WO2021111621A1 - Pathological diagnosis system for plants, pathological diagnosis method for plants, pathological diagnosis device for plants, and drone - Google Patents

Abstract

[Problem] To pathologically diagnose crops with high accuracy. [Solution] A pathological diagnosis system 1000 for plants is provided with: a flight control unit 1001 that causes a drone 100 to fly over a field; a pathological information acquisition unit 1004 that is mounted on the drone and acquires an image of a crop growing in the field 403; a spot measurement unit 604 for measuring at least any parameter among the size, density and number of spots on the crop on the basis of the image; and a pathological diagnosis unit 605 for pathologically determining whether the crop has a disease or not on the basis of the parameter measurement result.

Description

Plant pathological diagnosis system, plant pathological diagnosis method, plant pathological diagnosis device, and drone

The present invention relates to a plant pathological diagnosis system, a plant pathological diagnosis method, a plant pathological diagnosis device, and a drone.

The application of small helicopters (multicopters) generally called drones is advancing. One of the important application fields is spraying agricultural land (field) with pesticides, liquid fertilizers, etc. (for example, Patent Document 1). In relatively small farmlands, it is often appropriate to use drones rather than manned planes and helicopters.

Patent Document 2 describes an image analysis means for acquiring an image captured in flight, a pest detection means for detecting pests attached to a crop based on the image analysis means, and a crop to which the pests are attached. A mobile control application comprising a mobile control means for controlling a mobile so as to spray a pest control agent based on position information is disclosed.

Patent Publication Japanese Patent Application Laid-Open No. 2001-120151 Patent Gazette Patent 6427301

Provide a plant pathological diagnosis system that accurately diagnoses the pathological diagnosis of crops.

In order to achieve the above object, the plant pathological diagnosis system according to one aspect of the present invention includes a flight control unit for flying a drone over a field and an image of a crop mounted on the drone and growing in the field. Based on the pathological information acquisition unit to be acquired, the spot measurement unit that measures at least one parameter of the size, density, and number of spots generated in the crop based on the image, and the measurement result of the parameter. , A pathological diagnosis unit for determining whether the crop is sick or not.

A medical history storage unit that stores a past medical history in the field may be further provided, and the pathological diagnosis unit may perform the pathological determination based on the medical history.

The pathological diagnosis unit may make a pathological determination based on the climate information of the field.

The climate information may include at least one of temperature, humidity and wind speed information.

The drone may include a red light camera that detects the amount of light in the red light frequency band, and the pathological information acquisition unit may acquire the image by the red light camera.

The pathological diagnosis unit may determine the progress of the disease based on at least one of the shape and size of the spots generated on the crop.

The drone includes a visible light camera that detects light amounts of at least three wavelengths in the visible light band such as an RGB camera, and the pathological diagnosis unit determines the progress based on the information obtained by the visible light camera. May be.

A countermeasure determination unit for determining countermeasures to be taken in the field may be further provided according to the progress.

The countermeasure may include at least one of visual confirmation instruction of the strain origin, rephotographing, waiting, spraying of pesticides, removal of pathological leaves, removal of pathological strains, and removal of strains in the pathological strain occurrence area.

The countermeasure determination unit may determine the pesticide spraying area according to the progress.

The countermeasure determination unit may determine the spray concentration of the pesticide according to the progress.

The countermeasure determination unit may determine the type of pesticide to be sprayed according to the progress of the disease.

A result output unit for displaying the determination result of the countermeasure determination unit on the display unit or transmitting the determination result to the flight control unit of the drone may be further provided.

In order to achieve the above object, another method of pathological diagnosis of a plant according to another aspect of the present invention includes a flight control step of flying a drone over a field and an image of a crop mounted on the drone and growing in the field. Based on the pathological information acquisition step to be acquired, the spot measurement step of measuring at least one parameter of the size, density, and number of spots generated in the crop based on the image, and the measurement result of the parameter. , A pathological diagnosis step of making a pathological determination as to whether or not the crop is sick.

In order to achieve the above object, the plant pathological diagnosis apparatus according to still another aspect of the present invention occurs in the crop based on the image of the crop growing in the field acquired by the drone flying over the field. A spot measuring unit that measures at least one of the parameters of the size, density, and number of spots to be used, and a pathological diagnosis unit that determines the pathological condition of the crop based on the measurement results of the parameters. To be equipped.

In order to achieve the above object, the drone according to still another aspect of the present invention includes a flight control unit for flying the drone over the field, a pathology information acquisition unit for acquiring an image of a crop growing in the field, and the above. A spot measuring unit that measures at least one parameter of the size, density, and number of spots that occur on the crop based on the image, and whether or not the crop is sick based on the measurement result of the parameter. It is provided with a pathological diagnosis unit for determining pathology.

The pathological diagnosis of crops can be performed accurately.

It is a top view of the drone which concerns on this invention. It is a front view of the said drone. It is a right side view of the above drone. It is a rear view of the said drone. It is a perspective view of the said drone. It is an overall conceptual diagram of the pathological diagnosis system which concerns on this invention. It is a functional block diagram which the said drone has. It is a functional block diagram of the drone, the user interface apparatus, the diagnostic apparatus and the planning apparatus which the pathological diagnosis system has. This is another example of the result output screen output by the pathological diagnosis system. This is another example of the result output screen output by the pathological diagnosis system. The pathological diagnosis system is a flowchart for performing a pathological diagnosis of a crop. It is an image diagram of the photographed image obtained by photographing the rice leaf infected with blast with the red light camera provided in the drone.

Hereinafter, a mode for carrying out the present invention will be described with reference to the drawings. All figures are illustrations. In the following detailed description, certain details are given for illustration purposes and to facilitate a complete understanding of the disclosed embodiments. However, embodiments are not limited to these particular details. Also, to simplify the drawings, well-known structures and devices are outlined.

First, the configuration of the drone according to the present invention will be described. In the specification of the present application, the drone is regardless of the power means (electric power, prime mover, etc.) and the maneuvering method (wireless or wired, autonomous flight type, manual maneuvering type, etc.). It refers to all air vehicles with multiple rotor blades.

As shown in FIGS. 1 to 5, the rotors 101-1a, 101-1b, 101-2a, 101-2b, 101-3a, 101-3b, 101-4a, 101-4b (also referred to as rotors) are It is a means for flying the Drone 100, and is equipped with eight aircraft (four sets of two-stage rotor blades) in consideration of the balance between flight stability, aircraft size, and power consumption. Each rotor 101 is arranged on all sides of the housing 110 by an arm protruding from the housing 110 of the drone 100. That is, the rotors 101-1a and 101-1b are left rearward in the direction of travel, the rotors 101-2a and 101-2b are forward left, the rotors 101-3a and 101-3b are rearward right, and the rotors 101- are forward right. 4a and 101-4b are arranged respectively. In addition, the drone 100 has the traveling direction facing downward on the paper in FIG.

