WO2019114017A1 - 一种应用于智慧城市的绿化监测方法及智能监测机器人 - Google Patents

一种应用于智慧城市的绿化监测方法及智能监测机器人 Download PDF

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Publication number
WO2019114017A1
WO2019114017A1 PCT/CN2017/117683 CN2017117683W WO2019114017A1 WO 2019114017 A1 WO2019114017 A1 WO 2019114017A1 CN 2017117683 W CN2017117683 W CN 2017117683W WO 2019114017 A1 WO2019114017 A1 WO 2019114017A1
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Prior art keywords
target
tree
target tree
intelligent monitoring
electrical impedance
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PCT/CN2017/117683
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English (en)
French (fr)
Inventor
蔡任轩
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广州德科投资咨询有限公司
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Publication of WO2019114017A1 publication Critical patent/WO2019114017A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/0098—Plants or trees
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
    • G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
    • G01N27/04—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance
    • G01N27/041—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance of a solid body
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
    • G01N27/02—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance
    • G01N27/04—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance
    • G01N27/048—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating impedance by investigating resistance for determining moisture content of the material
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/04—Analysing solids
    • G01N29/06—Visualisation of the interior, e.g. acoustic microscopy
    • G01N29/0654—Imaging
    • G01N29/0672—Imaging by acoustic tomography
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N29/00—Investigating or analysing materials by the use of ultrasonic, sonic or infrasonic waves; Visualisation of the interior of objects by transmitting ultrasonic or sonic waves through the object
    • G01N29/04—Analysing solids
    • G01N29/09—Analysing solids by measuring mechanical or acoustic impedance

Definitions

  • the invention relates to the technical field of smart cities, and particularly relates to a green monitoring method and an intelligent monitoring robot applied to a smart city.
  • Urban greening monitoring includes the detection of pests and trees and the collection of basic information about trees such as tree circumference, tree moisture, and tree samples.
  • the greening monitoring work in the city requires managers to go to the green area to manually measure the basic information of the trees, and to use some testing equipment to detect the pests and diseases of the trees.
  • the method of green monitoring in the field is not only high labor cost but also green monitoring. low efficiency.
  • the embodiment of the invention discloses a greening monitoring method and an intelligent monitoring robot applied to a smart city, which can reduce the labor cost and improve the greening monitoring efficiency.
  • a first aspect of the embodiments of the present invention discloses a greening monitoring method applied to a smart city, where the method includes:
  • the intelligent monitoring robot detects basic data of the target trees in the preset area, and compares the basic data with existing data in the database to determine the tree species of the target tree; wherein the basic data includes the Location data of target trees and sample data;
  • the intelligent monitoring robot performs electrical impedance detection on the target tree to obtain an electrical impedance tomographic image of the target tree, and determines an immediate health condition of the target tree according to the electrical impedance tomographic image; wherein the instant The degree of health includes the moisture of the trees of the target tree;
  • the intelligent monitoring robot performs a lateral tensile test on the target tree to obtain an immediate degree of stability of the target tree, and performs pest and disease detection on the target tree to obtain an immediate degree of pest infestation of the target tree;
  • the intelligent monitoring robot determines a preset ratio value corresponding to the tree species of the target tree, and the preset ratio value is a preset value of a preset health status degree, a preset stability degree, and a predetermined degree of pest infestation;
  • the intelligent monitoring robot calculates the comprehensive health degree of the target tree according to the degree of the immediate health condition, the degree of immediate stability, the degree of the current pest-infested attack, and the preset ratio value.
  • the intelligent monitoring robot performs electrical impedance detection on the target tree to obtain an electrical impedance tomographic image of the target tree, including:
  • the intelligent monitoring robot controls a tree electrical impedance tomography device to input a current into the target tree;
  • the intelligent monitoring robot controls the tree electrical impedance tomography apparatus to measure a current change in the target tree to obtain a measurement result, and obtain the measurement result in the form of an electrical impedance tomographic image; wherein the electrical impedance is resistant
  • the image includes a high resistance indicating area, a low resistance indicating area, and a growth resistance indicating area of the trunk cross section of the target tree; wherein the water content of the trunk portion of the target tree corresponding to the high resistance indicating area is lower than the normal water content a minimum value of the range, the water content of the trunk portion of the target tree corresponding to the low resistance indicating region is in a range of normal water content, and the water content of the trunk portion of the target tree corresponding to the growth resistance indicating region is in a changing state.
  • the method further includes:
  • the intelligent monitoring robot controls the tree electrical impedance tomography device to perform sonication on the target tree to obtain an acoustic image; wherein the acoustic image includes a high-rate acoustic region and a low-rate acoustic region of the trunk cross-section ;
  • the method further includes:
  • the intelligent monitoring robot determines an immediate specific health condition level of a target trunk portion of the target tree
  • the intelligent monitoring robot determines that the immediate specific health condition of the target trunk portion is healthy;
  • the target trunk portion of the tree belongs to both the high-rate sound wave region and the low-resistance indicating region, and the intelligent monitoring robot determines that the instantaneous specific health condition of the target trunk portion is mildly decaying; if the target tree is The target trunk portion belongs to both the low-rate sound wave region and the high-resistance indicating region, and the intelligent monitoring robot determines that the instantaneous specific health condition of the target trunk portion is severely rotted and dies; if the target tree target The trunk portion belongs to both the low-rate sound wave region and the low-resistance indicating region, and the intelligent monitoring robot determines that the instantaneous specific health condition of the target trunk portion is moderately decayed.
  • the intelligent monitoring robot is configured according to the degree of the immediate health condition, the degree of immediate stability, the degree of the current pest and disease infestation, and the preset The ratio value, after calculating the comprehensive health of the target tree, the method further includes:
  • the intelligent monitoring robot sends a detection report of the target tree to a mobile terminal of a manager; wherein the detection report includes the instantaneous health status of the target tree, the immediate stability degree, and the immediate receiving The extent of pest and disease, the underlying data, and the overall health level.
  • the intelligent monitoring robot performs pest and disease detection on the target tree to obtain an immediate degree of pest infestation of the target tree, including:
  • the intelligent monitoring robot acquires a random sample of the target tree
  • the intelligent monitoring robot controls the pest detecting device to detect the random sample, and determines whether the pest is present in the random sample;
  • the intelligent monitoring robot compares the morphology of the pest to the existing pests and diseases in the database, obtains the species of the pest, and transmits the species of the pest to the mobile terminal.
  • the second aspect of the embodiment of the present invention discloses an intelligent monitoring robot, where the intelligent monitoring robot includes:
  • a basic data detecting unit configured to detect basic data of a target tree in a preset area, and compare the basic data with existing data in a database to determine a tree species of the target tree; wherein, the basic The data includes location data of the target tree and sample data;
  • An electrical impedance detecting unit configured to perform electrical impedance detection on the target tree to obtain an electrical impedance tomographic image of the target tree;
  • a first determining unit configured to determine an immediate health status of the target tree according to the electrical impedance tomography image; wherein the instantaneous health condition level includes a tree moisture of the target tree;
  • a lateral tensile test unit for performing a lateral tensile test on the target tree to obtain an immediate stability degree of the target tree
  • a pest detection unit configured to perform pest and disease detection on the target tree to obtain an immediate degree of pest infestation of the target tree
  • a second determining unit configured to determine a preset ratio value corresponding to the tree species of the target tree, where the preset ratio value is a preset health level, a preset stability level, and a preset proportion of the pest infestation degree value;
  • a calculating unit configured to calculate a comprehensive health degree of the target tree according to the degree of the immediate health condition, the degree of immediate stability, the degree of the current pest and disease infestation, and the preset ratio value.
  • the electrical impedance detecting unit includes:
  • a first control subunit configured to control a tree electrical impedance tomography device to input current into the target tree
  • a second control subunit configured to control the tree electrical impedance tomography device to measure a current change in the target tree to obtain a measurement result, and obtain the measurement result in the form of an electrical impedance tomography image;
  • the electrical impedance tomographic image includes a high resistance indicating area, a low resistance indicating area, and a growth resistance indicating area of a trunk cross section of the target tree; wherein a water content of a trunk portion of the target tree corresponding to the high resistance indicating area is lower than a minimum value of the normal water content range, wherein the water content of the trunk portion of the target tree corresponding to the low resistance indicating area is within a range of normal water content, and the water content of the trunk portion of the target tree corresponding to the growth resistance indicating area is at Change state.
  • the intelligent monitoring robot further includes:
  • control unit configured to: after the electrical impedance detecting unit obtains an electrical impedance tomographic image of the target tree, control the tree electrical impedance tomography device to perform sonication on the target tree to obtain an acoustic image;
  • the sound wave image includes a high rate sound wave region of the trunk cross section and a low rate sound wave region;
  • the first determining unit is further configured to determine an immediate specific health status of the target trunk portion of the target tree after performing the determining the immediate health status of the target tree according to the electrical impedance tomography image ;
  • the first determining unit is further configured to determine, when the target trunk portion of the target tree belongs to the high-rate sound wave region and the high-resistance indicating region, the instantaneous specific health status of the target trunk portion is Health; determining, when the target trunk portion of the target tree belongs to both the high-rate acoustic region and the low-resistance indicating region, determining an immediate specific health condition of the target trunk portion as mildly decaying; When the target trunk portion of the tree belongs to both the low-rate sound wave region and the high-resistance indicating region, determining the instantaneous specific health condition of the target trunk portion is severely rotted and dying; when the target trunk portion of the target tree When the low-rate acoustic wave region belongs to the low-resistance indicating region, the instantaneous specific health condition of the target trunk portion is determined to be moderately decaying.
  • the intelligent monitoring robot further includes:
  • a sending unit configured to calculate, at the calculating unit, the comprehensive health level of the target tree according to the current health condition level, the instantaneous stability level, the instantaneous degree of pest infestation, and the preset ratio value Afterwards, the detection report of the target tree is sent to the mobile terminal of the manager; wherein the detection report includes the degree of the immediate health condition of the target tree, the instantaneous stability degree, and the degree of the immediate pest infestation
  • the basic data and the overall health level configured to calculate, at the calculating unit, the comprehensive health level of the target tree according to the current health condition level, the instantaneous stability level, the instantaneous degree of pest infestation, and the preset ratio value Afterwards, the detection report of the target tree is sent to the mobile terminal of the manager; wherein the detection report includes the degree of the immediate health condition of the target tree, the instantaneous stability degree, and the degree of the immediate pest infestation The basic data and the overall health level.
  • the pest detection unit includes:
  • a third control subunit configured to control the pest detecting device to detect the random sample
  • a determining subunit configured to determine whether a pest or a pest exists in the random sample
  • a third aspect of the embodiments of the present invention discloses an intelligent monitoring robot, including:
  • a processor coupled to the memory
  • the processor invokes the executable program code stored in the memory to perform a greening monitoring method applied to a smart city disclosed in the first aspect of the embodiments of the present invention.
  • a fourth aspect of the embodiments of the present invention discloses a computer readable storage medium storing a computer program, wherein the computer program causes a computer to perform a greening monitoring method applied to a smart city disclosed in the first aspect of the embodiments of the present invention.
  • a fifth aspect of the embodiments of the present invention discloses a computer program product, when the computer program product is run on a computer, causing the computer to perform the greening monitoring method disclosed in the first aspect for smart city.
  • the embodiment of the invention has the following beneficial effects:
  • the intelligent monitoring robot in the preset area, can detect the position data of the target tree and the basic data such as the sample data, and can also detect the electrical impedance of the target tree and obtain the electrical impedance tomographic image to determine the health of the target tree.
