JP7411259B2 - Plant pathology diagnosis system, plant pathology diagnosis method, plant pathology diagnosis device, and drone - Google Patents

Description

The present invention relates to a plant pathology diagnosis system, a plant pathology diagnosis method, a plant pathology diagnosis apparatus, and a drone.

Applications of small helicopters (multicopters), commonly called drones, are progressing. One of its important application fields is the spraying of agricultural chemicals, liquid fertilizers, etc. onto farmland (fields) (for example, Patent Document 1). In relatively small agricultural areas, it is often appropriate to use drones rather than manned airplanes or helicopters.

Patent Document 2 describes an image analysis means for acquiring captured images during flight, a pest detection means for detecting pests attached to crops based on the image analysis means, and a method for detecting pests attached to crops. A mobile body control application is disclosed that includes a mobile body control means for controlling the mobile body to spray a pest control agent based on position information.

Patent publication publication JP2001-120151 Patent Publication Patent 6427301

A plant pathological diagnosis system that accurately performs pathological diagnosis of crops is provided.

In order to achieve the above object, a plant pathological diagnosis system according to one aspect of the present invention includes a flight control unit that flies a drone over a field, and a flight control unit that is mounted on the drone and that displays images of crops growing in the field. a pathological information acquisition unit that acquires pathological information; a spot measurement unit that measures at least one parameter of the size, density, and number of spots occurring on the crop based on the image; , and a pathological diagnosis section that performs pathological determination as to whether or not the crop is diseased.

The farm may further include a medical history storage section that stores past medical history in the field, and the pathological diagnosis section may perform the pathology determination based on the medical history.

The pathological diagnosis section may perform pathological determination based on climate information of the field.

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

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

The drone is equipped with a visible light camera such as an RGB camera that detects the amount of light of at least three wavelengths in the visible light band, and the pathological diagnosis section determines the progress based on information obtained by the visible light camera. You can also use it as

The method may further include a countermeasure determining unit that determines a countermeasure to be taken for the field depending on the progress.

The countermeasures may include at least one of the following: visually confirming the plant, re-photographing, observing, spraying pesticides, removing pathological leaves, removing pathological plants, and removing plants in areas where pathological plants occur.

The countermeasure determining unit may determine a pesticide spraying area depending on the progress.

The countermeasure determining unit may determine the spray concentration of the pesticide depending on the progress.

The countermeasure determining unit may determine the type of pesticide to be sprayed depending on the progress of the disease.

The drone may further include a result output unit that displays the determination result of the countermeasure determination unit on a display unit or transmits it to a flight control unit of the drone.

In order to achieve the above object, a method for diagnosing plant pathology according to another aspect of the present invention includes a flight control step of flying a drone over a field, and a flight control step of flying a drone over a field; a step of acquiring pathological information; a step of measuring spots, measuring at least one parameter of size, density, and number of spots occurring on the crop based on the image; , a pathological diagnosis step of performing a pathological determination as to whether or not the crop is diseased.

In order to achieve the above object, a plant pathological diagnosis device according to yet another aspect of the present invention provides a plant pathological diagnosis device based on images of crops growing in the field, which are acquired by a drone flying over the field. a spot measuring section that measures at least one parameter of the size, density, and number of spots; a pathological diagnosis section that makes a pathological determination as to whether or not the crop is diseased based on the measurement results of the parameters; Equipped with

In order to achieve the above object, a drone according to yet another aspect of the present invention includes: a flight control unit that flies the drone over a field; a pathological information acquisition unit that acquires images of crops growing in the field; a spot measuring unit that measures at least one parameter of the size, density, and number of spots appearing on the crop based on an image; and a spot measuring unit that determines whether or not the crop is diseased based on the measurement results of the parameters. A pathological diagnosis section that performs pathological determination.

It is possible to accurately perform pathological diagnosis of crops.

FIG. 1 is a plan view of a drone according to the present invention. It is a front view of the said drone. It is a right side view of the said drone. It is a rear view of the said drone. It is a perspective view of the above-mentioned drone. 1 is an overall conceptual diagram of a pathological diagnosis system according to the present invention. It is a functional block diagram that the above-mentioned drone has. FIG. 2 is a functional block diagram of a drone, a user interface device, a diagnostic device, and a planning device included in the pathological diagnosis system. It is another example of the result output screen output by the said pathological diagnosis system. It is another example of the result output screen output by the said pathological diagnosis system. The above-mentioned pathological diagnosis system is a flowchart for performing pathological diagnosis of crops. It is an image diagram of a photographed image obtained by photographing a rice leaf infected with blast disease using a red light camera equipped with the above-mentioned drone.

Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings. All figures are illustrative. In the detailed description that follows, for purposes of explanation, certain specific details are set forth to facilitate a thorough understanding of the disclosed embodiments. However, embodiments are not limited to these specific details. In other instances, well-known structures and devices are shown schematically in order to simplify the drawings.

First, the configuration of the drone according to the present invention will be explained. In this specification, a drone refers to a drone, regardless of its power means (electric power, prime mover, etc.), control method (wireless or wired, autonomous flight type or manually operated type, etc.). This refers to all flying vehicles with multiple rotary wings.

As shown in FIGS. 1 to 5, the rotary blades 101-1a, 101-1b, 101-2a, 101-2b, 101-3a, 101-3b, 101-4a, 101-4b (also called rotors) are It is a means to fly 100 drones, and is equipped with 8 aircraft (4 sets of two-stage rotor blades), taking into account the balance of flight stability, aircraft size, and power consumption. Each rotor blade 101 is arranged on the four sides of the housing 110 of the drone 100 by an arm extending from the housing 110. In other words, rotary blades 101-1a and 101-1b are located at the left rear in the direction of travel, rotary blades 101-2a and 101-2b are located at the left front, rotary blades 101-3a and 101-3b are located at the right rear, and rotary blade 101- is located at the right front. 4a and 101-4b are placed respectively. Note that the traveling direction of the drone 100 is downward in the plane of the paper in FIG.

