the fence, the server receives the second image data, Status information on whether the fence is abnormal may be obtained based on the second image data.

In addition, the drone may further include a fire detection sensor for detecting whether a fire has occurred in the first area, and the server may obtain information on whether the fire has occurred from the fire detection sensor.

In addition, the drone includes a camera that generates the first image data, the camera includes a camera module that generates a video image from an optical image, and the camera module includes a housing including a through hole in a sidewall, the through hole It may include a lens installed in the and a driving unit for driving the lens.

Also, the drone may acquire third image data for a second region other than the first region, and the server may acquire habitat information of the wild animal based on the third image data.

In addition, in order to solve the above problems, the present invention provides the steps of acquiring image data from a drone including a camera, recognizing a vision of a wild animal from the image data, and preventing invasion of the wild animal by the drone may include the step of controlling

In addition, in order to solve the above problem, the present invention provides a non-transitory computer-readable medium storing instructions, which, when executed by a processor, cause the processor to perform the above-described method, It may be a possible medium.

The present invention utilizes the maneuverability of a drone to efficiently prevent the intrusion of wild animals into a large land, easily and automatically checks the abnormal state of a fence to prevent wild animals, and automatically detects whether a fire has occurred on a large land. and has the effect of more easily grasping the habitat information of wild animals.

The present invention can propose a vision recognition technology capable of exhibiting the above-described effect more remarkably by generating clearer image data through a lens with strong stain resistance.

The effects obtainable according to the present invention are not limited to the above-mentioned effects, and other effects not mentioned may be clearly understood by those of ordinary skill in the art to which this specification belongs from the description below. will be.

1 is a view showing a system for preventing and managing wild animals using a drone according to the present invention.
2 and 3 are views showing a drone according to the present invention.
4 is a view showing a camera according to the present invention.
5 is a view showing a function module stored in a memory according to the present invention.
6 is a view showing a method for preventing and managing wild animals using a drone according to the present invention.
BRIEF DESCRIPTION OF THE DRAWINGS The accompanying drawings, which are included as a part of the detailed description to help the understanding of the present specification, provide embodiments of the present specification, and together with the detailed description, explain the technical features of the present specification.

Hereinafter, the embodiments disclosed in the present specification will be described in detail with reference to the accompanying drawings, but the same or similar components are assigned the same reference numerals regardless of reference numerals, and redundant description thereof will be omitted.

In addition, in describing the embodiments disclosed in the present specification, if it is determined that detailed descriptions of related known technologies may obscure the gist of the embodiments disclosed in this specification, the detailed description thereof will be omitted.

In addition, the accompanying drawings are only for easy understanding of the embodiments disclosed in this specification, and the technical idea disclosed herein is not limited by the accompanying drawings, and all changes included in the spirit and scope of the present invention , should be understood to include equivalents or substitutes.

Terms including ordinal numbers such as first, second, etc. may be used to describe various elements, but the elements are not limited by the terms. The above terms are used only for the purpose of distinguishing one component from another.

The singular expression includes the plural expression unless the context clearly dictates otherwise.

In the present application, terms such as “comprises” or “have” are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, but one or more other features It is to be understood that this does not preclude the possibility of the presence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Hereinafter, a system and method for preventing and managing wild animals using a drone according to a preferred embodiment of the present specification will be described in detail based on the above-mentioned contents.

1 is a view showing a system for preventing and managing wild animals using a drone according to the present invention.

1 , a system 100 according to the present invention may include a server and a drone 130 . In addition, the present invention can be defined by dividing the topography into a first area A1 and a second area A2 . The first area A1 may be indicated by a fence as an area where wild animals should be prevented from being invaded. The fence may be configured to prevent invasion of wild animals into the first area A1. The second area A2 may mean all areas other than the first area A1 . In addition, the second area A2 may limit the area where wild animals live. That is, the first area A1 and the second area A2 may be separated by a fence. At least a portion of the first area A1 may be surrounded by a fence.

