KR101984983B1 - System and method for monitoring wild animals - Google Patents

Abstract

A wildlife monitoring system and method are disclosed.
The wildlife monitoring system according to an embodiment of the present invention generates image data of wild animals captured and distributed in a habitat of wild animals and displays meta information based on photographing conditions and habitat information detected in habitats The monitoring terminal analyzes the image data collected by the monitoring terminal, recognizes the animal information, extracts meta information of the image data, and matches the obtained environment information with the animal information to generate monitoring data And the like.

Description

[0001] SYSTEM AND METHOD FOR MONITORING WILD ANIMALS [0002]

The present invention relates to a wildlife monitoring system and a method thereof, and more particularly, to a wildlife monitoring system and a method for analyzing ecological information of an animal in a wide range of wildlife through a camera-based monitoring terminal.

In general, wild animals are animals that grow and grow in their native habitat, and their habitat is natural. However, with the destruction of habitat by human activity worldwide, wildlife survival conditions are becoming poorer, which is increasing the number of animals that are already extinct or endangered.

In order to manage wildlife habitat and plan for species restoration, it is important to know the status of wildlife populations, geographical distribution, habitat types and endangered animals through long-term monitoring.

Therefore, interest in wildlife monitoring is increasing in Korea, and studies on changes in wild animal populations and habitat conditions are being carried out.

On the other hand, conventional wildlife monitoring methods are performing image-based monitoring by dispersing and installing unattended cameras due to the fact that wild animals live widely in mountains and fields.

More specifically, the images captured in the memory of the unmanned camera installed in the wildlife habitat of the whole country are collected, and the researchers confirm the type of the wild animal and input the information of the form environment into the computer by hand As shown in FIG.

However, the conventional monitoring method has the disadvantages that the researchers individually check the vast amount of images collected from the cameras distributed in the national habitat, which are tens / hundreds of giga or tens / millions of sheets, .

In other words, conventionally, a large number of monitoring data is difficult to be written by a researcher, and the processing time and cost of a large amount of data increase, and human errors may occur due to the load of the work. There is a problem that it may fall.

The matters described in the background section are intended to enhance the understanding of the background of the invention and may include matters not previously known to those skilled in the art.

The embodiment of the present invention can extract the recognition information and the format environment information of wild animals from the image data collected from the monitoring terminal distributed in the habitat and automatically generate the standardized monitoring data and analyze the ecological information of the animal based thereon A wildlife monitoring system and a method therefor.

According to an aspect of the present invention, there is provided a wildlife monitoring system, comprising: image data obtained by photographing wild animals dispersed and installed in habitats of wild animals; and a meta data based on photographing conditions and habitat information The monitoring terminal analyzes the image data collected by the monitoring terminal, recognizes animal information, extracts meta information of the image data, and matches the obtained environment information with the animal information to generate monitoring data And a server for generating the server.

The meta information may include at least one of a photographing condition including a date, a time, a location, a direction, and a distance to the subject of the image data, and a habitat environment information of an altitude, an amount of sunshine, a moonlight, a temperature, a humidity, .

The monitoring terminal may include: a communication module that transmits and receives data to and from the server through a wireless communication network; An animal detection module for detecting the wild animal through a motion detection sensor or a heat detection sensor; A camera module for photographing the detected wildlife and acquiring the image data; An environment sensor module for measuring the environment information of the habitat through an automatic weather observation device; A memory for storing image data of the wild animals; And a control module for receiving photographing conditions of the camera module and the format environment information as meta information of the image data and transmitting the meta information through the communication module.

In addition, the control module adjusts the pixel area of the wild animal occupying the entire pixel area of the image data at a predetermined ratio by adjusting zoom in or zoom out according to the distance between the camera module and the wild animal.

The control module may delete the image data from the memory upon receiving a response message (ACK) in response to completion of reception of the image data from the server.

In addition, the control module may detect an animal of interest attached with the position-tracking device through the communication module, and send an interest animal occurrence event including at least one of movement information of the animal of interest and biometric data to the server To the terminal.