  • the degree of condition can also be tested by stretching the target trees to obtain the stability of the target trees.
  • the target trees can also be tested for pests and diseases to obtain the degree of pests and diseases of the target trees.
  • the intelligent monitoring robot can calculate the comprehensive health degree of the target tree according to the preset degree of the degree of health, stability and pest and disease infestation of the target tree for the tree species of the target tree.
  • the embodiments of the present invention can reduce the labor cost and improve the greening monitoring efficiency by automatically monitoring the trees in the preset area.
  • FIG. 1 is a schematic flow chart of a greening monitoring method applied to a smart city according to an embodiment of the present invention
  • FIG. 2 is a schematic flow chart of another greening monitoring method applied to a smart city according to an embodiment of the present invention
  • FIG. 3 is a schematic flow chart of still another greening monitoring method applied to a smart city according to an embodiment of the present invention.
  • FIG. 4 is a schematic diagram of a scene of a smart monitoring robot performing a lateral tensile test on a target tree according to an embodiment of the present invention
  • FIG. 5 is a schematic structural diagram of an intelligent monitoring robot according to an embodiment of the present invention.
  • FIG. 6 is a schematic structural diagram of another intelligent monitoring robot disclosed in an embodiment of the present invention.
  • FIG. 7 is a schematic structural diagram of still another intelligent monitoring robot disclosed in an embodiment of the present invention.
  • FIG. 8 is a schematic structural diagram of still another intelligent robot disclosed in an embodiment of the present invention.
  • the embodiment of the invention discloses a greening monitoring method and an intelligent monitoring robot applied to a smart city, which can reduce the labor cost and improve the greening monitoring efficiency. The details are described below separately.
  • FIG. 1 is a schematic flowchart diagram of a greening monitoring method applied to a smart city according to an embodiment of the present invention.
  • the greening monitoring method applied to the smart city as shown in FIG. 1 may include the following steps:
  • the intelligent monitoring robot detects basic data of the target trees in the preset area, and compares the basic data with the existing data in the database to determine the tree species of the target tree; wherein the basic data includes the location data of the target tree and sample.
  • the preset area is the working area of the intelligent monitoring robot, that is, the intelligent monitoring robot can monitor all the trees in the preset area.
  • all the above trees include target trees.
  • the basic data of the target tree may include the age of the target tree in addition to the position data of the target tree and the sample data described above.
  • the age of the target trees can be measured by the intelligent monitoring robot controlling the tree growth cone.
  • the tree growth cone is a fast and reliable tool for calculating the age of trees. It can analyze the tree growth rate, the age of the trees, and the tree root samples according to the wood core samples without destroying the normal growth of the trees.
  • the degree of solidity of the trees After the intelligent monitoring robot determines the tree species of the target tree, the intelligent monitoring robot can select a tree growth cone corresponding to the tree species for the tree species.
  • the tree growth cone can use a two-thread thread drill (note that the two-thread thread drill is suitable for hard-wood trees, the two-thread thread drill can drill 8mm in one rotation) or three-thread thread Drill bit (It should be noted that the three-threaded drill bit is suitable for soft-skinned trees, and the three-threaded drill bit can be drilled into 12 mm in one rotation), which is not limited in the embodiment of the present invention; in addition, the sampling diameter of the tree growth cone can be It can be 5.15 mm or 12 mm, which is 4.35 mm, which is not limited by the embodiment of the present invention.
  • the step 101 can be performed by intelligently monitoring the detection of the basic data of the target tree and the determination of the target tree species, and the targeted maintenance of the target tree, improving the survival rate of the target tree, and also being able to pass the intelligence.
  • Monitoring robot detection instead of manual detection improves the efficiency of urban greening monitoring and reduces labor costs.
  • the intelligent monitoring robot performs electrical impedance detection on the target tree to obtain an electrical impedance tomographic image of the target tree, and determines an immediate health condition of the target tree according to the electrical impedance tomographic image; wherein the immediate health condition includes the water of the target tree.
  • the intelligent monitoring robot can perform electrical impedance detection on the target tree through a tree electrical impedance tomography diagnostic device (Tree Tronic).
  • the tree electrical impedance tomography diagnostic apparatus may comprise a plurality of electrodes (eg, ECG electrodes or EEG electrodes) and a body.
  • the tree electrical impedance tomography diagnostic device is connected to the intelligent monitoring robot, and the intelligent monitoring robot can automatically control the plurality of electrodes in the tree electrical impedance tomography diagnostic device when the intelligent monitoring robot performs electrical impedance detection on the target tree. Evenly distributed over the surface of the target tree for one week.
  • the intelligent monitoring robot can be applied to the Electrical Impedance Tomography (EIT) technology when performing electrical impedance detection on the target tree.
  • EIT Electrical Impedance Tomography
  • the intelligent monitoring robot can use the EIT technology to input a weak current on the surface of the target tree through a pair of input electrodes in the tree electrical impedance tomography diagnostic device (it is necessary that the weak current does not cause damage to the target tree), and then By measuring the voltage values on the remaining electrodes, a set of voltage values corresponding to the above weak currents is obtained; further, the intelligent monitoring robot can reconstruct the target according to the set of voltage values corresponding to the weak currents according to the EIT reconstruction algorithm.
  • the distribution of electrical impedance inside the cross section of the tree that is, the electrical impedance tomographic image of the target tree.
  • the electric impedance tomographic image of the target tree includes a low resistance indicating region indicating blue having a high water content, a red high resistance indicating region indicating a low water content, and a green and yellow resistance increasing region. Since the distribution of the resistance indication region in the electrical impedance tomography image of each tree is related to the species of the tree, the intelligent monitoring robot can determine the standard electrical impedance tomographic image of the target tree species determined in step 101 and the electrical impedance tomographic image of the target tree. A comparison is made to determine the immediate health status of the target tree.
  • step 102 can perform electrical impedance detection on the target tree to obtain an electrical impedance tomographic image of the target tree, and determine the instantaneous health status of the target tree according to the electrical impedance tomographic image, and automatically complete the electrical impedance detection work in the greening monitoring work. Improves the electrical impedance detection work.
  • the intelligent monitoring robot performs a lateral tensile test on the target tree to obtain the instantaneous stability degree of the target tree, and detects the pests of the target tree to obtain the immediate pest and disease damage degree of the target tree.
  • the intelligent monitoring robot can control the tree tensile testing device to perform lateral tensile testing on the target tree. Specifically, the intelligent monitoring robot can first control the stretching belt in the tree tensile testing device to surround the trunk of the target tree and contract the stretching belt to apply a pulling load to the trunk of the target tree; at this time, the intelligent monitoring robot can also control The elastic tester and inclinometer in the tree tensile test device measure the bark layer changes of the target trees and the degree of tilt of the trees; in turn, the intelligent monitoring robot can also change the bark layer and the inclination of the trees with standard bark changes and standard trees. The degree is compared to obtain the immediate stability of the target tree.
  • the intelligent monitoring robot can also use the acoustic resistance principle to control the pest detecting device to detect the pests and diseases of the target trees. Therefore, step 103 can improve the overall health of the target trees and improve the effect of urban greening monitoring by obtaining the immediate stability of the target trees and the degree of immediate pest and disease infestation.
  • the intelligent monitoring robot determines a preset proportion value corresponding to the tree species of the target tree, and the preset ratio value is a ratio of the preset health status level, the preset stability level, and the preset degree of pest infestation.
  • the intelligent monitoring robot may determine a preset ratio value corresponding to the tree species according to the tree species of the target tree in a preset plurality of ratio values.
  • different tree species correspond to different preset ratio values.
  • the tree species corresponds to a preset ratio value (for example, 3:3). :4)
  • the prevalence of pests and diseases will account for a greater proportion. Therefore, the step 104 can be performed to determine the preset proportion value corresponding to the tree species of the target tree, so that the comprehensive health level of the target tree calculated by the intelligent monitoring robot is more accurate, and the accuracy of the comprehensive health of the target tree is improved and improved.
  • the intelligent monitoring robot calculates the comprehensive health degree of the target tree according to the degree of immediate health condition, the degree of immediate stability, the degree of immediate pest and disease damage, and the preset ratio value.
  • step 102 may be performed before the step 103, or may be performed after the step 103, which is not limited by the embodiment of the present invention.
  • step 104 may be performed before the step 102 and the step 103, or may be performed after the step 102 and the step 103, which is not limited by the embodiment of the present invention.
  • the intelligent monitoring robot can perform targeted maintenance on the target trees by detecting the basic data of the target trees and determining the species of the target trees, thereby improving the survival rate of the target trees. It can also improve the efficiency of urban greening monitoring and reduce the labor cost by intelligent monitoring robot detection instead of manual detection.
  • the intelligent monitoring robot can obtain the electrical impedance of the target tree by performing electrical impedance detection on the target tree. Image, and determine the immediate health status of the target tree according to the electrical impedance tomographic image, automatically complete the electrical impedance detection work in the greening monitoring work, and improve the electrical impedance detection work; in addition, the intelligent monitoring robot can also obtain the immediate stability of the target tree.
  • the intelligent monitoring robot can also determine the preset proportion of the tree species of the target trees. Value, so that the comprehensive health level of the target trees calculated by the intelligent monitoring robot is more accurate, the accuracy of the comprehensive health of the target trees is improved, and the effect of urban greening monitoring is improved. Therefore, implementing the method described in FIG. 1 can reduce labor costs and improve greening monitoring efficiency.
  • FIG. 2 is a schematic flowchart diagram of another greening monitoring method applied to a smart city according to an embodiment of the present invention.
  • the greening monitoring method applied to the smart city as shown in FIG. 2 may include the following steps:
  • the intelligent monitoring robot detects basic data of the target trees in the preset area, and compares the basic data with the existing data in the database to determine the tree species of the target tree; wherein the basic data includes the location data of the target tree and sample.
  • the intelligent monitoring robot performs electrical impedance detection on the target tree to obtain an electrical impedance tomographic image of the target tree.
  • the intelligent monitoring robot controls the tree electrical impedance tomography device to perform sonication on the target tree to obtain an acoustic image; wherein the acoustic image includes a high-rate acoustic wave region of the trunk cross section and a low-speed acoustic wave region.
  • the intelligent monitoring robot can control the tree electrical impedance tomography device to perform acoustic wave tomography on trees (it should be noted that sonic wave tomography may also be referred to as ultrasonic tomography).
  • the intelligent monitoring robot can first automatically define a coordinate system of the cross section of the target tree, and automatically define two adjacent emitting surfaces and two adjacent receiving surfaces in the coordinate system (it is required that the emitting surface Not coincident with the receiving surface), multiple transmitting points (required that the transmitting point is on the transmitting surface), multiple receiving points (required that the receiving point is on the receiving surface), and the spacing between the receiving point and the receiving point .
  • the intelligent monitoring robot can fix the acoustic wave transmitting transducer in the tree electrical impedance tomography device to the first target transmitting point on the x-axis (or the y-axis), and control the first target transmitting point to emit sound waves, and So that all receiving points in the receiving surface corresponding to the emitting surface of the first target transmitting point are subjected to sound wave receiving (it is required that the transmitting-receiving test process can be analogized to a fan test); further, the intelligent monitoring robot can The acoustic emission transducer in the tree electrical impedance tomography apparatus is fixed to the second target emission point on the x-axis (or y-axis), and repeats the above-described fan-shaped test until the intelligent monitoring robot puts the above-mentioned tree electrical impedance tomography imaging device The acoustic wave transmitting transducer is fixed to the last target launching point on the x-axis (or y-axis) and the fan-shaped test is completed;
  • step 203 can be performed to perform acoustic tomography on the target tree by controlling the tree electrical impedance tomography device to obtain a high-rate acoustic wave region including a cross section of the trunk and a sound wave image of the low-rate acoustic region, so as to timely adjust and maintain the problem of the target tree.