A grid-shaped propeller guard 115-1,115-2,115-3,115-4 forming a substantially cylindrical shape is provided on the outer circumference of each set of the rotor blade 101 to prevent the rotor blade 101 from interfering with foreign matter. As shown in FIGS. 2 and 3, the radial members for supporting the propeller guards 115-1,115-2,115-3,115-4 are not horizontal but have a yagura-like structure. This is to encourage the member to buckle outside the rotor in the event of a collision and prevent it from interfering with the rotor.

Rod-shaped legs 107-1, 107-2, 107-3, 107-4 extend downward from the rotation axis of the rotor 101, respectively.

Motors 102-1a, 102-1b, 102-2a, 102-2b, 102-3a, 102-3b, 102-4a, 102-4b are rotary blades 101-1a, 101-1b, 101-2a, 101- It is a means to rotate 2b, 101-3a, 101-3b, 101-4a, 101-4b (typically an electric motor, but it may also be a motor, etc.), and one machine is provided for one rotary blade. Has been done. Motor 102 is an example of a thruster. The upper and lower rotors (eg, 101-1a and 101-1b) in one set, and their corresponding motors (eg, 102-1a and 102-1b), are used for drone flight stability, etc. The axes are on the same straight line and rotate in opposite directions.

Nozzles 103-1, 103-2, 103-3, 103-4 are means for spraying the sprayed material downward and are equipped with four nozzles. In the specification of the present application, the sprayed material generally refers to a liquid or powder sprayed on a field such as a pesticide, a herbicide, a liquid fertilizer, an insecticide, a seed, and water.

The tank 104 is a tank for storing the sprayed material, and is provided at a position close to the center of gravity of the drone 100 and at a position lower than the center of gravity from the viewpoint of weight balance. The hoses 105-1, 105-2, 1053, 105-4 are means for connecting the tank 104 and the nozzles 103-1, 103-2, 103-3, 103-4, and are made of a hard material. Therefore, it may also serve as a support for the nozzle. The pump 106 is a means for discharging the sprayed material from the nozzle.

FIG. 6 shows an overall conceptual diagram of the flight control system of the drone 100 according to the present invention. This figure is a schematic view, and the scale is not accurate. In the figure, the drone 100, the actuator 401, and the small mobile terminal 401a are each connected to the base station 404, and only the actuator 401 is connected to the farming cloud 405. Not limited to. The drone 100, the actuator 401, the small mobile terminal 401a, and the base station 404 are each connected to the farming cloud 405. These connections may be wireless communication by Wi-Fi, mobile communication system or the like, or may be partially or wholly connected by wire.

The controller 401 transmits a command to the drone 100 by the operation of the user 402, and also displays information received from the drone 100 (for example, position, amount of sprayed material, battery level, camera image, etc.). It may be realized by a portable information device such as a general tablet terminal that runs a computer program. The actuator 401 includes an input unit and a display unit as a user interface device. The drone 100 according to the present invention is controlled to perform autonomous flight, but may be capable of manual operation during basic operations such as takeoff and return, and in an emergency. In addition to the portable information device, an emergency operation device (not shown) having a function dedicated to emergency stop may be used. The emergency manipulator may be a dedicated device provided with a large emergency stop button or the like so that an emergency response can be taken quickly. Further, apart from the operating device 401, the system may include a small mobile terminal 401a capable of displaying a part or all of the information displayed on the operating device 401, for example, a smart phone. Further, it may have a function of changing the operation of the drone 100 based on the information input from the small mobile terminal 401a. The small mobile terminal 401a is connected to, for example, the base station 404, and can receive information and the like from the farming cloud 405 via the base station 404.

Field 403 is a rice field, field, etc. that is the target of spraying with the drone 100. In reality, the terrain of field 403 is complicated, and the topographic map may not be available in advance, or the topographic map and the situation at the site may be inconsistent. Field 403 is usually adjacent to houses, hospitals, schools, other crop fields, roads, railroads, etc. In addition, there may be intruders such as buildings and electric wires in the field 403.

The base station 404 is a device that provides a master unit function for Wi-Fi communication, etc., and may also function as an RTK-GPS base station so that it can provide an accurate position of the drone 100 (Wi-). The base unit function of Fi communication and the RTK-GPS base station may be independent devices). In addition, the base station 404 may be able to communicate with the farming cloud 405 using mobile communication systems such as 3G, 4G, and LTE.

The farming cloud 405 is typically a group of computers operated on a cloud service and related software, and may be wirelessly connected to the actuator 401 by a mobile phone line or the like. The farming cloud 405 may be configured by a hardware device. The farming cloud 405 may analyze the image of the field 403 taken by the drone 100, grasp the growing condition of the crop, and perform a process for determining the flight route. In addition, the topographical information of the stored field 403 may be provided to the drone 100. In addition, the history of the flight and captured images of the drone 100 may be accumulated and various analysis processes may be performed.

The small mobile terminal 401a is, for example, a smart phone or the like. On the display of the small mobile terminal 401a, information on expected operations regarding the operation of the drone 100, more specifically, the scheduled time when the drone 100 will return to the departure / arrival point 406, and the work to be performed by the user 402 at the time of return Information such as contents is displayed as appropriate. Further, the operation of the drone 100 may be changed based on the input from the small mobile terminal 401a.

Normally, the drone 100 takes off from the departure / arrival point 406 outside the field 403 and returns to the departure / arrival point 406 after spraying the sprayed material on the field 403 or when it becomes necessary to replenish or charge the sprayed material. The flight route (invasion route) from the departure / arrival point 406 to the target field 403 may be stored in advance in the farming cloud 405 or the like, or may be input by the user 402 before the start of takeoff. The departure / arrival point 406 may be a virtual point defined by the coordinates stored in the drone 100, or may have a physical departure / arrival platform.

FIG. 7 shows a block diagram showing a control function of an embodiment of the spraying drone according to the present invention. The flight controller 501 is a component that controls the entire drone, and may be an embedded computer including a CPU, memory, related software, and the like. The flight controller 501 uses motors 102-1a and 102-1b via control means such as ESC (Electronic Speed Control) based on the input information received from the controller 401 and the input information obtained from various sensors described later. , 102-2a, 102-2b, 102-3a, 102-3b, 104-a, 104-b to control the flight of the drone 100. The actual rotation speeds of the motors 102-1a, 102-1b, 102-2a, 102-2b, 102-3a, 102-3b, 104-a, 104-b are fed back to the flight controller 501, and normal rotation is performed. It is configured so that it can be monitored. Alternatively, the rotary blade 101 may be provided with an optical sensor or the like so that the rotation of the rotary blade 101 is fed back to the flight controller 501.