The server may further include an information collecting unit collecting image data from the monitoring terminal; An image processing unit for deleting the background by preprocessing the image data and extracting an animal image necessary for wildlife recognition; A meta information extracting unit for extracting meta information of at least one of date, time, location, direction, distance of the object, altitude of the habitat, daylight, moonlight, temperature, humidity, An animal recognition unit for recognizing the animal information by grasping the animal image through image matching with an animal recognition model; A database storing various programs and data for monitoring the wild animals; And a controller for adding animal detail information based on the habitat information to the animal information and matching the environmental information of the habitat to generate wildlife monitoring data according to a standardized format used in the wild animal analysis program.

The image processing unit may extract an outline of the animal from the original image of the image data to delete the background, and may divide the animal image into a plurality of animal images that are dependent on the original image when a plurality of wild animals exist.

In addition, the animal recognition unit may generate the animal recognition model by linking and learning various animal image characteristic information of an animal species and an animal's morphological characteristic information through a synthetic neural network.

The animal image characteristic information may include at least one of wild animal head, eyes, nose, mouth, tongue, ear, horn, torso, leg, tail, skin color, hair color, hair pattern, size, .

In addition, the format characteristic information may include at least one of an area of an animal species, a habitat environment, an activity time, a hibernation, and a cluster characteristic.

In addition, the animal information may include at least one of animal type, age, sex, and disease state.

In addition, the controller may accumulate the monitoring data in the database to generate RO data to be used for ecological environment analysis of wild animals.

In addition, the control unit may determine at least one of wildlife habitat utilization, species habitat share, habitat density inference, population change, endangered species number, common infectious disease infection status, and habitat evaluation based on accumulated data of the monitoring data One ecological information can be analyzed.

In addition, the control unit alerts the relevant researchers when the animal of interest animal event is received from the monitoring terminal, and requests the monitoring terminal for the image data and the biometric data.

In addition, if the video data is not collected for a certain period of time after the video data is finally collected at the monitoring terminal, or if the video data is not received after the video data is requested, the controller determines that the video data is a failure event, .

According to another aspect of the present invention, there is provided a method for monitoring wild animals by a server for monitoring wild animals through a monitoring terminal installed in a habitat of wild animals, comprising the steps of: a) Collecting; b) extracting photographing conditions and environment information from meta information included in the image data; c) comparing the animal image of the image data with an animal recognition model to recognize animal information through image matching; And d) generating the monitoring data according to the standardized format used in the wild animal analysis program by matching the animal information with the photographing condition and the format environment information.

The meta information may include a date, a time, a location, a direction, a distance of the subject, and altitude, sunshine, moonlight, temperature, humidity, and precipitation according to the photographing condition.

In addition, in the step c), if the animal information of the animal image fails to be recognized, the step of updating the animal recognition model by linking the characteristic information of the animal information inputted to the researcher and the characteristic information of the habitat through the synthesis neural network .

Further, after the step d), updating the monitoring data in the database to construct log data to be used for ecological environment analysis of wild animals; And analyzing at least one ecological information among the wildlife habitat utilization by region, habitat share of species, habitat density inference, population variation, endangered species population, infectious common infectious disease infection state, and habitat assessment based on the geographical data .

According to the embodiment of the present invention, the image data collected by the server managing the monitoring terminal distributed in the nationwide habitat is automatically analyzed to collect the wildlife and collect the monitoring data by collecting the monitoring data, The data can be efficiently processed.

In addition, the above monitoring data can be standardized to support linkage analysis of data with a specialized program for the ecological analysis of wild animals by constructing and sharing RO data based on analysis of ecological environment of wild animals.

In addition, we construct an animal recognition model for recognition of wildlife information through synthetic neural network, and analyze the image data by linking characteristic information of hair loss, skin discoloration, It is possible to detect the disease of an animal species early and to grasp the extent of spread by region.

In addition, effects obtainable or predicted by the embodiments of the present invention will be directly or implicitly disclosed in the detailed description of the embodiments of the present invention. That is, various effects to be predicted according to the embodiment of the present invention will be disclosed in the detailed description to be described later.

