KR102371909B1 - Smart farm crop monitoring method and system using drones - Google Patents

Abstract

The present invention comprises the steps of starting a flight according to a plurality of designated moving points in a crop area, detecting an abnormal target using a crop monitoring sensor provided while moving from a first point to a second point of the plurality of moving points; Flying from the current flight position between the first point and the second point to the abnormal target according to the detection of the abnormal target, and the crop abnormal information including the photographed image and the position information including the abnormal target Transmitting through wireless communication It relates to a smart farm crop monitoring method and monitoring system using a drone, comprising the steps.

Description

Smart farm crop monitoring method and monitoring system using drones {SMART FARM CROP MONITORING METHOD AND SYSTEM USING DRONES}

The present invention relates to a smart farm crop monitoring method and monitoring system using a drone, and more specifically, by using a drone flying in a farm area to monitor the growth status and pest status of crops, and to manage the status of the crops accordingly. It relates to a smart farm crop monitoring method and monitoring system using a drone.

A lot of automation is taking place in the secondary and tertiary industries. In the manufacturing and service industries, various processes and processes are being automated using robots, automated devices, artificial intelligence devices, and the like.

Various automation attempts are being made in the primary industries of agriculture and forestry, but there are no results and a lot of human involvement is still required. In particular, crops or fruits such as rice, barley, wheat, apples and pears (hereinafter referred to as 'crops') require continuous growth management and protection.

For example, a farmer (a farmer or manager) sows seeds of rice, barley, wheat, etc., and takes various management activities to ensure the normal growth of rice, barley, and wheat during germination and growth. Farmers spray pesticides on crops at designated times to remove weeds or reduce pests and pests. For these various activities, farmers must constantly visit farms or orchards where crops are grown.

In particular, when a crop is damaged by pests or there is a problem with its growth, the crop's crop condition is very bad, resulting in a reduced yield or poor quality. Accordingly, the farmer must preemptively spray various drugs to prevent diseases and pests on crops or perform additional growth promotion activities. These activities cause more human involvement than necessary and also lower the quality of crops.

As such, there is a need for a smart farm crop monitoring method and monitoring system using a drone that can predict and manage crop conditions in advance by automating the identification of crop growth problems and outbreaks of pests.

Patent Publication 10-2018-0079725, July 11, 2018

The present invention has been devised to solve the above problems, and an object of the present invention is to provide a smart farm crop monitoring method and monitoring system using a drone that can manage the optimal growth of crops using the drone.

In addition, the present invention is to provide a smart farm crop monitoring method and monitoring system using a drone capable of identifying the growth status of crops by location by tracking a target using a sensor mounted on a drone and preemptively analyzing the occurrence of pests and pests. There is this.

In addition, the present invention uses a plurality of drones capable of monitoring crops within the crop area to specify the location of abnormal growth conditions or pests in the crop area, and a smart drone using a drone capable of monitoring the growth of crops by analyzing images taken at the specified location An object of the present invention is to provide a method and a monitoring system for monitoring a farm crop.

In addition, the present invention is capable of monitoring crops according to a specified schedule within the crop area, and after completion of crop monitoring, safely landing at a designated docking station, and thereafter to provide a smart farm crop monitoring method and monitoring system using a drone capable of wireless charging. there is.

The technical problems to be achieved in the present invention are not limited to the technical problems mentioned above, and other technical problems not mentioned will be clearly understood by those of ordinary skill in the art to which the present invention belongs from the description below. will be able

Crop monitoring method according to an aspect of the present invention comprises the steps of starting a flight according to a plurality of designated movement points in a crop area by a drone, and monitoring crops provided while the drone moves from a first point to a second point of the plurality of movement points Detecting an abnormal target using a sensor, the drone flying to the abnormal target from the current flight position between the first point and the second point according to the detection of the abnormal target, and the image captured by the drone including the abnormal target and and transmitting crop abnormality information including location information through wireless communication.

In the above-described crop monitoring method, the detecting of the abnormal target includes changing the sensing direction of the drone during flight and sensing the data area exposed in the sensing direction changed by the crop monitoring sensor, which is a near-infrared sensor or a thermal image sensor, and the sensed data A giro abnormal target including data exceeding a specified threshold value in the area is detected.

In the above-described crop monitoring method, the detecting of the abnormal target comprises determining, as an abnormal target, a sub-region including data in which a data difference with neighboring data among a plurality of data of the sensed data region is equal to or greater than a specified threshold, and as an abnormal target. The flying step flies in a direction determined by the relative position of the sub-region in the sensed data area.

In the above crop monitoring method, after the transmission of crop abnormality information, the drone returns to the flight position determined by the current flight position, and the drone can be wirelessly charged after flying through a plurality of moving points for crop monitoring and landing at the drone station.

In the above-described crop monitoring method, the step of landing at the drone station includes moving to the location of the drone station using the provided GPS sensor, identifying the marker of the wireless charging pad from the image taken by the provided vision camera, and selecting the identified marker. It changes the 3D position of the drone according to its position and size.

In addition, the crop monitoring system according to an aspect of the present invention includes a plurality of drones, and each drone starts flying according to a plurality of movement points differently designated for each drone, and starts flying from the first point of the plurality of movement points. An abnormal target is detected using the crop monitoring sensor provided while moving to two points, and the image is taken including the abnormal target flying from the current flight position between the first point and the second point according to the detection of the abnormal target and crop abnormality information including location information is transmitted through wireless communication.

In the crop monitoring system described above, the drone changes the sensing direction of the drone during flight and senses the exposed data area in the sensing direction changed by the crop monitoring sensor, which is a near-infrared sensor or a thermal image sensor, and exceeds a specified threshold in the sensed data area. An abnormal target containing data is detected.

