WO2019034070A1 - 一种植物健康状态监测方法及装置 - Google Patents

一种植物健康状态监测方法及装置 Download PDF

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Publication number
WO2019034070A1
WO2019034070A1 PCT/CN2018/100606 CN2018100606W WO2019034070A1 WO 2019034070 A1 WO2019034070 A1 WO 2019034070A1 CN 2018100606 W CN2018100606 W CN 2018100606W WO 2019034070 A1 WO2019034070 A1 WO 2019034070A1
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Prior art keywords
plant
information
plant health
health
health status
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PCT/CN2018/100606
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English (en)
French (fr)
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刘波
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广州极飞科技有限公司
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Application filed by 广州极飞科技有限公司 filed Critical 广州极飞科技有限公司
Priority to US16/617,057 priority Critical patent/US11301986B2/en
Priority to AU2018317151A priority patent/AU2018317151A1/en
Priority to EP18846361.6A priority patent/EP3620774B1/en
Priority to CA3065851A priority patent/CA3065851A1/en
Priority to KR1020207007441A priority patent/KR102344031B1/ko
Priority to JP2020509112A priority patent/JP6960525B2/ja
Priority to RU2019141805A priority patent/RU2726033C1/ru
Publication of WO2019034070A1 publication Critical patent/WO2019034070A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0004—Industrial image inspection
    • G06T7/001—Industrial image inspection using an image reference approach
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
    • A01G7/00—Botany in general
    • A—HUMAN NECESSITIES
    • A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
    • A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
    • A01G7/00—Botany in general
    • A01G7/06—Treatment of growing trees or plants, e.g. for preventing decay of wood, for tingeing flowers or wood, for prolonging the life of plants
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
    • G01D21/00—Measuring or testing not otherwise provided for
    • G01D21/02—Measuring two or more variables by means not covered by a single other subclass
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/314—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry with comparison of measurements at specific and non-specific wavelengths
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
    • H04N23/60—Control of cameras or camera modules
    • H04N23/69—Control of means for changing angle of the field of view, e.g. optical zoom objectives or electronic zooming
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
    • G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
    • G01N21/314—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry with comparison of measurements at specific and non-specific wavelengths
    • G01N2021/3155—Measuring in two spectral ranges, e.g. UV and visible
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N2021/8466—Investigation of vegetal material, e.g. leaves, plants, fruits
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N2201/00—Features of devices classified in G01N21/00
    • G01N2201/12—Circuits of general importance; Signal processing
    • G01N2201/129—Using chemometrical methods
    • G01N2201/1296—Using chemometrical methods using neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20081—Training; Learning
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20084—Artificial neural networks [ANN]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30181—Earth observation
    • G06T2207/30188—Vegetation; Agriculture

Definitions

  • the invention relates to the field of intelligent agriculture technology, in particular to a method and a device for monitoring plant health status.
  • farmland management personnel regularly observe the plant growth status in the field, and judge the health status of the plant according to the plant growth status. Based on the experience of plant health, it is judged whether it is necessary to carry out the problem of poor plant health. governance.
  • At least some embodiments of the present invention provide a method and a device for monitoring a plant health condition, which are capable of intelligently judging the health status of a plant, and promptly reminding the farmland management personnel against the occurrence of plants having poor plant health conditions when the plant health is poor.
  • a plant health monitoring method is provided, and the plant health monitoring method includes:
  • the content indicated by the second determination information is that the plant is dysfunctional, it is confirmed that the plant health condition is in poor health, and the orientation information of the plant that is in poor health is determined.
  • An embodiment of the present invention further provides a plant health monitoring device, the plant health monitoring device comprising:
  • a receiving unit configured to receive first plant health status information provided by the plant health condition measuring device
  • a processing unit connected to the receiving unit, configured to perform a first judgment on the plant health condition according to the first plant health status information, to obtain first judgment information; and if the first judgment information indicates that the plant is healthy Poor risk, the receiving unit is further configured to receive the second plant health status information of the location of the plant having the risk of dystrophic; the processing unit is further configured to perform the plant health status according to the second plant health status information The second judgment determines that the second judgment information is obtained; if the content indicated by the second judgment information is that the plant is dysfunctional, it is confirmed that the plant health is in poor health, and determining the location information of the ill-healthy plant .
  • the method and the device for monitoring the state of health of the plant obtained by at least some embodiments of the present invention obtain the first judgment information by providing the first plant health status information to the plant health condition measuring device, and obtain the first judgment information.
  • the content indicated by the first judgment information is that the plant has a risk of dystrophicity, and receives the second plant health status information of the position of the plant having the risk of dystrophic, so as to perform the second judgment on the second plant health status information, so that 2.
  • FIG. 1 is a schematic diagram of an application environment of a plant health state monitoring method according to an embodiment of the present invention
  • FIG. 2 is a flowchart of a method for monitoring a plant health state according to an embodiment of the present invention
  • FIG. 3 is a flow chart of generating a report on a poor health condition of a plant according to an embodiment of the present invention
  • FIG. 4 is a flow chart showing the first judgment of a plant health condition according to the first plant health status information according to an embodiment of the present invention
  • FIG. 5 is a flow chart showing a second judgment of a plant health condition according to a second plant health status information according to an embodiment of the present invention
  • FIG. 6 is a structural block diagram of a plant health state monitoring apparatus according to an embodiment of the present invention.
  • FIG. 7 is a structural block diagram of a processing unit according to an embodiment of the present invention.
  • FIG. 8 is a hardware structural diagram of a plant health state monitoring terminal according to an embodiment of the present invention.
  • an embodiment of the present invention provides a method and a device for monitoring a plant health state, which are capable of determining the orientation of a plant having a ill-health risk, and receiving the orientation with higher precision.
  • Plant image information analyze it to determine the health status of the plant, and promptly remind the farmland management personnel to prevent and control when the plant health is bad, overcoming the limitation of traditional farmland management by time and space, and it cannot be discovered in time. Or missed the risk of missing the best time to take plant protection measures.
  • the technical solution provided by the embodiment of the present invention is implemented by the terminal device 100 and wirelessly or wiredly communicated with the plant health condition measuring device 200 to receive information provided by the plant health condition measuring device 200, and the terminal device 100
  • the information provided by the plant health condition measuring device 200 is processed, and the result is sent to the client 300 in the form of a report.
  • the client 300 can be an application client carried by the fax machine 301, the tablet computer 302, and the mobile phone 303, and the application client. Including SMS client, WeChat client, mail client, etc.
  • the method for monitoring plant health status includes the following steps:
  • Step S110 Receive first plant health status information provided by the plant health condition measuring device 200;
  • Step S120 The first judgment of the plant health status is performed according to the first plant health status information, and the first judgment information is obtained; if the content indicated by the first judgment information is that the plant has a health risk, step S130 is performed;
  • Step S130 Receive second plant health status information of the location of the plant having the risk of dystrophic provided by the plant health condition measuring device 200;
  • Step S140 Perform a second judgment on the health status of the plant according to the second plant health status information, and obtain second judgment information;
  • Step S150 If the content indicated by the second judgment information is that the plant is in poor health, it is confirmed that the plant health condition is in poor health, and the orientation information of the plant in the dysfunctional plant is determined;
  • the ill health of the plant is only a relatively certain state, that is, the probability of such ill-healing is higher than the ordinary probability, and it is defined as the physiology of the plant is in poor health.
  • the plant health state monitoring method obtains the first judgment information by providing the first plant health status information to the plant health condition measuring device, and obtains the first judgment information, and the first judgment information
  • the content indicated is that the plant has a risk of dysbiosis, and receives the second plant health status information of the plant in the position of the ill-health risk, so as to perform the second judgment on the second plant health status information, so that in the second judgment information, It is possible to determine the health status of plants and to determine the location of plants in poor health, so that farmland managers are not limited by time and space, and can understand the health status of plants in time to make plants in poor health. It is possible to quickly determine the location of a plant that is ill-healed based on the location of the plant in which the ill-healthy plant is located, so that plant protection measures can be taken as soon as possible to restore the plant to health.
  • farmland managers not only need to regularly observe the plant growth status in the field, but also need to place each area of a larger area when observing the growth of plants.
  • the plants in the corners are observed once, in order to accurately obtain the plant growth status, which not only brings inconvenience to the farmland management, but also wastes time greatly, and the plant health state method provided by the embodiments of the present invention can not only determine the plant health status. It is also able to determine the location of plants in poor health, enabling agricultural managers to provide early warning of plants in specific locations.
  • the plant health status information provided by the plant health condition measuring device 200 may be collected in real time or may be It is a periodic collection, and the specific type of plant health status information provided by the plant health condition measuring device 200 is determined by the module included in the plant health measuring device 200.
  • the plant health condition measuring device 200 may be a monitoring device installed in a farmland, or may be a drone capable of taking a picture, or Other devices that are capable of collecting plant images.
  • the plant health condition measuring device 200 should at least include a module having an image capturing function, such as a camera, a camera, and the like.
  • the type of plant image information is visible spectrum image information and/or invisible spectrum image information
  • the visible spectrum image information is collected by an ordinary camera or camera
  • the invisible spectral image information is collected by an image acquisition device having an infrared detection function, such as Infrared camera or infrared camera acquisition.
  • infrared detection function such as Infrared camera or infrared camera acquisition.
  • the method for monitoring the state of health of the plant provided by the embodiment of the present invention can accurately determine whether the plant has ill health by at least two judgments, so as to avoid the situation that the agricultural management personnel have no pests and diseases in the plant in the prior art.
  • the third plant health status information of the ill-healthy plant sent by the plant health condition measuring device 200 may be further received according to the determined orientation information of the ill-healthy plant, according to the third Plant health status information further determines whether the health of the plant is good.
  • plant health status information can be repeatedly received and judged to achieve monitoring of plant health status. As for the number of times to receive and judge plant health status information, it can be determined according to actual needs.
  • the first plant health status information includes at least the current plant image information
  • the second plant health status information includes at least the current plant image information corresponding to the orientation of the plant having the ill-health risk
  • the current state of the second plant health status information may be defined
  • the accuracy of the plant image information is greater than the accuracy of the current plant image information in the first plant health information (the accuracy here may be a higher resolution plant image information); at this time, after step S150, the second judgment is determined. Whether the accuracy of the information of the location of the ill-healthy plant is higher than the preset accuracy;
  • the determination is ended. Otherwise, the third plant condition information in the orientation of the ill-healthy plant is received and judged, and the accuracy of the third plant health status information is greater than the accuracy of the second plant health status information.
  • the plant health status information is received and judged multiple times until the accuracy of the position information of a plant that is in poor health is higher than the preset accuracy, and the receiving and judging plant health status information is ended.
  • the above limitation on the number of receiving and judging is based on the accuracy of the position of the ill-healthy plant.
  • the accuracy of the current plant health status information needs to be greater than the previous plant health status information.
  • the accuracy of the current plant image information in the second plant health status information is greater than the accuracy of the current plant image information in the first plant health status information.
  • the first judgment information includes the following steps:
  • Step S121 using a convolutional neural network model to judge the first plant health status information, and obtaining a first plant health failure probability
  • Step S122 determining whether the probability of the first plant health defect is greater than a set threshold
  • step S130 is performed; wherein the orientation information of the plant having the risk of dystrophic is determined according to the first plant health status information, that is, the volume is adopted.
  • the convolutional neural network model judges the first plant health status information, the convolutional neural network model also identifies the first plant health status information, and obtains the orientation information of the plant with the risk of dystrophic;
  • the risk of dysbiosis in plants includes the risk of pests and diseases and/or the risk of nutrient deficiency; the risk of nutrient deficiency includes one or more of the risks of trace element deficiency, nitrogen deficiency, phosphorus deficiency, and potassium deficiency.