Grid-like propeller guards 115-1, 115-2, 115-3, and 115-4, each having a substantially cylindrical shape, are provided around the outer periphery of each set of rotary blades 101 to prevent the rotary blades 101 from interfering with foreign objects. As shown in FIGS. 2 and 3, the radial members for supporting the propeller guards 115-1, 115-2, 115-3, and 115-4 are not horizontal but have a tower-like structure. This is to encourage the member to buckle to the outside of the rotor blade in the event of a collision, and to prevent interference with the rotor.

Rod-shaped legs 107-1, 107-2, 107-3, and 107-4 extend downward from the rotation axis of the rotor blade 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- 2b, 101-3a, 101-3b, 101-4a, 101-4b (typically an electric motor, but a motor etc. may also be used), one for each rotor. It is being Motor 102 is an example of a propulsion device. The upper and lower rotary blades (for example, 101-1a and 101-1b) and the corresponding motors (for example, 102-1a and 102-1b) in one set are for the stability of the drone's flight, etc. The axes are colinear and rotate in opposite directions.

Four nozzles 103-1, 103-2, 103-3, and 103-4 are provided as means for spraying the material downward. In the present specification, the term "sprayed material" generally refers to liquid or powder sprayed onto a field, such as agricultural chemicals, herbicides, liquid fertilizers, insecticides, seeds, and water.

The tank 104 is a tank for storing spray material, and is provided at a position close to and lower than the center of gravity of the drone 100 from the viewpoint of weight balance. Hoses 105-1, 105-2, 105-3, and 105-4 are means for connecting the tank 104 and each nozzle 103-1, 103-2, 103-3, and 103-4, and are made of hard material. The nozzle may also have the role of supporting the nozzle. Pump 106 is a means for discharging the spray from the nozzle.

FIG. 6 shows an overall conceptual diagram of a flight control system for a drone 100 according to the present invention. This figure is a schematic diagram and is not to scale. In the figure, the drone 100, the controller 401, and the small mobile terminal 401a are each connected to the base station 404, and only the controller 401 is connected to the farming cloud 405, but the connection relationship is for illustrative purposes only. Not limited to. The drone 100, the controller 401, the small mobile terminal 401a, and the base station 404 are each connected to the farming cloud 405. These connections may be made by wireless communication using Wi-Fi, a mobile communication system, or the like, or may be partially or entirely wired.

The controller 401 is operated by a user 402 to transmit commands to the drone 100, and also to display information received from the drone 100 (for example, position, stored amount of spray material, remaining battery level, camera image, etc.) It may be realized by a portable information device such as a general tablet terminal running a computer program. The operating device 401 includes an input section and a display section as a user interface device. Although the drone 100 according to the present invention is controlled to fly autonomously, it may be capable of manual operation during basic operations such as takeoff and return, and in emergencies. In addition to the portable information device, an emergency operating device (not shown) having a function exclusively for emergency stop may be used. The emergency operating device may be a dedicated device equipped with a large emergency stop button or the like so that a quick response can be taken in an emergency. Furthermore, in addition to the operating device 401, the system may include a small mobile terminal 401a, such as a smartphone, that can display part or all of the information displayed on the operating device 401. Further, the drone 100 may have a function of changing the operation of the drone 100 based on information input from the small mobile terminal 401a. The small mobile terminal 401a is connected to, for example, a base station 404, and can receive information etc. from the farming cloud 405 via the base station 404.

The field 403 is a rice field, field, etc. that is the target of spraying by the drone 100. In reality, the topography of field 403 is complex, and there are cases where a topographic map cannot be obtained in advance, or where the topographic map and the situation on the field are at odds. Typically, the field 403 is adjacent to houses, hospitals, schools, other crop fields, roads, railways, etc. Further, there may be cases where there are intruders such as buildings or electric wires in the field 403.

The base station 404 is a device that provides a base unit function for Wi-Fi communication, etc., and may also function as an RTK-GPS base station and be able to provide the accurate position of the drone 100 (Wi-Fi communication). (The base unit function for Fi communication and the RTK-GPS base station may be independent devices.) Furthermore, 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 and related software operated on a cloud service, and may be wirelessly connected to the controller 401 via a mobile phone line or the like. 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, understand the growth status of crops, and perform processing to determine a flight route. Additionally, the stored topographical information of the field 403 and the like may be provided to the drone 100. In addition, a history of flights 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. The display section of the small mobile terminal 401a displays 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 and arrival point 406, and the work that the user 402 should do when returning. Information such as content is displayed as appropriate. Furthermore, the operation of the drone 100 may be changed based on input from the small mobile terminal 401a.

Normally, the drone 100 takes off from a departure/arrival point 406 outside the field 403 and returns to the departure/arrival point 406 after spraying the material on the field 403 or when it is necessary to replenish or charge the material to be sprayed. The flight route (intrusion 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 and landing point 406 may be a virtual point defined by coordinates stored in the drone 100, or may have a physical departure and landing pad.

FIG. 7 shows a block diagram showing the control functions of the embodiment of the spraying drone according to the present invention. Flight controller 501 is a component that controls the entire drone, and specifically may be an embedded computer that includes a CPU, memory, related software, and the like. The flight controller 501 controls the motors 102-1a and 102-1b through a control means such as ESC (Electronic Speed Control) based on input information received from the controller 401 and input information obtained from various sensors described below. , 102-2a, 102-2b, 102-3a, 102-3b, 104-a, and 104-b to control the flight of the drone 100. The actual rotation speeds of motors 102-1a, 102-1b, 102-2a, 102-2b, 102-3a, 102-3b, 104-a, and 104-b are fed back to flight controller 501 to ensure normal rotation. The configuration is such that it is possible to monitor whether the Alternatively, a configuration may be adopted in which the rotary blade 101 is 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 a storage medium or a communication means such as Wi-Fi or USB in order to expand/change functions, correct problems, etc. In this case, protection is provided using encryption, checksums, electronic signatures, virus checking software, etc. to prevent rewriting by unauthorized software. Further, a part of the calculation processing used for control by the flight controller 501 may be executed by another computer existing on the controller 401, the farming cloud 405, or another location. Since the flight controller 501 is highly important, some or all of its components may be duplicated.