In the crop monitoring system described above, the drone determines, as an abnormal target, a sub-region including data in which a data difference with respect to neighboring data is greater than or equal to a specified threshold among a plurality of data in the sensed data region, and the sub-region in the sensed data region Fly in a direction determined by the relative position of

In the crop monitoring system described above, further comprising a drone station including a wireless charging pad marked with a marker, wherein the drone uses a GPS sensor provided after crop monitoring in a crop area through flight to a plurality of moving points. It moves to the station's location and identifies the marker of the wireless charging pad from the image taken by the vision camera equipped to land on the wireless charging pad, and changes the three-dimensional position of the drone according to the position and size of the identified marker.

In the crop monitoring system described above, further comprising a regional control center capable of wireless communication with a drone through a drone station, wherein the regional control center receives crop abnormality information from the drone and uses AI (Artificial Intelligence) learned from a plurality of crop images. Classify anomalies in crop anomaly information through

The smart farm crop monitoring method and monitoring system using a drone according to the present invention as described above is effective in managing the optimal growth of crops by using the drone.

In addition, the smart farm crop monitoring method and monitoring system using a drone according to the present invention as described above is an effect that can identify the growth state of crops by location and preemptively analyze the occurrence of pests by target tracking using a sensor mounted on the drone. there is

In addition, the smart farm crop monitoring method and monitoring system using a drone according to the present invention as described above uses a plurality of drones capable of monitoring crops in the crop area to specify the location of abnormalities in growth conditions or pests and abnormalities in the crop area and the specified location There is an effect of monitoring the growth of crops by analyzing the images taken in

In addition, the smart farm crop monitoring method and monitoring system using a drone according to the present invention as described above can monitor crops according to a specified schedule within the crop area, land safely at a designated docking station after crop monitoring is completed, and wirelessly charge thereafter. there is.

The effects obtainable in 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 the present invention belongs from the following description. will be.

1 is a diagram illustrating an exemplary smart farm crop monitoring system according to the present invention.
2 is a diagram illustrating an exemplary block diagram of a regional control center.
3 is a diagram illustrating an exemplary structure of a drone station.
4 is a diagram illustrating an exemplary block diagram of a drone.
5 is a view showing an exemplary external appearance of a drone constructed according to the present invention.
6 is a diagram illustrating an exemplary control flow for crop monitoring using a drone.
7 is a view for explaining an example of performing crop monitoring in a certain crop area using two drones.

The above-described objects, features and advantages will become more clear through the detailed description that will be described later in detail with reference to the accompanying drawings, and accordingly, those of ordinary skill in the art to which the present invention pertains can understand the technical spirit of the present invention It will be easy to implement. In addition, in the description of the present invention, if it is determined that a detailed description of a known technology related to the present invention may unnecessarily obscure the gist of the present invention, the detailed description thereof will be omitted. Hereinafter, preferred embodiments according to the present invention will be described in detail with reference to the accompanying drawings.

1 is a diagram illustrating an exemplary smart farm crop monitoring system in accordance with the present invention.

According to FIG. 1 , a system for monitoring the growth of crops grown in a smart farm (farm) using a drone 300 includes a regional control center 200 , one or more drones 300 and a drone station 400 . And the drone 300 and the drone station 400 are installed in the crop area 500 (farm) where crops are being grown to periodically and/or aperiodically monitor the state of the crops in the crop area 500 . The crop monitoring system may further include a central control center 100 .

Looking at the crop monitoring system through FIG. 1 , the central control center 100 manages and monitors one or more regional control centers 200 . The central control center 100 includes a server, a computer, and the like, and is connected to the regional control center 200 through the Internet. The regional control center 200 may transmit various types of information or control information to the central control center 100 , and the central control center 100 may receive information on abnormal crop growth from the regional control center 200 .

The central control center 100 may transmit various information related to, for example, information on growth significance for each period, information on pests currently in vogue, etc. to the regional control center 200, and other programs available in the regional control center 200; Programs available in the drone 300 or the drone station 400 may be transmitted to the regional control center 200 . The central control center 100 can manage and monitor several regional control centers 200 installed in a specific wide area.

The regional control center 200 monitors the state of the crop by controlling the drone 300 in the crop area 500 where crops are grown. The regional control center 200 can set flight schedules, flight routes, etc. of several drones 300 within the crop area 500, and receive and store crop abnormality information generated during flight through wireless communication with the drone 300 and crop anomaly information can be analyzed.

The regional control center 200 is equipped with a wireless AP, a router, an NVR, and a back-end server to analyze the crop abnormality information received through the drone 300 to analyze the growth or occurrence of pests of the crop to be managed. The regional control center 200 sets flight schedules and flight routes for a plurality of drones 300 within the crop area 500 (eg, a farm having a crop growing space separated from the outside by glass, etc.) and wirelessly A monitoring request may be transmitted to each drone 300 through communication.

A flight path set for one drone 300 in the crop zone 500 and a flight path set for another drone 300 may be different from each other, and the flight path may be specified by a plurality of movement points 501 . . That is, each drone 300 flies to a plurality of movement points 501 (eg, GPS coordinates of latitude and longitude) set for the corresponding drone 300 according to a monitoring request or a set period, and crops abnormalities during flight. can be detected and reported to the regional control center 200 .

The regional control center 200 may wirelessly communicate with the drone 300 through the drone station 400 or directly communicate with the drone 300 wirelessly.

The regional control center 200 will be described in more detail with reference to FIGS. 2 and 6 .