The software used by the flight controller 501 can be rewritten through storage media, etc. for function expansion / change, problem correction, etc., or through communication means such as Wi-Fi communication and USB. In this case, protection is performed by encryption, checksum, electronic signature, virus check software, etc. so that rewriting by malicious software is not performed. In addition, a part of the calculation process used by the flight controller 501 for control may be executed by another computer located on the controller 401, the farming cloud 405, or somewhere else. Due to the high importance of the flight controller 501, some or all of its components may be duplicated.

The flight controller 501 communicates with the actuator 401 via the Wi-Fi slave unit function 503 and further via the base station 404, receives necessary commands from the actuator 401, and receives necessary information from the actuator 401. Can be sent to 401. In this case, the communication may be encrypted so as to prevent fraudulent acts such as interception, spoofing, and device hijacking. The base station 404 has the function of an RTK-GPS base station in addition to the communication function by Wi-Fi. By combining the signal from the RTK base station and the signal from the GPS positioning satellite, the flight controller 501 can measure the absolute position of the drone 100 with an accuracy of about several centimeters. Flight controllers 501 are so important that they may be duplicated and multiplexed, and each redundant flight controller 501 should use a different satellite to handle the failure of a particular GPS satellite. It may be controlled.

The 6-axis gyro sensor 505 is a means for measuring the acceleration of the drone body in three directions orthogonal to each other, and further, a means for calculating the velocity by integrating the acceleration. The 6-axis gyro sensor 505 is a means for measuring the change in the attitude angle of the drone aircraft in the above-mentioned three directions, that is, the angular velocity. The geomagnetic sensor 506 is a means for measuring the direction of the drone body by measuring the geomagnetism. The barometric pressure sensor 507 is a means for measuring barometric pressure, and can also indirectly measure the altitude of the drone. The laser sensor 508 is a means for measuring the distance between the drone body and the ground surface by utilizing the reflection of the laser light, and may be an IR (infrared) laser. The sonar 509 is a means for measuring the distance between the drone aircraft and the ground surface by utilizing the reflection of sound waves such as ultrasonic waves. These sensors may be selected according to the cost target and performance requirements of the drone. In addition, a gyro sensor (angular velocity sensor) for measuring the inclination of the aircraft, a wind sensor for measuring wind power, and the like may be added. Further, these sensors may be duplicated or multiplexed. If there are multiple sensors for the same purpose, the flight controller 501 may use only one of them, and if it fails, it may switch to an alternative sensor for use. Alternatively, a plurality of sensors may be used at the same time, and if the measurement results do not match, it may be considered that a failure has occurred.

The flow rate sensor 510 is a means for measuring the flow rate of the sprayed material, and is provided at a plurality of locations on the path from the tank 104 to the nozzle 103. The liquid drainage sensor 511 is a sensor that detects that the amount of sprayed material has fallen below a predetermined amount.

The growth diagnosis camera 512a is a means for photographing the field 403 and acquiring data for the growth diagnosis. The growth diagnostic camera 512a is, for example, a multispectral camera and receives a plurality of light rays having different wavelengths from each other. The plurality of light rays are, for example, red light (wavelength of about 650 nm) and near-infrared light (wavelength of about 774 nm). Further, the growth diagnosis camera 512a may be a camera that receives visible light.

The pathological diagnosis camera 512b is a means for photographing the crops growing in the field 403 and acquiring the data for the pathological diagnosis. The pathological diagnosis camera 512b is, for example, a red light camera. The red light camera is a camera that detects the amount of light in the frequency band corresponding to the absorption spectrum of chlorophyll contained in the plant, and detects, for example, the amount of light in the band around 650 nm. The pathological diagnosis camera 512b may detect the amount of light in the frequency bands of red light and near infrared light. Further, the pathological diagnosis camera 512b may include both a red light camera and a visible light camera such as an RGB camera that detects light amounts of at least three wavelengths in the visible light band.

It is known that diseases that occur in plants cause lesions on leaves, leaf sheaths, stems or ears. Diseases in which lesions occur include, for example, blast disease, sesame leaf blight, blight, and striped leaf blight. The mechanism of lesion development is that chlorophyll is first altered, decomposed or deficient, then the site withers and becomes a visible lesion, and then the lesion expands. Therefore, according to the red light camera, it is possible to acquire an image of an early lesion at an invisible stage.

FIG. 12 shows an image diagram of a photographed image of a leaf obtained by photographing a leaf of rice infected with blast with a red light camera. When shooting with a red light camera, the part where chlorophyll that absorbs red light is present appears black, and the part where chlorophyll is destroyed due to a disease such as blast absorbs red light. It looks white because it does not. When a disease such as blast occurs, the chlorophyll of the leaf is destroyed in the form of spots, so that an image in which the spot L1 appears in the leaf L can be obtained as shown in FIG.

Further, according to the visible light camera, it is possible to acquire an image of a visible lesion and an image capable of analyzing the color and shape of leaves, stems and ears.

The growth diagnosis camera 512a and the pathology diagnosis camera 512b may be realized by one hardware configuration.

The obstacle detection camera 513 is a camera for detecting a drone intruder, and since the image characteristics and the orientation of the lens are different from the growth diagnosis camera 512a and the pathological diagnosis camera 512b, what are the growth diagnosis camera 512a and the pathological diagnosis camera 512b? Another device. The switch 514 is a means for the user 402 of the drone 100 to make various settings. The obstacle contact sensor 515 is a sensor for detecting that the drone 100, in particular, its rotor or propeller guard part, has come into contact with an intruder such as an electric wire, a building, a human body, a standing tree, a bird, or another drone. .. The obstacle contact sensor 515 may be replaced by a 6-axis gyro sensor 505. The cover sensor 516 is a sensor that detects that the operation panel of the drone 100 and the cover for internal maintenance are in the open state. The inlet sensor 517 is a sensor that detects that the inlet of the tank 104 is in an open state.

These sensors may be selected according to the cost target and performance requirements of the drone, and may be duplicated / multiplexed. Further, a sensor may be provided at the base station 404, the actuator 401, or some other place outside the drone 100, and the read information may be transmitted to the drone. For example, a wind sensor may be provided in the base station 404 to transmit information on the wind and wind direction to the drone 100 via Wi-Fi communication.

The flight controller 501 sends a control signal to the pump 106 to adjust the discharge amount and stop the discharge. The current status of the pump 106 (for example, the number of revolutions) is fed back to the flight controller 501.