1 is a network diagram schematically showing a wildlife monitoring system according to an embodiment of the present invention.
2 is a block diagram schematically illustrating a configuration of a monitoring terminal according to an embodiment of the present invention.
FIG. 3 shows a state in which the monitoring terminal senses the appearance of an animal of interest according to an embodiment of the present invention.
4 is a block diagram schematically illustrating a configuration of a server according to an embodiment of the present invention.
5 illustrates a process of preprocessing image data of an image processing unit according to an embodiment of the present invention.
FIG. 6 schematically shows an animal recognition model learning method according to an embodiment of the present invention.
FIG. 7 shows a process of generating wildlife monitoring data based on image data according to an embodiment of the present invention.
8 is a flowchart schematically illustrating a wildlife monitoring method according to an embodiment of the present invention.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily carry out the present invention. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein. In order to clearly illustrate the present invention, parts not related to the description are omitted, and similar parts are denoted by like reference characters throughout the specification.

Throughout the specification, when an element is referred to as " comprising ", it means that it can include other elements as well, without excluding other elements unless specifically stated otherwise. Also, the terms " part, " " module, " and " module ", etc. in the specification mean a unit for processing at least one function or operation and may be implemented by hardware or software or a combination of hardware and software have.

Now, a wildlife monitoring system according to an embodiment of the present invention will be described in detail with reference to the drawings.

1 is a network diagram schematically showing a wildlife monitoring system according to an embodiment of the present invention.

Referring to FIG. 1, a wildlife monitoring system according to an embodiment of the present invention includes a plurality of monitoring terminals 10 distributed in wildlife habitats throughout the country, And a server 20 for extracting recognition information and environment information and generating wildlife monitoring data.

The surveillance terminal 10 is installed in a habitat of wild animals to photograph the surrounding wild animals to generate image data, and stores meta information based on the photographing conditions and the habitat information detected in the habitat, Communication.

The surveillance terminal 10 may be mounted on a front end of a support vertically installed on the ground, but not limited thereto, and may be installed in a facility (structure) installed in a tree or a wild area.

The server 20 detects the animal image from the image data collected from the monitoring terminal 10, recognizes the animal information referring to the animal recognition model, extracts the meta information of the image data, Matches animal information to generate monitoring data for analysis of wildlife ecology.

The server 20 constructs a database (DB) based on the monitoring data and analyzes the geographical distribution of wild animals, population density, habitat type, disease state, emergence of new species (exotic species) Lt; / RTI >

The server 20 can provide the DB constructed with the monitoring data and the analysis information to the related institution server 30. For example, the related institution server 30 may be a government agency or an environmental research agency responsible for the development of the area such as a city and a road.

2 is a block diagram schematically showing the configuration of a monitoring terminal according to an embodiment of the present invention.

2, the monitoring terminal 10 according to the embodiment of the present invention includes a communication module 11, an animal detection module 12, a camera module 13, an environmental sensor module 14, a memory 15 And a control module 16.

The communication module 11 transmits and receives data to and from the server 20 through the wireless communication network connected to the base station with the communication identification information (ID) of the monitoring terminal 10.

The communication module 11 can transmit the image data photographed by the monitoring terminal 10 to the server 20 and receive the response message (ACK) from the server 20 in response to the completion of the reception of the image data.

Also, the communication module 11 can request real-time image data of the server 20 and receive a control command for setting the operation of the monitoring terminal 10. [

The communication module 11 may include at least one of a mobile communication (2G, 3G, 4G, etc.), a wireless LAN (WIFI), and a low power wide area communication (LPWAN).

The communication module 11 communicates with the object Internet (IoT) -based location tracking device (e.g., VHF, CDMA, RFID, GPS, etc.) attached to the wildlife to observe not only the communication with the server 20, And a transceiver that collects animal movement information and biometric data.

The animal detection module 12 includes a motion detection sensor and a heat detection sensor to detect the wild animals appearing in the surroundings where the monitoring terminal 10 is installed.