The drone 300 is installed in the crop zone 500 and is a device capable of monitoring the state of crops in the crop zone 500 while flying according to a set flight path. Each of the drones 300 installed and operated in the crop area 500 take off from the drone station 400 automatically according to a set period or according to a monitoring request from the regional control center 200 to monitor the crops being grown and Information according to the monitoring can be transmitted to the regional control center 200 .

The drone 300 will be described in more detail below with reference to FIG. 4 .

The drone station 400 is a hangar for protecting the drone 300 . The drone station 400 is configured to wirelessly charge the battery 313 of the drone 300 seated on the wireless charging pad 407 including the wireless charging pad 407 . The drone station 400 may include on the surface of the wireless charging pad 407 a marker 407 - 1 (mark) usable when the drone 300 is landed.

The drone station 400 will be described in more detail with reference to FIG. 3 .

Crop zone 500 represents an area in which crops are grown. Crop zone 500 may be a so-called paddy field, nursery, farm, orchard, or the like. Preferably, the crop area 500 is separated from the outside by using glass, vinyl, plastic, etc., and a movement passage 503 for movement and harvesting of a crop grower (farmer) within the farm and a crop cultivation area where crops are grown. 505 may be included. The crop zone 500 includes a plurality of movement passages 503 and a plurality of crop cultivation areas 505 so that a crop grower can move or the drone 300 can fly on the movement passage 503 .

2 is a diagram illustrating an exemplary block diagram of the regional control center 200 .

According to FIG. 2 , the regional control center 200 includes an input unit 201 , an output unit 203 , a communication unit 205 , a display unit 207 , a storage unit 209 , and a control unit 211 . The block diagram of FIG. 2 preferably shows a functional block diagram, and the regional control center 200 may configure this functional block through various hardware configurations. For example, the regional control center 200 may perform a function defined in each functional block, including a wireless AP, a router, an NVR, a back-end server, and a personal computer.

Referring to the regional control center 200 through FIG. 2 , the input unit 201 receives a user input such as a manager or a farmer in the regional control center 200 . The input unit 201 may include a button, a touch panel, a mouse, a keyboard, a microphone, and the like, and may receive input such as various driving controls and settings from an administrator or the like.

The output unit 203 outputs various signals. The output unit 203 may include a buzzer, an LED, a speaker, and the like, and output various signals for notifying a manager or the like. Depending on the design example, the configuration of the input unit 201 and the output unit 203 may be omitted from the regional control center 200 .

The communication unit 205 performs data communication. The communication unit 205 is provided with a router, a wireless AP, a wired LAN interface, etc. to transmit/receive various data to and from the central control center 100 through the Internet, or perform wireless communication according to a mobile communication network such as wireless LAN (Wi-Fi) and/or LTE. It transmits and receives various data to and from the drone station 400 and/or the drone 300 through the

The display unit 207 includes an LCD, an LED, a TFT-LCD display module, and the like, and outputs a video frame signal received from the control unit 211 . The display unit 207 may receive and output a visual image of crop abnormality information from the control unit 211 .

The storage unit 209 stores various data and programs including mass storage media such as volatile memory, non-volatile memory, and hard disk. For example, the storage unit 209 is a control program for controlling the regional control center 200 and further, a plurality of drones 300 in the crop area 500, and crop abnormality information from crop abnormality information received from the drone 300. An analysis program for analyzing a state, an abnormal image DB for storing an image (an image of crop abnormality information) received from the drone 300 and estimated as an abnormal state is stored. The crop abnormality information may include an image capable of identifying an abnormal state of a crop, such as a decrease in growth (growth), recognition of pests, and occurrence of pests.

The abnormal image DB is composed of a plurality of abnormal image items, and each abnormal image item includes a photographing time, a photographed vision image, and location information, and may further include a sensing data image. The visual image may be a two-dimensional array data that can be analyzed visually (by vision), and the sensing data image may be a two-dimensional sensing data array sensed by a crop monitoring sensor. The location information may indicate the location of the drone 300 taking an image.

The storage unit 209 may further store visual images and sensing data images that are pre-classified by other crop states (by abnormal states).

The control unit 211 controls the regional control center 200 . The control unit 211 may include one or more execution units capable of executing a program, and may control the regional control center 200 by executing the program of the storage unit 209 through the execution unit. The control unit 211 may include or indicate one or more of a CPU, an MPU, a GPU, a central processing unit, a microcomputer, and the like.

For example, the control unit 211 performing the control program sets a flight schedule, a flight route, etc. with the plurality of drones 300 in the crop area 500 through wireless communication and controls the flight of the plurality of drones 300 . (eg, sending a monitoring request, etc.). The controller 211 can uniformly control the plurality of drones 300 in the crop area 500 using a cloud-based control platform. In addition, the control unit 211 for performing the control program receives crop abnormality information from an arbitrary drone 300 and generates an abnormal image item to store a visual image of crop abnormality information, a sensing data image, and location information together with a shooting time. can

The control unit 211 may output the reception of crop abnormality information through the output unit 203 or output a visual image and a sensing data image through the display unit 207 . The control program may be executed in a personal computer operating as a front-end client.

The control unit 211 executing the analysis program analyzes the abnormal image item stored in the abnormal image DB. Simply, the controller 211 may output an image and a sensed image of the received abnormal image item to the display 207 and classify the abnormal state according to a user input.

Alternatively, the controller 211 classifies the abnormal state by comparing the visual image and the sensing data image that are pre-classified for each abnormal state of the storage unit 209 with the visual image and the sensing data image of the received abnormal image item, and displays the classified result. You can store more in the image item above. The control unit 211 classifies the abnormal state from the visual image of the abnormal image item through an artificial intelligence (AI) algorithm pre-learned by multiple crop images and abnormal state classification for each crop image, and the classified result is abnormal. You can store it in an image item. During analysis, the controller 211 may classify the abnormal state using only the visual image or classify the abnormal state by further using the sensing data image.