The flight controller 501 communicates with the controller 401 via the Wi-Fi handset function 503 and the base station 404, receives necessary commands from the controller 401, and transmits necessary information to the controller. You can send it to 401. In this case, the communication may be encrypted to prevent unauthorized acts such as interception, impersonation, and hijacking of the device. In addition to the Wi-Fi communication function, the base station 404 also has the function of an RTK-GPS base station. By combining signals from RTK base stations and signals from GPS positioning satellites, flight controller 501 can measure the absolute position of drone 100 with an accuracy of a few centimeters. Because the flight controllers 501 are so important, they may be duplicated or multiplexed, and each redundant flight controller 501 may be configured to use a different satellite in order to respond to 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 mutually orthogonal directions, and further is a means for calculating the speed by integrating the acceleration. The 6-axis gyro sensor 505 is a means for measuring changes in the attitude angle of the drone body in the three directions mentioned above, that is, the angular velocity. The geomagnetic sensor 506 is a means for measuring the direction of the drone body by measuring geomagnetism. The atmospheric pressure sensor 507 is a means of measuring atmospheric 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 using reflection of laser light, and may be an IR (infrared) laser. The sonar 509 is a means of measuring the distance between the drone body and the ground surface using the reflection of sound waves such as ultrasonic waves. These sensors may be selected depending on the drone's cost goals and performance requirements. Furthermore, a gyro sensor (angular velocity sensor) for measuring the inclination of the aircraft, a wind sensor for measuring wind force, etc. 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 that sensor fails, it may switch to use an alternative sensor. Alternatively, a plurality of sensors may be used simultaneously, and if the respective measurement results do not match, it may be assumed that a failure has occurred.

Flow rate sensors 510 are means for measuring the flow rate of the sprayed material, and are provided at multiple locations along the route from tank 104 to nozzle 103. The liquid outage sensor 511 is a sensor that detects when the amount of sprayed material has become less than a predetermined amount.

The growth diagnosis camera 512a is a means for photographing the field 403 and acquiring data for growth diagnosis. The growth diagnosis camera 512a is, for example, a multispectral camera, and receives a plurality of light beams with different wavelengths. The plurality of light rays are, for example, red light (wavelength of approximately 650 nm) and near-infrared light (wavelength of approximately 774 nm). Furthermore, the growth diagnosis camera 512a may be a camera that receives visible light.

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

Diseases that occur on plants are known to cause lesions on leaves, leaf sheaths, stems, or ears. Examples of diseases that cause lesions include rice blast, sesame leaf blight, leaf blight, and striped leaf blight. The mechanism by which lesions occur is that chlorophyll first deteriorates, decomposes, or becomes deficient, then the area dies and becomes a visible lesion, and then the lesion expands. Therefore, using a red light camera, it is possible to obtain images of lesions at an early stage where they cannot be visually recognized.

FIG. 12 shows an image of a leaf image obtained by photographing rice leaves infected with blast with a red light camera. When photographed with a red light camera, areas with chlorophyll that absorbs red light appear black, and areas where chlorophyll has been destroyed due to diseases such as rice blast absorb red light. It looks white because it doesn't. When a disease such as rice blast occurs, the chlorophyll on the leaves is destroyed in spots, resulting in an image in which spots L1 appear on the leaf L as shown in FIG. 12.

Furthermore, a visible light camera can obtain images of visible lesions and images that allow analysis of the color and shape of leaves, stems, and ears.

Note that the growth diagnosis camera 512a and the pathological diagnosis camera 512b may be realized by one hardware configuration.

The obstacle detection camera 513 is a camera for detecting a drone intruder, and the image characteristics and lens orientation are different from the growth diagnosis camera 512a and the pathology diagnosis camera 512b, so it is different from the growth diagnosis camera 512a and the pathology diagnosis camera 512b. It's a different device. Switch 514 is a means for user 402 of drone 100 to make various settings. The obstacle contact sensor 515 is a sensor for detecting when the drone 100, particularly its rotor or propeller guard portion, has come into contact with an intruder such as a power line, a building, a human body, a standing tree, a bird, or another drone. . Note that the obstacle contact sensor 515 may be replaced by a 6-axis gyro sensor 505. The cover sensor 516 is a sensor that detects whether the operation panel or internal maintenance cover of the drone 100 is open. Inlet sensor 517 is a sensor that detects that the inlet of tank 104 is open.

These sensors may be selected depending on the cost target and performance requirements of the drone, and may be duplicated or multiplexed. Alternatively, a sensor may be provided outside the drone 100 at the base station 404, the controller 401, or at another location, and the read information may be sent to the drone. For example, the base station 404 may be provided with a wind sensor, and information regarding the wind force and wind direction may be transmitted to the drone 100 via Wi-Fi communication.

Flight controller 501 sends a control signal to pump 106 to adjust the discharge amount and stop the discharge. The current status of the pump 106 (eg, rotation speed, etc.) is configured to be fed back to the flight controller 501.

The LED 107 is a display means for notifying the drone operator of the drone's status. Display means such as a liquid crystal display may be used instead of or in addition to the LED. The buzzer is an output means for notifying the state of the drone (especially error state) by an audio signal. The Wi-Fi slave function 519 is an optional component, separate from the controller 401, for communicating with an external computer, etc., for example, to transfer software. Instead of or in addition to the Wi-Fi handset function, you can use other wireless communication methods such as infrared communication, Bluetooth (registered trademark), ZigBee (registered trademark), NFC, or wired communication methods such as USB connection. May be used. Moreover, instead of the Wi-Fi handset function, mutual communication may be possible using a mobile communication system such as 3G, 4G, and LTE. The speaker 520 is an output means for notifying the state of the drone (especially error state) using a recorded human voice, a synthesized voice, or the like. Depending on the weather conditions, it may be difficult to see the visual display of the drone 100 during flight, so in such cases, communicating the situation by voice is effective. The warning light 521 is a display means such as a strobe light that informs the state of the drone (particularly an error state). These input/output means may be selected depending on the cost target and performance requirements of the drone, and may be duplicated or multiplexed.