LED107 is a display means for notifying the drone operator of the drone status. Display means such as a liquid crystal display may be used in place of or in addition to the LED. The buzzer is an output means for notifying the state of the drone (particularly the error state) by an audio signal. The Wi-Fi slave unit function 519 is an optional component for communicating with an external computer or the like for transferring software, for example, in addition to the actuator 401. Instead of or in addition to the Wi-Fi slave function, other wireless communication means such as infrared communication, Bluetooth (registered trademark), ZigBee (registered trademark), NFC, or wired communication means such as USB connection You may use it. Further, instead of the Wi-Fi slave unit function, mutual communication may be possible by a mobile communication system such as 3G, 4G, and LTE. The speaker 520 is an output means for notifying the state of the drone (particularly the error state) by means of recorded human voice, synthetic voice, or the like. Depending on the weather conditions, it may be difficult to see the visual display of the drone 100 in flight. In such cases, voice communication is effective. The warning light 521 is a display means such as a strobe light for notifying the state of the drone (particularly the error state). These input / output means may be selected according to the cost target and performance requirements of the drone, and may be duplicated / multiplexed.

● Outline of control system As shown in Fig. 8, the plant pathological diagnosis system 1000 is a system including, for example, a drone 100, a user interface device 200, a measuring device 500, a diagnostic device 600, and a planning device 700, and these are network NWs. They are connected so that they can communicate with each other through. The diagnostic device 600 and the planning device 700 may have a hardware configuration or may be configured on the farming cloud 405. The drone 100, the user interface device 200, the diagnostic device 600, and the planning device 700 may be connected to each other wirelessly, or may be partially or wholly connected by wire.

The configuration shown in FIG. 8 is an example, and one component may include another component, and the functional unit of each component may be included in another component. .. For example, some or all of the functions of the diagnostic device 600 and the planning device 700 may be mounted on the drone 100.

The user interface device 200 may be provided with an input unit and a display unit by an operator, and may be realized by the function of the operator 401. Further, the user interface device 200 may be a personal computer, or information may be input and displayed in the UI on the Web via a Web browser installed in the personal computer.

● Functional part of the drone Drone 100 is equipped with a computing device such as a CPU (Central Processing Unit) for executing information processing and a storage device such as RAM (Random Access Memory) and ROM (Read Only Memory). As resources, it has at least a flight control unit 1001, a spray control unit 1002, a growth information acquisition unit 1003, and a pathological information acquisition unit 1004.

The flight control unit 1001 is a functional unit that operates the motor 102 and controls the flight and takeoff and landing of the drone 100. The flight control unit 1001 is realized by, for example, a flight controller 501, and controls the flight altitude, flight speed, and flight path to fly the drone 100 over the field.

The spray control unit 1002 is a functional unit that operates the pump 106 and controls the spraying of the sprayed material from the nozzles 103-1, 103-2, 103-3, 103-4. The spray control unit 1002 is realized by, for example, a flight controller 501.

Growth information acquisition unit 1003 is a functional unit that acquires growth information of crops growing in the field while the drone 100 is flying over the field. The growth information includes an image of the crop for diagnosing the growth state of the crop.

Utilizing the fact that the density of leaf chlorophyll (chlorophyll a, chlorophyll b, carotenoid, etc.) changes depending on the amount of nitrogen absorbed, the density of chlorophyll is estimated by analyzing the characteristics of the reflected light of the leaves, and the nitrogen to the leaves is estimated. It is known that the amount of absorption can be estimated and the degree of growth of crops can be measured based on the amount of nitrogen absorbed. Therefore, the growth information acquisition unit 1003 acquires the data used for the analysis of the growth condition of the crop by receiving the reflected light of the sunlight obtained from the field 403.

The growth information acquisition unit 1003 acquires an image of the crop with the growth diagnosis camera 512a. The growth information acquisition unit 1003 has a beam splitter and acquires only light rays in a predetermined frequency range from the light source. The light rays received by the growth information acquisition unit 1003 include reflected light that is mainly reflected from the crop by the light rays transmitted from the growth information acquisition unit 1003. The drone 100 acquires the growth information of the crops growing in the field 403 by receiving the reflected light reflected from the field 403 by the growth information acquisition unit 1003 while flying in the field 403 by the flight control unit 1001.

In addition, instead of or in addition to this, the growth information acquisition unit 1003 provides visual information such as the number of tillers, the color of the stem or rice ear, the amount of rice ear, or the length or deflection of the stem. You may get it. When acquiring only this visual information, the growth information acquisition unit 1003 can use a camera capable of receiving visible light.

The pathology information acquisition unit 1004 is a functional unit that acquires pathological information, that is, pathological information of crop diseases in the field while the drone 100 is flying over the field. The pathological information acquisition unit 1004 acquires an image of the crop for diagnosing the pathological state of the crop by the pathological diagnosis camera 512b. The pathological information acquisition unit 1004 acquires an image of at least one of a site where a lesion appears, for example, a leaf, a leaf sheath, a stem, and an ear. In addition, the pathological information acquisition unit 1004 may photograph the color or shape of the stem or ear. This is because there is a possibility of discoloration or deformation due to illness.

In the present embodiment, the drone 100 is provided with a spray control unit 1002, a growth information acquisition unit 1003, and a pathology information acquisition unit 1004, but the technical idea of the present invention is not limited to this. , The drone 100 may include at least a flight control unit 1001 and a pathology information acquisition unit 1004. Further, the spray control unit 1002 may be included in the pathological diagnosis system 1000 or may be included in the land traveling machine connected to the pathological diagnosis system 1000.

● Functional part of the diagnostic device As shown in Fig. 8, the diagnostic device 600 is a functional part that diagnoses plants, that is, crops, that grow in the field 403 to which the drone 100 flies, based on the information acquired by the drone 100. .. The diagnostic device 600 includes a computing device such as a CPU (Central Processing Unit) for executing information processing, and a storage device such as RAM (Random Access Memory) and ROM (Read Only Memory), whereby at least as a software resource, It is equipped with a medical history memory unit 601, a growth diagnosis unit 602, a climate information acquisition unit 603, a spot measurement unit 604, and a pathological diagnosis unit 605.

The medical history memory unit 601 is a functional unit that stores the medical history of diseases that have occurred in the field 403 in the past. The medical history includes at least one of the disease outbreak area, the type of outbreak, and the time of outbreak within field 403. The medical history may also include climatic information of the outbreak area at the time of the outbreak.

The medical history memory unit 601 may memorize the response record to the disease carried out in the field 403. Correspondence results include spraying the drug to the outbreak area and removing pathological leaves or pathological strains. The response record may include the type or concentration of the sprayed drug. The medical history storage unit 601 may receive the countermeasure determined by the planning device 700 and store it as a response record. In addition, the medical history and the response record may be input from the user interface device 200 by, for example, an operator.

The growth diagnosis unit 602 is a functional unit that diagnoses the growth status of crops in the field based on the growth information acquired by the growth information acquisition unit 1003. The growth diagnosis unit 602 calculates the NDVI (Normalized Difference Vegetation Index) based on the image obtained by the reflected light of red light (wavelength about 650 nm) and near infrared light (wavelength about 774 nm), and obtains the absorption rate of red light. In addition, the effective light receiving area can be estimated by NDVI. Generally, NDVI is calculated by the formula (IR-R) / (IR + R) (where IR is the reflectance of near-infrared light and R is the reflectance of red light). IR and R are obtained by analyzing field images for each frequency band.