The camera module 13 photographs the wildlife detected by the animal detection module 12 through the image sensor and acquires image data. The image data includes a photograph and a moving image.

The camera module 13 photographs in the daytime mode and the nighttime mode according to the surrounding brightness, and can zoom in / zoom out through the optical system.

Also, the camera module 13 is mounted on a mechanism capable of rotating 360 degrees, and can recognize a photographing direction rotated through a gyro, and can measure the distance to a subject (wild animal) through a laser.

The environmental sensor module 14 may be configured as a simple automatic weather observation device (AWS) that measures at least one of the habitat information of the habitat on which the monitoring terminal 10 is installed, the amount of sunshine, moonlight, temperature, humidity, .

The memory 15 stores programs and data for operation of the monitoring terminal 10 and stores information generated according to the operation of the monitoring terminal 10. [

The memory 15 includes a flash memory card for storing image data of wild animals photographed by the camera module 13. The image data whose transmission to the server 20 is completed and a response message (ACK) is received is deleted .

The control module 16 may comprise a microcontroller unit (MCU) for controlling the overall operation of the monitoring terminal 10. [

The control module 16 tracks the wildlife detected by the animal detection module 12 with the camera module 13 and captures the image data of the captured wildlife.

At this time, the control module 16 adjusts the pixel area (size) of the wild animal occupying the entire pixel area of the image data to a predetermined ratio by controlling zooming in or zooming out according to the distance between the camera module 13 and the wild animal (subject) . For example, if the subject distance from the camera module 13 is 30 m, it may be difficult to recognize the animal species if the size of the subject is too small compared to the entire area of the image, so that the size of the subject can be enlarged by the predetermined ratio .

The control module 16 stores one image file generated by recording the photographing condition of the camera module 13 and the format environment information measured by the environmental sensor module 14 in the meta information into the image data, To the server (20).

Here, the photographing condition may include a date, a time, a location (coordinate), a direction, and a distance of the subject, and the habitat environment information may be an altitude, an amount of sunshine, a moonlight, a temperature, a humidity,

Thereafter, when the control module 16 receives a response message (ACK) in response to the completion of reception of the image data from the server 20, the control module 16 deletes the corresponding image data, which has been transmitted, from the memory 15 to secure a free storage space .

Meanwhile, FIG. 3 shows a state in which the surveillance terminal according to the embodiment of the present invention senses the appearance of an animal of interest.

Referring to FIG. 3, the control module 16 according to the embodiment of the present invention includes a communication module 11 (for example, ), And collects biometric data such as movement information of the animal of interest, body temperature and pulse. In addition, the distance m to the subject (wild animal) sensed by the camera module 13 and the moving speed (m / h) of the sensed subject can be measured.

Then, the control module 16 can transmit an event of interest animal including the collected information to the portable terminal of the server 20 and the related researcher to alert them.

At this time, the tag is attached to the neck or ear of a care animal such as a bear, a goat, and a mare, which requires research on an ecosystem, and is equipped with a communication device for tracking the position of the animal of interest, And a sensor for measuring the same bio-signal.

4 is a block diagram schematically illustrating a configuration of a server according to an embodiment of the present invention.

4, the server 20 according to the embodiment of the present invention includes an information collecting unit 21, an image processing unit 22, an animal recognizing unit 23, a meta information extracting unit 24, a database 25 and a control unit 26. [

The information collecting unit 21 includes a wired / wireless communication module and collects image data photographed by the monitoring terminal 10 distributed around the whole country for monitoring wild animals.

The information collecting unit 21 collects image data at a predetermined cycle from the monitoring terminal 10 or non-periodically collect image data at the time of occurrence of a wild animal. In addition, if necessary, the monitoring terminal 10 can request the transmission of image data to collect image data in real time.

The image processing unit 22 deletes the background by preprocessing the image data and extracts an animal image necessary for wild animal recognition.

5 illustrates a process of preprocessing image data of an image processing unit according to an embodiment of the present invention.