●Overview of the 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, which are connected to a network NW. are communicably connected to 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 some or all of them may be connected by wire.

Note that the configuration shown in FIG. 8 is an example, and one component may include another component, and the functional section 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 installed in the drone 100.

The user interface device 200 only needs to include an operator input section and a display section, and may be realized by the functions of the operating device 401. Further, the user interface device 200 may be a personal computer, and information may be input and displayed on a UI on the Web via a Web browser installed on the personal computer.

●Functional parts of the drone The Drone 100 is equipped with arithmetic units such as a CPU (Central Processing Unit) to execute information processing, and storage devices such as RAM (Random Access Memory) and ROM (Read Only Memory). It has at least a flight control section 1001, a dispersion control section 1002, a growth information acquisition section 1003, and a pathological information acquisition section 1004 as resources.

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

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

The 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 images of crops for diagnosing the growth state of the crops.

By utilizing the fact that the density of chlorophyll (chlorophyll a, chlorophyll B, carotenoids, etc.) in leaves changes depending on the amount of nitrogen absorbed, and by analyzing the characteristics of reflected light from leaves, the density of chlorophyll can be estimated and the amount of nitrogen added to leaves can be estimated. It is known that the amount of nitrogen absorbed can be estimated and the growth rate of crops can be measured based on this amount of nitrogen absorbed. Therefore, the growth information acquisition unit 1003 receives reflected sunlight obtained from the field 403 to acquire data used for analyzing the growth status of crops.

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

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

The pathological information acquisition unit 1004 is a functional unit that acquires disease information on crops in the field, that is, pathological information, while the drone 100 is flying over the field. The pathological information acquisition unit 1004 uses the pathological diagnosis camera 512b to acquire images of crops for diagnosing the pathological state of the crops. The pathological information acquisition unit 1004 acquires an image of at least one of a site where a lesion appears, such as a leaf, leaf sheath, stem, and panicle. Furthermore, 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.

Note that in this embodiment, the drone 100 is configured to include a spraying control section 1002, a growth information acquisition section 1003, and a pathological information acquisition section 1004, but the technical idea of the present invention is not limited to this. The drone 100 only needs to include at least a flight control section 1001 and a pathological information acquisition section 1004. Further, the dispersion control unit 1002 may be included in the pathological diagnosis system 1000 or a land traveling machine connected to the pathological diagnosis system 1000.

●Functional unit of the diagnostic device As shown in FIG. 8, the diagnostic device 600 is a functional unit that diagnoses plants, that is, crops, growing in the field 403 where the drone 100 flies, based on the information acquired by the drone 100. . The diagnostic device 600 is equipped with an arithmetic unit such as a CPU (Central Processing Unit) for executing information processing, and a storage device such as a RAM (Random Access Memory) or a ROM (Read Only Memory). It includes a medical history storage section 601, a growth diagnosis section 602, a climate information acquisition section 603, a spot measurement section 604, and a pathology diagnosis section 605.

The medical history storage unit 601 is a functional unit that stores the medical history of diseases that occurred in the field 403 in the past. The medical history includes at least one of the area where the disease occurred within the field 403, the type of disease that occurred, and the time of occurrence. Furthermore, the medical history may include climate information of the outbreak area at the time of occurrence.

The medical history storage unit 601 may store the results of disease response conducted in the field 403. Measures to be taken include spraying chemicals on infested areas and removing pathological leaves or plants. The response record may include the type or concentration of the sprayed medicine. The medical history storage unit 601 may receive the countermeasures determined by the planning device 700 and store them as a countermeasure record. Furthermore, the medical history and response history may be input from the user interface device 200, for example, by 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 an NDVI (Normalized Difference Vegetation Index) based on an image of reflected light of red light (wavelength: approximately 650 nm) and near-infrared light (wavelength: approximately 774 nm), and determines the absorption rate of red light. Furthermore, the effective light-receiving area can be estimated using NDVI. Generally, NDVI is calculated using 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 hardware or software frequency filter to the light beams received by the growth information acquisition unit 1003 to determine the light intensity of the light beams in a predetermined frequency range related to the growth situation, such as power spectral density. get. Note that the light amount calculation process may be performed by the growth information acquisition unit 1003, and the growth diagnosis unit 602 may diagnose the growth situation based on the received light amount.

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

The climate information acquisition unit 603 is a functional unit that acquires climate information of the field 403. The climate information includes information on at least one of temperature, humidity, and wind speed. Further, the climate information may include information on wind direction. The climate information acquisition unit 603 may receive measurement values from measuring instruments 500 disposed in the field 403, such as a thermometer, a hygrometer, and an anemometer, for example. Furthermore, the drone 100 may include some or all of the components included in the measuring device 500.

The climate information acquisition unit 603 may receive information transmitted from outside the pathological diagnosis system 1000. The climate information acquisition unit 603 may acquire information from a weather satellite. The weather satellite is Himawari, for example. The climate information acquisition unit 603 may acquire information (public notice information) processed by various organizations such as the Japan Meteorological Agency, especially public organizations, as climate information.

The spot measuring unit 604 is a functional unit that measures the appearance of spots appearing on crops based on the image acquired by the pathological information acquiring unit 1004. The spot measuring unit 604 measures at least one parameter of the size, density, and number of spots appearing on the crop based on the image. That is, the speckle measurement section 604 includes at least one of a speckle counting section 604a, a speckle size measurement section 604b, and a speckled density measurement section 604c.