  • the risk of nutrient deficiency includes one or more of the risks of trace element deficiency, nitrogen deficiency, phosphorus deficiency, and potassium deficiency.
  • the above-mentioned second judgment of the plant health condition according to the second plant health status information, and obtaining the second judgment information includes the following steps:
  • Step S141 using a convolutional neural network model to determine the second plant health status information, and obtaining a second plant health defect probability
  • Step S142 determining whether the probability of the second plant health defect is greater than a set threshold
  • Step S150 confirming that the plant has ill-health, the degree of physiology of the plant, and the position information of the ill-healthy plant; wherein the degree of plant ill-health can be set according to the difference between the probability of the second plant ill-health and the set threshold The percentage of the threshold is determined. The greater the difference, the higher the degree of dysfunction of the plant; the location information of the ill-healthy plant is determined based on the second plant health status information. That is, when the second plant health status information is judged by using the convolutional neural network model, the convolutional neural network model also identifies the second plant health status information, and obtains the orientation information of the dysfunctional plant;
  • the physiology of plants may include at least one of the symptoms of plants and pests and the symptoms of nutrient deficiency in plants; symptoms of nutrient deficiency may include symptoms of trace element deficiency, symptoms of deficiency of nitrogen, symptoms of phosphorus deficiency, potassium The element lacks one or more of the symptoms.
  • the above convolutional neural network model is obtained through learning and training. Therefore, before the first plant health status information is judged by using a convolutional neural network model, the plant health state identification method further includes:
  • historical plant health status information includes at least historical plant image information
  • the convolutional neural network is used to learn and train the historical plant health status information, and the convolutional neural network model is obtained.
  • the convolutional neural network model is used to judge the plant image information, so that the parallel data processing advantages possessed by the convolutional neural network model can be utilized to improve the data processing capability, and It is also possible that the convolutional neural network model can be adjusted by the process of learning and training because the adaptive ability of the convolutional neural network model is extremely high, so that the convolutional neural network model is more accurate in data processing.
  • the neural network learns and trains the historical plant image information in the historical plant health information, which is carried out in the form of pictures.
  • the plant image information When the plant image information is an image with a time dimension, the plant image information needs to be processed according to each frame of the image. Therefore, although the current plant image information and the historical plant image information can both be images having a time dimension, in actual processing In the middle, it is still processed in the form of pictures. That is, whether the current plant image information in the first plant health information is judged by using the convolutional neural network model, or whether the current plant image information in the second plant health information is judged, or whether the convolutional nerve is used
  • the network learns and trains historical plant image information in historical plant health status information, and performs judgment or learning training on a frame-by-frame picture.
  • the convolutional neural network model can more accurately determine the probability of the first plant health or the second plant health failure rate.
  • the historical plant health status information also includes historical soil information and historical air information. And one or more of the historical illumination information; at the same time, the first plant health status information includes at least one or more of current soil information, current air information, and current illumination information, and the second plant health status information is at least Including one or more of the current soil information, the current air information, and the current illumination information, so that when the current plant image information is judged by using the convolutional neural network model, the soil information, the air information, and the illumination information of the current plant can be used as For more accurate judgment of the poor health of plant health or the probability of second plant health, to avoid misjudgment caused by not considering soil, air and sun factors.
  • the plant health measurement device 200 should also include a soil information collection unit that measures soil information, such as one of a soil moisture sensor, a soil temperature sensor, a soil nutrient analyzer, or A variety of, of course, can also include other soil information collection units that can monitor soil information.
  • the above plant health condition measuring device 200 should also include an air information collecting unit that measures air information, such as one or more of an air humidity sensor, a thermometer, an air quality detector, and of course, other air information capable of monitoring air information. Acquisition unit.
  • an air information collecting unit that measures air information, such as one or more of an air humidity sensor, a thermometer, an air quality detector, and of course, other air information capable of monitoring air information. Acquisition unit.
  • the above plant health condition measuring device 200 should also include an illumination information collecting unit that measures the light information, such as one or more of a light intensity measuring instrument and an ultraviolet intensity detector.
  • an illumination information collecting unit that measures the light information, such as one or more of a light intensity measuring instrument and an ultraviolet intensity detector.
  • other illumination information collection units capable of monitoring illumination information may also be included.
  • the historical plant health status information, the first plant health status information, and the second plant health status information may include not only the above mentioned information, but also weather information and the like, which are not limited herein.
  • whether it is the current plant image information involved in the first judgment, or the current plant image involved in the second judgment may be a picture or an image having a time dimension, and the first time Both the judgment and the second judgment are to identify and process the corresponding current plant image to identify whether the plant in the current plant image information has symptoms of pests and diseases and lack of nutrition.
  • the method for monitoring the plant health status between the step S120 and the step S130 further includes:
  • the first step is to generate an image acquisition unit control instruction, where the image acquisition unit control instruction includes at least the orientation information of the plant at the risk of dystrophic risk and the image enlargement control information; the image enlargement control information includes the image enlargement control information including the image magnification control information and the image Zoom in on the angle control information.
  • the image collection unit control instruction is sent to the plant health condition measuring device 200, so that the plant health condition measuring device 200 collects the second plant health status information of the position of the plant having the risk of dysfunction according to the image collecting unit control instruction;
  • the current plant image information included in the second plant health status information is image enlargement information of different angles of the current plant image in the orientation of the plant in which the health risk risk exists in the first plant health status information.
  • the image collecting unit in the plant health condition measuring device 200 when the image collecting unit in the plant health condition measuring device 200 receives the image capturing unit control instruction, it can adjust the position of the plant position information capable of collecting the plant having the risk of dystrophy according to the orientation information of the plant having the risk of dystrophic, And adjusting the image magnification according to the image magnification control information, and adjusting the angle at which the plant health status information is collected according to the image magnification angle control information, so as to perform the plants in the orientation of the plant in a state of poor plant health from different angles. Zoom in to capture.
  • the omnidirectional pan/tilt head receives the orientation information of the plant with the risk of dystrophic, and can rotate horizontally and vertically by a certain angle.
  • the angle at which the camera captures the plant image is adjusted to the orientation of the plant at risk of ill-health.
  • the camera receives the image magnification information, and adjusts the focal length of the camera to adjust the depth of field of the target plant, thereby collecting a macro photograph of the target plant, that is, a magnified photograph of the plant, thus improving the second plant.
  • the resolution of the current plant image information included in the health status information is not limited to, a photograph of the target plant, that is, a magnified photograph of the plant, thus improving the second plant.
  • the image capturing unit may also be movable.
  • the image collecting unit is installed in a drone or a hot air balloon. By periodically controlling the drone to collect plant image information, the drone may be a quadrotor drone or Fixed-wing drones, etc.
  • the plant health condition measuring device 200 described above is a stationary plant health condition measuring device; for example, the plant health condition measuring device 200 includes an image collecting unit fixed in the field.
  • the image magnification control information is at least m
  • the image enlargement angle control information is at least n
  • each image enlargement angle control information includes device horizontal rotation angle control information and device vertical rotation angle control information
  • m and n are greater than or equal to 1
  • the second plant health status information collected by the plant health condition measuring device 200 should include m ⁇ n group plant health status data; each group of the plant health status data includes device rotation angle information, image enlargement information, and ill health.
  • the current plant image information of the risk after receiving the plurality of sets of plant health status data, the device rotation angle information and the image enlargement information may be recorded to determine the orientation information of the corresponding group of plant health status data collection, so that the second judgment information is represented
  • the content of the plant is that when the plant is in poor health, it can determine the orientation information of the plant that is in poor health according to the rotation angle information of the device and the image enlargement information.
  • the rotation angle information and the image enlargement information of the second receiving device can be further refined, and all the rotation angles and magnifications after the refinement are commanded.
  • the form is sent to the plant health condition measuring device 200, so that the plant health condition measuring device 200 can collect the current plant image information in a more detailed manner, thereby ensuring that the accuracy of the current plant image information collected each time is greater than the current plant image information collected last time. Precision.
  • the image collecting unit control instruction further includes: k device coordinates Control information; at least m image magnification control information, the image enlargement angle control information is at least n; each image enlargement angle control information includes device horizontal rotation angle control information and device vertical rotation angle control information; m, n , k are greater than or equal to 1;
  • the second plant health status information includes m ⁇ n ⁇ k group plant health status data; each set of plant health status data includes device coordinate information, device rotation angle information, image enlargement information, and current plant image information at risk of ill-health .
  • the device can determine not only the orientation information of the plant that is in poor health according to the device rotation angle information and the image enlargement information, but also the device when the third determination information is present.
  • the rotation angle information and the image enlargement information are further refined to ensure that the accuracy of the current plant image information collected each time is greater than the accuracy of the current plant image information collected previously; and, by refining the device coordinate information,
  • the plant health condition measuring device 200 performs image acquisition with more precise coordinates.
  • the plant health state monitoring method further includes a step S190 of selecting a relationship with the step S130. Including the following steps:
  • Step S191 determining, according to the content indicated by the first determination information, the location of the plant in good health
  • Step S192 Periodically generate a good report on the health status of the plant according to the content indicated by the first judgment information and the position information of the plant in good health, and send a good report on the health status of the plant to the client. and / or,
  • the method for monitoring the health state of the plant further includes the step S210, which specifically includes the following steps:
  • Step S211 determining, according to the content indicated by the second determination information, the location of the plant in good health
  • Step S212 Periodically generate a good report on the health status of the plant according to the content indicated by the second determination information and the location information of the plant in good health, and send the report of the good health of the plant to the client 300.
  • the health condition report can be periodically generated and sent to the client 300.
  • step S150 the method further includes step S160: the content represented by the second determination information and the orientation information of the plant in poor health. Generate reports of poor plant health.
  • monitoring methods also include:
  • Step S170 Send the plant health condition bad report to the client 300 to prompt the farmland management personnel to view the plant health condition bad report in real time.
  • step S180 includes: generating an alarm instruction.
  • the alarm command is sent to the alarm 400, so that the alarm 400 alarms according to the alarm instruction to further remind the farmland manager.
  • the plant health status report or the plant health status report is sent to the client, it can be sent to the corresponding SMS client and WeChat client in the form of SMS, WeChat message or email. Apps such as mail clients.
  • the WeChat message may be sent to the WeChat client of the farmland management personnel in the form of a private message, or may be sent to various clients of various farmland management personnel in the form of a service push message.
  • Step S161 Retrieving plant information data in the crop knowledge database according to the content indicated by the second judgment information
  • Step S162 generating a plant health prevention and control strategy according to the acquired plant information data; the crop knowledge database includes a plurality of plant information data, and each of the plant information data includes plant information and a corresponding plant health prevention and control strategy.
  • the crop knowledge database herein may be a database that already has information about plant information and corresponding plant health control strategies, or may be collected by collecting various plant information and plant health control strategies; for example, plant health
  • the adverse control strategies may include pest control strategies for various plants, and lack of nutrient elements for various plants;
  • Step S163 generating a plant health condition adverse report according to the content indicated by the second judgment information, the plant health control strategy, and the position information of the plant in a poor health;
  • the plant health condition poor report may include the location area of the target plant, the plant The extent of ill-health, plant ill-health pictures, recognition time and plant health prevention strategies, etc.
  • Plant dysfunction can include not only pests, diseases, nutrient deficiencies, but also other unhealthy conditions.
  • the plant health state monitoring method provided by the embodiment of the present invention is poor in the health of the plant.
  • the plant information data in the crop knowledge database is retrieved according to the content indicated by the second judgment information, and the plant health prevention and control strategy is given in a targeted manner, and the content indicated by the second judgment information and the plant health are poor.