The drone 130 may acquire first image data obtained by photographing the first area A1. The drone 130 according to the present invention is a generic term for an unmanned aerial vehicle, and details will be described later.

The server may receive the first image data from the drone 130 and detect a wild animal that has invaded the first area A1 based on the received first image data. The server may control the drone 130 through wireless communication or the like, and may control the drone 130 to prevent invasion of wild animals into the first area A1 .

2 and 3 are views showing a drone according to the present invention.

According to FIG. 2 , the drone 130 according to the present invention includes a communication module 131 , a camera 132 , a GPS module 133 , a lidar sensor 134a , a fire detection sensor 134b , and a warning generating device 135 . ), a processor 136 and a memory 137 .

The communication module 131 may be configured to communicate with the server 110 . The camera 132 may be configured to find wild animals. The GPS module 133 may be configured to detect the current location of the drone 130 . The lidar sensor 134a may be configured to detect a fence. The fire detection sensor 134b may be configured to detect whether a fire has occurred. The alert generating device 135 may be configured to generate noise to prevent access of wild animals. The processor 136 may be a configuration for controlling the aforementioned configurations. The memory 137 may be a configuration for storing commands for controlling the aforementioned configurations. The processor 136 may control the above-described configurations based on the instructions stored in the memory 137 . The communication module 131 may transmit image data generated by the camera to the server.

In the case of the communication module 131, information is transmitted and received with a base station or a server including a communication function through an antenna. The communication module 131 may include a modulator, a demodulator, and a signal processor.

Wireless communication may refer to communication using a communication facility installed by telecommunication companies and a wireless communication network using a frequency of the communication facility. At this time, the communication module 131 is CDMA (code division multiple access), FDMA (frequency division multiple access), TDMA (time division multiple access), OFDMA (orthogonal frequency division multiple access), SC-FDMA (single carrier frequency division multiple) access), etc., may be used in various wireless communication systems, and the communication module 131 may also be used in 3rd generation partnership project (3GPP), long term evolution (LTE), and the like. In addition, not only 5G communication that is being commercialized recently, but also 6G, which is scheduled to be commercialized in the future, may be used. However, in the present specification, a pre-installed communication network may be utilized without being limited by such a wireless communication method.

The processor 136 is a component capable of performing calculations and controlling other devices. Mainly, it may mean a central processing unit (CPU), an application processor (AP), a graphics processing unit (GPU), or the like. In addition, the CPU, AP, or GPU may include one or more cores therein, and the CPU, AP, or GPU may operate using an operating voltage and a clock signal. However, a CPU or AP may consist of a few cores optimized for serial processing, whereas a GPU may consist of thousands of smaller and more efficient cores designed for parallel processing.

The processor 136 may provide or process appropriate information or functions to the user by processing signals, data, information, etc. input or output through the above-described components or driving an application program stored in the memory 137 .

The memory 137 stores data supporting various functions of the drone 130 . The memory 137 may store a plurality of application programs (application programs or applications) driven by the drone 130 , data for operation of the drone 130 , and commands. At least some of these application programs may be downloaded from an external server through wireless communication. Also, the application program may be stored in the memory 137 , installed on the drone 130 , and driven to perform an operation (or function) of the drone 130 by the processor 136 .

The memory 137 is a flash memory type, a hard disk type, a solid state disk type (SSD), a silicon disk drive type (SDD), and a multimedia card micro type. ), card-type memory (such as SD or XD memory), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read (EEPROM) -only memory), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, and an optical disk may include at least one type of storage medium. Also, the memory 137 may include a web storage that performs a storage function on the Internet.

According to FIGS. 1 and 2 , at least a portion of the first area A1 may be surrounded by a fence, and the drone 130 uses the lidar sensor 134a to photograph the fence B. Second image data can create That is, the lidar sensor 134a may generate the second image data for the fence (B). The server 110 may receive the second image data from the drone 130 , and may acquire status information on whether the fence B is abnormal based on the second image data. The server 110 may acquire state information of the fence (B) by using a vision recognition technology for an image obtained from the lidar sensor 134a.