The spot counting unit 604a is a functional unit that counts spots appearing on at least one of the leaves, leaf sheaths, stems, and panicles of plants by image analysis. The spot counting unit 604a may count the number of spots for each site where spots occur. Counts for each site of occurrence include, for example, leaves, leaf sheaths, and stems. Alternatively, the leaf tip, leaf midsection, and base may be counted separately. The spot size measurement unit 604b is a functional unit that measures the size of spots by image analysis. The spot density measurement unit 604c is a functional unit that measures the number of spots occurring per predetermined area, that is, the density of spots. The spot density measurement unit 604c may determine the density of spots by measuring the distance between spots.

The pathological diagnosis unit 605 is a functional unit that diagnoses the disease status of plants in the field. The pathological diagnosis unit 605 performs a pathological determination as to whether or not the patient has a disease based on the measurement results of at least one of parameters such as the size of the spots, the density of the spots, and the number of spots. That is, the pathological diagnosis unit 605 may determine that the spot is diseased when the size is larger than a predetermined size. In this case, for example, it can be determined that the person is sick on the condition that the area of the spot is 100 square millimeters or more. The pathological diagnosis unit 605 may determine that the patient has a disease when the spot density is equal to or higher than a predetermined value. In this case, it may be determined that a disease has occurred, for example, when the distance between spots is 10 cm or less. The pathological diagnosis unit 605 may determine that the person has a disease when the number of spots is a predetermined number or more. In this case, for example, if the number of spots with an area of 4 square millimeters or more is 10 or more around a predetermined area, it may be determined that a disease has occurred. Alternatively, the pathological diagnosis unit 605 may perform pathological determination based on a plurality of parameters among the size of the spots, the density of spots, and the number of spots.

When determining pathology based on one or more of the following parameters: spot size, spot density, and number of spots, pathology is determined based on a likelihood distribution table based on the value of one parameter or a combination of values of multiple parameters. It is also possible to generate occurrence likelihoods. In this case, the generated pathological likelihood value may be output, or if the generated pathological likelihood value exceeds a predetermined threshold, a message indicating that pathological occurrence has been detected may be output. Alternatively, both the likelihood of pathological occurrence and the information on the detection of pathological occurrence may be output.

The pathological diagnosis unit 605 may perform pathological diagnosis for each plant strain. Furthermore, 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 mesh shapes, for example. Each area has a rectangular shape of, for example, 1 m square. Further, the pathological diagnosis unit 605 may perform pathological diagnosis for each image captured by the pathological diagnosis camera 512b.

The pathological diagnosis unit 605 may diagnose the type of disease that the plant is suffering from based on the size of the spots, the density of the spots, or the number of spots. The pathological diagnosis unit 605 may diagnose the type of disease based on the site where the spots occur. For example, the pathological diagnosis unit 605 stores the type of disease in association with the shape, size, density, number of spots, or site or range of spots that occur, and refers to this information to diagnose the disease. Diagnose the type.

Furthermore, the pathological diagnosis section 605 may perform pathological determination based on past medical history information stored in the medical history storage section 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 disease has occurred in the area. Specifically, even if some or all of the measurement results of spots do not satisfy the first threshold, it may be determined that the disease is present based on the history of occurrence. In addition, a second threshold value smaller than the first threshold value is defined in advance for the measurement result of spots, and if the measurement result is greater than or equal to the second threshold value and less than the first threshold value, and there is a history of disease occurrence, the disease is present in the area. It may be determined that this has occurred. Alternatively, the above-described likelihood of pathological occurrence may be calculated in consideration of past medical history information.

The pathological diagnosis unit 605 may perform pathological determination based on 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 a disease is occurring. This is because the conditions are known to be climates where diseases can easily occur and 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, part or all of the measurement results of the spots do not satisfy the first threshold value. In this case, it may be determined that the patient is sick. Alternatively, the above-described likelihood of pathological occurrence may be calculated in consideration of climate information.

The pathological diagnosis unit 605 may determine the progress of the disease. The degree of progress is, for example, three stages: early, middle, and late, but it may be two stages or may be further subdivided into multiple stages. Further, even if the condition has not been diagnosed as a disease, a state in which there is a possibility of a disease may be determined as a "suspected pathological occurrence" state. The pathological diagnosis unit 605 determines the progress of the disease based on at least one of the shape and size of the spots. The shape of the spot is, for example, the length of the spot. The length of a spot may be calculated by obtaining the short axis and long axis of an elliptical spot and calculating the ratio of the short axis to the long axis. This is because the spots are known to grow as the disease progresses. If the length of the spot is equal to or greater than a predetermined third threshold, the pathological diagnosis unit 605 determines that the condition 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 information obtained by a visible light camera. For example, it is known that after lesions occur due to destruction of chlorophyll, the area around the lesions turns black as the disease progresses. A visible light camera can detect the discolored area. Since discoloration around the lesion occurs after the lesion occurs, the pathological diagnosis unit 605 determines that when the discolored area is detected, it is in a state that is more advanced than the earliest stage of development, for example, "middle stage" or "late stage". do.

Note that the pathological diagnosis unit 605 may use the growth status of the plant for pathological determination or for determining the progress of the disease. For example, when determining a disease that is likely to be contracted under a specific growth situation, the pathological diagnosis unit 605 may refer to the specific growth situation to determine that the disease is present.

Furthermore, the pathological diagnosis unit 605 may perform pathological diagnosis based on the color or shape of the stem or ear.

Although it is assumed that the target plant for pathological determination by the diagnostic device 600 is paddy rice, the technical scope of the present invention is not limited thereto, and may be other plants that can be pathologically diagnosed mainly by photographing from above. The diagnostic device 600 is capable of pathological diagnosis based on images of leaves, stems, fruits, etc. that contain chlorophyll. The diagnostic device 600 may perform pathological determination on multiple types of plants, store different pathological determination criteria for each type of plant, and perform pathological determination based on different determination criteria for each type of plant.

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

The countermeasure determining unit 701 is a functional unit that determines whether or not a response to a disease is necessary based on the results of pathological diagnosis. The countermeasure determining unit 701 determines whether a response to the disease is necessary for each plant or region. The countermeasure determining unit 701 determines to take countermeasures when the diagnosis device 600 determines that the patient is sick.