  • the prevention and control strategy is also generated as a report on the adverse health status of the plant, so that when the farmland managers see the report on the poor health of the plant, they can not only know which plants in the specific orientation are in a bad state, but also can see the recommendations.
  • the plant health prevention and control strategy can provide a more comprehensive reference for agricultural managers.
  • each first plant health status information further includes: identification information of the plant health condition measuring device 200 (eg, plant health status) The ID address of the measuring device 200) and the geographical coordinate information (latitude and longitude) of the plant health measuring device 200; each second plant health information further includes: identification information of the plant health measuring device 200; of course, may also include plant health status The geographic coordinate information of the measurement device 200 is measured.
  • each second plant health condition information further includes: identification information of the plant health condition measuring device 200.
  • the plant health state identifying method After receiving the first plant health status information provided by the plant health condition measuring device 200, before the first judgment of the plant health condition according to the first plant health status information, the plant health state identifying method further includes:
  • the first step is to establish a plant health condition measuring device in each first plant health status information according to the identification information of the plant health condition measuring device 200 and the geographical coordinate information of the plant health condition measuring device in each first plant health condition information. Corresponding relationship between the identification information and the geographic coordinate information of the plant health condition measuring device; storing the correspondence between the identification information of the plant health condition measuring device in each first plant health status information and the geographic coordinate information of the plant health condition measuring device;
  • Plant health monitoring methods also include:
  • the plant in each second plant health status information is identified according to the correspondence between the identification information of the plant health condition measuring device 200 and the geographic coordinate information of the plant health condition measuring device 200 in each first plant health condition information.
  • the identification information of the health condition measuring device 200 obtains the geographical coordinate information of the plant health condition measuring device 200 in each second plant health condition information to determine the source of each second plant health condition information.
  • the identification information and the plant health condition measurement of the plant health condition measuring device 200 in each first plant health condition information are determined.
  • Corresponding relationship between the identification information of the plant health condition measuring device 200 and the geographic coordinate information of the plant health condition measuring device 200 in each first plant health status information is established and saved, so that the plant health status is received.
  • the second plant health status information of the plant having the risk of dystrophicity provided by the measuring device is received, only the identification information of the plant health condition measuring device in each second plant health status information needs to be received, and the corresponding correspondence can be determined according to the established The relationship is obtained by using the identification information of the plant health condition measuring device in each second plant health information to find the geographical coordinate information of the corresponding plant health measuring device to determine the source of each second plant health information.
  • the source of the second plant health status information can be made, so that the farmland management personnel can according to the second plant health status information.
  • the source a more accurate understanding of the health of the plant, in order to be able to accurately locate the location of the plant's poor health when the plant is in poor health.
  • the above report of generating a plant health condition according to the content indicated by the second judgment information and the orientation information of the plant in a state of poor plant health includes:
  • a report on the poor health status of the plant is generated based on the content indicated by the second determination information, the orientation information of the plant in a state of poor plant health status, and the source of the second plant health status information of the plant in a state of poor plant health.
  • An embodiment of the present invention further provides a plant health monitoring device, as shown in FIGS. 1 and 6, the plant health monitoring device includes:
  • the receiving unit 110 is in communication with the plant health condition measuring device 100, and is configured to receive the first plant health status information provided by the plant health condition measuring device 100;
  • the processing unit 120 connected to the receiving unit 110 is configured to perform a first judgment on the plant health status according to the first plant health status information, to obtain first judgment information; and if the first judgment information indicates that the plant has a dysfunctional risk
  • the receiving unit 110 is further configured to receive the second plant health status information of the location of the plant having the risk of dystrophic; the processing unit 120 is further configured to perform the second judgment on the plant health status according to the second plant health status information, to obtain the second The information is judged; if the content indicated by the second judgment information is that the plant is ill-healthy, it is confirmed that the plant health condition is in poor health, and the position information of the plant in which the ill health is located is determined.
  • the first plant health status information includes at least current plant image information
  • the second plant health status information includes at least current plant image information corresponding to the orientation of the plant having a plant health risk
  • the first plant health status information is at least
  • the plant health measurement device 100 includes an image acquisition unit, and specifically, the reception unit 110 communicates with the image acquisition unit.
  • the type of current plant image information included in the first plant health status information includes visible spectrum image information and/or invisible spectrum image information; and the type of current plant image information included in the second plant health status information includes a visible spectrum image. Information and/or invisible spectral image information.
  • the accuracy of the current plant image information in the second plant health status information is greater than the accuracy of the current plant image information in the first plant health status information, so as to achieve the limitation of the receiving and judging times of the plant image information in the foregoing.
  • the processing unit 120 includes: a probability analysis module 121 connected to the receiving unit 110, configured to determine the first plant health status information by using a convolutional neural network model, to obtain the first plant health defect. Probability; and using a convolutional neural network model to judge the health information of the second plant to obtain a second plant health failure probability;
  • the determining module 122 respectively connected to the probability analysis module 121 and the report generating unit 130 is configured to determine whether the first plant health defect probability is greater than a set threshold; if yes, confirming that the plant health has a bad risk and the plant health has a bad risk The position of the plant; otherwise, it is determined that the plant is in good health; and, whether the probability of the second plant health is greater than a set threshold;
  • the receiving unit 110 is further configured to receive historical plant health status information, and the historical plant health status information includes at least historical plant image information;
  • the processing unit 120 further includes an information training module 123 connected to the receiving unit 110 and the probability analysis module 121 respectively, configured to perform learning training on the historical plant health status information by using a convolutional neural network to obtain a convolutional neural network model.
  • the historical plant health status information further includes one or more of historical soil information, historical air information, and historical illumination information; and the first plant health status information includes at least current soil information, current air information, and current illumination information.
  • the second plant health status information further includes at least one of a current soil information, current air information, and current lighting information.
  • the ill-health risks of plants include the risk of pests and diseases and/or the risk of nutrient deficiencies; the risk of nutrient deficiencies includes one or more of the risks of trace element deficiency, nitrogen deficiency, phosphorus deficiency, and potassium deficiency; Health deficiencies include symptoms of pests and diseases in plants and/or symptoms of nutrient deficiencies in plants; symptoms of nutrient deficiency include symptoms of trace element deficiency, symptoms of nitrogen deficiency, symptoms of phosphorus deficiency, and symptoms of potassium deficiency .
  • the first plant health status information further includes at least one of current soil information, current air information, and current illumination information
  • the second plant health status information includes at least current soil information, current air information, and current illumination information.
  • the plant health condition measuring device 100 further includes one of an air information collecting unit that implements air information measurement, a soil information collecting unit that implements soil information measurement, and an illumination information collecting unit that implements light information measurement. Kind or more.
  • the plant health state monitoring apparatus further includes an instruction generating unit 160 connected to the processing unit 120 and the transmitting unit 150, respectively. And configured to generate an image acquisition unit control instruction when the content indicated by the first determination information is a plant dystrophic risk, and the image collection unit control instruction includes at least a position information and an image enlargement control information of the plant at risk of dysfunction;
  • the amplification control information includes image magnification control information and image magnification angle control information;
  • the sending unit 150 is configured to send the image collecting unit control instruction to the plant health condition measuring device, so that the plant health condition measuring device collects the second plant health condition information of the plant in the position of the health risk risk according to the image collecting unit control instruction.
  • the image magnification control information is at least m, and the image magnification angle control information is at least n; each image magnification angle control information includes a device level. Rotation angle control information and device vertical rotation angle control information; m and n are both greater than or equal to 1;
  • the second plant health status information includes m ⁇ n group plant health status data; each set of plant health status data includes device rotation angle information, image enlargement information, and current plant image information at risk of ill-health.
  • the image collecting unit control instruction further comprises: k device coordinate control information; the image magnification control information is at least m, and the image zooming angle control information is at least n; each image magnification angle control information includes device horizontal rotation angle control information and device vertical rotation angle control information; m, n, k are greater than or equal to 1;
  • the second plant health status information includes m ⁇ n ⁇ k group plant health status data; each set of plant health status data includes device coordinate information, device rotation angle information, image enlargement information, and current plant image information at risk of ill-health.
  • the plant health state monitoring device is used when the content indicated by the first judgment information and/or the second judgment information is good for the plant health. Further comprising a report generating unit 130 connected to the processing unit 120, the processing unit 120 further configured to determine, according to the content indicated by the first determining information and/or the second determining information, the location information of the plant in good health;
  • the report generating unit 130 is further configured to periodically and according to the first judgment information and/or the second judgment information, when the content indicated by the first judgment information and/or the second judgment information is good for the health of the plant. Good plant location information generates a good report on plant health;
  • the plant health monitoring device further includes: the sending unit 150 is further configured to send the plant health report to the client 300.
  • the sending unit 150 may be wireless or wired.
  • the transmitting unit 150 has a communication relationship with the client 300.
  • the report generating unit 130 is further configured to generate a plant health condition bad report according to the content indicated by the second judgment information and the orientation information of the ill-healthy plant;
  • the unit 150 is also arranged to send a report of the plant health condition to the client so that the farmland manager can timely prevent and control the plant health.
  • command generating unit 160 is further configured to generate an alarm instruction when the content indicated by the second determination information is that the plant is in poor health
  • the sending unit 150 is further configured to send an alarm command to the alarm 400 such that the alarm command controls the alarm 400 to alert the farmland manager.
  • the transmitting unit 150 has a communication relationship with the alarm 400; wherein, when the processing unit 120 adopts the structural block diagram shown in FIG. 7, the instruction generating unit 160 is connected to the determining module 122.
  • the sending unit 150 is further configured to send a plant health status report to the client 300 when the content indicated by the second determination information is that the plant health condition is poor;
  • the plant health health device further includes a crop knowledge database connected to the processing unit 120;
  • the crop knowledge database includes a plurality of plant information data; each plant information data includes plant information and corresponding The plant health prevention and control strategy;
  • the processing unit 120 is further configured to: retrieve the plant information data in the crop knowledge database according to the content indicated by the second judgment information, and generate a plant health prevention and control strategy according to the acquired plant information data;
  • the report generation unit 130 is configured to generate a report on the poor health status of the plant according to the content indicated by the second determination information, the plant health control strategy, and the orientation information of the plant in a poor health, so that the plant health condition report includes not only the plant health dysfunction.
  • the information also contains strategies for how to prevent plant health problems. Among them, plant health prevention strategies include pest control strategies and/or plant nutrient element deficiency prevention strategies.
  • each first plant health status information further includes: identification information of the plant health condition measuring device and the plant Geographical coordinate information of the health condition measuring device;
  • Each of the second plant health status information further includes: identification information of the plant health condition measuring device;
  • the plant health monitoring device further includes: a device identification unit 140 connected to the receiving unit 110 and the processing unit 120, the processing unit adopts a structural block diagram as shown in FIG. 7, and the device identification unit 140 and The probability analysis module 121 is connected; wherein
  • the device identifying unit 140 After receiving the first plant health status information provided by the plant health condition measuring device 200, and prior to making the first determination of the plant health condition according to the first plant health status information, the device identifying unit 140 is configured to be based on each first plant health condition. Identification information of the plant health condition measuring device and geographic coordinate information of the plant health condition measuring device in the information, establishing identification information of the plant health condition measuring device in each first plant health status information and geographic coordinate information of the plant health condition measuring device Corresponding relationship; storing the correspondence between the identification information of the plant health condition measuring device in each first plant health status information and the geographic coordinate information of the plant health condition measuring device;
  • the device identifying unit 140 Receiving the second plant health status information of the plant in the plant health status measuring device provided by the plant health condition measuring device, and performing the second judgment on the plant health status information according to the second plant health status information, the device identifying unit 140 Also set to:
  • Identifying identification information of the plant health condition measuring device in each second plant health condition information obtaining geographic coordinate information of the plant health condition measuring device in each of the second plant health status information, to determine each second plant Source of health status information;
  • the report generation unit 130 includes a source of plant health status report based on the content indicated by the second determination information, the orientation information of the plant in a state of poor plant health status, and the source of the second plant health status information of the plant in a poor health.