Referring to FIG. 5, an information collecting unit 21 according to an embodiment of the present invention shows a state in which two image data of a half-moon bear are photographed.

The image processing unit 22 extracts the outline of the animal from the collected image data (hereinafter referred to as an original image for the sake of convenience) and deletes the unnecessary background (S1).

The image processing unit 22 divides the wild type image into a plurality of wild animal images depending on the original image when a plurality of wild animals exist in one original image (S2).

That is, the original image in which two birds are present can be divided into a first animal image and a second animal image, respectively, in accordance with the number of the birds.

The animal recognition unit 23 recognizes the animal information by grasping the animal image extracted from the image data through image matching with the animal recognition model. The animal information may include an animal type, an age (month number), a sex, and a disease state through the animal recognition model.

Here, the animal recognition model refers to information modeled for animal species recognition through deep learning.

FIG. 6 schematically shows an animal recognition model learning method according to an embodiment of the present invention.

Referring to FIG. 6, an animal recognition unit 23 according to an embodiment of the present invention includes various animal image characteristics information (animal shape parameters) and animal morphology information (geographical information Environment information) in advance through a synthetic neural network to generate an animal recognition model, and stores the animal recognition model in the database 25 to construct animal image analysis data.

The animal image characteristic information is visual information related to the appearance of the animal and is a visual information related to the appearance of the animal such as the head, eyes, nose, mouth, tongue, ear, horn, torso, leg, tail, skin color, hair color, Specific posture. Such animal image characteristic information includes visual information according to an animal species sex (eg, presence of horns), age (eg, size relative to adult) and disease state (eg, hair loss, skin discoloration, appearance variation) .

The habitat information of the animal includes an animal species habitat, habitat environment, activity time, hibernation, community characteristics, and the like.

Particularly, when the animal recognition unit 23 generates an animal recognition model for recognizing animal information, the reason for learning the animal's morphological characteristics information is that the extracted animal image is photographed at night, This is to compensate for the low recognition rate due to insufficient image characteristic information.

For example, animal image characteristics are concentrated in the head, whereas when the hips are photographed, the matching rate with the animal recognition model may be low and the recognition may fail.

Therefore, when the matching rate (for example, 70%) of the animal image characteristic information is less than the animal recognition standard (for example, 80%), the animal recognition unit 23 recognizes the learned animal species , The animal species can be estimated automatically considering the activity season and time.

Accordingly, the animal recognition unit 23 can acquire the advantage of improving the recognition success rate of the animal image captured at night and at various angles through the animal recognition model that is learned by combining the animal image characteristic information and the animal form characteristic information with the input information .

On the other hand, the meta-information extracting unit 24 extracts the meta-information extracted from the captured image data based on the captured date, time, position (coordinate), direction, distance of the subject, altitude, hatching amount, moonlight, temperature, humidity, And automatically extracts the meta information of the user.

The meta information extracting unit 24 may be a program for extracting meta information recorded in an EXIF (exchangeable image file format) format. When the image data is collected, the meta information extracting unit 24 extracts meta information from the original and stores the meta information in the database 25 .

The database 25 stores various programs and data for monitoring wild animals according to an embodiment of the present invention, and stores the data generated through the monitoring of wild animals into data.

The control unit 26 controls the overall operation of the respective units for wildlife monitoring according to an embodiment of the present invention.

The control unit 26 matches the animal information identified in the animal image of the image data with the environmental information of the habitat contained in the meta information and generates wildlife monitoring data in a standardized format according to the wild animal analysis program. At this time, the generated wildlife monitoring data serves as a basis for raw data used in a wildlife ecological environment analysis program.

FIG. 7 shows a process of generating wildlife monitoring data based on image data according to an embodiment of the present invention.

7, the controller 26 according to the embodiment of the present invention selects image data collected from the monitoring terminal 10 for image data analysis, And meta information including habitat environment information. The control unit 26 recognizes the animal information through image matching of the animal image extracted through the image processing unit 22 and the animal recognition model. The habitat environment information may be referred to the animal information recognition.