The growth diagnosis unit 602 applies a frequency filter to the light rays received by the growth information acquisition unit 1003 in a hard or soft manner, so that the amount of light rays in a predetermined frequency range related to the growth situation, for example, the power spectral density. To get. The calculation process of the amount of light may be performed by the growth information acquisition unit 1003, and the growth diagnosis unit 602 may diagnose the growth state based on the amount of light received.

The growth diagnosis unit 602 diagnoses the growth status of the field based on the information stored in advance that associates the amount of light with the amount of growth in a predetermined frequency band. The growth diagnosis unit 602 may predict the yield in the field based on the growth condition.

The climate information acquisition unit 603 is a functional unit that acquires the climate information of the field 403. Climate information includes at least one of temperature, humidity and wind speed information. In addition, the climate information may include information on the wind direction. The climate information acquisition unit 603 may receive each measured value from, for example, a measuring instrument 500 arranged in the field 403, for example, a thermometer, a hygrometer, and an anemometer. Further, the drone 100 may include a part or all of each configuration of the measuring instrument 500.

The climate information acquisition unit 603 may receive information transmitted from the outside of the pathological diagnosis system 1000. The climate information acquisition unit 603 may acquire information from a meteorological satellite. Meteorological satellites are, for example, sunflowers. The climate information acquisition unit 603 may acquire information (public information) processed by various organizations such as the Japan Meteorological Agency, particularly public organizations, as climate information.

The spot measurement unit 604 is a functional unit that measures the state of spots occurring on the crop based on the image acquired by the pathological information acquisition unit 1004. The spot measuring unit 604 measures at least one parameter of the size, density, and number of spots generated on the crop based on the image. That is, the spot measurement unit 604 includes at least one of a spot counting unit 604a, a spot size measuring unit 604b, and a spot density measuring unit 604c.

The spot counting unit 604a is a functional unit that counts spots occurring on at least one of the leaves, leaf sheaths, stems and ears of a plant by image analysis. The spot counting unit 604a may count the number of spots for each site where the spots are generated. Counting for each development site is performed by distinguishing, for example, leaves, leaf sheaths and stems. In addition, the tip of the leaf, the middle of the leaf, and the origin of the leaf may be counted separately. The spot size measuring unit 604b is a functional unit that measures the size of spots by image analysis. The spot density measuring unit 604c is a functional unit that measures the number of spots generated per predetermined region, that is, the density of spots. The spot density measuring unit 604c may obtain the spot density by measuring the distance between the spots.

The pathological diagnosis unit 605 is a functional unit that diagnoses the morbidity of plant diseases in the field. The pathological diagnosis unit 605 makes a pathological determination as to whether or not the disease is a disease based on the measurement results of at least one of the parameters of the spot size, the spot density, and the number of spots. That is, the pathological diagnosis unit 605 may determine that the patient is ill when the spots are larger than a predetermined size. In this case, for example, the disease can be determined on condition that the area of the spots is 100 square millimeters or more. The pathological diagnosis unit 605 may determine that the patient is ill when the spot density is equal to or higher than a predetermined value. In this case, for example, when the distance between the spots is 10 cm or less, it may be determined that the disease has occurred. The pathological diagnosis unit 605 may determine that the patient is ill when the number of spots is equal to or greater than a predetermined value. In this case, for example, when the number of spots having a spot area of 4 square millimeters or more is 10 or more around a predetermined area, it may be determined that the disease has occurred. Alternatively, the pathological diagnosis unit 605 may make a pathological determination based on a plurality of parameters among the spot size, the spot density, and the number of spots.

When making a pathological determination based on one or more of the spot size, spot density, and spot number, the pathology is based on the likelihood distribution table by the value of one parameter or the combination of the values of multiple parameters. It is also possible to generate an occurrence likelihood. In this case, the generated pathological likelihood value may be output, or the fact that the pathological occurrence is detected when the generated pathological likelihood value exceeds a predetermined threshold value is output. Alternatively, both the pathological occurrence likelihood and the pathological occurrence detection information may be output.

The pathological diagnosis unit 605 may make a pathological diagnosis for each plant strain. Further, the pathological diagnosis unit 605 may subdivide the field 403 into a plurality of regions and perform pathological diagnosis for each region. The pathological diagnosis unit 605 subdivides the field 403 into a mesh, for example. Each area has a rectangular shape of, for example, 1 m square. Further, the pathological diagnosis unit 605 may make a pathological diagnosis for each image taken by the pathological diagnosis camera 512b.

The pathological diagnosis unit 605 may diagnose the type of disease affecting the plant based on the spot size, spot density or spot number. The pathological diagnosis unit 605 may diagnose the type of disease based on the site where the spots are generated. For example, the pathological diagnosis unit 605 stores the type of the disease in association with the shape, size, density, number of spots, or spot occurrence site or range of the spots that occur, and refers to the information to store the disease. Diagnose the type.

Further, the pathological diagnosis unit 605 may make a pathological determination based on the past medical history information stored in the medical history storage unit 601. For example, if there is a history of disease outbreaks in the same area last year, it may be determined that there is a high probability that the area has a disease. Specifically, even when a part or all of the measurement results of the spots do not satisfy the first threshold value, it may be determined that the patient is ill based on the occurrence history. Further, a second threshold value smaller than the first threshold value is defined in advance for the measurement result of the spot, and if the measurement result is equal to or more than the second threshold value and less than the first threshold value and there is an occurrence history, the disease is found in the area. It may be determined that it has occurred. Alternatively, the above-mentioned pathological likelihood may be calculated in consideration of past medical history information.

The pathological diagnosis unit 605 may make a pathological judgment based on the climate information. Specifically, it may be determined that the lower the temperature, the higher the humidity, and the lower the wind speed, the higher the probability that the disease has occurred. This condition is because it is known that the climate is vulnerable to disease and easy to progress. The pathological diagnosis unit 605 has a threshold value for at least one of temperature, humidity and wind speed, and when the acquired climate information is equal to or higher than the threshold value, a part or all of the measurement results of the spots do not meet the first threshold value. In some cases, it may be determined that the patient is ill. Alternatively, the above-mentioned pathological likelihood may be calculated in consideration of climate information.

The pathological diagnosis unit 605 may determine the progress of the disease. The progress is, for example, three stages of early, middle and late stages, but may be two stages or further subdivided into multiple stages. Further, even if the condition is not diagnosed as ill, the condition that may be ill may be determined as the "suspected pathology" condition. The pathological diagnosis unit 605 determines the progress of the disease based on at least one of the shape and size of the spot. The shape of the spot is, for example, the length of the spot. The length of the spots may be calculated by obtaining the minor axis and the major axis of the oval-shaped spots and calculating the ratio of the minor axis to the major axis. This is because the spots are known to grow as the disease progresses. When the length of the spot is equal to or greater than a predetermined third threshold value, the pathological diagnosis unit 605 determines that the state is more advanced than the earliest stage of development, for example, "middle stage" or "late stage".