  • the embodiment of the present invention further provides a storage medium, which is configured to store executable program code that supports the implementation of the plant health state monitoring method, and the beneficial effects produced by the method are the same as the beneficial effects of the plant health state monitoring method. Let me repeat.
  • an embodiment of the present invention further provides a plant health status monitoring terminal, which includes a transceiver 501, a memory 502, and a processor 503, a transceiver 501, a memory 502, and a processing unit.
  • the 503 communicate with one another via a bus 504.
  • the transceiver 501 is configured to communicate with the plant health condition measuring device 200, the client 300, and the alarm 400;
  • the memory 502 is arranged to store executable program code to cause the processor 503 to execute various control instructions to implement the plant health monitoring method described above.
  • the processor 503 in the embodiment of the present invention may be a processor or a collective name of multiple processing elements.
  • the processor 503 may be a central processing unit (CPU), or may be an application specific integrated circuit (ASIC), or one or more configured to implement the embodiments of the present invention.
  • An integrated circuit such as one or more digital signal processors (DSPs), or one or more Field Programmable Gate Arrays (FPGAs).
  • the memory 502 may be a storage device or a collective name of a plurality of storage elements, and is configured to store executable program code or the like. And the memory 502 may include random access memory (RAM), and may also include non-volatile memory such as a magnetic disk memory, a flash memory, or the like.
  • RAM random access memory
  • non-volatile memory such as a magnetic disk memory, a flash memory, or the like.
  • the bus 504 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus.
  • ISA Industry Standard Architecture
  • PCI Peripheral Component
  • EISA Extended Industry Standard Architecture
  • the bus 504 can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, only one thick line is shown in Figure 8, but it does not mean that there is only one bus or one type of bus.
  • the storage medium may be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

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Abstract

一种植物健康状态监控方法，涉及智能农业技术领域，用于智能化的判断植物健康状况，及时提醒农田管理人员针对发生植物健康状况不良的植物进行防治。该植物健康状态监控方法根据植物健康状况信息进行第一次判断，在判断结果为植物健康存在不良风险时，根据植物健康存在不良风险的植物所在方位的第二植物健康状况信息进行第二次判断，以准确得到植物健康状况信息，以使得农田管理人员能够及时了解田间植物现状，并及时防治。一种应用所述植物健康状态监控方法的装置，并用于植物健康状况监测。

Description

一种植物健康状态监测方法及装置 技术领域
本发明涉及智能农业技术领域，尤其涉及一种植物健康状态监测方法及装置。
背景技术
传统农田管理中，一般是农田管理人员定期到田间观察植物生长状况，并根据植物生长状况判断植物健康状况，并根据植物健康不良时，依据经验知识，判断是否需要对植物健康状况不良的问题进行治理。
但是，传统农田管理需要农田管理人员定期到田间观察植物生长状况，以根据植物生长状况判断植物健康状况，其受到时间、空间范围的限制，存在不能及时发现，或者遗漏的风险，从而错过采取植保措施的最佳时间。
发明内容
本发明至少部分实施例提供了一种植物健康状态监测方法及装置，以智能化的判断植物健康状况，并在植物健康存在不良时，及时提醒农田管理人员针对发生植物健康状况不良的植物进行防治。
在本发明其中一实施例中，提供了一种植物健康状态监控方法，该植物健康状态监控方法包括：
接收植物健康状况测量设备提供的第一植物健康状况信息，根据所述第一植物健康状况信息对植物健康状况进行判断，得到第一判断信息；
若所述第一判断信息所表示的内容为植物存在健康不良风险，则接收所述存在健康不良风险的植物所在方位的第二植物健康状况信息；根据所述第二植物健康状况信息对植物健康状况进行判断，得到第二判断信息；
若所述第二判断信息所表示的内容为植物存在健康不良，则确认所述植物健康状况处于健康不良，以及确定处于健康不良的植物所在方位信息。
本发明其中一实施例还提供了一种植物健康状态监控装置，该植物健康监测装置包括：
接收单元，设置为接收植物健康状况测量设备提供的第一植物健康状况信息；
与接收单元连接的处理单元，设置为根据所述第一植物健康状况信息对植物健康状况进行第一次判断，得到第一判断信息；若所述第一判断信息所表示的内容为植物存在健康不良风险，所述接收单元还设置为接收所述存在健康不良风险的植物所在方位的第二植物健康状况信息；所述处理单元还设置为根据所述第二植物健康状况信息对植物健康状况进行第二次判断，得到第二判断信息；若所述第二判断信息所表示的内容为植物存在健康不良，则确认所述所述植物健康处于健康不良，以及确定处于健康不良的植物所在方位信息。
与现有技术相比，本发明至少部分实施例提供的植物健康状态监测方法及装置，通过对植物健康状况测量设备提供第一植物健康状况信息进行第一次判断，得到第一判断信息，当第一判断信息所表示的内容为植物存在健康不良风险，接收存在健康不良风险的植物所在方位的第二植物健康状况信息，以对该第二植物健康状况信息进行第二次判断，使得在第二判断信息时，能够确定植物健康状况处于健康不良，以及确定处于健康不良的植物所在方位信息，从而使得农田管理人员不受时间、空间范围的限制，能够及时了解田间植物健康状况，以在植物处于健康不良时，能够根据处于健康不良的植物所在的方位信息迅速确定处于健康不良的植物的位置，从而尽快采取植保措施使得植物恢复健康。
附图说明
此处所说明的附图用来提供对本发明的进一步理解，构成本发明的一部分，本发明的示意性实施例及其说明用于解释本发明，并不构成对本发明的不当限定。在附图中：
图1为本发明实施例提供的植物健康状态监控方法的应用环境示意图；
图2为本发明实施例提供的植物健康状态监控方法的流程图；
图3为本发明实施例中生成植物健康状况不良报告的流程图；
图4为本发明实施例中根据第一植物健康状况信息对植物健康状况进行第一次判断的流程图
图5为本发明实施例中根据第二植物健康状况信息对植物健康状况进行第二次判断的流程图；
图6为本发明实施例提供的植物健康状态监控装置的结构框图；
图7为本发明实施例中处理单元的结构框图；
图8为本发明实施例提供的植物健康状态监控终端的硬件结构图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
如图2、图6和图8所示，本发明实施例提供了一种植物健康状态监控方法及装置，其能够判断出植物存在健康不良风险的植物所在方位，并接收该方位更高精度的植物图像信息，对其进行分析，以最终确定植物健康状况，并在植物健康存在不良时，及时提醒农田管理人员进行防治，克服了传统农田管理受到时间、空间范围的限制，存在不能及时发现，或者遗漏的风险，从而错过采取植保措施的最佳时间的问题。
如图1所示，本发明实施例提供的技术方案通过终端设备100实现，并与植物健康状况测量设备200无线或有线通信，以接收植物健康状况测量设备200所提供的信息，终端设备100将植物健康状况测量设备200所提供的信息进行处理，将结果以报告的形式发送给客户端300，客户端300可以为传真机301、平板电脑302、手机303上携带的应用客户端，应用客户端包括短信客户端、微信客户端、邮件客户端等。
如图2所示，本发明实施例提供的植物健康状态监控方法包括如下步骤：
步骤S110：接收植物健康状况测量设备200提供的第一植物健康状况信息；
步骤S120：根据第一植物健康状况信息对植物健康状况进行第一次判断，得到第一判断信息；若第一判断信息所表示的内容为植物存在健康不良风险，则执行步骤S130；
步骤S130：接收植物健康状况测量设备200提供的存在健康不良风险的植物所在方位的第二植物健康状况信息；
步骤S140：根据第二植物健康状况信息对植物健康状况进行第二次判断，得到第二判断信息；
步骤S150：若第二判断信息所表示的内容为植物存在健康不良，则确认植物健康状况处于健康不良，以及确定处于健康不良的植物所在方位信息；
可以知道的是，植物健康状况处于健康不良只是一种相对确定状态，即这种健康不良的机率高出普通的机率，被定义为植物健康状况处于健康不良。
基于上述工作过程可知，本发明实施例提供的植物健康状态监控方法，通过对植物健康状况测量设备提供第一植物健康状况信息进行第一次判断，得到第一判断信息，当第一判断信息所表示的内容为植物存在健康不良风险，接收存在健康不良风险的植物所在方位的第二植物健康状况信息，以对该第二植物健康状况信息进行第二次判断，使得在第二判断信息时，能够确定植物健康状况处于健康不良.，以及确定处于健康不良的植物所在方位信息，从而使得农田管理人员不受时间、空间范围的限制，能够及时了解田间植物健康状况，以在植物处于健康不良时，能够根据处于健康不良的植物所在的方位信息迅速确定处于健康不良的植物的位置，从而尽快采取植保措施使得植物恢复健康。