The control unit 26 generates a monitoring data name by combining the terminal ID, the animal, the date, and the time of the image data.

The control unit 26 extracts animal detail information based on the animal information and the habitat information from the DB 25 and adds the extracted information. For example, an animal name, a phylogenetic tree, a legal status (a protected species classification), an animal ID, an alias, and an individual characteristic according to animal information can be added. In addition, GPS coordinates, topographic features, and forest environment (eg, coniferous forest, broadleaved forest, etc.) can be added according to the habitat environment information.

The control unit 26 collects animal information, habitat information extracted from the image data, and animal detailed information further extracted from the DB 25 to generate standardized monitoring data.

The control unit 26 records the extracted information in accordance with the standardized format of the monitoring data, and accumulates the information in the DB 25, thereby generating RO data to be used for the ecological environment analysis of wild animals.

Thereafter, the control unit 26 analyzes the RO data stored in the DB 25 to evaluate ecological information such as a wildlife population variation, an endangered species number, a common infectious disease infection state, and a habitat evaluation.

On the other hand, when receiving the event of interest animal appearance from the monitoring terminal 10, the control unit 26 alerts the corresponding researcher, requests the monitoring terminal 10 for image data and biometric data, and generates monitoring data based on the collected information .

The control unit 26 may monitor the operation status by requesting the test image data if the image data is not collected for a certain period of time after the last image data is collected from the monitoring terminal 10.

If the control unit 26 does not receive the video data from the monitoring terminal 10 after the test video data is requested, the control unit 26 may determine that the event is a failure event and alert the operator. At this time, the researcher can request maintenance of the monitoring terminal 10 and generate monitoring data by copying the image data stored in the memory.

A method for monitoring wild animals according to an embodiment of the present invention will now be described with reference to FIG. 8 based on the above-described wildlife monitoring system. In the flow of monitoring the monitoring terminal 10 and the server 20 .

8 is a flowchart schematically illustrating a wildlife monitoring method according to an embodiment of the present invention.

Referring to FIG. 8, a monitoring terminal 10 according to an exemplary embodiment of the present invention captures wildlife through a camera module 13 to acquire image data (S101).

The monitoring terminal 10 measures at least one of the habitat environment information of the habitat, the amount of sunshine, moonlight, temperature, humidity, precipitation, and altitude through the environmental sensor module 14 (S102).

The monitoring terminal 10 stores the photographing conditions of the camera module 13 and the above-described environment information as meta information of the image data (S103) and transmits the meta information to the server 20 through the communication module 11 (S104) .

When receiving the image data transmitted from the monitoring terminal 10, the server 20 transmits a response message (ACK) according to the completion of the reception of the image data to the monitoring terminal 10 (S105). At this time, the monitoring terminal 10 can delete the image data according to the reception of the response message (ACK) of the server 20 from the memory 15.

Meanwhile, the server 20 extracts the meta information included in the image data received from the monitoring terminal 10 (S106). At this time, the server 20 extracts meta information such as date, time, location (coordinate), direction of the subject, distance of the subject, altitude of the habitat, daylight, moonlight, temperature, humidity, can do.

The server 20 deletes the background through the preprocessing of the image data and extracts an animal image necessary for wild animal recognition (S107). At this time, if there are a plurality of objects in the original image of the image data, a plurality of divided animal images depending on the original image may be extracted.

The server 20 compares the extracted animal image with an animal recognition model and attempts to recognize the animal information through image matching (S 108). In animal information recognition using the animal recognition model, an image characteristic of an animal and the habitat environment information can be referred to.

If the matching rate between the animal image and the animal recognition model satisfies the reference value and the animal information is successfully recognized (S109; YES), the server 20 inquires of the database 25 the animal detail information based on the animal information and the habitat information (S112).

For example, the server 20 stores the GPS coordinates, the topographic features, and the forest environment according to the animal information, such as animal name, system classification, legal status (protection classification), animal ID, It can be extracted as detailed information.

The server 20 collects animal information, habitat information extracted from the meta information of the image data, and animal detailed information further extracted from the DB 25 to generate standardized monitoring data (S113).