  • the plan is to extend the life of the target trees and improve the effect of urban greening monitoring.
  • ultrasonic tomography refers to a technique of inverting an image of an internal structure of an object based on a scattered wave around the object.
  • Ultrasonic waves are widely used in biomedical engineering, non-destructive testing, geophysics and pattern recognition because they are non-ionizing radiation, harmless to humans, and inexpensive.
  • the intelligent monitoring robot determines an immediate health condition of the target tree according to the electrical impedance tomographic image; wherein the immediate health condition includes the water of the tree of the target tree.
  • the intelligent monitoring robot determines the instantaneous specific health status of the target trunk portion of the target tree.
  • the instantaneous specific health condition of the target trunk portion may be classified into healthy, mildly rotted, moderately rotted, and severely rotted and died.
  • the intelligent monitoring robot determines that the instantaneous specific health condition of the target trunk portion is healthy.
  • the intelligent monitoring robot determines that the instantaneous specific health condition of the target trunk portion is mildly rotted.
  • the intelligent monitoring robot determines that the instantaneous specific health condition of the target trunk portion is severely rotted and dies.
  • the intelligent monitoring robot determines that the instantaneous specific health condition of the target trunk portion is moderately decayed.
  • the greening monitoring method applied to the smart city includes steps 210 to 212.
  • steps 210 to 212 refer to the detailed description of steps 103 to 105 in the first embodiment, the present invention. The embodiment will not be described again.
  • the intelligent monitoring robot performs electrical impedance detection on the target tree to obtain an electrical impedance tomographic image of the target tree, which may include:
  • the intelligent monitoring robot controls the tree electrical impedance tomography device to input current into the target tree
  • the intelligent monitoring robot controls the tree electrical impedance tomography device to measure the current change in the target tree to obtain a measurement result, and obtains the measurement result in the form of an electrical impedance tomographic image; wherein the electrical impedance tomographic image includes the height of the trunk cross section of the target tree. a resistance indicating area, a low resistance indicating area, and a growth resistance indicating area; wherein, the water content of the trunk portion of the target tree corresponding to the high resistance indicating area is lower than the minimum value of the normal water content range, and the trunk portion of the target tree corresponding to the low resistance indicating area The water content is in the range of normal water content, and the water content of the trunk portion of the target tree corresponding to the growth resistance indicating area is in a changing state.
  • the implementation of the optional embodiment can measure the current change in the target tree by automatically controlling the tree electrical impedance tomography device, obtain the specific moisture content distribution in the target tree, reduce the labor cost, and improve the efficiency of urban greening monitoring.
  • the intelligent monitoring robot can perform targeted maintenance on the target trees by detecting the basic data of the target trees and determining the species of the target trees, thereby improving the survival rate of the target trees. It can also improve the efficiency of urban greening monitoring and reduce the labor cost by intelligent monitoring robot detection instead of manual detection.
  • the intelligent monitoring robot can obtain the electrical impedance of the target tree by performing electrical impedance detection on the target tree. Image, and determine the immediate health status of the target tree according to the electrical impedance tomographic image, automatically complete the electrical impedance detection work in the greening monitoring work, and improve the electrical impedance detection work; in addition, the intelligent monitoring robot can also obtain the immediate stability of the target tree.
  • the intelligent monitoring robot can also determine the preset proportion of the tree species of the target trees. Value, so that the comprehensive health level of the target trees calculated by the intelligent monitoring robot is more accurate, the accuracy of the overall health of the target trees is improved, and the effect of urban greening monitoring is improved; in addition, the intelligent monitoring robot can also control the resistance of the trees.
  • the tomographic imaging apparatus performs sonication on the target tree to obtain a high-rate acoustic wave region including the cross section of the trunk and a sound wave image of the low-rate acoustic region, so as to timely adjust the maintenance plan for the problem of the target tree, prolong the life of the target tree, and improve the city.
  • the intelligent monitoring robot can also measure the current change in the target tree by automatically controlling the tree electrical impedance tomography device, obtain the specific moisture content distribution in the target tree, reduce the labor cost, and improve the urban greening monitoring. effectiveness. Therefore, implementing the method described in FIG. 2 can further reduce labor costs and improve greening monitoring efficiency.
  • FIG. 3 is a schematic flowchart diagram of another greening monitoring method applied to a smart city according to an embodiment of the present invention.
  • the greening monitoring method applied to the smart city as shown in FIG. 3 may include the following steps:
  • the greening monitoring method applied to the smart city includes steps 301 to 312.
  • steps 301 to 312 refer to the detailed description of steps 201 to 212 in the second embodiment. The embodiment will not be described again.
  • the intelligent monitoring robot sends the detection report of the target tree to the mobile terminal of the manager; wherein the detection report includes the immediate health status of the target tree, the instantaneous stability degree, the degree of immediate pest and disease damage, basic data, and comprehensive health level.
  • the intelligent monitoring robot can send a detection report including the degree of immediate health status of the target tree, the instantaneous stability degree, the degree of immediate pest infestation, the basic data, and the comprehensive health degree to the mobile terminal of the manager, so that the management personnel can Targeted conservation of the overall health of the target trees. Therefore, step 313 can improve the convenience and timeliness of urban greening monitoring by transmitting the detection report of the target tree to the mobile terminal of the manager, and at the same time improve the efficiency of urban greening monitoring.
  • the intelligent monitoring robot performs pest and disease detection on the target tree to obtain the immediate pest and disease degree of the target tree, and may include:
  • the intelligent monitoring robot acquires a random sample of the target tree
  • the intelligent monitoring robot controls the pest detecting device to detect random samples and determine whether there are pests and diseases in the random samples;
  • the intelligent monitoring robot compares the morphology of the pests and diseases with the existing forms of pests and diseases in the database, obtains the types of pests and diseases, and transmits the types of pests and diseases to the mobile terminal.
  • the implementation of the optional embodiment can detect the pests and diseases of the target trees through the intelligent monitoring robot, and determine the types of the pests and diseases when the target trees have pests and diseases, further increasing the convenience of urban greening monitoring.
  • the intelligent monitoring robot can perform targeted maintenance on the target trees by detecting the basic data of the target trees and determining the species of the target trees, thereby improving the survival rate of the target trees. It can also improve the efficiency of urban greening monitoring and reduce the labor cost by intelligent monitoring robot detection instead of manual detection.
  • the intelligent monitoring robot can obtain the electrical impedance of the target tree by performing electrical impedance detection on the target tree. Image, and determine the immediate health status of the target tree according to the electrical impedance tomographic image, automatically complete the electrical impedance detection work in the greening monitoring work, and improve the electrical impedance detection work; in addition, the intelligent monitoring robot can also obtain the immediate stability of the target tree.
  • the intelligent monitoring robot can also determine the preset proportion of the tree species of the target trees. Value, so that the comprehensive health level of the target trees calculated by the intelligent monitoring robot is more accurate, the accuracy of the overall health of the target trees is improved, and the effect of urban greening monitoring is improved; in addition, the intelligent monitoring robot can also control the resistance of the trees.
  • the tomographic imaging apparatus performs sonication on the target tree to obtain a high-rate acoustic wave region including the cross section of the trunk and a sound wave image of the low-rate acoustic region, so as to timely adjust the maintenance plan for the problem of the target tree, prolong the life of the target tree, and improve the city.
  • the intelligent monitoring robot can also measure the current change in the target tree by automatically controlling the tree electrical impedance tomography device, obtain the specific moisture content distribution in the target tree, reduce the labor cost, and improve the urban greening monitoring.
  • the intelligent monitoring robot can also improve the convenience and timeliness of urban greening monitoring by transmitting the detection report of the target tree to the mobile terminal of the manager, and at the same time improve the efficiency of urban greening monitoring; Intelligent Monitoring robot can also be detected by the target pest trees, and when determined in the presence of the target pest species of trees of the pests and diseases, further increases the convenience of urban greening monitoring. Therefore, implementing the method described in FIG. 3 can further reduce labor costs and improve greening monitoring efficiency.
  • FIG. 4 is an intelligent monitoring robot disclosed in the embodiment of the present invention.
  • the intelligent monitoring robot is provided with a tree tensile test device, and a tensile tester is provided in the tree tensile test device.
  • the intelligent monitoring robot can control the stretching belt in the tree tensile testing device to surround the trunk of the target tree and apply a pulling load to the trunk of the target tree by contracting the stretching belt to tilt the tree toward the direction in which the intelligent monitoring robot is located.
  • the intelligent robot described in the implementation of FIG. 7 can perform a lateral tensile test on the target tree by controlling the tree tensile test device.
  • This test method can reduce labor costs and improve the efficiency of greening monitoring.
  • FIG. 5 is a schematic structural diagram of an intelligent monitoring robot according to an embodiment of the present invention.
  • the intelligent monitoring robot may include:
  • the basic data detecting unit 501 is configured to detect basic data of the target trees in the preset area, and compare the basic data with the existing data in the database to determine the tree species of the target tree; wherein the basic data includes the target trees. Location data as well as sample data.
  • the basic data detecting unit 501 determines the tree species of the target tree
  • the triggering electrical impedance detecting unit 502 determines the tree species of the target tree
  • the lateral tensile testing unit 504 the pest detecting unit 505, and the second determining unit 506 are activated.
  • the preset area is the working area of the intelligent monitoring robot, that is, the intelligent monitoring robot can monitor all the trees in the preset area.
  • all the above trees include target trees.
  • the basic data of the target tree may include the age of the target tree in addition to the position data of the target tree and the sample data described above.
  • the age of the target tree can be measured by the basic data detecting unit 501 controlling the tree growth cone (not shown in FIG. 5).
  • the tree growth cone is a fast and reliable tool for calculating the age of trees. It can analyze the tree growth rate, the age of the trees, and the tree root samples according to the wood core samples without destroying the normal growth of the trees.
  • the degree of solidity of the trees After the basic data detecting unit 501 determines the tree species of the target tree, the basic data detecting unit 501 can select a tree growth cone corresponding to the tree species for the tree species.
  • the tree growth cone can use a two-thread thread drill (note that the two-thread thread drill is suitable for hard-wood trees, the two-thread thread drill can drill 8mm in one rotation) or three-thread thread Drill bit (It should be noted that the three-threaded drill bit is suitable for soft-skinned trees, and the three-threaded drill bit can be drilled into 12 mm in one rotation), which is not limited in the embodiment of the present invention; in addition, the sampling diameter of the tree growth cone can be It can be 5.15 mm or 12 mm, which is 4.35 mm, which is not limited by the embodiment of the present invention.
  • the execution basic data detecting unit 501 can perform targeted maintenance on the target trees by detecting the basic data of the target trees and determining the species of the target trees, thereby improving the survival rate of the target trees and also being able to pass the intelligence.
  • Monitoring robot detection instead of manual detection improves the efficiency of urban greening monitoring and reduces labor costs.
  • the electrical impedance detecting unit 502 is configured to perform electrical impedance detection on the target tree to obtain an electrical impedance tomographic image of the target tree.
  • the first determining unit 503 is triggered to be activated.