例如：采用传统农田管理手段管理一块较大面积的田地，农田管理人员不仅需要定期到田间观察植物生长状况，而且在观察植物生长状况时，需要将较大面积的田地的每一方位，每一个角落的植物都观察一遍，才能准确获取植物生长状况，这不仅给农田管理带来不便，也极大的浪费了时间，而本发明实施例提供的植物健康状态方法中，不仅能够确定植物健康状况，而且还能够确定处于健康不良的植物所在方位信息，使得农业管理人员能够针对 特定方位的植物进行预警。
需要说明的是，对于植物健康状况测量设备200来说，其所提供的植物健康状况信息，不管是第一植物健康状况信息，还是第二植物健康状况信息，其都可以是实时采集，也可以是周期性采集，而植物健康状况测量设备200所提供的植物健康状况信息具体种类，则是由植物健康状况测量设备200所包括的模组决定的。
例如：植物健康状况测量设备200所提供的植物健康状况信息至少包括植物图像信息时，植物健康状况测量设备200可以是设置在农田中的监控设备，也可以是能够拍摄图片的无人机，或者其他能够采集植物图像的设备。总之，该植物健康状况测量设备200至少应当包括具有图像采集功能的模组，例如摄像机、照相机等。
而如果植物图像信息的类型为可见光谱图像信息和/或不可见光谱图像信息，可见光谱图像信息通过普通的摄像机或照相机采集，不可见光谱图像信息通过具有红外线探测功能的图像采集设备采集，如红外线照相机或红外摄像机采集.对于具有红外线探测功能的图像采集设备来说，其能够在夜间充分发挥其优势，捕捉到普通的摄像机无法采集的信息，同时，对于植物在可见光下不能发现的病例症状也能够采集，相对普通的摄像机或照相机来说，其优势是不言而喻的。
值得注意的是，本发明实施例提供的植物健康状态监测方法，至少经过两次判断，就能够精确确定植物是否存在健康不良，以避免现有技术中，农业管理人员在植物没有病虫害发生的情况下，依据经验知识，在植物生长到一定时期结合气候环境因素进行人工经验判断，提前施喷药物预防，导致农药施喷不合理的问题。
而在上述步骤S150结束后，还可以进一步根据所确定的处于健康不良的植物所在方位信息，接收植物健康状况测量设备200发送的处于健康不良的植物的第三植物健康状况信息，以根据第三植物健康状况信息进一步确定植物的健康状况是否良好。以此类推，可以反复接收并判断植物健康状况信息， 以实现植物健康状态的监控。至于接收和判断植物健康状况信息的次数，可以根据实际需要确定。
具体的，当第一植物健康状况信息至少包括当前植物图像信息；第二植物健康状况信息至少包括存在健康不良风险的植物所在方位对应的当前植物图像信息；可限定第二植物健康状况信息中当前植物图像信息的精度大于第一植物健康状况信息中当前植物图像信息的精度(此处的精度可以为更高分辨率的植物图像信息)；此时，在步骤S150后，判断第二次判断确定的处于健康不良的植物所在方位信息的精确度是否高于预设精确度；
如果是，则结束判断，否则，接收处于健康不良的植物所在方位的第三植物状况信息并进行判断，并限定第三植物健康状况信息的精度大于第二植物健康状况信息的精度。
以此类推，进行多次接收和判断植物健康状况信息，直到某次处于健康不良的植物所在方位信息的精确度高于预设精确度，结束接收和判断植物健康状况信息。
需要说明的是，上述对于接收和判断次数的限定，是以处于健康不良的植物所在方位的精确度为依据进行的，此时需要限定当次植物健康状况信息的精度大于前次植物健康状况信息的精度，即第二植物健康状况信息中当前植物图像信息的精度大于第一植物健康状况信息中当前植物图像信息的精度。
考虑到现有技术中图像识别判断技术多种多样，但大多智能化程度不高，基于此，如图4所示，上述根据第一植物健康状况信息对植物健康状况进行第一次判断，得到第一判断信息包括如下步骤：
步骤S121：采用卷积神经网络模型对第一植物健康状况信息进行判断，得到第一植物健康不良机率；
步骤S122：判断第一植物健康不良机率是否大于设定阈值；
如果是，则确认植物存在健康不良风险和存在健康不良风险的植物所在方位信息，执行步骤S130；其中，存在健康不良风险的植物所在方位信息是根据第一植物健康状况信息确定的，即采用卷积神经网络模型对第一植物健 康状况信息进行判断时，卷积神经网络模型还会识别第一植物健康状况信息，得到存在健康不良风险的植物所在方位信息；
否则，确定植物健康良好。
其中，植物所存在的健康不良风险包括病虫害风险和/或营养物质缺乏风险；营养物质缺乏风险包括微量元素缺乏风险、氮元素缺乏风险、磷元素缺乏风险、钾元素缺乏风险中的一种或多种。
同理，如图5所示，上述根据第二植物健康状况信息对植物健康状况进行第二次判断，得到第二判断信息包括如下步骤：
步骤S141：采用卷积神经网络模型对第二植物健康状况信息进行判断，得到第二植物健康不良机率；
步骤S142：判断第二植物健康不良机率是否大于设定阈值；
如果是，则执行步骤S150；
否则，确定植物健康良好；
步骤S150：确认植物存在健康不良、植物健康不良的程度，以及处于健康不良的植物所在方位信息；其中，植物健康不良的程度可以根据第二植物健康不良机率与设定阈值的差值占设定阈值的百分比进行确定，差值越大，则植物健康不良的程度越高；处于健康不良的植物所在方位信息是根据第二植物健康状况信息进行确定的。即采用卷积神经网络模型对第二植物健康状况信息进行判断时，卷积神经网络模型还会识别第二植物健康状况信息，得到处于健康不良的植物所在方位信息；
需要说明的是，植物存在的健康不良可以包括植物存在病虫害症状和植物存在营养物质缺乏症状中至少之一；营养物质缺乏症状可以包括微量元素缺乏症状、氮元素缺乏症状、磷元素缺乏症状、钾元素缺乏症状中的一种或多种。
具体的，上述卷积神经网络模型是通过学习训练得到的，因此采用卷积神经网络模型对第一植物健康状况信息进行判断前，上述植物健康状态识别方法还包括：
首先，接收历史植物健康状况信息；历史植物健康状况信息至少包括历史植物图像信息；
其次：利用卷积神经网络对历史植物健康状况信息进行学习训练，得到卷积神经网络模型。
本发明实施例提供的植物健康状态监测方法中，采用卷积神经网络模型对植物图像信息进行判断，以能够利用卷积神经网络模型自身所具有的并行数据处理优势，提高数据的处理能力，而且，还可以由于卷积神经网络模型的自适应能力极高，可以通过学习训练的过程对卷积神经网络模型进行调整，以使得卷积神经网络模型在数据处理时更为精确。
需要说明的是，不管是采用卷积神经网络模型对第一植物健康状况信息中的当前植物图像信息进行判断，还是对第二植物健康状况信息中的当前植物图像信息进行判断，抑或是采用卷积神经网络对历史植物健康状况信息中的历史植物图像信息进行学习训练，其都是以图片的形式进行的。
当具有植物图像信息是具有时间维度的影像，需要将植物图像信息按照每帧图片进行处理，因此，虽然当前植物图像信息和历史植物图像信息都可以为具有时间维度的影像，但是在实际处理过程中，还是以图片的形式进行处理的。也就是说，对采用卷积神经网络模型对第一植物健康状况信息中的当前植物图像信息进行判断，还是对第二植物健康状况信息中的当前植物图像信息进行判断，抑或是采用卷积神经网络对历史植物健康状况信息中的历史植物图像信息进行学习训练，都是逐帧图片进行判断或学习训练。
而为了能够在判断当前植物图像信息时，卷积神经网络模型更为准确的判断第一植物健康不良机率或第二植物健康不良机率，上述历史植物健康状况信息还包括历史土壤信息、历史空气信息、历史光照信息中的一种或多种；同时，第一植物健康状况信息至少还包括当前土壤信息、当前空气信息和当前光照信息中的一种或多种，第二植物健康状况信息至少还包括当前土壤信息、当前空气信息和当前光照信息中的一种或多种，这样利用卷积神经网络模型判断当前植物图像信息时，能够将当前植物所处的土壤信息、空气信息、 光照信息作为参考，以更为准确的判断植物健康状况不良机率或第二植物健康不良机率，避免没有考虑土壤因素、空气因素和阳光因素等条件时，所造成的误判。
可以理解的是，当第一植物健康状况信息至少还包括当前土壤信息、当前空气信息和当前光照信息中的一种或多种；第二植物健康状况信息至少还包括当前土壤信息、当前空气信息和当前光照信息中的一种或多种时，上述植物健康状况测量设备200还应当包括测量土壤信息的土壤信息采集单元，如土壤湿度传感器、土壤温度传感器、土壤养分分析仪中的一种或多种，当然还可以包括其他能够监测土壤信息的土壤信息采集单元。
上述植物健康状况测量设备200还应当包括测量空气信息的空气信息采集单元，如空气湿度传感器、温度计、空气质量检测仪中的一种或多种，当然还可以包括其他能够监测空气信息的空气信息采集单元。
上述植物健康状况测量设备200还应当包括测量光照信息的光照信息采集单元，如：光照强度测量仪、紫外线强度探测仪中的一种或多种。当然还可以包括其他能够监测光照信息的光照信息采集单元。
需要说明的是，上述历史植物健康状况信息、第一植物健康状况信息、第二植物健康状况信息不仅可以包括上述提到的信息，还可以包括气象信息等，在此不做一一限定。
另外，上述植物健康状况监测方法中，不管是第一次判断中涉及的当前植物图像信息，还是第二次判断中所涉及的当前植物图像可以为图片或者具有时间维度的影像，而第一次判断和第二次判断均是对对应的当前植物图像进行识别处理，以识别当前植物图像信息中的植物是否有病虫害症状、营养缺乏状况。
具体的，为了使得第二植物健康状况信息所提供的当前图像信息的内容比较丰富，在第一判断信息所表示的内容为植物存在健康不良风险，则接收植物健康状况测量设备200提供的存在健康不良风险的植物所在方位的第二植物健康状况信息前，在步骤S120和步骤S130之间，上述植物健康状态监 控方法还包括：
第一步，生成图像采集单元控制指令，图像采集单元控制指令至少包括处于健康不良风险的植物所在方位信息和图像放大控制信息；图像放大控制信息包括图像放大控制信息包括图像放大倍数控制信息和图像放大角度控制信息。
第二步，将图像采集单元控制指令发送给植物健康状况测量设备200，使得植物健康状况测量设备200根据图像采集单元控制指令，采集存在健康不良风险的植物所在方位的第二植物健康状况信息；第二植物健康状况信息所包括的当前植物图像信息，是第一植物健康状况信息中存在健康不良风险的植物所在方位的当前植物图像的不同角度的图像放大信息。
具体的，当植物健康状况测量设备200中的图像采集单元接收图像采集单元控制指令，能够根据存在健康不良风险的植物所在方位信息，调整到能够采集存在健康不良风险的植物所在方位信息的位置，并根据图像放大倍数控制信息调整图像放大倍数，以及根据图像放大角度控制信息调整采集植物健康状况信息时的所在的角度，以从不同角度对处在植物健康状况不良状态的植物所在方位的植物进行放大采集。
例如：当所使用的图像采集单元包括全方位云台以及设在全方位云台上的摄像机，全方位云台接收到存在健康不良风险的植物所在方位信息，可以通过水平旋转和垂直旋转一定角度，以使调整摄像机采集植物图像的角度，使得摄像机采集植物图像的角度调至存在健康不良风险的植物所在方位。
而摄像机在接收到图像放大倍数信息，可通过调节自身的焦距，以调节采集目标植物的景深，从而采集对目标植物的微距照片，也就是植物的放大照片，这样也就提高了第二植物健康状况信息所包括的当前植物图像信息的分辨率。
另外，上述图像采集单元也可以是可移动的，例如将图像采集单元安装在无人机或热气球，通过定期控制无人机采集植物图像信息，无人机可以为是四旋翼无人机或固定翼无人机等。