The server 20 updates monitoring data created in conformity with the standardized format to the DB 25 to construct log data used for analyzing the ecological environment of wild animals (S114).

Thereafter, the server 20 analyzes the RO data stored in the DB 25 (S115), and the server 20 analyzes the RO data stored in the DB 25 (S115), and determines whether the wildlife habitat utilization rate, species habitat share, habitat density inference, population variation, Ecological information such as infection status and habitat evaluation can be evaluated.

If it is determined that the matching rate of the animal image and the animal recognition model is less than the set reference value (S109: NO), the server 20 receives the animal information confirmed by the researcher (S110) Step S112 may be performed.

At this time, the server 20 learns the characteristic information of the animal image confirmed to the researcher due to the failure of recognition of the animal information and the habitat characteristic information corresponding thereto through the synthetic neural network (S111), and updates the animal recognition model. The updated animal recognition model can be used for analyzing animal images in the future, thereby improving the recognition performance of animal information.

In addition, animal image analysis data constructed with animal recognition models can be used to identify uninhabited alien species, regional spread, and disturbance information of native ecosystems.

As described above, according to the embodiment of the present invention, wildlife is automatically recognized by analyzing image data collected from a server that manages a monitoring terminal distributed nationwide and collected with the form environment information to generate monitoring data, The data can be efficiently processed.

In addition, by standardizing the monitoring data and establishing data as a basis for analyzing the ecological environment of wild animals, it is effective to support linkage analysis of the data with the specialized program for the analysis of wild animals.

In addition, we construct an animal recognition model for recognition of wildlife information through synthetic neural network, and analyze the image data by linking characteristic information of hair loss, skin discoloration, It is possible to detect the disease of an animal species early and to grasp the extent of spread by region.

The embodiments of the present invention are not limited to the above-described apparatuses and / or methods, but may be implemented through a program for realizing functions corresponding to the configuration of the embodiment of the present invention, a recording medium on which the program is recorded And such an embodiment can be easily implemented by those skilled in the art from the description of the embodiments described above.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, It belongs to the scope of right.

10: Monitoring terminal 11: Communication module
12: Animal detection module 13: Camera module
14: environmental sensor module 15: memory
16: control module 20: server
21: Information collecting unit 22: Image processing unit
23: Animal recognition unit 24: Meta information extraction unit
25: Database (DB) 26:
30: Related institution server

Claims (20)