The control unit 211 classifies and stores abnormal states such as growth failure, pest detection, etc. for abnormal image items, and clusters abnormal states of each abnormal image item by location of abnormal image items to start occurrence of pests, increase pests, reduce The possibility of early growth period, slow growth spread, etc. may be predicted in advance using artificial intelligence technology or the like, and the prediction result may be output by the control unit 211 through the display unit 207 or the output unit 203 . The controller 211 may output the clustered location area together with the prediction results of growth, pests, and the like. Accordingly, the manager or the like can identify major abnormalities in various location areas within the crop area 500 .

The regional control center 200 will be described in more detail with reference to FIG. 6 .

3 is a diagram illustrating an exemplary structure of a drone station 400 .

The drone station 400 of FIG. 3 is configured to accommodate the drone 300 inside, charge the drone 300, and transmit/receive various data from the drone 300 to and from the regional control center 200 when necessary.

3, the drone station 400 includes a wireless communication module 401, a drone station control module 403, a wireless charging module 405 and a wireless charging pad 407, and a drone ( It may further include a wall 409 for accommodating and separating from the outside and one or more slopes 411 for guiding the landing of the drone 300 .

The drone station 400 may have an open top, and an open top may have a rectangular shape. For example, the open top of the drone station 400 has a 1.3 meter * 1.3 meter size opening and has walls 409 on four sides to accommodate the drone 300 inside. The wall 409 may be made of a material such as glass, acrylic, or metal, and is preferably made of glass.

The wireless communication module 401 transmits and receives data through wireless communication. The wireless communication module 401 may be a mobile communication module for transmitting and receiving wireless packets through a wireless AP and/or a mobile communication network. The mobile communication module may be, for example, an LTE module. The drone station 400 may transmit/receive various data to and from the regional control center 200 through the wireless communication module 401 . The wireless communication module 401 can operate as a repeater through a wireless AP or LTE module, so that data from the drone 300 is transmitted to the regional control center 200 and data from the regional control center 200 is wirelessly connected to the drone. It can be sent to (300). The wireless communication module 401 is configured to perform wireless communication (eg, Wi-Fi communication) in the 2.4 GHz/5.8 GHz band or mobile communication such as LTE, 5G, and the like.

The drone station control module 403 controls the drone station 400 . The drone station control module may include a known computing board (eg, Arduino, Raspberry Pi, etc.) to control wireless charging and the like in the wireless charging pad 407 .

The wireless charging module 405 may supply or block wireless power to the wireless charging pad 407 . The wireless charging module 405 includes a transmitter for generating wireless power and drives the transmitter according to a control signal received from the drone station control module 403 to drive the transmitter to internal and external power sources (eg, built-in drone station 400). Battery power or AC power supplied from the outside) is converted and output to the transmission coil of the wireless charging pad 407 . The wireless charging module 405 may generate or block a power signal for wireless power according to a received control signal.

The wireless charging pad 407 has a transmission coil therein and supplies wireless power to the drone 300 (receiving coil of) positioned on the wireless charging pad 407 . The wireless charging pad 407 is configured to supply wireless power to the drone 300 on the wireless charging pad 407 by applying a magnetic resonance or magnetic induction type wireless charging technology.

The wireless charging pad 407 is configured to include a marker 407-1 displayed on the surface. The marker 407-1 (marker) is an indicator that the drone 300 can identify in the visual image, and is a mark having a shape promised with the drone 300, such as a pattern image, a crossbar image, an 'H' mark, etc. .

The slope 411 is configured to guide (guide) the landing from the opening on the wall 409 to the wireless charging pad 407 for the drone 300 attempting to land. The drone station 400 has two or four slopes 411, and each slope 411 has a constant inclination (eg, 70 degrees, etc.) from one side of the opening to the outside of the surface of the wireless charging pad 407. ) has The slope 411 may be made of plastic, rubber, metal, or fabric. Preferably, the slope 411 is made of a fabric material such as cloth. Even when the landing by the drone 300 deviates due to an error, the drone 300 can be safely seated on the wireless charging pad 407 by the slope 411 .

4 is a diagram illustrating an exemplary block diagram of the drone 300 .

According to FIG. 4 , the drone 300 includes a wireless communication unit 301 , a storage unit 303 , a camera unit 305 , a sensing unit 307 , a drone driving unit 309 , a battery charging unit 311 , and a battery 313 . and a control unit 315 . The block diagram of Fig. 4 preferably shows a functional block diagram and the drone 300 is configured to have corresponding hardware blocks (components) for performing each function.

Referring to the drone 300 through FIG. 4 , the wireless communication unit 301 performs wireless data communication. The wireless communication unit 301 is provided with a communication chipset and circuit for performing wireless mobile communication such as 2.4GHz/5.8GHz band wireless communication (eg, Wi-Fi communication) or LTE, 5G, and can transmit and receive various data. . For example, the wireless communication unit 301 may receive control data from the regional control center 200 and transmit crop abnormality information detected according to the flight according to the control data to the regional control center 200 through wireless communication. The wireless communication unit 301 may directly perform wireless communication with the regional control center 200 or perform wireless communication with the regional control center 200 via an arbitrary (or designated) drone station 400 .

The storage unit 303 stores various data and programs including non-volatile memory and volatile memory. For example, the storage unit 303 stores a flight control program for controlling flight within the crop zone 500, an abnormal target tracking program for detecting an abnormal target during flight, and setting data such as a flight path and a flight period. .