  • the electrical impedance detecting unit 502 can perform electrical impedance detection on the target tree through a tree electrical impedance tomography diagnostic device (not shown in FIG. 5).
  • the tree electrical impedance tomography diagnostic apparatus may include a plurality of electrodes (eg, ECG electrodes or EEG electrodes) (not shown in FIG. 5) and a body (not shown in FIG. 5).
  • the tree electrical impedance tomography diagnostic apparatus is connected to the intelligent monitoring robot, and when the electrical impedance detecting unit 502 performs electrical impedance detection on the target tree, the electrical impedance detecting unit 502 can automatically control the tree electrical impedance tomography diagnostic apparatus.
  • the plurality of electrodes are evenly distributed over the surface of the target tree for one week.
  • the electrical impedance detecting unit 502 can apply the Electrical Impedance Tomography (EIT) technology to the electrical impedance detection of the target tree.
  • EIT Electrical Impedance Tomography
  • the electrical impedance detecting unit 502 can input a weak current on the surface of the target tree through a pair of input electrodes in the tree electrical impedance tomography diagnostic apparatus by using EIT technology (it should be noted that the weak current does not cause damage to the target tree) And measuring a voltage value on the remaining electrodes to obtain a set of voltage values corresponding to the weak current; and, the electrical impedance detecting unit 502 can perform a set of voltage values corresponding to the weak current according to the EIT reconstruction algorithm.
  • the electrical impedance distribution inside the cross section of the target tree is reconstructed, that is, the electrical impedance tomographic image of the target tree.
  • the electric impedance tomographic image of the target tree includes a low resistance indicating region indicating blue having a high water content, a red high resistance indicating region indicating a low water content, and a green and yellow resistance increasing region. Since the resistance indication region distribution in the electrical impedance tomographic image of each tree is related to the species of the tree, the electrical impedance detecting unit 502 can determine the standard electrical impedance tomographic image of the target tree species determined by the basic data detecting unit 501 and the target tree. The electrical impedance tomographic images are compared to determine the immediate health status of the target tree.
  • the performing electrical impedance detecting unit 502 can obtain an electrical impedance tomographic image of the target tree by performing electrical impedance detection on the target tree, and determine an immediate health condition of the target tree according to the electrical impedance tomographic image determined by the first determining unit 503.
  • the electrical impedance detection work in the greening monitoring work is automatically completed, and the electrical impedance detection work is improved.
  • the first determining unit 503 is configured to determine an immediate health condition of the target tree according to the electrical impedance tomography image; wherein the immediate health condition level includes the tree moisture of the target tree.
  • the lateral tensile testing unit 504 is configured to perform a lateral tensile test on the target tree to obtain an immediate stability degree of the target tree.
  • the lateral tensile testing unit 504 can control the tree tensile testing device to perform a lateral tensile test on the target tree. Specifically, the lateral tensile test unit 504 can first control the stretch band (not shown in FIG. 5) in the tree tensile test device (not shown in FIG. 5) to surround the trunk of the target tree and contract the stretch band. To apply a tensile load to the trunk of the target tree; at this time, the lateral tensile test unit 504 can also control the elastic tester (not shown in FIG. 5) and the inclinometer in the tree tensile test device (in FIG. 5).
  • the lateral tensile test unit 504 can also compare the bark layer change and the degree of tilt of the tree with the standard bark change and the standard tree tilt degree to obtain The immediate stability of the target trees.
  • the pest detection unit 505 is configured to perform pest and disease detection on the target tree to obtain an immediate degree of pest infestation of the target tree.
  • the pest detection unit 505 can control the pest and disease detection device (not shown in FIG. 5) using the principle of acoustic resistance to perform pest detection on the target tree. Therefore, the execution of the lateral tensile test unit 504 and the pest detection unit 505 can improve the overall health of the target trees by analyzing the instantaneous stability of the target trees and the degree of immediate pest and disease damage, thereby improving urban greening monitoring. effect.
  • the second determining unit 506 is configured to determine a preset proportion value corresponding to the tree species of the target tree, where the preset ratio value is a preset value of the preset health status level, the preset stability level, and the preset degree of pest infestation.
  • the second determining unit 506 may determine a preset ratio value corresponding to the tree species according to a tree species of the target tree in a preset plurality of scale values.
  • different tree species correspond to different preset ratio values.
  • the tree species corresponds to a preset ratio value (for example, 3:3). :4)
  • the prevalence of pests and diseases will account for a greater proportion. Therefore, the execution second determining unit 506 can determine the preset proportion value corresponding to the tree species of the target tree, so that the comprehensive health degree of the target tree calculated by the calculating unit 507 is more accurate, and the accuracy of the comprehensive health of the target tree is improved. Degree, improved the effect of urban greening monitoring.
  • the calculating unit 507 is configured to calculate the comprehensive health degree of the target tree according to the degree of immediate health condition, the degree of immediate stability, the degree of immediate pest and disease damage, and the preset ratio value.
  • the calculation unit 507 can determine the instantaneous health status determined by the first determining unit 503, the instantaneous stability degree determined by the lateral tensile testing unit 504, and the degree of immediate pest and disease damage determined by the pest detecting unit 505. And the preset ratio value determined by the second determining unit 506, and the comprehensive health degree of the target tree is calculated.
  • the basic data detecting unit 501 can perform targeted maintenance on the target trees and improve the target trees by detecting the basic data of the target trees and determining the varieties of the target trees.
  • the survival rate can also improve the efficiency of urban greening monitoring and reduce the labor cost by replacing the manual detection by intelligent monitoring robot detection;
  • the electrical impedance detecting unit 502 can obtain the target tree by performing electrical impedance detection on the target tree.
  • the electrical impedance tomographic image is determined according to the electrical impedance tomographic image determined by the first determining unit 503 to determine the instantaneous health status of the target tree, automatically completing the electrical impedance detection work in the greening monitoring work, and improving the electrical impedance detecting work; lateral pulling
  • the extension test unit 504 and the pest detection unit 505 can improve the overall health of the target tree by comprehensively determining the degree of immediate stability of the target tree and the degree of immediate pest and disease damage, and improve the effect of urban greening monitoring; 506 can pass The preset proportion value corresponding to the tree species of the target tree is determined, so that the comprehensive health degree of the target tree calculated by the calculation unit 507 is more accurate, the accuracy of the comprehensive health of the target tree is improved, and the effect of the urban greening monitoring is improved. Therefore, implementing the intelligent monitoring robot described in FIG. 5 can reduce labor costs and improve greening monitoring efficiency.
  • FIG. 6 is a schematic structural diagram of another intelligent monitoring robot according to an embodiment of the present invention. Among them, the intelligent monitoring robot shown in FIG. 6 is optimized by the intelligent monitoring robot shown in FIG. 5. Compared with the intelligent monitoring robot shown in FIG. 5, the intelligent monitoring robot shown in FIG. 6 may further include:
  • the control unit 508 is configured to: after the electrical impedance detecting unit 502 obtains the electrical impedance tomographic image of the target tree, control the tree electrical impedance tomography device to perform sonication on the target tree to obtain an acoustic image; wherein the acoustic image includes a cross section of the trunk High rate acoustic regions and low rate acoustic regions.
  • control unit 508 can control the tree electrical impedance tomography device to perform acoustic wave tomography on trees (it should be noted that sonic wave tomography may also be referred to as ultrasonic tomography).
  • the control unit 508 may first automatically define a coordinate system of the cross section of the target tree, and automatically define two adjacent emission surfaces and two adjacent receiving surfaces in the coordinate system (in addition, the emission surface is required) Not coincident with the receiving surface), multiple transmitting points (required that the transmitting point is on the transmitting surface), multiple receiving points (required that the receiving point is on the receiving surface), and the spacing between the receiving point and the receiving point .
  • control unit 508 can fix the acoustic wave transmitting transducer (not shown in FIG. 6) in the tree electrical impedance tomography imaging device to the first target transmitting point on the x-axis (or the y-axis), and control the first A target transmitting point emits sound waves and causes sound waves to be received at all receiving points in the receiving surface corresponding to the emitting surface where the first target transmitting point is located (it is to be noted that the transmitting-receiving test process can be analogized to a sector test); Further, the control unit 508 may fix the acoustic wave transmitting transducer in the tree electrical impedance tomography apparatus to the second target transmitting point on the x-axis (or the y-axis), and repeat the above-described sector test until the control unit 508 The acoustic wave transmitting transducer in the tree electrical impedance tomography apparatus is fixed to the last target transmitting point on the x-axis (or y-axis) and the fan
  • control processor calculates and analyzes the test result, and finally obtains a high-rate acoustic wave region including a cross section of the trunk and an acoustic wave image of the low-rate acoustic region. Therefore, the execution control unit 508 can perform sonication on the target tree by controlling the tree electrical impedance tomography device to obtain a high-rate acoustic wave region including the cross section of the trunk and a sound wave image of the low-rate acoustic region, so as to timely adjust the problem of the target tree. Maintenance programs to extend the life of target trees and improve the effectiveness of urban greening monitoring.
  • ultrasonic tomography refers to a technique of inverting an image of an internal structure of an object based on a scattered wave around the object.
  • Ultrasonic waves are widely used in biomedical engineering, non-destructive testing, geophysics and pattern recognition because they are non-ionizing radiation, harmless to humans, and inexpensive.
  • the first determining unit 503 is further configured to determine an instantaneous specific health condition level of the target trunk portion of the target tree after the first determining unit 503 determines the instantaneous health status of the target tree according to the electrical impedance tomographic image.
  • the instantaneous specific health condition of the target trunk portion may be classified into healthy, mildly rotted, moderately rotted, and severely rotted and died.
  • the first determining unit 503 is further configured to determine, when the target trunk portion of the target tree belongs to both the high-rate sound wave region and the high-resistance indicating region, the instantaneous specific health condition of the target trunk portion is healthy; when the target trunk portion of the target tree When both the high-rate acoustic wave region and the low-resistance indicating region are determined, the instantaneous specific health condition of the target trunk portion is determined to be mildly decayed; when the target trunk portion of the target tree belongs to both the low-rate sound wave region and the high-resistance indicating region, Determining the instantaneous specific health status of the target trunk portion is severely decayed and dying; when the target trunk portion of the target tree belongs to both the low-rate sonic region and the low-resistance indicating region, the instantaneous specific health status of the target trunk portion is determined to be moderate. rot.
  • the electrical impedance detecting unit 502 can include:
  • the first control subunit 5021 is configured to control the tree electrical impedance tomography device to input current into the target tree.
  • the second control subunit 5022 is triggered to be activated.
  • a second control subunit 5022 configured to control a tree electrical impedance tomography device to measure a current change in the target tree to obtain a measurement result, and obtain a measurement result expressed in the form of an electrical impedance tomographic image;
  • the electrical impedance tomographic image includes a target tree The high resistance indicating area, the low resistance indicating area and the increasing resistance indicating area of the trunk cross section; wherein, the water content of the trunk portion of the target tree corresponding to the high resistance indicating area is lower than the minimum value of the normal water content range, and the low resistance indicating area corresponds to The water content of the trunk portion of the target tree is within the normal water content, and the water content of the trunk portion of the target tree corresponding to the growth resistance indicating area is in a state of change.
  • the first control subunit 5021 and the second control subunit 5022 can measure the current change in the target tree by automatically controlling the tree electrical impedance tomography device, thereby obtaining a specific moisture content distribution in the target tree, and reducing the artificial The cost has improved the efficiency of urban greening monitoring.