进一步，当上述植物健康状况测量设备200为固定式植物健康状况测量设备；如植物健康状况测量设备200包括固设在田间的图像采集单元。图像放大倍数控制信息至少为m个，图像放大角度控制信息至少为n个；每个图像放大角度控制信息包括设备水平旋转角度控制信息和设备垂直旋转角度控制信息；m和n均大于等于1；此时，植物健康状况测量设备200所采集的第二植物健康状况信息应当包括m×n组植物健康状况数据；每组所述植物健康状况数据包括设备旋转角度信息、图像放大信息和处于健康不良风险的当前植物图像信息，这样接收多组植物健康状况数据后，可以记录设备旋转角度信息、图像放大信息，以确定对应组的植物健康状况数据采集的方位信息，使得在第二判断信息所表示的内容为植物存在健康不良时，能够根据设备旋转角度信息和图像放大信息确定处于健康不良的植物所在方位信息。同时，如果还需要进行第三次接收和判断，还可以将第二次接收的这些设备旋转角度信息和图像放大信息进行进一步细化，将细化后的所有旋转角度和放大倍数，以指令的形式发送给植物健康状况测量设备200，使得植物健康状况测量设备200能够更加细致的采集当前植物图像信息，从而保证每次所采集的当前植物图像信息的精度大于前次所采集的当前植物图像信息的精度。
而当植物健康状况测量设备200为移动式植物健康状况测量设备，如将上述图像采集单元设在无人机或热气球上，此时，所述图像采集单元控制指令还包括：k个设备坐标控制信息；图像放大倍数控制信息至少为m个，所述图像放大角度控制信息至少为n个；每个图像放大角度控制信息包括设备水平旋转角度控制信息和设备垂直旋转角度控制信息；m、n、k均大于等于1；
相应的，第二植物健康状况信息包括m×n×k组植物健康状况数据；每组植物健康状况数据包括设备坐标信息、设备旋转角度信息、图像放大信息和处于健康不良风险的当前植物图像信息。
此时，在第二判断信息所表示的内容为植物存在健康不良时，不仅能够根据设备旋转角度信息和图像放大信息确定处于健康不良的植物所在方位信息，以及在第三判断信息时，将设备旋转角度信息和图像放大信息进行进一 步细化，以保证每次所采集的当前植物图像信息的精度大于前次所采集的当前植物图像信息的精度；而且，还可以通过细化设备坐标信息，使得植物健康状况测量设备200以更加精确的坐标进行图像采集。
而为了使得农田管理人员能够充分了解植物健康状态，如图2所示，若第一判断信息所表示的内容为植物健康良好，植物健康状态监控方法还包括与步骤S130存在选择关系的步骤S190，包括如下步骤：
步骤S191：根据第一判断信息所表示的内容，确定处于健康良好的植物所在方位；
步骤S192：周期性根据第一判断信息所表示的内容，和处于健康良好的植物所在方位信息，生成植物健康状况良好报告，将植物健康状况良好报告发送给客户端。和/或，
若第二判断信息所表示的内容为植物健康良好，上述植物健康状态监控方法还包括步骤S210，具体包括如下步骤：
步骤S211：根据第二判断信息所表示的内容，确定处于健康良好的植物所在方位；
步骤S212：周期性根据第二判断信息所表示的内容，和处于健康良好的植物所在方位信息，生成植物健康状况良好报告，将植物健康状况良好报告发送给客户端300。
可以理解的是，由于植物健康良好时，并不需要农田管理人员对植物进行病虫害防治等操作，因此，可以周期性的生成健康状况良好报告，发送给客户端300。
此外，对于处于健康不良的植物来说，需要及时进行病虫害防治等操作，基于此，在步骤S150后，还包括步骤S160：根据第二判断信息所表示的内容和处于健康不良的植物所在方位信息生成植物健康状况不良报告。
进一步，为了避免农田管理人员没有及时看到植物健康状况不良报告，而导致错过病虫害防治时机，若第二判断信息所表示的内容为植物健康状况不良，则如图2所示，上述植物健康状态监控方法还包括：
步骤S170：将植物健康状况不良报告发送给客户端300，以实时提醒农田管理人员查看植物健康状况不良报告。
同时，若第二判断信息所表示的内容为植物健康不良，继续如图2所示，上述植物健康状态监控方法还包括与步骤S150并行的步骤S180，具体的，步骤S180包括：生成报警指令，将报警指令发送给报警器400，使得报警器400根据报警指令报警，以进一步提醒农田管理人员。
需要说明的是，不管是将植物健康状况良好报告还是植物健康状况不良报告，其发送给客户端时，可以是以短信、微信消息、邮件的形式发送到对应的短信客户端、微信客户端、邮件客户端等应用。其中，微信消息可以是以私信的形式发送到农田管理人员的微信客户端，当然也可以是以服务推送消息的形式发送到各个农田管理人员的各种客户端。
进一步，为了使得植物健康状况不良报告的内容更为全面，如图3所示，若第二判断信息所表示的内容为植物健康存在不良，则根据第二判断信息所表示的内容和处在植物健康状况不良状态的植物所在方位信息生成植物健康状况不良报告包括：
步骤S161：根据第二判断信息所表示的内容，调取农作物知识数据库中的植物信息数据；
步骤S162：根据所调取的植物信息数据生成植物健康不良防治策略；农作物知识数据库中包括多种植物信息数据，每种所述植物信息数据包括植物信息以及对应植物健康不良防治策略。
可以理解的是，此处的农作物知识数据库可以为已经存在具有植物信息以及对应植物健康不良防治策略信息的数据库，也可以是通过采集各种植物信息，以及植物健康不良防治策略；如：植物健康不良防治策略可以包括各种植物的病虫害防治策略、各种植物的营养元素缺乏防治策略；
步骤S163：根据第二判断信息所表示的内容、植物健康不良防治策略以及处于健康不良的植物所在方位信息，生成植物健康状况不良报告；植物健康状况不良报告可以包括目标植物的所在位置区域、植物健康不良发生范围， 植物健康不良图片、识别时间和植物健康不良防治策略等，植物健康不良不仅可以包括虫害、病害、营养元素缺乏，还可以包括其他不健康状态。
基于上述根据第二判断信息所表示的内容和处于植物健康不良的植物所在方位信息生成植物健康状况不良报告的具体过程可知：本发明实施例提供的植物健康状态监测方法，在生成植物健康状况不良报告的过程中，根据第二判断信息所表示的内容调取农作物知识数据库中的植物信息数据，针对性的给出植物健康不良防治策略，并将第二判断信息所表示的内容和植物健康不良防治策略同时作为植物健康状况不良报告的内容进行生成，这样在农田管理人员看到植物健康状况不良报告时，不仅能够了解到具体方位的哪些植物处在健康不良状态，而且还能够看到所建议的植物健康不良防治策略，这样能够更加全面的给农业管理人员提供参考。
而对于第一植物健康状况信息和第二植物健康状况信息均至少具有两个来源这种情况；每个第一植物健康状况信息还包括：植物健康状况测量设备200的识别信息(如植物健康状况测量设备200的ID地址)和植物健康状况测量设备200的地理坐标信息(经纬度)；每个第二植物健康状况信息还包括：植物健康状况测量设备200的识别信息；当然也可以包括植物健康状况测量设备200的地理坐标信息。
优选的，每个第二植物健康状况信息还包括：植物健康状况测量设备200的识别信息。在接收植物健康状况测量设备200提供的第一植物健康状况信息后，根据第一植物健康状况信息对植物健康状况进行第一次判断前，上述植物健康状态识别方法还包括：
第一步，根据每个第一植物健康状况信息中的植物健康状况测量设备200的识别信息和植物健康状况测量设备的地理坐标信息，建立每个第一植物健康状况信息中植物健康状况测量设备的识别信息与植物健康状况测量设备的地理坐标信息的对应关系；保存每个第一植物健康状况信息中植物健康状况测量设备的识别信息与植物健康状况测量设备的地理坐标信息的对应关系；
第二步，接收植物健康状况测量设备200提供的存在健康不良风险的植 物所在方位的第二植物健康状况信息后，根据第二植物健康状况信息对植物健康状况信息进行第二次判断前，上述植物健康状态监控方法还包括：
第三步，根据每个第一植物健康状况信息中植物健康状况测量设备200的识别信息与植物健康状况测量设备200的地理坐标信息的对应关系，识别每个第二植物健康状况信息中的植物健康状况测量设备200的识别信息，得到每个第二植物健康状况信息中的植物健康状况测量设备200的地理坐标信息，以确定每个第二植物健康状况信息的来源。
通过上述描述可以发现，由于在接收植物健康状况测量设备200提供的第一植物健康状况信息后，根据每个第一植物健康状况信息中的植物健康状况测量设备200的识别信息和植物健康状况测量设备200的地理坐标信息，建立每个第一植物健康状况信息中植物健康状况测量设备200的识别信息与植物健康状况测量设备200的地理坐标信息的对应关系并进行保存，使得在接收植物健康状况测量设备提供的存在健康不良风险的植物所在方位的第二植物健康状况信息时，只需要接收每个第二植物健康状况信息中的植物健康状况测量设备的识别信息，就能够根据所建立的对应关系，利用每个第二植物健康状况信息中植物健康状况测量设备的识别信息，找到对应的植物健康状况测量设备的地理坐标信息，以确定每个第二植物健康状况信息的来源。
另外，不管是生成植物健康状况不良报告还是植物健康状况良好报告，除了含有植物健康状况信息外，还可以将对应第二植物健康状况信息的来源，使得农田管理人员能够根据第二植物健康状况信息的来源，更为准确的了解确定植物健康状况，以能够在植物健康状况不良时，准确定位植物健康状况不良所发生的位置。
例如：上述根据第二判断信息所表示的内容和处在植物健康状况不良状态的植物所在方位信息生成植物健康状况不良报告包括：
根据第二判断信息所表示的内容、处在植物健康状况不良状态的植物所在方位信息以及处在植物健康状况不良状态的植物所在第二植物健康状况信息的来源，生成植物健康状况不良报告。
本发明实施例还提供了一种植物健康状态监控装置，如图1和6所示，该植物健康状态监控装置包括：
接收单元110，接收单元110与植物健康状况测量设备100进行通信，设置为接收植物健康状况测量设备100提供的第一植物健康状况信息；
与接收单元110连接的处理单元120，设置为根据第一植物健康状况信息对植物健康状况进行第一次判断，得到第一判断信息；若第一判断信息所表示的内容为植物存在健康不良风险，接收单元110还设置为接收存在健康不良风险的植物所在方位的第二植物健康状况信息；处理单元120还设置为根据第二植物健康状况信息对植物健康状况进行第二次判断，得到第二判断信息；若第二判断信息所表示的内容为植物存在健康不良，则确认所述植物健康状况处于健康不良，以及确定处于健康不良的植物所在方位信息。
与现有技术相比，本发明实施例提供的植物健康状态监控装置的有益效果与上述实施例提供的植物健康状态监控方法的有益效果相同，在此不做赘述。
示例性的，第一植物健康状况信息至少包括当前植物图像信息，第二植物健康状况信息至少包括植物健康存在不良风险的植物所在方位对应的当前植物图像信息，且当第一植物健康状况信息至少包括当前植物图像信息时，植物健康状况测量设备100中含有图像采集单元，具体的，接收单元110与图像采集单元通信。
其中，第一植物健康状况信息所包括的当前植物图像信息的类型包括可见光谱图像信息和/或不可见光谱图像信息；第二植物健康状况信息所包括的当前植物图像信息的类型包括可见光谱图像信息和/或不可见光谱图像信息。
另外，第二植物健康状况信息中当前植物图像信息的精度大于第一植物健康状况信息中当前植物图像信息的精度，以实现对前文中植物图像信息的接收和判断次数的限定。
具体的，如图7所示，上述处理单元120包括：与接收单元110连接的机率分析模块121，设置为采用卷积神经网络模型对第一植物健康状况信息进 行判断，得到第一植物健康不良机率；以及采用卷积神经网络模型对第二植物健康状况信息进行判断，得到第二植物健康不良机率；
与机率分析模块121和报告生成单元130分别连接的判断模块122，设置为判断第一植物健康不良机率是否大于设定阈值；如果是，则确认植物健康存在不良风险和所述植物健康存在不良风险的植物所在方位；否则，确定植物健康状况良好；以及，判断第二植物健康不良机率是否大于设定阈值；
如果是，则确认植物存在健康不良，以及植物健康不良的程度以及处于健康不良的植物所在方位信息；否则，确定植物健康良好。
可选的，接收单元110还设置为接收历史植物健康状况信息，历史植物健康状况信息至少包括历史植物图像信息；
处理单元120还包括与接收单元110和机率分析模块121分别连接的信息训练模块123，设置为利用卷积神经网络对历史植物健康状况信息进行学习训练，得到卷积神经网络模型。
其中，历史植物健康状况信息还包括历史土壤信息、历史空气信息、历史光照信息中的一种或多种；第一植物健康状况信息至少还包括当前土壤信息、当前空气信息和当前光照信息中的一种或多种；第二植物健康状况信息至少还包括当前土壤信息、当前空气信息和当前光照信息中的一种或多种。