The camera unit 305 takes a visual (video) image exposed through the provided lens. The camera unit 305 includes a vision camera to capture a visual (vision) image exposed to the lens, and transmits the captured vision (vision) image to the controller 315 or may be stored in the storage unit 303 .

The sensing unit 307 senses various external environments outside the drone 300 . The sensing unit 307 senses the outside of the drone 300 including a GPS sensor, a collision avoidance sensor, and a crop monitoring sensor. The GPS sensor receives the GPS signal, and the collision avoidance sensor can recognize an object in front during flight. The collision avoidance sensor may be an ultrasonic sensor (ultra sonic sensor), a laser, a lidar sensor, or the like. The crop monitoring sensor is a sensor capable of monitoring the condition of crops in the crop zone 500 . The crop monitoring sensor may be a Near Infrared sensor (camera) capable of detecting a state change in a crop or a thermal image sensor (camera). The crop monitoring sensor may sense a data value corresponding to a near-infrared value or a thermal image value in the exposed region and output the sensed data in the exposed region to the controller 315 . The sensed data may constitute two-dimensional sensing data (image).

The drone driving unit 309 includes one or more engines or motors for moving the drone 300 up, down, left, right, forward, and backward, and operates a designated engine or motor according to a control signal received from the control unit 315 . Control to operate the drone 300 . The drone 300 can fly through the drone driving unit 309 and can move to a specific location.

The battery 313 stores power available to blocks of the drone 300 . The battery 313 stores power supplied from the wireless charging pad 407 including known batteries such as lithium ion and lithium polymer, and stores the stored power in blocks requiring power (eg, the control unit 315, the wireless communication unit). 301 , the drone driving unit 309 , the sensing unit 307 , the camera unit 305 , the storage unit 303 , etc.).

The battery charging unit 311 charges the battery 313 with power. The battery charging unit 311 includes a receiving coil and a power generating circuit or component for generating charging power from a signal derived from the receiving coil. The battery charging unit 311 may be connected to the battery 313 to supply charging power to the battery 313 or to cut off the supply of charging power. The battery charging unit 311 may measure the output power of the battery 313 and output the measured power data to the control unit 315 . The measured power data may be current, voltage, or power data, and the remaining amount of the battery 313 may be measured by the controller 315 therefrom.

The drone 300 may include one or a plurality of receiving coils included in the battery charging unit 311 , and the receiving coil may be attached to or embedded in one or a plurality of four legs of the drone 300 . As described above, the receiving coil is installed on the leg (lower side) of the drone 300 in contact with the wireless charging pad 407 to receive wireless power according to the wireless charging method from the wireless charging pad 407 .

The controller 315 controls the drone 300 . The control unit 315 includes one or more execution units capable of executing the program, and performs the flight control program of the storage unit 303 through the execution unit to fly according to a designated flight path and control the abnormal target tracking program during flight A target having an abnormal condition in the crop area 500 may be tracked.

The control unit 315 executing the flight control program may control the flight of the drone 300 according to a communication protocol promised with the drone driving unit 309 . For example, the controller 315 may control the drone driving unit 309 according to the MAVlink (ROSlink) protocol to fly according to a designated flight path.

A control flow for flight and target detection performed by the drone 300 will be described in more detail with reference to FIGS. 6 and 7 .

5 is a diagram illustrating an exemplary external appearance of a drone 300 configured according to the present invention.

As can be seen from FIG. 5 , the drone 300 according to the present invention includes various sensors and cameras. For example, the drone 300 includes a computing board, a GPS sensor, a collision avoidance sensor, a crop monitoring sensor, and a vision camera for performing various processes. The GPS sensor is derived from the body of the drone 300 upward, and one or a plurality of collision avoidance sensors are installed in all directions (front, rear, left, right) of the body of the drone 300 to sense obstacles in all directions of flying. A crop monitoring sensor installed in front of the body of the drone 300 is a sensor capable of sensing abnormalities in crops in the crop area 500, and a vision camera installed in front of the body of the drone 300 is capable of capturing an image of the front. In addition, the drone 300 may have a built-in reception coil in a leg used for landing and protection of a computing board or may be provided outside.

6 is a diagram illustrating an exemplary control flow for crop monitoring using the drone 300 .

The control flow of FIG. 6 shows the control flow for movement and action performed by the drone 300 , and the other drone 300 in the crop zone 500 also has the same control flow for the main movement and action. The control flow of FIG. 6 is controlled by the control unit 315 of the drone 300 and consists of, for example, a flight control program performed in conjunction with the regional control center 200 and execution of an abnormal target tracking program.

Hereinafter, the control flow performed in a single drone 300 will be mainly described, but if necessary, the same control flow performed in multiple drones 300 in conjunction with FIG. 7 will also be described.

First, each of the plurality of drones 300 in the crop area 500 sets various information related to flight and monitoring ( S101 ). For example, the drone 300 sets a flight route, a flight period (time), and the like, and establishes a wireless communication channel with the regional control center 200 . The flight path may include a plurality of movement points 501 . The moving point 501 may indicate GPS coordinates (latitude and longitude coordinates).

One drone 300 (FIG. 7(a)) moves to the moving points 501 {E, F, G, H} in a state of landing at a specific drone station 400 (FIG. 7(A)). The other drone 300 (FIG. 7(b)) is set to a specified flight path, and the other specific drone station 400 (FIG. 7(B)) is set at the moving points 501 in the state of landing. A,B,C,D} can be set to the flight path specified. The flight cycle may be, for example, set to a specific flight start time or set to once or twice a day. The drone 300 may perform automatic crop monitoring according to a flight cycle or may start crop monitoring according to control from the regional control center 200 .