  • the control unit 508 can perform sonication on the target tree by controlling the tree electrical impedance tomography device to obtain a high-rate acoustic wave region including a cross section of the trunk and a sound wave image of the low-rate acoustic region.
  • the first control subunit 5021 and the second control subunit 5022 can be measured by automatically controlling the tree electrical impedance tomography device
  • the current change in the target tree obtains the specific moisture content distribution in the target tree, reduces the labor cost, and improves the efficiency of urban greening monitoring. Therefore, implementing the intelligent monitoring robot described in FIG. 6 can further reduce labor costs and improve greening monitoring efficiency.
  • FIG. 7 is a schematic structural diagram of still another intelligent monitoring robot disclosed in an embodiment of the present invention.
  • the intelligent monitoring robot shown in FIG. 7 is optimized by the intelligent monitoring robot shown in FIG. 6.
  • the intelligent monitoring robot shown in FIG. 7 may further include:
  • the sending unit 509 is configured to send the detection report of the target tree to the calculating unit 507 after calculating the comprehensive health degree of the target tree according to the degree of immediate health condition, the degree of immediate stability, the degree of immediate pest infestation, and the preset ratio value.
  • the mobile terminal of the manager wherein the test report includes the immediate health status of the target tree, the degree of immediate stability, the degree of immediate pest infestation, basic data, and comprehensive health.
  • the sending unit 509 may send a detection report including the degree of immediate health status of the target tree, the degree of immediate stability, the degree of immediate pest infestation, the basic data, and the comprehensive health level to the mobile terminal of the manager, so that the management personnel can Targeted conservation of the overall health of the target trees. Therefore, the execution sending unit 509 can improve the convenience and timeliness of urban greening monitoring by transmitting the detection report of the target tree to the mobile terminal of the manager, and at the same time improve the efficiency of urban greening monitoring.
  • the pest detection unit 505 may include:
  • the obtaining subunit 5051 is configured to acquire a random sample of the target tree.
  • the third control subunit 5052 is configured to control the pest detecting device to detect the random sample.
  • the determining sub-unit 5053 is configured to determine whether there is a pest or disease in the random sample.
  • the comparison subunit 5054 is configured to compare the morphology of the pests and diseases with the existing pests and diseases in the database after the judgment subunit 5053 determines that there are pests and diseases in the random sample, obtain the types of the pests and diseases, and send the types of the pests and diseases. To the mobile terminal.
  • the obtaining subunit 5051, the third control subunit 5052, the judging subunit 5053, and the comparison subunit 5054 detect the pests and diseases of the target trees through the intelligent monitoring robot, and the pests and diseases are caused when the target trees have pests and diseases.
  • the types are determined to further increase the convenience of urban greening monitoring.
  • the transmitting unit 509 can improve the convenience and timeliness of urban greening monitoring by transmitting the detection report of the target tree to the mobile terminal of the manager, and at the same time, improve the urban greening.
  • the monitoring efficiency; the obtaining sub-unit 5051, the third controlling sub-unit 5052, the determining sub-unit 5053, and the comparing sub-unit 5054 detect the pests and diseases of the target trees through the intelligent monitoring robot, and when the target trees have pests and diseases, the types of the pests and diseases are Determined, further increasing the convenience of urban greening monitoring. Therefore, implementing the intelligent monitoring robot described in FIG. 7 can further reduce labor costs and improve greening monitoring efficiency.
  • FIG. 8 is a schematic structural diagram of still another intelligent monitoring robot disclosed in an embodiment of the present invention.
  • the intelligent monitoring robot may include:
  • a memory 801 storing executable program code
  • processor 802 coupled to the memory 801;
  • the processor 802 calls the executable program code stored in the memory 801, and executes any of the greening monitoring methods applied to the smart city in any of FIGS. 1 to 3.
  • the embodiment of the invention discloses a computer readable storage medium, which stores a computer program, wherein the computer program causes the computer to perform any of the greening monitoring methods applied to the smart city in any of FIGS. 1 to 3.
  • ROM Read-Only Memory
  • RAM Random Access Memory
  • PROM Programmable Read-Only Memory
  • EPROM Erasable Programmable Read Only Memory
  • OTPROM One-Time Programmable Read-Only Memory
  • EEPROM Electronically-Erasable Programmable Read-Only Memory
  • CD-ROM Compact Disc Read-Only Memory

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Abstract