As an example, it may be assumed that a part of the fence (B) is broken. The fence (B) is generally composed of a repeating structure. The server 110 may learn the repetitive structure of the fence B by learning the second image data. The server 110 may extract a point that is not a repetitive structure of the fence B from among the second image data, and classify the point as the following case.

(1) When a point that is not a repetitive structure is an empty space

(2) When a new, unlearned structure exists at a point that is not a repetitive structure

The server 110 may store past image data obtained from the lidar sensor 134a. When the above two cases are detected, the server 110 may load and compare past image data. As a result of the comparison, if the above two cases have a different structure from the past image data, the server 110 may define the fence B as an abnormal state. When the server 110 detects an abnormal state of the fence B, the server 110 may transmit a warning message to the manager server (not shown).

That is, the server 110 according to the present invention can detect the abnormal state of the fence through the following two steps.

(1) extracting a point that is not a repetitive structure from the second image data

(2) extracting and collating a point that is not a repetitive structure and a point corresponding to the point among past image data

(3) determining the abnormal state of the fence according to the comparison result

Also, the drone 130 may patrol the sky of the first area A1. The drone 130 may include a fire detection sensor 134b that detects whether a fire has occurred in the first area A1. The server may receive the fire occurrence information from the fire detection sensor 134b of the drone 130 and, upon receiving the fire occurrence information, transmit it to the manager server. When the drone 130 is equipped with firefighting equipment, the server 110 may control the drone 130 to suppress the fire. The fire detection sensor 134b may detect heat and/or smoke. When smoke of a certain concentration or more is detected, the server 110 may receive fire occurrence information.

In addition, the drone 130 may patrol the air over the first area A1 as well as over the second area A2 . The drone 130 may acquire third image data for the second area A2, and the server receives the third image data from the drone 130, and based on the received third image data, Habitat information can be obtained.

Since wild animals have a habit of moving within a living radius, the drone 130 may acquire movement path information by tracking the wild animals. The server 110 may learn movement path information and extract a path mainly traveled by a specific wild animal. The server 110 may derive habitat information of wild animals based on a mainly moving path. That is, the habitat information of the wild animal may be an area surrounded by a path through which the wild animal mainly moves.

According to FIG. 3 , the drone 130 has a camera 132 , a main body 139a , a wing 138a , a leg 138b , and a connector 139b connecting the camera 132 and the main body 139a. may include.

The main body 139a may be configured to include components necessary for driving the drone 130 therein. In detail, the configuration of the communication module 131 , the GPS module 133 , the processor 136 , and the memory 137 of FIG. 2 may be included in the main body 139a. In addition, the body portion 139a may include a battery (not shown) therein.

The wing part 138a is a configuration that generates propulsion force for driving the drone 130 , and the drone 130 may include a plurality of wing parts 138a. The wing portion 138a may include a propeller and an electric motor driving the propeller. The plurality of wing portions 138a included in the drone 130 may be an even number, and the corresponding wing portions 138a may rotate the propeller in opposite directions.

The leg part 138b is a configuration for supporting the drone 130 on the floor when the drone 130 lands, and may be provided in plurality for stability. The connection part 139b is a configuration for connecting the camera 132 to the body part 139a and may include a wiring therein. In addition, the power of the battery may be transmitted to the camera 132 through the wiring. In addition, the power of the battery may be transmitted to the electric motor of the wing portion 138a.

4 is a view showing a camera according to the present invention.

According to FIG. 4 , the camera 132 of the present invention may include a camera module 1320 . The camera module 1320 may generate a video image from the optical image. The camera module 1320 may include a housing including a through hole in a sidewall, a lens 1321 installed in the through hole, and a driving unit 1323 for driving the lens 1321 . The through hole may be formed to have a size corresponding to the diameter of the lens 1321 . The lens 1321 may be inserted into the through hole.

The driving unit 1323 may be configured to control the lens 1321 to move forward or backward. The lens 1321 and the driving unit 1323 may be connected in a conventionally known manner, and the lens 1321 may be controlled by the driving unit 1323 in a conventionally known manner.