After setting various setting information, the drone 300 recognizes the occurrence of a flight event (S103). For example, the drone 300 may recognize the arrival of a set flight period, the arrival of a flight time, or the occurrence of a flight event as a result of receiving a monitoring request from the regional control center 200 through the wireless communication unit 301 .

Each drone 300 recognizing a flight event (flight events for each drone 300 may occur at the same or different times) is a flight path according to a plurality of movement points 501 set for each drone 300. to start the flight of (S105).

The drone 300 may set a start movement point 501 and an end movement point 501 among the plurality of movement points 501 , and start flying from the start movement point 501 to the end movement point 501 . For example, one drone 300 (FIG. 7(a)) starts flying from E (start movement point 501) to F (end movement point 501), and the other drone 300 (B) of FIG. 7 starts a flight from A (start movement point 501) to B (end movement point 501).

To fly from the start moving point 501 to the end moving point 501, the control unit 315 of the drone 300 controls the drone driving unit 309 through the flight control program, and among the moving points 501 on the flight path An abnormal target is detected ( S107 ) by using the crop monitoring sensor provided during the movement (flight) from the starting movement point 501 to the ending movement point 501 .

For example, the drone 300 flies according to a flight speed (10 cm per second, 20 cm, 1 meter, etc.) set from the starting movement point 501 to the ending movement point 501 . While flying the moving passage 503 between the start moving point 501 and the end moving point 501, the drone 300 flies while avoiding obstacles in front (further left and right) through the collision avoidance sensor of the sensing unit 307 . can do.

During flight at a specified speed, the drone 300 sets the sensing direction of the crop monitoring sensor from the start movement point 501 to the end movement point 501 (moving passage 503) at a left and right angle at a certain angle (e.g., left, 30 degrees to the right, 45 degrees, etc.) and sense the crop cultivation area 505 exposed to the crop monitoring sensor in (toward) the changed sensing direction. The drone 300 may detect an abnormal target including data greater than or equal to a specified threshold in the sensed data area (eg, a sensing image (two-dimensional array)). The drone 300 changes the direction of the drone 300 to the left and right at a constant angle while flying through the passage 503 from the start movement point 501 to the end movement point 501 at a slow speed and cultivates crops in the changed direction. A sensing image (eg, a two-dimensional data array) for the region 505 may be captured.

Furthermore (simultaneously), the drone 300 captures a visual image toward the changed sensing direction through the vision camera of the camera unit 305, and a crop to be monitored from the captured visual image (eg, fruit trees, crops, etc.) ) can be identified. The control unit 315 of the drone 300 may determine whether it is a crop to be monitored by analyzing the captured visual images (compare between images, judgment by a learned program, etc.).

The drone 300 may determine, as an abnormal target, a location of data having a difference greater than or equal to a specified threshold value from neighboring data among the two-dimensional data of the sensed data area. For example, the drone 300 may determine, as an abnormal target, a location in which temperature values of a plurality of neighboring locations (left, right, top, bottom, etc.) have a specified temperature difference (eg, 3 degrees, etc.) or more.

For example, the drone 300 classifies the sensed data area into a series of two-dimensional sub-areas (eg, 2*2, 4*4, 8*8 data area, etc.) and senses for each sub-area. The average value of the data may be calculated and a sub-region having a predetermined threshold or more (eg, 3 degrees, etc.) than a neighboring sub-region among a plurality of sub-regions may be determined as an abnormal target.

The part of the crop branch where crop growth is declining, the part where there are pests, or the part where the damage by pests has occurred has a different sensing value from the surrounding parts in the thermal image or near-infrared image. For example, the temperature at which a pest is located is different and generally higher than the temperature sensed in other crop areas. In addition, the temperature sensed at the point where the leaves of the crop are dry is different from the temperature sensed at the point during normal growth.

The process of determining the abnormal target may be performed only when a crop to be monitored is identified in the sensed data area, or may be performed regardless of whether the crop is identified.

According to the detection of the abnormal target, the drone 300 flies to the abnormal target at the current drone position on the moving passage 503 between the starting movement point 501 and the ending movement point 501 ( S109 ).

Specifically, the drone 300 stores the current drone position determined through the GPS sensor of the sensing unit 307 in the storage unit 303 and starts flying in a direction determined by the position of the abnormal target in the sensed data area. do.

For example, the drone 300 changes the flight direction according to the relative position of the sub-region specified as the abnormal target in the sensed data area. When the abnormal target is to the left (right) from the center of the sensed data region, the drone 300 may be rotated to the left (right) so that the abnormal target (a sub region of) is located in the center of the sensed data region. In this process, the drone 300 may continuously detect an abnormal target through the crop monitoring sensor.

As the flight direction is changed, the drone 300 flies toward the abnormal target at a constant speed (10 cm per second, 20 cm, 1 meter, etc.). In the process of flying to the abnormal target, the drone 300 continues to detect the abnormal target through the crop monitoring sensor, and the size of the abnormal target is within a specified size (eg, 25% size) within the sensed data area. It can fly in and can stop flying if it exceeds the specified size.

The drone 300 takes a visual image in the course of flying to an abnormal target and stores it in the storage unit 303 together with location information determined by the GPS sensor. For example, the drone 300 stores a visual image captured by the camera unit 305 in the process of flying to an abnormal target, location information at the time of photographing, and furthermore, a photographing time and a data area image sensed by a crop monitoring sensor. may be stored in unit 303 . The drone 300 provides a visual image, location information, and a data area image sensed by the photographing time and crop monitoring sensor once (at the flight end position to the target) or multiple times (for example, according to a specified period) may be stored in the storage unit 303 .