The countermeasure determining unit 701 determines countermeasures to be applied to the field based on the progress of the disease. Countermeasures include, for example, at least one of the following: visually confirming the plant, re-photographing, observing, spraying pesticides, removing pathological leaves, removing pathological plants, and removing plants in areas where pathological plants occur.

The instruction to visually check the stock price is a measure to encourage people to visually check the stock price. In field 403, the humidity around the plant base is higher than that around the leaves, and the probability of disease outbreaks is high.However, because the plant base is difficult to see from above, diseases may not be detected when photographed from above. According to the plant's visual inspection instructions, the Drone 100 can detect diseases at an early stage, even if they are difficult to detect.

Pesticide spraying is the process of spraying pesticides on a predetermined area that includes plants where diseases have been discovered. The area to be sprayed, the type and concentration of the pesticide are determined by a spraying mode determining unit 702, which will be described later.

Removal of pathological leaves is the process of removing only diseased leaves, that is, pathological leaves. Removal of pathological plants is the process of removing diseased plants, that is, pathological plants. Removal of plants in areas where pathological plants occur is the process of removing all crops growing in a predetermined area, including pathological plants.

Elimination of the disease requires more severe countermeasures as the disease progresses. Specifically, as the disease progresses, the recommended order is to visually confirm the plant, re-photograph, wait and see, spray pesticides, remove pathological leaves, remove pathological plants, and remove plants in areas where pathological plants occur. Note that the instruction to visually confirm stock prices, re-photographing, and observation may be presented in any order, and may be presented at the same time as countermeasures. For example, in a case where the countermeasure determining unit 701 is equipped with a function of determining the progress of the disease in at least two stages including "early" and "late", the countermeasure determining unit 701 may output "wait and see" when the progress is "initial". , in the case of the "late stage" where the progress is more advanced than the initial stage, "spraying pesticides", "removal of pathological leaves", or "removal of pathological plants" is output.

Further, the countermeasure determining unit 701 outputs "spraying pesticides" when the progress is "early", and outputs "removal of pathological leaves" or "removal of pathological strains" when the progress is "late". It can also be used as a thing.

Furthermore, the countermeasure determining unit 701 may output "remove pathological leaves" when the progress is "early" and output "remove pathological plants" when the progress is "late".

When determining the progress of the disease in at least three stages including "early", "middle", and "late", the countermeasure determining unit 701 outputs "wait and see" when the progress is "initial"; "Pesticide spraying" is output when the progress is more advanced than the initial stage, and "removal of pathological leaves" or "pathological strain removal" is output when the progress is more advanced than the middle stage, "late". You can also output it.

Further, the countermeasure determination unit 701 outputs "spraying pesticides" when the progress is "initial", outputs "remove pathological leaves" when the progress is "middle", and outputs "remove pathological leaves" when the progress is "late". In this case, "removal of pathological strain" may be output.

The countermeasure determining unit 701 may determine countermeasures by referring to climate information. This is because depending on the weather, the disease may not progress or spread to surrounding crops. For example, when the humidity is below a predetermined value, the temperature is above a predetermined value, and the wind speed is below a predetermined value, the countermeasure determining unit 701 outputs a countermeasure that is lighter than the countermeasure associated with the determined progress. You can. That is, for example, in a mode where the progress is determined to be "initial" and "pesticide spraying" is associated with "initial", the countermeasure determination unit 701 outputs "wait and see" if the above conditions are met. You may. Assuming that the disease is cured only in the initial stage, if the climate information satisfies a predetermined condition, a milder countermeasure may be output only if the progress is in the early stage. According to this configuration, appropriate countermeasures can be determined more accurately by utilizing the characteristics of the disease. In particular, excessive measures can be suppressed and yield reductions due to excessive pesticide spraying or excessive removal can be prevented.

According to the countermeasure determining unit 701, a countermeasure suitable for stopping the spread of the disease in the field 403 can be determined. Furthermore, since the countermeasure determining unit 701 can determine appropriate countermeasures depending on the progress of the disease, excessive spraying of pesticides can be prevented. In turn, it is possible to reduce the cost of pesticides and grow crops that require less pesticides. Furthermore, the countermeasure determination unit 701 can appropriately remove pathological leaves and pathological plants, thereby preventing excessive removal work. As a result, labor costs for removal work can be reduced. Also, since leaves and plants are not removed excessively, yields can be maintained.

The countermeasure determining section 701 includes a dispersion mode determining section 702 and a countermeasure timing calculating section 703.

The dispersion mode determining unit 702 is a functional unit that determines the mode of dispersing the chemical onto the field 403. The spraying mode determining unit 702 includes a spraying area determining unit 702a, a pesticide determining unit 702b, and a concentration determining unit 702c.

The dispersion area determining unit 702a is a functional unit that determines a predetermined range including a pathological strain determined to be diseased as a dispersion area.

The spraying area determination unit 702a sprays pesticides on areas with a high risk of disease spread. Bacterial growth is a cause of diseases that affect plants. Since fungal spores are blown away by the wind, it is presumed that the higher the wind speed, the wider the spores will spread. It is also estimated that the spores are spreading downwind. Furthermore, if the disease in the discovered pathological strain is progressing, it is presumed that some time has passed since the onset of the disease, that is, the spores are presumed to have spread over a wide area.

Therefore, the spray area determining unit 702a determines the distance from the pathological plant to which the pesticide is to be sprayed based on the wind speed information. That is, the spraying area determining unit 702a increases the distance from the pathological plant to which the pesticide is to be sprayed as the wind speed increases. Further, the spraying area determining unit 702a determines an area for spraying pesticides based on wind direction information. That is, the spray area determining unit 702a decides to spray the pesticide in an area extending downwind from the pathological strain. In other words, the dispersion area determination unit 702a makes the distance from the pathological plant to the end of the dispersion range in the leeward direction longer than the distance from the pathological plant to the end of the dispersion range in the upwind direction. The wind speed information and wind direction information may be received from the measuring device 500.