一种应用于智慧城市的绿化监测方法及智能监测机器人，包括：在预设区域内，智能监测机器人可以检测目标树木的位置数据以及样本数据等基本数据，还可以检测目标树木的电阻抗并得到电阻抗断层图像以确定出目标树木的健康状况程度，还可以对目标树木进行拉伸测试以得到目标树木的稳定程度，还可以对目标树木进行病虫害检测以得到目标树木的受病虫害侵害程度。进而，智能监测机器人可以针对目标树木的树木品种将目标树木的健康状况程度、稳定程度以及受病虫害侵害程度按照预设比例计算得出目标树木的综合健康程度。实施本发明实施例，能够降低人工成本，并提高绿化监测效率。

Description

一种应用于智慧城市的绿化监测方法及智能监测机器人 技术领域
本发明涉及智慧城市技术领域，具体涉及一种应用于智慧城市的绿化监测方法及智能监测机器人。
背景技术
在众多市政建设工作中，城市的绿化监测是其中较为重要的一项工作。城市的绿化监测包括对树木进行病虫害检测以及对树木进行基本信息(例如树围、树木水分以及树木样本等)的采集。
通常，城市中的绿化监测工作需要管理人员前往绿化区域对树木的基本信息进行人工测量，以及借助一些检测设备对树木进行病虫害检测，但是这种实地进行绿化监测的方法不仅人工成本高并且绿化监测效率低。
发明内容
本发明实施例公开了一种应用于智慧城市的绿化监测方法及智能监测机器人，能够降低人工成本，并提高绿化监测效率。
本发明实施例第一方面公开了一种应用于智慧城市的绿化监测方法，所述方法包括：
智能监测机器人检测预设区域内目标树木的基本数据，并将所述基本数据与数据库中的现有数据进行比对，确定出所述目标树木的树木品种；其中，所述基本数据包括所述目标树木的位置数据以及样本数据；
所述智能监测机器人对所述目标树木进行电阻抗检测，得到所述目标树木的电阻抗断层图像，并根据所述电阻抗断层图像确定所述目标树木的即时健康状况程度；其中，所述即时健康状况程度包括所述目标树木的树木水分；
所述智能监测机器人对所述目标树木进行侧向拉伸测试，得到所述目标树木的即时稳定程度，并对所述目标树木进行病虫害检测得到所述目标树木的即时受病虫害侵害程度；
所述智能监测机器人确定所述目标树木的树木品种对应的预设比例值，所述预设比例值是预设健康状况程度、预设稳定程度以及预设受病虫害侵害程度三者的比例值；
所述智能监测机器人根据所述即时健康状况程度、所述即时稳定程度以及所述即时受病虫害侵害程度以及所述预设比例值，计算得出所述目标树木的综合健康程度。
作为一种可选的实施方式，在本发明实施例第一方面中，所述智能监测机器人对所述目标树木进行电阻抗检测，得到所述目标树木的电阻抗断层图像，包括：
所述智能监测机器人控制树木电阻抗断层成像装置向所述目标树木中输入电流；
所述智能监测机器人控制所述树木电阻抗断层成像装置测量所述目标树木中的电流变化得到测量结果，并得到以电阻抗断层图像的形式表示的所述测量结果；其中，所述电阻抗断层图像包括所述目标树木的树干横断面的高电阻指示区域、低电阻指示区域以及增长电阻指示区域；其中，所述高电阻指示区域对应的 所述目标树木的树干部分含水量低于正常含水量范围的最小值，所述低电阻指示区域对应的所述目标树木的树干部分含水量处于正常含水量范围内，所述增长电阻指示区域对应的所述目标树木的树干部分含水量处于变化状态。
作为一种可选的实施方式，在本发明实施例第一方面中，所述智能监测机器人得到所述目标树木的电阻抗断层图像之后，所述方法还包括：
所述智能监测机器人控制所述树木电阻抗断层成像装置对所述目标树木进行声波层析，得到声波图像；其中，所述声波图像包括所述树干横断面的高速率声波区域以及低速率声波区域；
所述智能监测机器人根据所述电阻抗断层图像确定所述目标树木的即时健康状况程度之后，所述方法还包括：
所述智能监测机器人确定所述目标树木的目标树干部分的即时具体健康状况程度；
若所述目标树木的目标树干部分既属于所述高速率声波区域又属于所述高电阻指示区域，所述智能监测机器人确定所述目标树干部分的即时具体健康状况程度为健康；若所述目标树木的目标树干部分既属于所述高速率声波区域又属于所述低电阻指示区域，所述智能监测机器人确定所述目标树干部分的即时具体健康状况程度为轻度腐烂；若所述目标树木的目标树干部分既属于所述低速率声波区域又属于所述高电阻指示区域，所述智能监测机器人确定所述目标树干部分的即时具体健康状况程度为重度腐烂并且死亡；若所述目标树木的目标树干部分既属于所述低速率声波区域又属于所述低电阻指示区域，所述智能监测机器人确定所述目标树干部分的即时具体健康状况程度为中度腐烂。
作为一种可选的实施方式，在本发明实施例第一方面中，所述智能监测机器人根据所述即时健康状况程度、所述即时稳定程度以及所述即时受病虫害侵害程度以及所述预设比例值，计算得出所述目标树木的综合健康程度之后，所述方法还包括：
所述智能监测机器人将所述目标树木的检测报告发送至管理人员的移动终端；其中，所述检测报告包括所述目标树木的所述即时健康状况程度、所述即时稳定程度、所述即时受病虫害侵害程度、所述基本数据以及所述综合健康程度。
作为一种可选的实施方式，在本发明实施例第一方面中，所述智能监测机器人对所述目标树木进行病虫害检测得到所述目标树木的即时受病虫害侵害程度，包括：
所述智能监测机器人获取所述目标树木的随机样本；
所述智能监测机器人控制病虫害检测装置对所述随机样本进行检测，并判断所述随机样本中是否存在病虫害；
如果是，所述智能监测机器人将所述病虫害的形态与所述数据库中现有的病虫害的形态进行比对，得到所述病虫害的种类，并将所述病虫害的种类发送至所述移动终端。
本发明实施例第二方面公开了一种智能监测机器人，所述智能监测机器人包括：
基本数据检测单元，用于检测预设区域内目标树木的基本数据，并将所述基本数据与数据库中的现有数据进行比对，确定出所述目标树木的树木品种；其中， 所述基本数据包括所述目标树木的位置数据以及样本数据；
电阻抗检测单元，用于对所述目标树木进行电阻抗检测，得到所述目标树木的电阻抗断层图像；
第一确定单元，用于根据所述电阻抗断层图像确定所述目标树木的即时健康状况程度；其中，所述即时健康状况程度包括所述目标树木的树木水分；
侧向拉伸测试单元，用于对所述目标树木进行侧向拉伸测试，得到所述目标树木的即时稳定程度
病虫害检测单元，用于对所述目标树木进行病虫害检测得到所述目标树木的即时受病虫害侵害程度；
第二确定单元，用于确定所述目标树木的树木品种对应的预设比例值，所述预设比例值是预设健康状况程度、预设稳定程度以及预设受病虫害侵害程度三者的比例值；
计算单元，用于根据所述即时健康状况程度、所述即时稳定程度以及所述即时受病虫害侵害程度以及所述预设比例值，计算得出所述目标树木的综合健康程度。
作为一种可选的实施方式，在本发明实施例第二方面中，所述电阻抗检测单元包括：
第一控制子单元，用于控制树木电阻抗断层成像装置向所述目标树木中输入电流；
第二控制子单元，用于控制所述树木电阻抗断层成像装置测量所述目标树木中的电流变化得到测量结果，并得到以电阻抗断层图像的形式表示的所述测量结果；其中，所述电阻抗断层图像包括所述目标树木的树干横断面的高电阻指示区域、低电阻指示区域以及增长电阻指示区域；其中，所述高电阻指示区域对应的所述目标树木的树干部分含水量低于正常含水量范围的最小值，所述低电阻指示区域对应的所述目标树木的树干部分含水量处于正常含水量范围内，所述增长电阻指示区域对应的所述目标树木的树干部分含水量处于变化状态。
作为一种可选的实施方式，在本发明实施例第二方面中，所述智能监测机器人还包括：
控制单元，用于在所述电阻抗检测单元得到所述目标树木的电阻抗断层图像之后，控制所述树木电阻抗断层成像装置对所述目标树木进行声波层析，得到声波图像；其中，所述声波图像包括所述树干横断面的高速率声波区域以及低速率声波区域；
所述第一确定单元，还用于在执行所述的根据所述电阻抗断层图像确定出所述目标树木的即时健康状况程度之后，确定所述目标树木的目标树干部分的即时具体健康状况程度；
所述第一确定单元，还用于当所述目标树木的目标树干部分既属于所述高速率声波区域又属于所述高电阻指示区域时，确定所述目标树干部分的即时具体健康状况程度为健康；当所述目标树木的目标树干部分既属于所述高速率声波区域又属于所述低电阻指示区域时，确定所述目标树干部分的即时具体健康状况程度为轻度腐烂；当所述目标树木的目标树干部分既属于所述低速率声波区域又属于所述高电阻指示区域时，确定所述目标树干部分的即时具体健康状况程度为重度 腐烂并且死亡；当所述目标树木的目标树干部分既属于所述低速率声波区域又属于所述低电阻指示区域时，确定所述目标树干部分的即时具体健康状况程度为中度腐烂。
作为一种可选的实施方式，在本发明实施例第二方面中，所述智能监测机器人还包括：
发送单元，用于在所述计算单元根据所述即时健康状况程度、所述即时稳定程度以及所述即时受病虫害侵害程度以及所述预设比例值，计算得出所述目标树木的综合健康程度之后，将所述目标树木的检测报告发送至管理人员的移动终端；其中，所述检测报告包括所述目标树木的所述即时健康状况程度、所述即时稳定程度、所述即时受病虫害侵害程度、所述基本数据以及所述综合健康程度。
作为一种可选的实施方式，在本发明实施例第二方面中，所述病虫害检测单元包括：
获取子单元，用于获取所述目标树木的随机样本；
第三控制子单元，用于控制病虫害检测装置对所述随机样本进行检测；
判断子单元，用于判断所述随机样本中是否存在病虫害；
比对子单元，用于在所述判断子单元判断出所述随机样本中存在病虫害之后，将所述病虫害的形态与所述数据库中现有的病虫害的形态进行比对，得到所述病虫害的种类，并将所述病虫害的种类发送至所述移动终端。
本发明实施例第三方面公开了一种智能监测机器人，包括：
存储有可执行程序代码的存储器；
与所述存储器耦合的处理器；
所述处理器调用所述存储器中存储的所述可执行程序代码，执行本发明实施例第一方面公开的应用于智慧城市的绿化监测方法。
本发明实施例第四方面公开了一种计算机可读存储介质，其存储计算机程序，其中，所述计算机程序使得计算机执行本发明实施例第一方面公开的应用于智慧城市的绿化监测方法。
本发明实施例第五方面公开了一种计算机程序产品，当所述计算机程序产品在计算机上运行时，使得所述计算机执行第一方面公开的应用于智慧城市的绿化监测方法。
与现有技术相比，本发明实施例具有以下有益效果：
本发明实施例中，在预设区域内，智能监测机器人可以检测目标树木的位置数据以及样本数据等基本数据，还可以检测目标树木的电阻抗并得到电阻抗断层图像以确定出目标树木的健康状况程度，还可以对目标树木进行拉伸测试以得到目标树木的稳定程度，还可以对目标树木进行病虫害检测以得到目标树木的受病虫害侵害程度。进而，智能监测机器人可以针对目标树木的树木品种将目标树木的健康状况程度、稳定程度以及受病虫害侵害程度按照预设比例计算得出目标树木的综合健康程度。综上所述，实施本发明实施例，能够通过对预设区域内树木的自动监测，降低人工成本并且提高绿化监测效率。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实 施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1是本发明实施例公开的一种应用于智慧城市的绿化监测方法的流程示意图；
图2是本发明实施例公开的另一种应用于智慧城市的绿化监测方法的流程示意图；
图3是本发明实施例公开的又一种应用于智慧城市的绿化监测方法的流程示意图；
图4是本发明实施例公开的一种智能监测机器人对目标树木进行侧向拉伸测试的场景示意图；
图5是本发明实施例公开的一种智能监测机器人的结构示意图；
图6是本发明实施例公开的另一种智能监测机器人的结构示意图；
图7是本发明实施例公开的又一种智能监测机器人的结构示意图；
图8是本发明实施例公开的又一种智能机器人的结构示意图。
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，所描述的实施例仅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。
需要说明的是，本发明实施例及附图中的术语“包括”和“具有”以及它们任何变形，意图在于覆盖不排他的包含。例如包含了一系列步骤或单元的过程、方法、系统、产品或设备没有限定于已列出的步骤或单元，而是可选地还包括没有列出的步骤或单元，或可选地还包括对于这些过程、方法、产品或设备固有的其它步骤或单元。
本发明实施例公开了一种应用于智慧城市的绿化监测方法及智能监测机器人，能够降低人工成本，并提高绿化监测效率。以下分别进行详细说明。
实施例一
请参阅图1，图1是本发明实施例公开的一种应用于智慧城市的绿化监测方法的流程示意图。如图1所示该应用于智慧城市的绿化监测方法可以包括以下步骤：
101、智能监测机器人检测预设区域内目标树木的基本数据，并将基本数据与数据库中的现有数据进行比对，确定出目标树木的树木品种；其中，基本数据包括目标树木的位置数据以及样本数据。