植物存在的健康不良风险包括病虫害风险和/或营养物质缺乏风险；营养物质缺乏风险包括微量元素缺乏风险、氮元素缺乏风险、磷元素缺乏风险、钾元素缺乏风险中的一种或多种；植物存在的健康不良包括植物存在病虫害症状和/或植物存在营养物质缺乏症状；营养物质缺乏症状包括微量元素缺乏症状、氮元素缺乏症状、磷元素缺乏症状、钾元素缺乏症状中的一种或多种。
上述第一植物健康状况信息至少还包括当前土壤信息、当前空气信息和当前光照信息中的一种或多种；第二植物健康状况信息至少还包括当前土壤信息、当前空气信息和当前光照信息中的一种或多种时，上述植物健康状况测量设备100还应当包括实现空气信息测量的空气信息采集单元、实现土壤信息测量的土壤信息采集单元、实现光照信息测量的光照信息采集单元中的 一种或多种。
另外，为了使得第二植物健康状况信息所提供的当前图像信息的内容比较丰富，如图6所示，上述植物健康状态监控装置还包括与处理单元120和发送单元150分别连接的指令生成单元160，设置为在第一判断信息所表示的内容为植物存在健康不良风险时，生成图像采集单元控制指令，图像采集单元控制指令至少包括处于健康不良风险的植物所在方位信息和图像放大控制信息；图像放大控制信息包括图像放大倍数控制信息和图像放大角度控制信息；
发送单元150，设置为将图像采集单元控制指令发送给植物健康状况测量设备，使得植物健康状况测量设备根据图像采集单元控制指令，采集处于健康不良风险的植物所在方位的第二植物健康状况信息。
可选的，当植物健康状况测量设备200为固定式植物健康状况测量设备；图像放大倍数控制信息至少为m个，图像放大角度控制信息至少为n个；每个图像放大角度控制信息包括设备水平旋转角度控制信息和设备垂直旋转角度控制信息；m和n均大于等于1；
第二植物健康状况信息包括m×n组植物健康状况数据；每组植物健康状况数据包括设备旋转角度信息、图像放大信息和处于健康不良风险的当前植物图像信息。
可选的，当植物健康状况测量设备为移动式植物健康状况测量设备；图像采集单元控制指令还包括：k个设备坐标控制信息；图像放大倍数控制信息至少为m个，图像放大角度控制信息至少为n个；每个图像放大角度控制信息包括设备水平旋转角度控制信息和设备垂直旋转角度控制信息；m、n、k均大于等于1；
第二植物健康状况信息包括m×n×k组植物健康状况数据；每组植物健康状况数据包括设备坐标信息、设备旋转角度信息、图像放大信息和处于健康不良风险的当前植物图像信息。
而为了使得农田管理人员能够充分了解植物健康状态，如图2和图6所 示，在第一判断信息和/或第二判断信息所表示的内容为植物健康良好时，上述植物健康状态监测装置还包括与处理单元120连接的报告生成单元130，上述处理单元120还设置为根据第一判断信息和/或第二判断信息所表示的内容确定处在健康良好的植物所在方位信息；
报告生成单元130还设置为在第一判断信息和/或第二判断信息所表示的内容为植物健康良好时，周期性根据第一判断信息和/或第二判断信息所表示的内容和处于健康良好的植物所在方位信息生成植物健康状况良好报告；
如图2和图6所示，上述植物健康状态监控装置还包括：发送单元150还设置为将植物健康状况良好报告发送给客户端300。发送时，可以是无线发送也可以是有线发送，此时，发送单元150与客户端300存在通信关系。
而在第二判断信息所表示的内容为植物存在健康不良时，报告生成单元130还设置为根据第二判断信息所表示的内容和处于健康不良的植物所在方位信息生成植物健康状况不良报告；发送单元150还设置为将植物健康状况不良报告发送给客户端，以使得农田管理人员能够及时针对植物健康不良进行防治。
另外，指令生成单元160还设置为在第二判断信息所表示的内容为植物存在健康不良时，生成报警指令；
发送单元150还设置为将报警指令发送给报警器400，使得报警指令控制报警器400报警，以提醒农田管理人员。此时，发送单元150与报警器400存在通信关系；其中，当处理单元120采用如图7所示的结构框图时，指令生成单元160与判断模块122连接。
另外，上述发送单元150还设置为在第二判断信息所表示的内容为植物健康状况不良时，将植物健康状况不良报告发送给客户端300；
而为了使得植物健康不良报告的内容更加丰富，上述植物健康状况健康装置还包括与处理单元120连接的农作物知识数据库；农作物知识数据库包括多种植物信息数据；每种植物信息数据包括植物信息以及对应植物健康不良防治策略；处理单元120还设置为根据第二判断信息所表示的内容，调取 农作物知识数据库中的植物信息数据，根据所调取的植物信息数据生成植物健康不良防治策略；
报告生成单元130设置为根据第二判断信息所表示的内容、植物健康不良防治策略以及处于健康不良的植物所在方位信息，生成植物健康状况不良报告，这样植物健康状况不良报告不仅含有植物健康不良的信息还含有如何防治植物健康不良的策略。其中，植物健康不良防治策略包括病虫害防治策略和/或植物营养元素缺乏防治策略。
需要说明的是，若第一植物健康状况信息和第二植物健康状况信息均至少具有两个来源；此时，每个第一植物健康状况信息还包括：植物健康状况测量设备的识别信息和植物健康状况测量设备的地理坐标信息；
每个第二植物健康状况信息还包括：植物健康状况测量设备的识别信息；
此时，如图6所示，上述植物健康状态监控装置还包括：与接收单元110和处理单元120连接的设备识别单元140，处理单元采用如图7所示的结构框图，设备识别单元140与机率分析模块121连接；其中，
接收植物健康状况测量设备200提供的第一植物健康状况信息后，与根据第一植物健康状况信息对植物健康状况进行第一次判断前，设备识别单元140设置为根据每个第一植物健康状况信息中的植物健康状况测量设备的识别信息和植物健康状况测量设备的地理坐标信息，建立每个第一植物健康状况信息中植物健康状况测量设备的识别信息与植物健康状况测量设备的地理坐标信息的对应关系；保存每个第一植物健康状况信息中植物健康状况测量设备的识别信息与植物健康状况测量设备的地理坐标信息的对应关系；以及，
接收植物健康状况测量设备提供的植物健康存在不良风险的植物所在方位的第二植物健康状况信息后，根据第二植物健康状况信息对植物健康状况信息进行第二次判断前，上述设备识别单元140还设置为：
识别每个第二植物健康状况信息中的植物健康状况测量设备的识别信息，得到每个所述第二植物健康状况信息中的植物健康状况测量设备的地理坐标信息，以确定每个第二植物健康状况信息的来源；
报告生成单元130包括根据第二判断信息所表示的内容、处在植物健康状况不良状态的植物所在方位信息以及处于健康不良的植物所在第二植物健康状况信息的来源，生成植物健康状况不良报告。
本发明实施例还提供了一种存储介质，设置为存储支持上述植物健康状态监测方法实现的可执行程序代码，其所产生的有益效果与上述植物健康状态监测方法的有益效果相同，在此不再赘述。
如图1和图8所示，本发明实施例还提供了一种植物健康状态监测终端，该植物健康状态监测终端包括收发器501、存储器502和处理器503，收发器501、存储器502和处理器503通过总线504相互通信。
其中，收发器501设置为与植物健康状况测量设备200、客户端300、报警器400通信；
存储器502设置为存储可执行程序代码，以使得处理器503执行多种控制指令，实现上述植物健康状态监测方法。
其中，本发明实施例所述的处理器503可以是一个处理器，也可以是多个处理元件的统称。例如，该处理器503可以是中央处理器(Central Processing Unit，简称CPU)，也可以是特定集成电路(Application Specific Integrated Circuit，简称ASIC)，或者是被配置成实施本发明实施例的一个或多个集成电路，例如：一个或多个微处理器(digital signal processor，简称DSP)，或，一个或者多个现场可编程门阵列(Field Programmable Gate Array，简称FPGA)。
存储器502可以是一个存储装置，也可以是多个存储元件的统称，且设置为存储可执行程序代码等。且存储器502可以包括随机存储器(RAM)，也可以包括非易失性存储器(non-volatile memory)，例如磁盘存储器，闪存(Flash)等。
总线504可以是工业标准体系结构(Industry Standard Architecture，ISA)总线、外部设备互连(Peripheral Component，PCI)总线或扩展工业标准体系结构(Extended Industry Standard Architecture，EISA)总线等。该总线504可以分为地址总线、数据总线、控制总线等。为便于表示，图8中仅用一条粗线 表示，但并不表示仅有一根总线或一种类型的总线。
本说明书中的各个实施例均采用递进的方式描述，各个实施例之间相同相似的部分互相参见即可，每个实施例重点说明的都是与其他实施例的不同之处。尤其，对于设备实施例而言，由于其基本相似于方法实施例，所以描述得比较简单，相关之处参见方法实施例的部分说明即可。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机程序来指令相关的硬件来完成，所述的程序可存储于计算机可读取存储介质中，该程序在执行时，可包括如上述各方法的实施例的流程。其中，所述的存储介质可为磁碟、光盘、只读存储记忆体(Read-Only Memory，ROM)或随机存储记忆体(Random Access Memory，RAM)等。
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到的变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应该以权利要求的保护范围为准。
在上述实施方式的描述中，具体特征、结构、材料或者特点可以在任何的一个或多个实施例或示例中以合适的方式结合。
以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应以所述权利要求的保护范围为准。

Claims (28)

  1. 一种植物健康状态监控方法，包括：
    接收植物健康状况测量设备提供的第一植物健康状况信息，根据所述第一植物健康状况信息对植物健康状况进行判断，得到第一判断信息；
    若所述第一判断信息所表示的内容为植物存在健康不良风险，则接收所述存在健康不良风险的植物所在方位的第二植物健康状况信息；根据所述第二植物健康状况信息对植物健康状况进行判断，得到第二判断信息；
    若所述第二判断信息所表示的内容为植物存在健康不良，则确认所述植物健康状况处于健康不良，以及确定处于健康不良的植物所在方位信息。
  2. 根据权利要求1所述的植物健康状态监控方法，其中，所述第一植物健康状况信息至少包括当前植物图像信息；
    所述根据所述第一植物健康状况信息对植物健康状况进行判断，得到第一判断信息包括：
    采用卷积神经网络模型对所述第一植物健康状况信息进行判断，得到第一植物健康不良机率；
    判断所述第一植物健康不良机率是否大于设定阈值；
    如果是，则确认植物存在健康不良风险和所述存在健康不良风险的植物所在方位信息。
  3. 根据权利要求2所述的植物健康状态识别方法，其中，所述采用卷积神经网络模型对所述第一植物健康状况信息进行判断前，所述植物健康状态识别方法还包括：
    接收历史植物健康状况信息，所述历史植物健康状况信息至少包括历史植物图像信息；
    利用所述卷积神经网络对所述历史植物健康状况信息进行学习训练，得到卷积神经网络模型。
  4. 根据权利要求3所述的植物健康状态监控方法，其中，所述历史植物健康状况信息还包括历史土壤信息、历史空气信息、历史光照信息中的一种 或多种；
    所述第一植物健康状况信息至少还包括当前土壤信息、当前空气信息和当前光照信息中的一种或多种；
    所述第二植物健康状况信息至少还包括当前土壤信息、当前空气信息和当前光照信息中的一种或多种。
  5. 根据权利要求2所述的植物健康状态识别方法，其中，所述第一植物健康状况信息所包括的当前植物图像信息的类型包括可见光谱图像信息和/或不可见光谱图像信息；
  6. 根据权利要求1所述的植物健康状态监控方法，其中，所述第二植物健康状况信息至少包括存在健康不良风险的植物所在方位对应的当前植物图像信息；