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

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

Note that the countermeasure determining unit 701 may determine the area in which the dispersion area determining unit 702a decides to spray as information on the area where the strain needs to be removed, that is, the target range in "removal of the strain in the pathological strain outbreak area". .

The area in which the spraying area determining unit 702a decides to spray is not limited to the flight range of the drone 100, but may also include areas 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 areas requiring spraying may be managed by a local general manager of fields, and the general manager may notify each worker. Further, information on the determined spraying area may be output to another system to be linked.

The pesticide determining unit 702b is a functional unit that determines the type of pesticide depending on the progress of the disease. The pesticide determining unit 702b may have a table that associates the progress of the disease with suitable pesticides, and may determine the type of pesticide by referring to the table. In addition, in this description, the term "agricultural chemicals" is a concept that broadly includes various liquids, powders, granules, etc. that can be effectively sprayed as a disease control measure.

The concentration determining unit 702c is a functional unit that determines the concentration of the pesticide to be sprayed depending on the progress of the disease. The concentration determination unit 702c determines that the more the disease progresses, the higher the concentration of the pesticide should be sprayed. In addition, when spraying high-concentration pesticides using the drone 100, in addition to filling the tank 104 with high-concentration pesticides in advance and spraying, the drones also spray while flying at a slower speed than when spraying standard concentrations. The concentration of the pesticide in the field may be maintained by changing the flight mode, such as increasing the discharge amount from the nozzle 103, or flying and spraying the same location multiple times. In this case, the concentration determination unit 702c may have a function of determining the flight mode of the drone 100 according to the spray concentration.

The countermeasure timing calculation unit 703 is a functional unit that calculates a deadline for taking countermeasures. Crop diseases progress day by day, and if measures are taken in the early stages, the disease can be eliminated with minor measures. For example, it is advisable to take measures within a predetermined time from the onset of the disease. Therefore, the countermeasure timing calculation unit 703 estimates the elapsed time from the onset of the disease based on the progress of the disease, and calculates the time point when the disease outbreak is added to a predetermined time as the deadline for countermeasures. The deadline for taking measures is, for example, within 48 hours from the onset 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 timing of flight and prompt the operator.

The result output unit 704 is a functional unit that outputs the determination result of the countermeasure. The result output unit 704 outputs at least one of the determination result of the presence or absence of a disease, the progress of the disease, a recommended countermeasure, and a deadline for taking the countermeasure. The result output unit 704 may cause the user interface device 200 to display the determination result. Further, the result output unit 704 may display the decision result on the screen of the personal computer, or may display the decision result on a UI on the Web via a 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 order of recommendation. Workers can flexibly take measures according to their work circumstances. After displaying a plurality of recommended countermeasures, the user interface device 200 accepts the selection input of the countermeasure to be actually performed, and when the countermeasure is input, records the input countermeasure in the medical history storage unit 601 as a response record. 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 dispersing medicine based on the determination result. Additionally, the drone 100 may perform preparatory operations necessary for those flights.

●Result Output Screen As shown in FIG. 9, the user interface device 200 displays a result output screen G1. On the result output screen G1, fields 403a, 403b, 403c, and 403d and virtual lines dividing each field into a mesh are displayed. Among the divided areas, areas 403a-1 and 403b-1 where pathological strains exist are displayed in a different manner from other areas. In this embodiment, the fields 403a to 403d are shown in shading, and areas 403a-1 and 403b-1 where pathological strains exist 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 a superimposed manner. For the shape of the field, reference may be made to aerial photographs or data from a farmland bank, or 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, for example, by RTK-GPS information acquired by the drone 100 during flight. According to this configuration, the locations of pathological strains can be listed.

In addition, the result output screen G1 displays a progress display field g10 that shows the progress of the disease in the pathological strains, and a countermeasure display field g20 that displays countermeasures for the pathological strains displayed in the progress display field g10. has been done. If there are multiple areas where pathological strains exist, the area where pathological strains exist 403a-1 displayed in the progress display field g10 and countermeasure display field g20 can be distinguished from other areas where pathological strains exist 403b-1. . For example, a pin P is displayed in the presence area 403a-1. By selecting the presence areas 403a-1 and 403b-1 on the result output screen G1, the presence areas that display the progress and countermeasures are switched.

The countermeasure display column g20 displays one or more countermeasure columns g21 and g22. When the countermeasure columns g21 and g22 are pressed, the details of the countermeasure and the response deadline may be displayed. Furthermore, the user interface device 200 may be configured to allow the operator to input that the countermeasure has been implemented based on operations on the countermeasure columns g21 and g22.

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

As shown in FIG. 10, an image g30 acquired by the pathological diagnosis camera 512b is displayed on the result output screen G2. Furthermore, a pathological region specifying mark g31 indicating a pathological leaf or pathological strain is displayed superimposed on the image g30. According to this configuration, it is easy to search for pathological leaves or pathological plants in the field. It is particularly useful for visual confirmation or removal of pathological leaves or plants. 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.

●Flowchart for performing pathological diagnosis As shown in FIG. 11, first, the drone 100 flies over the field and acquires images of the crops (S11). Next, based on the acquired image, parameters such as size, density, and/or number of spots are measured (S12). Next, it is determined whether the parameter measurement results are within a predetermined range (S13). When the measurement result of the parameter is within a predetermined range, it is determined that the subject to be determined is not sick (S14). When the measurement result of the parameter is outside the predetermined range, it is determined that the determination target is sick (S15). Next, the progress of the disease is determined (S16). Countermeasures are determined based on the progress and output (S17). Note that the determination in step S12 may be performed for each stock or for each image. If the determination is made for each stock and multiple stocks are reflected in one acquired image, the processes of steps S12 to S17 are repeated for one acquired image.
Instead of determining the occurrence of pathology by determining the threshold value of each parameter, the likelihood of occurrence of pathology may be generated based on the value of each parameter, and the presence or absence of occurrence of pathology may be determined based on the likelihood of occurrence of pathology. In this case, S13 to S15 can be replaced as shown below. That is, in S13, the likelihood of pathological occurrence is generated based on the measurement results of the parameters (S13). Next, in S14, if the generated likelihood of pathological occurrence is less than a predetermined value, it is determined that the determination target is not a disease (S14). Further, in S15, if the generated pathological occurrence likelihood is equal to or greater than a predetermined value, it is determined that the determination target is a disease (S15).