The method of claim 1, further comprising the steps of: generating image data of a wild animal distributed in a habitat of wild animals, wherein the photographing condition includes a date, time, location, direction and distance to the subject measured in the image data; A monitoring terminal for storing meta information based on format environment information including altitude, daylight, moonlight, temperature, humidity, and precipitation, and transmitting the meta information to wireless communication; And
A monitoring server for analyzing the image data collected by the monitoring terminal to recognize animal information and for generating monitoring data by matching the photographing condition and the form environment information obtained by extracting the meta information from the image data to the animal information,
Lt; RTI ID = 0.0 > a < / RTI > delete The method according to claim 1,
The monitoring terminal includes:
A communication module for transmitting and receiving data to and from the server through a wireless communication network;
An animal detection module for detecting the wild animal through a motion detection sensor or a heat detection sensor;
A camera module for photographing the detected wildlife and acquiring the image data;
An environment sensor module for measuring the environment information of the habitat through an automatic weather observation device;
A memory for storing image data of the wild animals; And
A control module for receiving photographing conditions of the camera module and the format environment information as meta information of the image data and transmitting the meta information through the communication module;
Lt; / RTI > The method of claim 3,
The control module includes:
And controlling zooming in or zooming out according to a distance between the camera module and a wild animal to adjust a pixel area of a wild animal occupying an entire pixel area of the image data at a predetermined ratio. The method of claim 3,
The control module includes:
And deletes the image data from the memory upon receiving a response message (ACK) in response to completion of reception of the image data from the server. The method of claim 3,
The control module includes:
A wildlife animal monitoring unit that detects an animal of interest attached with the position tracking device through the communication module and transmits an animal animal appearance event including at least one of movement information of the animal of interest and biometric data to the terminal of the server and the related researcher system. The method according to claim 1,
The server comprises:
An information collecting unit for collecting image data from the monitoring terminal;
An image processing unit for deleting the background by preprocessing the image data and extracting an animal image necessary for wildlife recognition;
A meta information extracting unit for extracting meta information of at least one of date, time, location, direction, distance of the object, altitude of the habitat, daylight, moonlight, temperature, humidity,
An animal recognition unit for recognizing the animal information by grasping the animal image through image matching with an animal recognition model;
A database storing various programs and data for monitoring the wild animals; And
A control unit for adding animal detail information based on the habitat information to the animal information and for matching the environmental information of the habitat and generating wildlife monitoring data in accordance with a standardized format used in the wild animal analysis program;
Lt; RTI ID = 0.0 > a < / RTI > 8. The method of claim 7,
Wherein the image processing unit comprises:
Extracting an outline of an animal from an original image of the image data to delete a background, and dividing the image into a plurality of animal images that are dependent on the original image when a plurality of wild animals exist. 8. The method of claim 7,
The animal recognition unit may include:
A wild animal monitoring system for generating the animal recognition model by linking various animal image characteristic information and animal morphological characteristic information of an animal species through a synthetic neural network. 10. The method of claim 9,
Wherein the animal image characteristic information comprises:
A wildlife monitoring system comprising at least one of a wild animal's head, eyes, nose, mouth, tongue, ear, horn, torso, leg, tail, skin color, hair color, hair pattern, size, 10. The method of claim 9,
Wherein the format property information comprises:
A wildlife monitoring system comprising at least one of an animal species-specific region, a habitat environment, an activity time, hibernation, and a community characteristic. 8. The method of claim 7,
The animal information includes:
A wildlife monitoring system comprising at least one of animal species, age, sex, and disease state. 8. The method of claim 7,
Wherein,
Wherein the monitoring data is accumulated in the database to generate log data for use in analysis of ecological environment of wild animals. 8. The method of claim 7,
Wherein,
Based on the accumulated data of the monitoring data, at least one of the ecological information of wildlife habitat utilization, species habitat share, habitat density inference, population change, endangered species, accepting common infectious disease infection, and habitat evaluation is analyzed Wildlife Monitoring System. 8. The method of claim 7,
Wherein,
And an alarming device for alarming the related researchers when the animal of interest is received from the monitoring terminal and requesting the monitoring terminal for the image data and the biometric data. 8. The method of claim 7,
Wherein,
Wherein the monitoring terminal determines that the video data is not collected for a certain period of time after the video data is collected last time or if the video data is not received after the video data is received, it is determined as a failure event and the operator is alerted. A method for monitoring a wild animal by a server for monitoring a wild animal through a monitoring terminal distributed in a wildlife habitat,
a) collecting image data of wild animals taken from a monitoring terminal by wireless communication;
b) photographing conditions including the date, time, location, direction, distance to the subject, and altitude, sunshine, moonlight, temperature, humidity, and precipitation detected in the habitat are included in the meta information included in the image data Extracting the format environment information;
c) comparing the animal image of the image data with an animal recognition model to recognize animal information through image matching; And
d) generating the monitoring data according to the standardized format used in the wild animal analysis program by matching the animal information with the photographing condition and the format environment information
≪ / RTI > delete 18. The method of claim 17,
The step c)
And if the animal information of the animal image fails to be recognized, the animal information model is updated by associating the characteristic information of the animal information inputted to the researcher with the characteristic information of the habitat through the synthetic neural network. 18. The method of claim 17,
After the step d)
Updating the monitoring data in a database to construct log data for analysis of ecological environment of wild animals; And
Analyzing at least one ecological information among the wildlife habitat utilization by region, habitat share of species, habitat density inference, population variation, endangered species population, infection common infectious disease infection state, and habitat assessment based on the above data
≪ / RTI >

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