The pathological diagnosis unit 605 may determine the progress of the disease based on the information obtained by the visible light camera. For example, it is known that the area around the lesion turns black as the disease progresses after the chlorophyll is destroyed and the lesion develops. According to the visible light camera, the discolored region can be detected. Since discoloration around the lesion occurs after the onset of the lesion, the pathological diagnosis unit 605 determines that the discolored region is more advanced than the earliest stage of development, for example, "middle stage" or "late stage". To do.

The pathological diagnosis unit 605 may use the growth status of the plant for pathological determination or determination of disease progression. For example, the pathological diagnosis unit 605 may determine that the disease is ill by referring to the specific growth condition when determining the disease that is likely to be affected in the case of the specific growth condition.

Further, the pathological diagnosis unit 605 may make a pathological diagnosis based on the color or shape of the stem or ear.

The target plant for which the diagnostic device 600 performs pathological determination is assumed to be paddy rice, but the technical scope of the present invention is not limited to this, and another plant capable of pathological diagnosis mainly by photographing from the sky may be used. The diagnostic apparatus 600 can perform pathological diagnosis based on images of leaves, stems, fruits and the like having chlorophyll. The diagnostic apparatus 600 may perform pathological determination of a plurality of types of plants, store different pathological determination criteria for each type of plant, and perform pathological determination according to different determination criteria for each type of plant.

● Functional part of the planning device As shown in Fig. 8, the planning device 700 includes arithmetic units such as a CPU (Central Processing Unit) for executing information processing, RAM (Random Access Memory), ROM (Read Only Memory), etc. It has at least a countermeasure decision unit 701 and a result output unit 704 as software resources.

The countermeasure decision unit 701 is a functional unit that determines the necessity of dealing with a disease based on the result of pathological diagnosis. The countermeasure decision unit 701 determines the necessity of dealing with the disease for each strain or each area. The countermeasure determination unit 701 decides to take countermeasures when the diagnostic device 600 determines that the patient is ill.

The countermeasure decision unit 701 determines the countermeasures to be taken in the field based on the progress of the disease. Countermeasures include, for example, at least one of visual confirmation of the strain origin, rephotographing, waiting, spraying pesticides, removal of pathological leaves, removal of pathological strains, and removal of strains in the pathological strain outbreak area.

The stock yuan visual confirmation instruction is a measure to encourage the stock yuan to be visually confirmed. In the field 403, the humidity around the plant root is higher than that around the leaves, and the probability of developing the disease is high. On the other hand, since the plant root is difficult to see from above, the disease may not be detected by photographing from the sky. According to the stock origin visual confirmation instruction, even if the pathological condition is difficult to detect by the drone 100, the disease can be detected at an early stage.

Agricultural chemical spraying is the work of spraying pesticides on a predetermined area including plants in which a disease has been found. The area to be sprayed, the type and concentration of the pesticide are determined by the spraying mode determining unit 702 described later.

Removal of pathological leaves is the work of removing only the diseased leaves, that is, the pathological leaves. Removal of pathological strains is the task of removing diseased strains, i.e. pathological strains. Removal of strains in the pathological strain development area is an operation of removing all crops growing in a predetermined area including the pathological strains.

In removing the disease, severe countermeasures are required as the disease progresses. Specifically, as the disease progresses, it is recommended to in order to visually confirm the strain origin, re-photograph, wait, spray pesticides, remove pathological leaves, remove pathological strains, and remove strains in the pathological strain occurrence area. In addition, the instruction to visually confirm the stock origin, re-photographing, and waiting are in no particular order, and may be presented at the same time as a countermeasure. For example, the countermeasure decision unit 701 outputs "wait and see" when the progress is "early" when it has a function of judging the progress of the disease in at least two stages including "early stage" and "late stage". , "Agricultural chemical spraying", "Removal of pathological leaves" or "Removal of pathological strain" is output in the case of "late stage" in which the progress is more advanced than the initial stage.

In addition, the countermeasure determination unit 701 outputs "pesticide spraying" when the progress is "early", and outputs "removal of pathological leaves" or "removal of pathological strain" when the progress is "late". It may be a thing.

Further, the countermeasure determination unit 701 may output "removal of pathological leaves" when the progress is "early" and "removal of pathological strains" when the progress is "late".

The countermeasure decision unit 701 outputs "wait and see" when the progress is "early" when the progress of the disease is judged in at least three stages including "early", "middle" and "late". "Agricultural chemical spraying" is output when the progress is more advanced than the initial stage, and "pathological leaf removal" or "pathological strain removal" is output when the progress is more advanced than the middle stage. It may be output.

In addition, the countermeasure decision unit 701 outputs "pesticide spraying" when the progress is "early", outputs "removal of pathological leaves" when the progress is "middle", and the progress is "late". In the case of, "removal of pathological strain" may be output.

The countermeasure decision unit 701 may decide the countermeasure by referring to the climate information. This is because the disease may not progress and spread to surrounding crops depending on the weather. For example, when the humidity is below the specified value, the temperature is above the specified value, and the wind speed is at least the specified value, the countermeasure determination unit 701 outputs a countermeasure that is lighter than the countermeasure associated with the determined progress. You may. That is, for example, the countermeasure determination unit 701 outputs "wait and see" when the above conditions are satisfied in a mode in which the progress is determined to be "initial" and "pesticide spraying" is associated with "initial". You may. Assuming that the disease is cured only in the early stage, a milder countermeasure may be output only when the climate information meets the predetermined conditions and the progress is early. With this configuration, the characteristics of the disease can be used to more accurately determine appropriate countermeasures. In particular, it is possible to suppress excessive measures and prevent excessive spraying of pesticides and reduction in yield due to excessive removal.

According to the measure determination unit 701, suitable measures can be determined to stop the spread of the disease in the field 403. Further, according to the countermeasure determination unit 701, it is possible to determine an appropriate countermeasure according to the progress of the disease, so that excessive spraying of pesticides can be prevented. As a result, the cost of pesticides can be suppressed, and crops with a small amount of pesticides can be grown. Further, according to the countermeasure determination unit 701, since the pathological leaves can be appropriately removed and the pathological strains can be removed, excessive removal work can be prevented. As a result, the labor cost of the removal work can be suppressed. In addition, the yield can be maintained because the leaves and strains are not excessively removed.

The countermeasure determination unit 701 includes a spray mode determination unit 702 and a countermeasure timing calculation unit 703.

The spraying mode determining unit 702 is a functional unit that determines the mode in which the drug is sprayed on the field 403. The spraying mode determining unit 702 has a spraying area determining unit 702a, a pesticide determining unit 702b, and a concentration determining unit 702c.