In order to obtain various video images, the lens 1321 needs to be exposed to the outside of the camera module 1320 or the housing.

In particular, since the camera 132 according to the present invention has to directly photograph the first area A1, it must be located outside the housing, so a lens with strong contamination resistance is required. Therefore, the present invention is to solve this problem by proposing a coating layer for coating the lens.

Preferably, the lens 1321 may include an acrylic compound represented by the following Chemical Formula 1 on its surface; It may be coated with a coating composition containing an organic solvent, inorganic particles and a dispersing agent.

[Formula 1]

here,

n and m are the same as or different from each other, and are each independently an integer from 1 to 100,

L ₁ is a biphenylene group.

When the lens 1321 is coated with the coating composition, it can exhibit excellent water repellency and stain resistance, so even if the lens 1321 installed outside the vehicle is exposed to a polluted environment for a long time, images or images that can be used as road information are collected. can do.

The inorganic particles may be selected from the group consisting of silica, alumina, and mixtures thereof. The average diameter of the inorganic particles is 70 to 100 μm, but is not limited to the above example. After the inorganic particles are formed as a coating layer 1322 on the surface of the lens 1321 , physical strength may be improved, and the viscosity may be maintained within a certain range to increase moldability.

The organic solvent is selected from the group consisting of methyl ethyl ketone (MEK), toluene, and mixtures thereof, and preferably methyl ethyl ketone may be used, but is not limited thereto.

As the dispersant, a polyester-based dispersant may be used, and specifically, as a polyester-based dispersion stabilizer composed of a copolymer of 2-methoxypropyl acetate and 1-methoxy-2-propyl acetate, TEGO-Disperse 670 (manufacturer : EVONIK), but is not limited to the above examples and any dispersing agent apparent to those skilled in the art can be used without limitation.

The coating composition may further include a stabilizer as other additives, and the stabilizer may include a UV absorber, an antioxidant, etc., but is not limited to the above examples and may be used without limitation.

For forming the coating layer 1322, the coating composition may include an acrylic compound represented by Chemical Formula 1; organic solvents, inorganic particles and dispersants.

The coating composition may include 40 to 60 parts by weight of the acrylic compound represented by Chemical Formula 1, 20 to 40 parts by weight of inorganic particles, and 5 to 15 parts by weight of a dispersant based on 100 parts by weight of the organic solvent. In the case of the above range, a synergistic effect is expressed to the extent that the water repellency effect due to the interaction of each component has a critical significance, and when it is out of the above range, the synergistic effect is rapidly reduced or almost absent.

More preferably, the viscosity of the coating composition is 1500 to 1800 cP, and when the viscosity is less than 1500 cP, when applied to the surface of the lens 1321, it flows down and the formation of the coating layer 1322 is not easy, and it exceeds 1800 cP In this case, there is a problem in that the formation of a uniform coating layer 1322 is not easy.

[Preparation Example 1: Preparation of coating layer]

1. Preparation of coating composition

A coating composition was prepared by mixing methyl ethyl ketone with an acrylic compound represented by the following Chemical Formula 1, inorganic particles, and a dispersing agent:

[Formula 1]

here,

n and m are the same as or different from each other, and are each independently an integer from 1 to 100,

L ₁ is a biphenylene group.

A more specific composition of the antistatic composition is shown in Table 1 below.

TX1 TX2 TX3 TX4 TX5 organic solvent 100 100 100 100 100 acrylic compound 30 40 50 60 70 inorganic particles 10 20 30 40 50 dispersant One 5 10 15 20

(unit parts by weight)

2. Preparation of coating layer

The coating composition of DX1 to DX5 was applied to one surface of the lens 1321 and cured to form a coating layer 1322 .

[Experimental example]

1. Evaluation of surface appearance

Due to the viscosity difference of the coating composition, after the coating layer 1322 was prepared, a sensory evaluation was performed as to whether a uniform surface was formed. Whether or not a uniform coating layer 1322 was formed was evaluated, and evaluation was performed according to the following criteria.