As the flight to the abnormal target is terminated according to the size of the abnormal target in the sensed data area, the drone 300 configures the crop abnormal information including the photographed visual image including the abnormal target and location information, and wireless communication It is transmitted to the regional control center 200 through (S111).

The regional control center 200 receives crop abnormality information through a local area wireless communication network or mobile communication network, creates a new abnormal image item in the abnormal image DB, and visual image of crop abnormality information, location information, shooting time, and further sensed data Save the image. One or more of the visual image, location information, shooting time, and further sensed data image may be stored in the image item.

The regional control center 200 may classify an abnormal state at a feature position in the crop area 500 by analyzing one or more abnormal image items of the abnormal image DB, and further store the classified result in the abnormal image item. The regional control center 200 may classify an abnormal state through a pre-learned artificial intelligence (AI) algorithm, and store the classified result in an abnormal image item.

After the transmission of the crop abnormality information, the drone 300 returns to the existing flight position on the moving passage 503 ( S113 ). For example, the drone 300 returns to the current drone location stored in the storage unit 303 using a GPS sensor and resumes flight to the end movement point 501 on the movement passage 503 .

The drone 300 may periodically check the current location information using the GPS sensor and determine whether the current location information is the end moving point 501 ( S115 ). For example, the drone 300 indicates that the drone 300 is located at the current ending movement point 501 when the current location information is within a certain distance (eg, 50 cm, etc.) from the ending movement point 501 . can decide

If the drone 300 on the moving passage 503 has not yet been positioned at the end moving point 501, the drone 300 continues to fly to the end moving point 501 while detecting an abnormal target (S107) and flying (S109). ), the information transmission (S111) and return (S113) processes are repeated.

When arriving at the ending moving point 501 , the drone 300 determines whether the current ending moving point 501 is the final moving point 501 ( S117 ).

For example, according to the completion of the flight of the 'E'-'F' moving passage 503, the drone 300 located at 'F' (FIG. It is determined whether it is the same as the ending point 'H', and according to the completion of the flight of the 'A'-'B' moving passage 503, the drone 300 (in FIG. 501) It may be determined whether 'B' is the same as the final moving point 501 'D'.

When the ending movement point 501 and the final movement point 501 are different positions, the drone 300 resets the starting movement point 501 and the ending movement point 501 ( S119 ).

For example, the drone 300 ((a) of FIG. 7) that has completed the flight of the 'E'-'F' passage 503 has an 'F' following the 'E'-'F' movement passage 503 -'G' Set 'F' of the moving passage 503 as the start moving point 501 and set 'G' as the end moving point 501 . In addition, the drone 300 (FIG. 7(b)) that has completed the flight of the 'A'-'B' passage 503 is 'B'-' following the 'A'-'B' movement passage 503 'B' of the moving passage C' 503 is set as the starting moving point 501 and 'C' is set as the ending moving point 501 .

As the start movement point 501 and the end movement point 501 are reset, the drone 300 flies through the reset movement path 503 while detecting an abnormal target and transmitting crop abnormal information (S107 to S115). carry out

The drone 300 positioned at the final moving point 501 by completing the flight through several moving points 501 set according to the flight path for crop monitoring land (S121) on the drone station 400 capable of wireless charging. In addition to the case of flight completion, when the built-in battery 313 has power below a specified threshold, the drone 300 moves to the drone station 400 to land, wirelessly charge, and move to the location where the flight was stopped after the wireless charging is completed. to re-perform the crop monitoring process (S107 to S119).

For landing on the drone station 400 , the drone 300 moves to a location of the drone station 400 designated for landing. For example, one drone 300 (FIG. 7(a)) moves using a GPS sensor provided to a preset location of one drone station 400 (FIG. 7(A)), and the other The drone 300 ((b) of FIG. 7) moves to the preset location of another drone station 400 (((B) of FIG. 7) using a GPS sensor provided.

As the drone 300 moves to the location of the designated drone station 400 , the drone 300 faces the vision camera of the camera unit 305 downward (downward direction) and takes an image through the vision camera. The drone 300 identifies the marker 407-1 included in the wireless charging pad 407 in the captured image (visual image), and according to the location and size of the identified marker 407-1 in the image, the drone ( 300) and try to land by changing the position (three-dimensional position).

For example, the drone 300 identifies a marker 407-1 of a promised shape in a visual image taken by a downward-facing vision camera, and the identified marker 407-1 is located in the center (central region) of the visual image. Controls the drone driving unit 309 so as to be positioned in the , and moves the drone 300 in the forward, backward, left, and right directions. The drone 300 may determine that the marker 407 - 1 is located in the central region with some error in the visual image by reflecting the hovering and movement of the drone 300 . The drone 300 controls the drone driving unit 309 to position the marker 407 - 1 in the central area, and continuously captures and compares images through the vision camera.

As the identified marker 407-1 is located in the central region of the visual image, the drone 300 controls the drone driving unit 309 according to the size of the marker 407-1 to have a wireless charging pad 407. The drone 300 is moved in a downward (downward) direction. As the drone 300 moves in the downward direction, it controls the camera unit 305 to continuously shoot a visual image, and further controls forward, backward, left, and right for positioning the marker 407-1 in the central area in the captured image. there is.

A marker 407-1 located in the center has a specified size or more or is in contact with the wireless charging pad 407 (eg, a pressure sensor provided in the sensing unit 307 and located under the leg of the drone 300 ) pressure recognition), the drone 300 ends the engine driving through the drone driving unit 309 and starts wireless charging.