The spraying area determination unit 702a is a functional unit that determines a predetermined range including a pathological strain determined to be disease as a spraying area.

The spraying area determination unit 702a sprays pesticides in areas where there is a high risk of spreading the disease. Bacterial growth is a cause of diseases that affect plants. Since the spores of the fungus are blown by the wind and move, it is presumed that the higher the wind speed, the wider the spores spread. It is also estimated that spores are spreading leeward. Furthermore, if the disease in the found pathological strain is advanced, it is presumed that time has passed since the onset of the disease, that is, the spores have spread over a wide area.

Therefore, the spraying area determination unit 702a determines the distance from the pathological strain to which the pesticide is sprayed based on the wind speed information. That is, the spraying area determination unit 702a increases the distance from the pathological strain on which the pesticide is sprayed as the wind speed increases. In addition, the spraying area determination unit 702a determines the area where the pesticide is sprayed based on the wind direction information. That is, the spraying area determination unit 702a determines to spray the pesticide on the area extending from the pathological strain toward the leeward side. In other words, the spray area determination unit 702a makes the distance from the pathological strain to the spray range end in the leeward direction longer than the distance from the pathological strain to the spray range end in the leeward direction. The wind speed information and the wind direction information may receive information from the measuring instrument 500.

The spraying area determination unit 702a determines the area to spray pesticides based on the progress of the disease in the found pathological strain. That is, the spraying area determination unit 702a increases the area of the spraying area as the disease of the pathological strain progresses. In other words, the spray area determination unit 702a increases the distance from the pathological strain to the end of the spray range as the disease progresses.

The spraying area determination unit 702a may estimate the elapsed time from the onset of the disease based on the progress of the disease, and determine the area to spray the pesticide based on the elapsed time. The spraying area determination unit 702a increases the spraying area as the elapsed time increases. The elapsed time may be estimated by referring to temperature, humidity, and wind speed information in addition to the progress. For example, the lower the temperature, the higher the humidity, or the lower the wind speed, the faster the disease progresses, and the shorter the elapsed time from the onset of the disease may be estimated.

In addition, the countermeasure determination unit 701 may determine the area for which the spraying area determination unit 702a determines the spraying as the information of the target range in the area requiring the removal of the strain, that is, the "removal of the strain in the pathological strain occurrence area". ..

The area where the spraying area determination unit 702a determines the spraying is not limited to the flight range of the drone 100, but may include the area around the flight range. The area may be a field managed by another worker, regardless of the field directly managed by the worker using the pathological diagnosis system 1000. Information on the area requiring spraying may be managed by the comprehensive manager of the field in the area, and the comprehensive manager may notify each worker. Further, the information of the determined spraying area may be output to another system to be linked.

The pesticide determination unit 702b is a functional unit that determines the type of pesticide according to the progress of the disease. The pesticide determination unit 702b has a table for associating the progress of the disease with suitable pesticides, and the type of pesticide may be determined with reference to the table. In this description, pesticides are a concept that broadly includes various liquids, powders, granules, etc. that are effective for spraying as a countermeasure against diseases.

The concentration determination unit 702c is a functional unit that determines the concentration of pesticides to be sprayed according to the progress of the disease. Concentration determination unit 702c decides to apply a higher concentration of pesticide as the disease progresses. When spraying high-concentration pesticides with Drone 100, the tank 104 is filled with high-concentration pesticides in advance and sprayed, and the pesticides are sprayed while flying at a lower speed than when spraying the standard concentration. , The concentration of the pesticide in the field may be ensured by changing the flight mode such as increasing the discharge amount from the nozzle 103 or flying and spraying the same location a plurality of times. In this case, the concentration determining unit 702c may have a function of determining the flight mode of the drone 100 according to the spray concentration.

Countermeasure timing calculation unit 703 is a functional unit that calculates the deadline for taking countermeasures. Crop diseases progress day by day, and by taking countermeasures at an early stage, the diseases can be eliminated with mild measures. For example, it is advisable to take measures within a predetermined time from the outbreak of the disease. Therefore, the countermeasure timing calculation unit 703 estimates the elapsed time from the occurrence of the disease based on the progress of the disease, and calculates the time when the predetermined time is added to the time of the occurrence of the disease as the countermeasure deadline. The deadline for countermeasures is, for example, within 48 hours after the outbreak of the disease. Further, the countermeasure timing calculation unit 703 may determine the flight timing of the drone 100. The countermeasure timing calculation unit 703 may refer to the flight plan of the drone 100 and decide to take countermeasures at the timing when the flight is scheduled. The countermeasure timing calculation unit 703 may newly determine the flight timing and urge the operator.

The result output unit 704 is a functional unit that outputs the decision result of the countermeasure. The result output unit 704 outputs at least one of a determination result of the presence or absence of a disease, a progress of the disease, a recommended countermeasure, and a countermeasure deadline for which the countermeasure should be taken. The result output unit 704 may display the determination result on the user interface device 200. Further, the result output unit 704 may display the determination result on the screen of the personal computer, or may display the determination result on the UI on the Web via the Web browser installed in the personal computer.

The result output unit 704 may display a plurality of recommended countermeasures and allow the operator to select the countermeasure to be executed. The result output unit 704 may display the recommended countermeasures in the recommended order. The worker can flexibly take measures according to the work convenience and the like. After displaying a plurality of recommended countermeasures, the user interface device 200 accepts the selection input of the countermeasures to be actually performed, and when the countermeasures are input, the input countermeasures are recorded in the medical history storage unit 601 as the response record. To do.

The result output unit 704 may transmit the determination result to the flight control unit 1001 of the drone 100. The drone 100 may fly for pathological diagnosis or for drug spraying based on the decision result. The drone 100 may also perform the necessary preparatory movements for those flights.

● Result output screen As shown in Fig. 9, the result output screen G1 is displayed on the user interface device 200. The result output screen G1 displays fields 403a, 403b, 403c, and 403d, and virtual lines that divide each field into a mesh. Of the divided areas, the areas 403a-1 and 403b-1 where the pathological strain exists are displayed in a manner different from those of the other areas. In the present embodiment, the fields 403a to 403d are shaded, and the areas 403a-1 and 403b-1 where the pathological strains are present are shown in white.

In other words, the result output screen G1 displays the shape of the field and the area where the pathological strain exists in an overlapping manner. For the shape of the field, the data of the aerial photograph or the farmland bank may be referred to, or the data input by the operator may be used. The field displayed on the result output screen G1 may be a photograph or an illustration. The area where the pathological strain exists is identified by, for example, the RTK-GPS information acquired by the drone 100 during flight. According to this configuration, the location of the pathological strain can be listed.