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

Claims (12)

a flight control unit that flies the drone over the field;
a first camera that detects the amount of light in a frequency band corresponding to at least the absorption spectrum of chlorophyll;
a pathology information acquisition unit that is mounted on the drone and acquires images of crops growing in the field in the frequency band through the first camera;
a spot measuring unit that measures at least one parameter of size and shape of spots appearing on the crop based on the image;
a pathological diagnosis unit that performs pathological determination as to whether or not the crop is diseased based on the measurement results of the parameters;
a medical history storage unit that stores past medical history in the field;
Equipped with
The pathological diagnosis unit determines that the crop is diseased if the measurement result of the parameter satisfies a predetermined first threshold value, and even if the measurement result of the parameter is less than the first threshold value. , if the disease is at least a predetermined second threshold smaller than the first threshold and there is a history of outbreak in the field in the past, it is determined that the disease has occurred;
Plant pathology diagnosis system.
The pathological diagnosis unit refers to the past medical history stored in the medical history storage unit and calculates the likelihood that a disease has occurred based on the past medical history information.
A plant pathological diagnosis system according to claim 1..
The pathological diagnosis unit stores the type of disease in association with the shape, size, density, number of spots, or spot occurrence site or range of spots that occur when suffering from the disease, and stores the measurement results of the parameters. determining the type of disease that the crop is suffering from based on;
The plant pathological diagnosis system according to claim 1 or 2 .
The spot measuring unit counts the number of spots for each site where the spots occur, and the pathological diagnosis unit determines the type of the disease based on the site or range where the spots occur.
The plant pathological diagnosis system according to any one of claims 1 to 3 .
The pathological diagnosis section performs pathological determination based on the climate information of the field, and determines that the crop is diseased when the measurement result of the parameter satisfies a first threshold, and the measurement result of the parameter satisfies the first threshold. Even if the climate information is less than a first threshold, if the climate information is equal to or higher than a fourth predetermined threshold, determining that the person is sick;
The plant pathological diagnosis system according to any one of claims 1 to 4.
The climate information includes at least one of temperature, humidity, and wind speed.
The plant pathological diagnosis system according to claim 5.
The pathological diagnosis unit determines the progress of the disease based on the length of spots appearing on the crop, and if the length is equal to or greater than a third threshold, the disease is at the earliest stage of occurrence. It is determined that the condition is more advanced than that of
The plant pathological diagnosis system according to any one of claims 1 to 6.
The drone further includes a visible light camera that detects the amount of light of at least three wavelengths in the visible light band,
The pathological diagnosis unit determines the progress of the disease based on the information obtained by the visible light camera, and if a discolored area is detected around the spot measured by the spot measurement unit, determining that the disease is in a more advanced state than the earliest stage;
The plant pathological diagnosis system according to any one of claims 1 to 7.
The pathological diagnosis unit acquires growth information of the crop, and in determining a disease that the crop is likely to contract if the crop is in a specific growth condition, the pathological diagnosis section refers to the specific growth condition to determine whether the crop is sick or not. determine that there is
The plant pathological diagnosis system according to any one of claims 1 to 8.
a flight control step of flying a drone over the field, including a first camera that detects the amount of light in a frequency band corresponding to at least the absorption spectrum of chlorophyll;
a pathological information acquisition step of acquiring images in the frequency band of crops growing in the field through the first camera mounted on the drone;
a spot measuring step of measuring at least one parameter of size and shape of spots occurring on the crop based on the image;
a pathological diagnosis step of determining pathologically whether or not the crop is diseased based on the measurement results of the parameters;
a medical history storage step of storing past medical history in the field;
including ;
In the pathological diagnosis step, the crop is determined to be diseased if the measurement result of the parameter satisfies a predetermined first threshold value, and even if the measurement result of the parameter is less than the first threshold value. , if the disease is at least a predetermined second threshold smaller than the first threshold and there is a history of outbreak in the field in the past, it is determined that the disease has occurred;
Plant pathological diagnosis method.
A drone flying over a field is configured to detect the crop on the basis of an image of the crop growing in the field in the frequency band obtained by a first camera that detects light intensity in a frequency band corresponding to at least the absorption spectrum of chlorophyll. a spot measuring unit that measures at least one parameter of the size and shape of the spots that occur;
a pathological diagnosis unit that performs pathological determination as to whether or not the crop is diseased based on the measurement results of the parameters;
a medical history storage unit that stores past medical history in the field;
Equipped with
The pathological diagnosis unit determines that the crop is diseased if the measurement result of the parameter satisfies a predetermined first threshold value, and even if the measurement result of the parameter is less than the first threshold value. , if the disease is at least a predetermined second threshold smaller than the first threshold and there is a history of outbreak in the field in the past, it is determined that the disease has occurred;
Plant pathology diagnostic equipment.
a flight control unit that flies the drone over the field;
a first camera that detects the amount of light in a frequency band corresponding to at least the absorption spectrum of chlorophyll;
a pathological information acquisition unit that acquires images of crops growing in the field in the frequency band via the first camera;
a spot measuring unit that measures at least one parameter of size and shape of spots appearing on the crop based on the image;
a pathological diagnosis unit that performs pathological determination as to whether or not the crop is diseased based on the measurement results of the parameters;
a medical history storage unit that stores past medical history in the field;
Equipped with
The pathological diagnosis unit determines that the crop is diseased if the measurement result of the parameter satisfies a predetermined first threshold value, and even if the measurement result of the parameter is less than the first threshold value. , if the disease is at least a predetermined second threshold smaller than the first threshold and there is a history of outbreak in the field in the past, it is determined that the disease has occurred;
Drone.

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