The drone 300 interworks with the drone station 400 to start wireless charging through the wireless charging pad 407, and when it is fully charged to more than a specified amount of power through the battery charging unit 311, the drone station 400 indicates a fully charged state. Data can be transmitted through wireless communication or the like. Accordingly, the drone station 400 may control the wireless charging module 405 to stop wireless power transmission.

After charging the wireless power, the drone 300 may monitor the state of the crop according to the next flight event (S103 to S119).

By means of such a control flow and a corresponding system, the growth of crops and the occurrence of pests can be monitored and predicted early by the drone 300 without frequent management and monitoring of the grower or manager (farmer) for the cultivated crops.

The present invention described above, for those of ordinary skill in the art to which the present invention pertains, various substitutions, modifications and changes are possible without departing from the technical spirit of the present invention. It is not limited by the drawings.

100: central control center
200: regional control center
201: input unit 203: output unit
205: communication unit 207: display unit
209: storage unit 211: control unit
300 : drone
301: wireless communication unit 303: storage unit
305: camera unit 307: sensing unit
309: drone driving unit 311: battery charging unit
313: battery 315: control unit
400 : drone station
401: wireless communication module 403: drone station control module
405: wireless charging module
407: wireless charging pad 407-1: marker
409: wall 411: slope
500 : crop area
501 : moving point
503: moving passage
505: crop cultivation area

Claims (10)

Initiating, by the drone, flying according to a plurality of designated movement points in a crop area that is separated from the outside and includes a plurality of crop growing areas where crops are grown and a plurality of passages for movement or harvesting of crops;
(a) the drone detects the sensing direction of the crop monitoring sensor provided during the movement of the movement passage from the first point to the second point of the plurality of movement points among the plurality of movement passages left or right adjacent to the movement passage detecting an abnormal target from the crop cultivation area by changing it to a specified angle left or right from the axis of the moving passage to sense the crop cultivation area of ;
(b) the drone flying to the abnormal target from a current flight position between the first point and the second point according to the detection of the abnormal target;
transmitting, by the drone, crop abnormality information including a photographed image including the abnormal target and location information through wireless communication; and
The drone sets the second point as a first point and sets a point following the second point among the plurality of movement points as a second point to repeat steps (a) and (b) step; including;
In the step (a), a data area sensed by the crop monitoring sensor, which is a thermal image sensor, is classified into a plurality of two-dimensional sub-regions, an average value of the sensed data for the plurality of sub-regions is calculated, and a neighbor among the plurality of sub-regions. Determining a sub-region having a temperature difference greater than or equal to a specified threshold than a sub-region to be an abnormal target,
Crop monitoring methods. delete According to claim 1,
In the step (a), a visual image is captured in a sensing direction changed to a specified angle through an provided vision camera, and the abnormal target is detected only when a crop to be monitored is identified in the captured visual image,
The step of flying to the abnormal target is flying in a direction determined by the relative position of the sub-region of the abnormal target in the sensed data region,
Crop monitoring methods. According to claim 1,
After repeating the steps (a) and (b), returning the drone to a flight position determined by the current flight position; and
After flying through the plurality of moving points for crop monitoring, the drone landing at a drone station capable of wireless charging; further comprising,
Crop monitoring methods. 5. The method of claim 4,
In the step of landing at the drone station, the drone moves to the location of the drone station using the provided GPS sensor, identifies the marker of the wireless charging pad from the image taken by the provided vision camera, and according to the location and size of the identified marker, the drone to change the three-dimensional position of
Crop monitoring methods. A crop monitoring system for monitoring crops in a crop area including a plurality of drones, including a plurality of crop cultivation areas separated from the outside and where crops are grown, and a plurality of movement paths for movement or harvesting of crops,
Each drone starts flying according to a plurality of movement points that are differently designated for each drone, and monitors crops provided during movement of a movement passage from a first point to a second point of the plurality of movement points among the plurality of movement passages. By changing the sensing direction of the sensor to a designated angle left or right from the axis of the moving passage to sense the left or right crop cultivation area adjacent to the movement passage, an abnormal target is detected from the crop cultivation area, and the abnormal target is According to the detection, from the current flight position between the first point and the second point, fly to the abnormal target, and transmit crop abnormal information including the image and location information taken including the abnormal target through wireless communication, and the A second point is set as a first point and a point subsequent to the second point among the plurality of moving points is set as a second point to repeatedly perform detection of the abnormal target and flight to the abnormal target,
The drone classifies a data area sensed by the crop monitoring sensor, which is a thermal image sensor, into a plurality of two-dimensional sub-regions, calculates an average value of the sensed data for the plurality of sub-regions, and neighboring sub-regions among the plurality of sub-regions. determining a sub-region having a temperature difference greater than or equal to a specified threshold as an abnormal target,
crop monitoring system. delete 7. The method of claim 6,
The drone captures a visual image in a sensing direction changed to a specified angle through an provided vision camera, and detects the abnormal target only when a crop to be monitored is identified in the captured visual image, and in the sensed data area to fly in a direction determined by the relative position of the sub-region of the anomaly of the target,
crop monitoring system. 7. The method of claim 6,
A drone station including a wireless charging pad marked with a marker; further comprising,
The drone moves to the location of the drone station using a GPS sensor provided after crop monitoring in the crop area through flight to the plurality of movement points and is photographed by a vision camera provided to land on the wireless charging pad. Identifying the marker of the wireless charging pad in the image and changing the three-dimensional position of the drone according to the position and size of the identified marker,
crop monitoring system. 10. The method of claim 9,
Further comprising a regional control center capable of wireless communication with the drone through the drone station,
The regional control center receives the crop abnormality information from the drone and classifies the abnormality of the crop abnormality information through AI (Artificial Intelligence) learned from a plurality of crop images,
crop monitoring system.

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