Further, on the result output screen G1, a progress display column g10 indicating the progress of the disease in the pathological strain and a countermeasure display column g20 for displaying the countermeasures for the pathological strain displayed in the progress display column g10 are displayed. Has been done. When there are multiple areas where the pathological strain exists, the pathological strain existing area 403a-1 displayed in the progress display column g10 and the countermeasure display column g20 can be distinguished from the other existing area 403b-1. .. For example, pin P is displayed in the existence area 403a-1. By selecting the existence areas 403a-1 and 403b-1 on the result output screen G1, the existence area for displaying the progress and countermeasures is switched.

One or more countermeasure columns g21 and g22 are displayed in the countermeasure display column g20. By pressing the countermeasure columns g21 and g22, the details of the countermeasure and the response deadline may be displayed. Further, the user interface device 200 may be able to input that the operator has implemented the countermeasure based on the operation for the countermeasure columns g21 and g22.

When the existence areas 403a-1 and 403b-1 are specified, the screen transitions to the detailed result output screen G2 shown in FIG. 10, which enlarges and displays the pathological strains in the existence area.

As shown in FIG. 10, the image g30 acquired by the pathological diagnosis camera 512b is displayed on the result output screen G2. In addition, a pathological region identification mark g31 indicating a pathological leaf or a pathological strain is displayed superimposed on the image g30. According to this configuration, it is easy to search for a pathological leaf or a pathological strain in the field. In particular, it is useful for visual confirmation or removal of pathological leaves or pathological strains. By selecting the pathological region identification mark g31, it may be possible to input that the visual confirmation has been completed. According to this configuration, it is easy to manage the results of countermeasures against pathological strains.

● Flow chart for pathological diagnosis As shown in Fig. 11, the drone 100 first flies over the field and acquires an image of the crop (S11). Then, based on the acquired image, at least one of the parameters of spot size, density and number is measured (S12). Next, it is determined whether the parameter measurement result is within the predetermined range (S13). When the measurement result of the parameter is within the predetermined range, it is determined that the determination target is not a disease (S14). When the measurement result of the parameter is out of the predetermined range, it is determined that the determination target is ill (S15). Next, the progress of the disease is determined (S16). Determine countermeasures based on the progress and output (S17). The determination in step S12 may be made for each stock or for each image. When the determination is performed for each stock and a plurality of stocks are reflected in one acquired image, the processes of steps S12 to S17 are repeated for one acquired image.
Instead of determining the pathological occurrence based on the threshold value determination of each parameter, the pathological occurrence likelihood may be generated based on the value of each parameter, and the presence or absence of the pathological occurrence may be determined based on the pathological occurrence likelihood. In this case, S13 to S15 can be replaced as follows. That is, in S13, the pathological likelihood is generated based on the measurement result of the parameter (S13). Next, in S14, when the generated pathological likelihood is less than a predetermined value, it is determined that the determination target is not a disease (S14). Further, in S15, when the generated pathological likelihood is equal to or higher than a predetermined value, it is determined that the determination target is a disease (S15).

(Technically remarkable effect of the present invention)
In the plant pathological diagnosis system according to the present invention, the pathological diagnosis of crops can be accurately performed.

Claims (16)

1. A flight control unit that flies the drone over the field,
   A pathology information acquisition unit that is mounted on the drone and acquires images of crops growing in the field.
   A spot measuring unit for measuring at least one parameter of the size, density, and number of spots generated in the crop based on the image.
   Based on the measurement results of the parameters, a pathological diagnosis unit that determines the pathology of whether or not the crop is sick, and
   To prepare
   Plant pathological diagnosis system.
   
2. Further provided with a medical history storage unit for storing the past medical history in the field,
   The pathological diagnosis unit makes the pathological determination based on the medical history.
   The plant pathological diagnosis system according to claim 1.
   
3. The pathological diagnosis unit makes a pathological determination based on the climate information of the field.
   The plant pathological diagnosis system according to claim 1 or 2.
   
4. The climate information includes at least one of temperature, humidity and wind speed information.
   The plant pathological diagnosis system according to claim 3.
   
5. The drone is equipped with a red light camera that detects the amount of light in the frequency band of red light.
   The pathology information acquisition unit acquires the image with the red light camera.
   The plant pathological diagnosis system according to any one of claims 1 to 4.
   
6. The pathological diagnosis unit determines the progress of the disease based on at least one of the shapes and sizes of the spots generated on the crop.
   The plant pathological diagnosis system according to any one of claims 1 to 5.
   
7. The drone further comprises a visible light camera that detects light intensity at at least three wavelengths in the visible light band.
   The pathological diagnosis unit determines the progress based on the information obtained by the visible light camera.
   The plant pathological diagnosis system according to claim 6.
   
8. A countermeasure determination unit for determining countermeasures to be taken in the field according to the progress is further provided.
   The plant pathological diagnosis system according to claim 6 or 7.
   
9. The countermeasures include at least one of visual confirmation of the strain origin, re-photographing, waiting, spraying pesticides, removal of pathological leaves, removal of pathological strains, and removal of strains in the pathological strain occurrence area.
   The plant pathological diagnosis system according to claim 8.
   
10. The countermeasure determination unit determines the pesticide spraying area according to the progress.
    The plant pathological diagnosis system according to claim 8 or 9.
    
11. The countermeasure determination unit determines the spraying concentration of the pesticide according to the progress.
    The plant pathological diagnosis system according to any one of claims 8 to 10.
    
12. The countermeasure determination unit determines the type of pesticide to be sprayed according to the progress of the disease.
    The plant pathological diagnosis system according to any one of claims 8 to 11.
    
13. A result output unit for displaying the determination result of the countermeasure determination unit on the display unit or transmitting the determination result to the flight control unit of the drone is further provided.
    The plant pathological diagnosis system according to any one of claims 8 to 12.
    
14. Flight control steps to fly the drone over the field,
    A pathological information acquisition step of acquiring an image of a crop mounted on the drone and growing in the field, and
    A spot measurement step that measures at least one parameter of the size, density, and number of spots that occur on the crop based on the image.
    Based on the measurement results of the parameters, a pathological diagnosis step for determining whether the crop is diseased or not, and a pathological diagnosis step.
    including,
    Pathological diagnosis method of plants.
    
15. With a spot measuring unit that measures at least one parameter of the size, density, and number of spots generated in the crop based on the image of the crop growing in the field acquired by the drone flying over the field. ,
    Based on the measurement results of the parameters, a pathological diagnosis unit that determines the pathology of whether or not the crop is sick, and
    To prepare
    Plant pathological diagnosis device.
    
16. A flight control unit that flies the drone over the field,
    A pathology information acquisition unit that acquires images of crops growing in the field, and
    A spot measuring unit for measuring at least one parameter of the size, density, and number of spots generated in the crop based on the image.
    Based on the measurement results of the parameters, a pathological diagnosis unit that determines the pathology of whether or not the crop is sick, and
    To prepare
    Drone.
    
    
    

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