本发明实施例中，预设区域为智能监测机器人的工作区域，即智能监测机器人可以对预设区域内的所有树木实施监测。其中，上述所有树木包括目标树木。另外，目标树木的基本数据除了包括上述的目标树木的位置数据以及样本数据之外，还可以包括目标树木的树龄。其中，目标树木的树龄可以由智能监测机器人控制树木生长锥进行测量。树木生长锥是一种快速可靠的计算树木年龄的工具，可以在不破坏树木正常生长的情况下，通过钻取树木木芯样本以及根据该树木木芯样本来分析确定树木生长速率、树木年龄、树木生长坚实程度、树木深层角质化程度、树木生长环境污染情况以及营养物质运移情况。在该智能监测机器人确定出目标树木的树木品种之后，该智能监测机器人可以针对该树木品种选择出与该树木品种对应的树木生长锥。其中，树木生长锥可以使用两线螺纹式钻头(需要说明的是，两线螺纹式钻头适用于质地较硬的树木，该两线螺纹式钻头旋转一圈可钻入8mm)也可以使用三线螺纹式钻头(需要说明的是，三线螺纹式钻头适 用于质地较软的树木，该三线螺纹式钻头旋转一圈可钻入12mm)，本发明实施例不作限定；此外，树木生长锥的取样直径可以为4.35mm也可以为5.15mm也可以为12mm，本发明实施例不作限定。所以，执行步骤101能够通过智能监测机器人对目标树木的基本数据的检测以及对目标树木的品种的确定，有针对性的对目标树木实施养护，提高了目标树木的存活率，还能够通过由智能监测机器人检测代替人工检测，提高了对城市绿化监测的效率，并且降低了人工成本。
102、智能监测机器人对目标树木进行电阻抗检测，得到目标树木的电阻抗断层图像，并根据电阻抗断层图像确定目标树木的即时健康状况程度；其中，即时健康状况程度包括目标树木的树木水分。
本发明实施例中，智能监测机器人可以通过树木电阻抗断层成像诊断装置(Tree Tronic)对目标树木进行电阻抗检测。其中，树木电阻抗断层成像诊断装置可以包含多个电极(例如，ECG电极或EEG电极)以及主体。另外，该树木电阻抗断层成像诊断装置与智能监测机器人相连，并且，在智能监测机器人对目标树木进行电阻抗检测时，智能监测机器人可以自动控制该树木电阻抗断层成像诊断装置中的多个电极均匀分布于目标树木的表面一周。
本发明实施例中，智能监测机器人对目标树木进行电阻抗检测时可以应用到生物电阻抗断层成像(Electrical Impedance Tomography，EIT)技术。首先，智能监测机器人可以利用EIT技术通过树木电阻抗断层成像诊断装置中的一对输入电极在目标树木的表面输入微弱电流(需要说明的是，该微弱电流不会对目标树木造成损伤)，再通过测量其余电极上的电压值，得到与上述微弱电流相对应的一组电压值；进而，智能监测机器人可以根据EIT重构算法根据上述与上述微弱电流相对应的一组电压值重构出目标树木横断面内部的电阻抗分布，即目标树木的电阻抗断层图像。
本发明实施例中，在目标树木的电阻抗断层图像中包括表示含水量高的蓝色的低电阻指示区域、表示含水量低的红色的高电阻指示区域以及绿色和黄色的电阻增长区域。由于每一种树木的电阻抗断层图像中电阻指示区域分布与该树木的品种有关，智能监测机器人可以将步骤101确定出的目标树木品种的标准电阻抗断层图像与该目标树木的电阻抗断层图像进行比对，确定出该目标树木的即时健康状况程度。所以，执行步骤102能够通过对目标树木进行电阻抗检测，得到目标树木的电阻抗断层图像，并根据电阻抗断层图像确定目标树木的即时健康状况程度，自动完成绿化监测工作中的电阻抗检测工作，提高了电阻抗检测工作。
103、智能监测机器人对目标树木进行侧向拉伸测试，得到目标树木的即时稳定程度，并对目标树木进行病虫害检测得到目标树木的即时受病虫害侵害程度。
本发明实施例中，智能监测机器人可以控制树木拉伸测试装置对目标树木进行侧向拉伸测试。具体地，智能监测机器人首先可以控制树木拉伸测试装置中的拉伸带环绕目标树木的树干并收缩上述拉伸带，以向目标树木的树干施加拉力负荷；此时，智能监测机器人还可以控制树木拉伸测试装置中的弹性测试器和测斜仪测量目标树木的树皮层变化以及树木倾斜程度；进而，智能监测机器人还可以将树皮层变化以及树木倾斜程度与标准树皮变化以及标准树木倾斜程度进行比对，得到目标树木的即时稳定程度。
本发明实施例中，智能监测机器人还可以利用声波电阻原理控制病虫害检测装置对目标树木进行病虫害检测。所以，执行步骤103能够通过得到目标树木的 即时稳定程度以及即时受病虫害侵害程度，以便更全面的对目标树木的综合健康程度进行分析，改善城市绿化监测的效果。
104、智能监测机器人确定目标树木的树木品种对应的预设比例值，预设比例值是预设健康状况程度、预设稳定程度以及预设受病虫害侵害程度三者的比例值。
本发明实施例中，智能监测机器人可以根据目标树木的树木品种在预设的多个比例值中确定出与该树木品种对应的预设比例值。其中，不同的树木品种对应不同的预设比例值，举例来说，当该树木品种相比其他树木品种属于更容易受到病虫害的侵害时，该树木品种对应的预设比例值(例如3：3：4)中预设受病虫害侵害程度则会占更大的比重。所以，执行步骤104能够通过确定目标树木的树木品种对应的预设比例值，以便智能监测机器人计算得出的目标树木的综合健康程度更为准确，提高了目标树木综合健康程度的精准度，改善了城市绿化监测的效果。
105、智能监测机器人根据即时健康状况程度、即时稳定程度以及即时受病虫害侵害程度以及预设比例值，计算得出目标树木的综合健康程度。
需要说明的是，步骤102可以在步骤103之前执行，也可以在步骤103之后执行，本发明实施例不作限定。还需要说明的是，步骤104可以在步骤102和步骤103之前执行，也可以在步骤102和步骤103之后执行，本发明实施例不作限定。
可见，实施图1所描述的方法，智能监测机器人能够通过对目标树木的基本数据的检测以及对目标树木的品种的确定，有针对性的对目标树木实施养护，提高了目标树木的存活率，还能够通过由智能监测机器人检测代替人工检测，提高了对城市绿化监测的效率，并且降低了人工成本；此外，智能监测机器人还能够通过对目标树木进行电阻抗检测，得到目标树木的电阻抗断层图像，并根据电阻抗断层图像确定目标树木的即时健康状况程度，自动完成绿化监测工作中的电阻抗检测工作，提高了电阻抗检测工作；此外，智能监测机器人还能够通过得到目标树木的即时稳定程度以及即时受病虫害侵害程度，以便更全面的对目标树木的综合健康程度进行分析，改善城市绿化监测的效果；此外，智能监测机器人还能够通过确定目标树木的树木品种对应的预设比例值，以便智能监测机器人计算得出的目标树木的综合健康程度更为准确，提高了目标树木综合健康程度的精准度，改善了城市绿化监测的效果。所以，实施图1所描述的方法能够降低人工成本，并提高绿化监测效率。
实施例二
请参阅图2，图2是本发明实施例公开的另一种应用于智慧城市的绿化监测方法的流程示意图。如图2所示该应用于智慧城市的绿化监测方法可以包括以下步骤：
201、智能监测机器人检测预设区域内目标树木的基本数据，并将基本数据与数据库中的现有数据进行比对，确定出目标树木的树木品种；其中，基本数据包括目标树木的位置数据以及样本数据。
202、智能监测机器人对目标树木进行电阻抗检测，得到目标树木的电阻抗断层图像。
203、智能监测机器人控制树木电阻抗断层成像装置对目标树木进行声波层析，得到声波图像；其中，声波图像包括树干横断面的高速率声波区域以及低速 率声波区域。
本发明实施例中，智能监测机器人能够控制树木电阻抗断层成像装置对树木进行声波层析(需要说明的是，声波层析也可以称为超声波层析)。具体地，智能监测机器人首先可以自动定义目标树木的横截面的坐标系，并在该坐标系中自动定义两个相邻的发射面、两个相邻的接收面(需要说明的是，发射面与接收面不重合)、多个发射点(需要说明的是，发射点处于发射面上)、多个接收点(需要说明的是，接收点处于接收面上)以及接收点和接收点的间距。进而，智能监测机器人可以将上述树木电阻抗断层成像装置中的声波发射换能器固定在x轴(或者y轴)上的第一目标发射点，并控制该第一目标发射点发射声波，并使得与第一目标发射点所在发射面对应的接受面中所有接收点进行声波接收(需要说明的是，该发射-接收的测试过程可类比为扇形测试)；进而，智能监测机器人可以把上述树木电阻抗断层成像装置中的声波发射换能器固定在x轴(或者y轴)上的第二目标发射点，并重复上述扇形测试，直到智能监测机器人把上述树木电阻抗断层成像装置中的声波发射换能器固定在x轴(或者y轴)上的最后一个目标发射点，并完成扇形测试为止；智能监测机器人还可以采集上述所有扇形测试的测试结果，并控制处理器将该测试结果进行计算分析，最终得到包括树干横断面的高速率声波区域以及低速率声波区域声波图像。所以，执行步骤203能够通过控制树木电阻抗断层成像装置对目标树木进行声波层析，得到包括树干横断面的高速率声波区域以及低速率声波区域声波图像，以便及时针对目标树木出现的问题调整养护方案，延长目标树木的寿命，改善城市绿化监测的效果。
本发明实施例中，超声层析成像(超声CT)是指根据物体周围的散射波反演物体内部结构图像的技术。由于超声波具有无电离辐射、对人体无害、设备价格便宜等特点，广泛应用于生物医学工程、无损检测、地球物理以及模式识别等领域。
204、智能监测机器人根据电阻抗断层图像确定目标树木的即时健康状况程度；其中，即时健康状况程度包括目标树木的树木水分。
205、智能监测机器人确定目标树木的目标树干部分的即时具体健康状况程度。
本发明实施例中，目标树干部分的即时具体健康状况程度可以为分为健康、轻度腐烂、中度腐烂以及重度腐烂并且死亡。
206、当目标树木的目标树干部分既属于高速率声波区域又属于高电阻指示区域时，智能监测机器人确定目标树干部分的即时具体健康状况程度为健康。
207、当目标树木的目标树干部分既属于高速率声波区域又属于低电阻指示区域时，智能监测机器人确定目标树干部分的即时具体健康状况程度为轻度腐烂。
208、当目标树木的目标树干部分既属于低速率声波区域又属于高电阻指示区域时，智能监测机器人确定目标树干部分的即时具体健康状况程度为重度腐烂并且死亡。
209、当目标树木的目标树干部分既属于低速率声波区域又属于低电阻指示区域时，智能监测机器人确定目标树干部分的即时具体健康状况程度为中度腐烂。
在本发明实施例中，该应用于智慧城市的绿化监测方法包括步骤210～步骤 212，针对步骤210～步骤212的描述，请参照实施例一中针对步骤103～步骤105的详细描述，本发明实施例不再赘述。
作为一种可选的实施例，在该应用于智慧城市的绿化监测方法中，智能监测机器人对目标树木进行电阻抗检测，得到目标树木的电阻抗断层图像，可以包括：
智能监测机器人控制树木电阻抗断层成像装置向目标树木中输入电流；
智能监测机器人控制树木电阻抗断层成像装置测量目标树木中的电流变化得到测量结果，并得到以电阻抗断层图像的形式表示的测量结果；其中，电阻抗断层图像包括目标树木的树干横断面的高电阻指示区域、低电阻指示区域以及增长电阻指示区域；其中，高电阻指示区域对应的目标树木的树干部分含水量低于正常含水量范围的最小值，低电阻指示区域对应的目标树木的树干部分含水量处于正常含水量范围内，增长电阻指示区域对应的目标树木的树干部分含水量处于变化状态。
可见，实施该可选的实施例能够通过自动控制树木电阻抗断层成像装置测量目标树木中的电流变化，得到目标树木中具体的水分含量分布，降低了人工成本，提高了城市绿化监测的效率。
可见，实施图2所描述的方法，智能监测机器人能够通过对目标树木的基本数据的检测以及对目标树木的品种的确定，有针对性的对目标树木实施养护，提高了目标树木的存活率，还能够通过由智能监测机器人检测代替人工检测，提高了对城市绿化监测的效率，并且降低了人工成本；此外，智能监测机器人还能够通过对目标树木进行电阻抗检测，得到目标树木的电阻抗断层图像，并根据电阻抗断层图像确定目标树木的即时健康状况程度，自动完成绿化监测工作中的电阻抗检测工作，提高了电阻抗检测工作；此外，智能监测机器人还能够通过得到目标树木的即时稳定程度以及即时受病虫害侵害程度，以便更全面的对目标树木的综合健康程度进行分析，改善城市绿化监测的效果；此外，智能监测机器人还能够通过确定目标树木的树木品种对应的预设比例值，以便智能监测机器人计算得出的目标树木的综合健康程度更为准确，提高了目标树木综合健康程度的精准度，改善了城市绿化监测的效果；此外，智能监测机器人还能够通过控制树木电阻抗断层成像装置对目标树木进行声波层析，得到包括树干横断面的高速率声波区域以及低速率声波区域声波图像，以便及时针对目标树木出现的问题调整养护方案，延长目标树木的寿命，改善城市绿化监测的效果；此外，智能监测机器人还能够通过自动控制树木电阻抗断层成像装置测量目标树木中的电流变化，得到目标树木中具体的水分含量分布，降低了人工成本，提高了城市绿化监测的效率。所以，实施图2所描述的方法能够进一步降低人工成本，并提高绿化监测效率。
实施例三
请参阅图3，图3是本发明实施例公开的又一种应用于智慧城市的绿化监测方法的流程示意图。如图3所示该应用于智慧城市的绿化监测方法可以包括以下步骤：