    所述根据所述第二植物健康状况信息对植物健康状况进行判断，得到第二判断信息包括：
    采用卷积神经网络模型对所述第二植物健康状况信息进行判断，得到第二植物健康不良机率；
    判断所述第二植物健康不良机率是否大于设定阈值；
    如果是，则确认植物存在健康不良、植物健康不良的程度，以及处于健康不良的植物所在方位信息。
  7. 根据权利要求6所述的植物健康状态监控方法，其中，所述第二植物健康状况信息所包括的当前植物图像信息的类型包括可见光谱图像信息和/或不可见光谱图像信息。
  8. 根据权利要求2-7任一项所述的植物健康状态监控方法，其中，若所述第一判断信息所表示的内容为植物存在健康不良风险，则所述接收所述存在健康不良风险的植物所在方位的第二植物健康状况信息前，所述植物健康状态监控方法还包括：
    生成图像采集单元控制指令，所述图像采集单元控制指令至少包括所述处于健康不良风险的植物所在方位信息和图像放大控制信息；所述图像放大 控制信息包括图像放大倍数控制信息和图像放大角度控制信息；
    将所述图像采集单元控制指令发送给植物健康状况测量设备，使得所述植物健康状况测量设备根据图像采集单元控制指令，采集存在健康不良风险的植物所在方位的第二植物健康状况信息。
  9. 根据权利要求8所述的植物健康状态监控方法，其中，当所述植物健康状况测量设备为固定式植物健康状况测量设备；所述图像放大倍数控制信息至少为m个，所述图像放大角度控制信息至少为n个；每个所述图像放大角度控制信息包括设备水平旋转角度控制信息和设备垂直旋转角度控制信息；m和n均大于等于1；
    所述第二植物健康状况信息包括m×n组植物健康状况数据；每组所述植物健康状况数据包括设备旋转角度信息、图像放大信息和处于健康不良风险的当前植物图像信息。
  10. 根据权利要求8所述的植物健康状态监控方法，其中，当所述植物健康状况测量设备为移动式植物健康状况测量设备；所述图像采集单元控制指令还包括：k个设备坐标控制信息；
    所述图像放大倍数控制信息至少为m个，所述图像放大角度控制信息至少为n个；每个所述图像放大角度控制信息包括设备水平旋转角度控制信息和设备垂直旋转角度控制信息；m、n、k均大于等于1；
    所述第二植物健康状况信息包括m×n×k组植物健康状况数据；每组所述植物健康状况数据包括设备坐标信息、设备旋转角度信息、图像放大信息和处于健康不良风险的当前植物图像信息。
  11. 根据权利要求1～7任一项所述的植物健康状态监控方法，其中，所述植物存在的健康不良风险包括病虫害风险和/或营养物质缺乏风险；所述营养物质缺乏风险包括微量元素缺乏风险、氮元素缺乏风险、磷元素缺乏风险、钾元素缺乏风险中的一种或多种；
    所述植物存在的所述健康不良包括植物存在病虫害症状和/或植物存在营养物质缺乏症状；所述营养物质缺乏症状包括微量元素缺乏症状、氮元素缺 乏症状、磷元素缺乏症状、钾元素缺乏症状中的一种或多种。
  12. 根据权利要求1-7任一项所述的植物健康状态监控方法，其中，若所述第一判断信息和/或第二判断信息所表示的内容为植物健康良好，所述植物健康状态监控方法还包括：
    根据所述第一判断信息和/或第二判断信息所表示的内容，确定处于健康良好的植物所在方位；
    周期性根据所述第一判断信息和/或第二判断信息所表示的内容，和处于健康良好的植物所在方位信息，生成植物健康状况良好报告，将所述植物健康状况良好报告发送给客户端。
  13. 根据权利要求1-7任一项所述的植物健康状态监控方法，其中，确认所述植物健康状况处于健康不良，以及确定处于健康不良的植物所在方位信息后，所述植物健康状态监控方法还包括：
    根据所述第二判断信息所表示的内容和处于健康不良的植物所在方位信息生成植物健康状况不良报告；
    将所述植物健康状况不良报告发送给客户端；以及，
    生成报警指令，将所述报警指令发送给报警器，使得所述报警器根据报警指令报警。
  14. 根据权利要求13所述的植物健康状态监控方法，其中，所述根据所述第二判断信息所表示的内容和处于健康不良的植物所在方位信息生成植物健康状况不良报告包括：
    根据所述第二判断信息所表示的内容，调取农作物知识数据库中的植物信息数据，根据所调取的植物信息数据生成植物健康不良防治策略；所述农作物知识数据库包括多种植物信息数据，每种所述植物信息数据包括植物信息以及对应植物健康不良防治策略；
    根据所述第二判断信息所表示的内容、所述植物健康不良防治策略以及处于健康不良的植物所在方位信息，生成植物健康状况不良报告。
  15. 根据权利要求14所述的植物健康状态监控方法，其中，所述植物健 康不良防治策略包括病虫害防治策略和/或植物营养元素缺乏防治策略。
  16. 一种植物健康状态监控装置，包括：
    接收单元，设置为接收植物健康状况测量设备提供的第一植物健康状况信息；
    与接收单元连接的处理单元，设置为根据所述第一植物健康状况信息对植物健康状况进行第一次判断，得到第一判断信息；若所述第一判断信息所表示的内容为植物存在健康不良风险，所述接收单元还设置为接收所述存在健康不良风险的植物所在方位的第二植物健康状况信息；所述处理单元还设置为根据所述第二植物健康状况信息对植物健康状况进行第二次判断，得到第二判断信息；若所述第二判断信息所表示的内容为植物存在健康不良，则确认所述植物健康状况处于健康不良，以及确定处于健康不良的植物所在方位信息。
  17. 根据权利要求16所述的植物健康状态监控装置，其中，所述第一植物健康状况信息至少包括当前植物图像信息，所述第二植物健康状况信息至少包括存在健康不良风险的植物所在方位对应的当前植物图像信息；
    所述处理单元包括：
    与接收单元连接的机率分析模块，设置为采用卷积神经网络模型对所述第一植物健康状况信息进行判断，得到第一植物健康不良机率；以及采用卷积神经网络模型对所述第二植物健康状况信息进行判断，得到第二植物健康不良机率；
    与机率分析模块和所述报告生成单元分别连接的判断模块，设置为判断所述第一植物健康不良机率是否大于设定阈值；如果是，则确认植物存在健康不良风险和所述存在健康不良风险的植物所在方位信息；以及，
    判断所述第二植物健康不良机率是否大于设定阈值；
    如果是，则确认植物存在健康不良，植物健康不良的程度以及处于健康不良的植物所在方位信息。
  18. 根据权利要求17所述的植物健康状态监控装置，其中，
    所述接收单元还设置为接收历史植物健康状况信息，所述历史植物健康状况信息至少包括历史植物图像信息；
    所述处理单元还包括与所述接收单元和机率分析模块分别连接的信息训练模块，设置为利用所述卷积神经网络对所述历史植物健康状况信息进行学习训练，得到卷积神经网络模型。
  19. 根据权利要求18所述的植物健康状态监控装置，其中，所述历史植物健康状况信息还包括历史土壤信息、历史空气信息、历史光照信息中的一种或多种；
    所述第一植物健康状况信息至少还包括当前土壤信息、当前空气信息和当前光照信息中的一种或多种；
    所述第二植物健康状况信息至少还包括当前土壤信息、当前空气信息和当前光照信息中的一种或多种。
  20. 根据权利要求17～19任一项所述的植物健康状态监控装置，其中，所述植物健康状态监控装置还包括与处理单元120和发送单元150分别连接的指令生成单元160，设置为在第一判断信息所表示的内容为植物存在健康不良风险时，生成图像采集单元控制指令，所述图像采集单元控制指令至少包括处于健康不良风险的植物所在方位信息和图像放大控制信息；所述图像放大控制信息包括图像放大倍数控制信息和图像放大角度控制信息；
    发送单元150设置为将所述图像采集单元控制指令发送给植物健康状况测量设备，使得所述植物健康状况测量设备根据图像采集单元控制指令，采集处于健康不良风险的植物所在方位的第二植物健康状况信息。
  21. 根据权利要求20所述的植物健康状态监控装置，其中，当所述植物健康状况测量设备为固定式植物健康状况测量设备；所述图像放大倍数控制信息至少为m个，所述图像放大角度控制信息至少为n个；每个所述图像放大角度控制信息包括设备水平旋转角度控制信息和设备垂直旋转角度控制信息；m和n均大于等于1；
    所述第二植物健康状况信息包括m×n组植物健康状况数据；每组所述植 物健康状况数据包括设备旋转角度信息、图像放大信息和处于健康不良风险的当前植物图像信息。
  22. 根据权利要求20所述的植物健康状态监控装置，其中，当所述植物健康状况测量设备为移动式植物健康状况测量设备；所述图像采集单元控制指令还包括：k个设备坐标控制信息；
    所述图像放大倍数控制信息至少为m个，所述图像放大角度控制信息至少为n个；每个所述图像放大角度控制信息包括设备水平旋转角度控制信息和设备垂直旋转角度控制信息；m、n、k均大于等于1；
    所述第二植物健康状况信息包括m×n×k组植物健康状况数据；每组所述植物健康状况数据包括设备坐标信息、设备旋转角度信息、图像放大信息和处于健康不良风险的当前植物图像信息。
  23. 根据权利要求17～19任一项所述的植物健康状态监控装置，其中，所述第一植物健康状况信息所包括的当前植物图像信息的类型包括可见光谱图像信息和/或不可见光谱图像信息；
    所述第二植物健康状况信息所包括的当前植物图像信息的类型包括可见光谱图像信息和/或不可见光谱图像信息。
  24. 根据权利要求16～19任一项所述的植物健康状态监控装置，其中，所述植物存在的健康不良风险包括病虫害风险和/或营养物质缺乏风险；所述营养物质缺乏风险包括微量元素缺乏风险、氮元素缺乏风险、磷元素缺乏风险、钾元素缺乏风险中的一种或多种；
    所述植物存在的健康不良包括植物存在病虫害症状和/或植物存在营养物质缺乏症状；所述营养物质缺乏症状包括微量元素缺乏症状、氮元素缺乏症状、磷元素缺乏症状、钾元素缺乏症状中的一种或多种。
  25. 根据权利要求16-19任一项所述的植物健康状态监控装置，其中，所述处理单元还设置为在所述第一判断信息和/或第二判断信息所表示的内容为所述植物健康良好时，根据所述第一判断信息和/或第二判断信息所表示的内容确定处于健康良好的植物所在方位信息；
    所述植物健康状态监控装置还包括与处理单元连接的报告生成单元，设置为在所述第一判断信息和/或第二判断信息所表示的内容为植物健康良好时，周期性根据所述第一判断信息和/或第二判断信息所表示的内容和处于健康良好的植物所在方位信息，生成植物健康状况良好报告；
    所述植物健康状态监控装置还包括与所述报告生成单元连接的发送单元，所述发送单元设置为将所述植物健康状况良好报告发送给客户端。
  26. 根据权利要求25所述的植物健康状态监控装置，其中，
    所述报告生成单元还设置为在所述第二判断信息所表示的内容为植物存在健康不良时，根据所述第二判断信息所表示的内容和处于健康不良的植物所在方位信息生成植物健康状况不良报告；
    所述发送单元还设置为将所述植物健康状况不良报告发送给客户端；
    所述植物健康状态监控装置还包括与处理单元和发送单元分别连接的指令生成单元，设置为在所述第二判断信息所表示的内容为植物存在健康不良时，生成报警指令；
    所述发送单元还设置为将所述报警指令发送给报警器，使得所述报警指令控制所述报警器报警。
  27. 根据权利要求26所述的植物健康状态监控装置，其中，
    与处理单元连接的农作物知识数据库；所述农作物知识数据库包括多种植物信息数据；每种所述植物信息数据包括植物信息以及对应植物健康不良防治策略；所述处理单元还设置为根据所述第二判断信息所表示的内容，调取农作物知识数据库中的植物信息数据，根据所调取的植物信息数据生成植物健康不良防治策略；
    所述报告生成单元设置为根据所述第二判断信息所表示的内容、所述植物健康不良防治策略以及处于健康不良的植物所在方位信息，生成植物健康状况不良报告。
  28. 根据权利要求27所述的植物健康状态监控装置，其中，所述植物健康不良防治策略包括病虫害防治策略和/或植物营养元素缺乏防治策略。
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