○: uniform coating layer formation

×: Formation of a non-uniform coating layer

TX1 TX2 TX3 TX4 TX5 sensory evaluation Х ○ ○ ○ Х

When the coating layer 1322 is formed, if the viscosity is less than a certain viscosity, a flow occurs on the surface of the lens 1321 , and after the curing process, it is difficult to form the uniform coating layer 1322 in many cases. Accordingly, there may be a problem in that the production yield is lowered. In addition, even when the viscosity is too high, it is difficult to uniformly apply the composition to form a uniform coating layer 1322 .

2. Measurement of water repellency angle

After forming the coating layer 1322 on the surface of the lens 1321, the results of measuring the water repellency angle are shown in Table 3 below.

)advancing contact angle (

) stop contact angle (

) receding contact angle (

) TX1 117.1±2.9 112.1±4.1 < 10 TX2 132.4±1.5 131.5±2.7 141.7±3.4 TX3 138.9±3.0 138.9±2.7 139.8±3.7 TX4 136.9±2.0 135.6±2.6 140.4±3.4 TX5 116.9±0.7 115.4±3.0 < 10

As shown in Table 3, after the coating layer 1322 was formed using the coating composition of TX1 to TX5, the result of measuring the contact angle was confirmed. For TX1 and TX5, the receding contact angle was measured to be less than 10 degrees. That is, when it is out of the optimal range for preparing the coating composition, it was confirmed that the phenomenon of pinning water droplets occurs. On the other hand, it was confirmed that the peening phenomenon did not occur in TX2 to 4, thereby exhibiting an excellent waterproof effect.

3. Pollution resistance evaluation

The lens 1321 having the coating layer 1322 formed according to the embodiment on the outside of the facility was attached to the model camera, and exposed to the driving environment on a general road for 4 days. As the comparative example (Con), the same lens 1321 on which the coating layer 1322 was not formed was used, and in each embodiment, the model camera was attached to the same position of the vehicle.

Thereafter, the degree of contamination of the lens 1321 before and after the experiment was evaluated as related, and for objective comparison, the result was evaluated as an index of 1 to 10 in comparison with the comparative example in which the coating layer 1322 was not formed. shown in In the following index, the lower the number, the better the stain resistance.

Con TX1 TX2 TX3 TX4 TX5 stain resistance 10 7 3 3 3 8

(Unit: Index)

Referring to Table 4, when the coating layer 1322 is formed on the lens 1321, the high contamination resistance is easily analyzed for a long period of time even when the lens 1321 is exposed to the outside while the camera is installed in an external environment. It can be seen that image data can be collected. In particular, in the case of TX2 to TX4, it can be seen that the stain resistance by the coating layer 1322 is very excellent.

5 is a view showing a function module stored in a memory according to the present invention.

5, the memory according to the present invention includes a vision recognition module 1371, a noise generation module 1372, a fence abnormality detection module 1373, a fire detection module 1374, and a wild animal habitat information generation module 1375. may include

The vision recognition module 1371 may recognize a wild animal from the first image data. The vision recognition module 1371 may include data obtained by learning raw data about wild animals expected to exist in the vicinity of the first area A1 . The vision recognition module 1371 may extract or recognize a wild animal based on the learned data from the first image data. When it is determined by the vision recognition module 1371 that the wild animal is located near the fence (B in FIG. 1, hereinafter the same) of the first area (A1 in FIG. 1, hereinafter the same), the noise generating module 1372 is configured in advance. Noise can be generated using the stored noise data. That is, the noise generating module 1372 may generate noise by transmitting the noise data to the warning generating device 135 of FIG. 2 .

The fence abnormality detection module 1373 may detect an abnormal state of the fence B based on the second image data. The fence abnormality detection module 1373 receives the second image data from the lidar sensor (134a in FIG. 2, hereinafter the same), extracts a point different from the repeated structure based on the second image data, and in advance with the point It is possible to detect an abnormal state of the fence by comparing it with the stored fence (B) image. The fence abnormal state detection method is the same as described above, and thus will be omitted.

The fire detection module 1374 may detect whether a fire has occurred based on a detection value received from the fire detection sensor (134b of FIG. 2 , hereinafter the same).

The wild animal habitat information generation module 1375 may generate information on the habitat of the wild animal based on the information on the second area (A2 of FIG. 1 , hereinafter the same) from the third image data. The habitat information generation method is the same as the above description, and thus will be omitted.

6 is a flowchart illustrating a method for preventing invasion of wild animals using a drone according to the present invention.

According to FIG. 6 , the method according to the present invention includes obtaining image data from a drone including a camera (S1100), recognizing a vision of a wild animal from the image data (S1200), and a drone to prevent invasion of wild animals It may include a step (S1300) of controlling the.

In this case, the drone including the camera may be the drone 130 described with reference to FIGS. 1 to 3 described above, and the subject performing the method according to the present invention may be the server 110 of FIG. 1 .

Among the contents of FIG. 6 , contents identical to or overlapping with those described above will be omitted.

The present invention described above can be modeled as computer readable code on a medium in which a program is recorded. The computer-readable medium includes all types of recording devices in which data readable by a computer system is stored. Examples of computer-readable media include Hard Disk Drive (HDD), Solid State Disk (SSD), Silicon Disk Drive (SDD), ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage device, etc. It also includes modeling in the form of a carrier wave (eg, transmission over the Internet). Accordingly, the above detailed description should not be construed as restrictive in all respects but as exemplary. The scope of this specification should be determined by a reasonable interpretation of the appended claims, and all modifications within the equivalent scope of this specification are included in the scope of this specification.

Any or other embodiments of the present invention described above are not mutually exclusive or distinct. Any of the above-described embodiments or other embodiments of the present invention may be combined or combined with each configuration or function.

The above detailed description should not be construed as restrictive in all respects and should be considered as illustrative. The scope of the present invention should be determined by a reasonable interpretation of the appended claims, and all modifications within the equivalent scope of the present invention are included in the scope of the present invention.

100: system
110: server
130: drone
A1: Area 1
A2: Area 2

Claims (8)

a drone for acquiring first image data of a first area; and
A server that detects a wild animal that has invaded the first area based on the first image data; including,
The server is
Controlling the drone in order to prevent the invasion of the wild animal, the wild animal invasion prevention and management system using a drone.
According to claim 1,
The drone further comprises a warning generating device for generating noise,
The drone is to prevent the invasion of the wild animal by using the noise, the wild animal invasion prevention and management system using the drone.
According to claim 1,
at least a portion of the first area is surrounded by a fence,
The drone further includes a lidar sensor that generates second image data for the fence,
The server receives the second image data, and acquires status information on whether or not the fence is abnormal based on the second image data, Wild animal invasion prevention and management system using a drone.
According to claim 1,
The drone is
Further comprising a fire detection sensor for detecting whether a fire has occurred in the first area,
The server is to obtain information on whether the fire has occurred from the fire detection sensor, wild animal invasion prevention and management system using a drone.
According to claim 1,
The drone is
A camera for generating the first image data,
The camera is
A camera module that generates a video image from an optical image; includes,
The camera module,
a housing including a through hole in the sidewall;
a lens installed in the through hole; and
A drive unit for driving the lens; which includes, a wildlife invasion prevention and management system using a drone.
According to claim 1,
The drone is
acquiring third image data for a second region other than the first region;
The server is
A system for preventing and managing wildlife invasion using a drone, which acquires habitat information of the wild animal based on the third image data.
acquiring image data from a drone including a camera;
vision-recognizing a wild animal from the image data; and
Controlling the drone to prevent invasion of the wild animal;
A non-transitory computer-readable medium having stored thereon instructions, comprising:
The non-transitory computer-readable medium, wherein the instructions, when executed by a processor, cause the processor to perform the method of claim 7 .

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