在本发明实施例中，该应用于智慧城市的绿化监测方法包括步骤301～步骤312，针对步骤301～步骤312的描述，请参照实施例二中针对步骤201～步骤212的详细描述，本发明实施例不再赘述。
313、智能监测机器人将目标树木的检测报告发送至管理人员的移动终端；其中，检测报告包括目标树木的即时健康状况程度、即时稳定程度、即时受病虫害侵害程度、基本数据以及综合健康程度。
本发明实施例中，智能监测机器人可以将包含目标树木即时健康状况程度、 即时稳定程度、即时受病虫害侵害程度、基本数据以及综合健康程度的检测报告发送至管理人员的移动终端，以便管理人员针对目标树木的综合健康程度进行有针对性的养护。所以，执行步骤313能够通过将目标树木的检测报告发送至管理人员的移动终端，提高了城市绿化监测的便捷性和及时性，与此同时提高了城市绿化监测效率。
作为一种可选的实施例，在该应用于智慧城市的绿化监测方法中，智能监测机器人对目标树木进行病虫害检测得到目标树木的即时受病虫害侵害程度，可以包括：
智能监测机器人获取目标树木的随机样本；
智能监测机器人控制病虫害检测装置对随机样本进行检测，并判断随机样本中是否存在病虫害；
如果是，智能监测机器人将病虫害的形态与数据库中现有的病虫害的形态进行比对，得到病虫害的种类，并将病虫害的种类发送至移动终端。
可见，实施该可选的实施例，能够通过智能监测机器人对目标树木进行病虫害的检测，并且当目标树木存在病虫害时对该病虫害的种类进行确定，更进一步的增加了城市绿化监测的便捷性。
可见，实施图3所描述的方法，智能监测机器人能够通过对目标树木的基本数据的检测以及对目标树木的品种的确定，有针对性的对目标树木实施养护，提高了目标树木的存活率，还能够通过由智能监测机器人检测代替人工检测，提高了对城市绿化监测的效率，并且降低了人工成本；此外，智能监测机器人还能够通过对目标树木进行电阻抗检测，得到目标树木的电阻抗断层图像，并根据电阻抗断层图像确定目标树木的即时健康状况程度，自动完成绿化监测工作中的电阻抗检测工作，提高了电阻抗检测工作；此外，智能监测机器人还能够通过得到目标树木的即时稳定程度以及即时受病虫害侵害程度，以便更全面的对目标树木的综合健康程度进行分析，改善城市绿化监测的效果；此外，智能监测机器人还能够通过确定目标树木的树木品种对应的预设比例值，以便智能监测机器人计算得出的目标树木的综合健康程度更为准确，提高了目标树木综合健康程度的精准度，改善了城市绿化监测的效果；此外，智能监测机器人还能够通过控制树木电阻抗断层成像装置对目标树木进行声波层析，得到包括树干横断面的高速率声波区域以及低速率声波区域声波图像，以便及时针对目标树木出现的问题调整养护方案，延长目标树木的寿命，改善城市绿化监测的效果；此外，智能监测机器人还能够通过自动控制树木电阻抗断层成像装置测量目标树木中的电流变化，得到目标树木中具体的水分含量分布，降低了人工成本，提高了城市绿化监测的效率；此外，智能监测机器人还能够通过将目标树木的检测报告发送至管理人员的移动终端，提高了城市绿化监测的便捷性和及时性，与此同时提高了城市绿化监测效率；此外，智能监测机器人还能够通过对目标树木进行病虫害的检测，并且当目标树木存在病虫害时对该病虫害的种类进行确定，更进一步的增加了城市绿化监测的便捷性。所以，实施图3所描述的方法能够更进一步降低人工成本，并提高绿化监测效率。
其中，图1～3所描述的智能监测机器人对目标树木进行侧向拉伸测试的场景可以如图4所示，图4是本发明实施例公开的一种智能监测机器人对目标树木进行侧向拉伸测试的场景示意图。如图7所示，智能监测机器人中设置有树木拉伸测试装置，并且树木拉伸测试装置中设置有拉伸带。智能监测机器人可以控制树木拉伸测试装置中的拉伸带环绕目标树木的树干并通过收缩上述拉伸带向目标 树木的树干施加拉力负荷，以使得树木朝智能监测机器人所在的方向倾斜。
可见，实施图7所描述的智能机器人能够通过对树木拉伸测试装置的控制，对目标树木进行侧向拉伸测试。此测试方法能够降低人工成本，并提高绿化监测效率。
实施例四
请参阅图5，图5是本发明实施例公开的一种智能监测机器人的结构示意图。如图5所示，该智能监测机器人可以包括：
基本数据检测单元501，用于检测预设区域内目标树木的基本数据，并将基本数据与数据库中的现有数据进行比对，确定出目标树木的树木品种；其中，基本数据包括目标树木的位置数据以及样本数据。
本发明实施例中，在基本数据检测单元501确定出目标树木的树木品种之后，触发电阻抗检测单元502、侧向拉伸测试单元504、病虫害检测单元505以及第二确定单元506启动。
本发明实施例中，预设区域为智能监测机器人的工作区域，即智能监测机器人可以对预设区域内的所有树木实施监测。其中，上述所有树木包括目标树木。另外，目标树木的基本数据除了包括上述的目标树木的位置数据以及样本数据之外，还可以包括目标树木的树龄。其中，目标树木的树龄可以由基本数据检测单元501控制树木生长锥(在图5中未画出)进行测量。树木生长锥是一种快速可靠的计算树木年龄的工具，可以在不破坏树木正常生长的情况下，通过钻取树木木芯样本以及根据该树木木芯样本来分析确定树木生长速率、树木年龄、树木生长坚实程度、树木深层角质化程度、树木生长环境污染情况以及营养物质运移情况。在该基本数据检测单元501确定出目标树木的树木品种之后，该基本数据检测单元501可以针对该树木品种选择出与该树木品种对应的树木生长锥。其中，树木生长锥可以使用两线螺纹式钻头(需要说明的是，两线螺纹式钻头适用于质地较硬的树木，该两线螺纹式钻头旋转一圈可钻入8mm)也可以使用三线螺纹式钻头(需要说明的是，三线螺纹式钻头适用于质地较软的树木，该三线螺纹式钻头旋转一圈可钻入12mm)，本发明实施例不作限定；此外，树木生长锥的取样直径可以为4.35mm也可以为5.15mm也可以为12mm，本发明实施例不作限定。所以，执行基本数据检测单元501能够通过对目标树木的基本数据的检测以及对目标树木的品种的确定，有针对性的对目标树木实施养护，提高了目标树木的存活率，还能够通过由智能监测机器人检测代替人工检测，提高了对城市绿化监测的效率，并且降低了人工成本。
电阻抗检测单元502，用于对目标树木进行电阻抗检测，得到目标树木的电阻抗断层图像。
本发明实施例中，在电阻抗检测单元502得到目标树木的电阻抗断层图像之后，触发第一确定单元503启动。
本发明实施例中，电阻抗检测单元502可以通过树木电阻抗断层成像诊断装置(Tree Tronic)(图5中未画出)对目标树木进行电阻抗检测。其中，树木电阻抗断层成像诊断装置可以包含多个电极(例如，ECG电极或EEG电极)(图5中未画出)以及主体(图5中未画出)。另外，该树木电阻抗断层成像诊断装置与智能监测机器人相连，并且，在电阻抗检测单元502对目标树木进行电阻抗检测时，电阻抗检测单元502可以自动控制该树木电阻抗断层成像诊断装置中的多个电极均匀分布于目标树木的表面一周。
本发明实施例中，电阻抗检测单元502对目标树木进行电阻抗检测时可以应 用到生物电阻抗断层成像(Electrical Impedance Tomography，EIT)技术。首先，电阻抗检测单元502可以利用EIT技术通过树木电阻抗断层成像诊断装置中的一对输入电极在目标树木的表面输入微弱电流(需要说明的是，该微弱电流不会对目标树木造成损伤)，再通过测量其余电极上的电压值，得到与上述微弱电流相对应的一组电压值；进而，电阻抗检测单元502可以根据EIT重构算法根据上述与上述微弱电流相对应的一组电压值重构出目标树木横断面内部的电阻抗分布，即目标树木的电阻抗断层图像。
本发明实施例中，在目标树木的电阻抗断层图像中包括表示含水量高的蓝色的低电阻指示区域、表示含水量低的红色的高电阻指示区域以及绿色和黄色的电阻增长区域。由于每一种树木的电阻抗断层图像中电阻指示区域分布与该树木的品种有关，电阻抗检测单元502可以将基本数据检测单元501确定出的目标树木品种的标准电阻抗断层图像与该目标树木的电阻抗断层图像进行比对，确定出该目标树木的即时健康状况程度。所以，执行电阻抗检测单元502能够通过对目标树木进行电阻抗检测，得到目标树木的电阻抗断层图像，并根据第一确定单元503确定出的电阻抗断层图像确定目标树木的即时健康状况程度，自动完成绿化监测工作中的电阻抗检测工作，提高了电阻抗检测工作。
第一确定单元503，用于根据电阻抗断层图像确定目标树木的即时健康状况程度；其中，即时健康状况程度包括目标树木的树木水分。
侧向拉伸测试单元504，用于对目标树木进行侧向拉伸测试，得到目标树木的即时稳定程度。
本发明实施例中，侧向拉伸测试单元504可以控制树木拉伸测试装置对目标树木进行侧向拉伸测试。具体地，侧向拉伸测试单元504首先可以控制树木拉伸测试装置(图5中未画出)中的拉伸带(图5中未画出)环绕目标树木的树干并收缩上述拉伸带，以向目标树木的树干施加拉力负荷；此时，侧向拉伸测试单元504还可以控制树木拉伸测试装置中的弹性测试器(图5中未画出)和测斜仪(图5中未画出)测量目标树木的树皮层变化以及树木倾斜程度；进而，侧向拉伸测试单元504还可以将树皮层变化以及树木倾斜程度与标准树皮变化以及标准树木倾斜程度进行比对，得到目标树木的即时稳定程度。
病虫害检测单元505，用于对目标树木进行病虫害检测得到目标树木的即时受病虫害侵害程度。
本发明实施例中，病虫害检测单元505可以利用声波电阻原理控制病虫害检测装置(图5中未画出)对目标树木进行病虫害检测。所以，执行侧向拉伸测试单元504和病虫害检测单元505能够通过得到目标树木的即时稳定程度以及即时受病虫害侵害程度，以便更全面的对目标树木的综合健康程度进行分析，改善城市绿化监测的效果。
第二确定单元506，用于确定目标树木的树木品种对应的预设比例值，预设比例值是预设健康状况程度、预设稳定程度以及预设受病虫害侵害程度三者的比例值。
本发明实施例中，第二确定单元506可以根据目标树木的树木品种在预设的多个比例值中确定出与该树木品种对应的预设比例值。其中，不同的树木品种对应不同的预设比例值，举例来说，当该树木品种相比其他树木品种属于更容易受到病虫害的侵害时，该树木品种对应的预设比例值(例如3：3：4)中预设受病虫害侵害程度则会占更大的比重。所以，执行第二确定单元506能够通过确定目 标树木的树木品种对应的预设比例值，以便计算单元507计算得出的目标树木的综合健康程度更为准确，提高了目标树木综合健康程度的精准度，改善了城市绿化监测的效果。
计算单元507，用于根据即时健康状况程度、即时稳定程度以及即时受病虫害侵害程度以及预设比例值，计算得出目标树木的综合健康程度。
本发明实施例中，计算单元507能够根据第一确定单元503确定出的即时健康状况程度、侧向拉伸测试单元504确定出的即时稳定程度、病虫害检测单元505确定出的即时受病虫害侵害程度以及第二确定单元506确定出的预设比例值，计算得出目标树木的综合健康程度。
可见，实施图5所描述的智能监测机器人，基本数据检测单元501能够通过对目标树木的基本数据的检测以及对目标树木的品种的确定，有针对性的对目标树木实施养护，提高了目标树木的存活率，还能够通过由智能监测机器人检测代替人工检测，提高了对城市绿化监测的效率，并且降低了人工成本；电阻抗检测单元502能够通过对目标树木进行电阻抗检测，得到目标树木的电阻抗断层图像，并根据第一确定单元503确定出的电阻抗断层图像确定目标树木的即时健康状况程度，自动完成绿化监测工作中的电阻抗检测工作，提高了电阻抗检测工作；侧向拉伸测试单元504和病虫害检测单元505能够通过得到目标树木的即时稳定程度以及即时受病虫害侵害程度，以便更全面的对目标树木的综合健康程度进行分析，改善城市绿化监测的效果；第二确定单元506能够通过确定目标树木的树木品种对应的预设比例值，以便计算单元507计算得出的目标树木的综合健康程度更为准确，提高了目标树木综合健康程度的精准度，改善了城市绿化监测的效果。所以，实施图5所描述的智能监测机器人能够降低人工成本，并提高绿化监测效率。
实施例五
请参阅图6，图6是本发明实施例公开的另一种智能监测机器人的结构示意图。其中，图6所示的智能监测机器人是由图5所示的智能监测机器人进行优化得到的。与图5所示的智能监测机器人相比较，图6所示的智能监测机器人还可以包括：
控制单元508，用于在电阻抗检测单元502得到目标树木的电阻抗断层图像之后，控制树木电阻抗断层成像装置对目标树木进行声波层析，得到声波图像；其中，声波图像包括树干横断面的高速率声波区域以及低速率声波区域。
本发明实施例中，控制单元508能够控制树木电阻抗断层成像装置对树木进行声波层析(需要说明的是，声波层析也可以称为超声波层析)。具体地，控制单元508首先可以自动定义目标树木的横截面的坐标系，并在该坐标系中自动定义两个相邻的发射面、两个相邻的接收面(需要说明的是，发射面与接收面不重合)、多个发射点(需要说明的是，发射点处于发射面上)、多个接收点(需要说明的是，接收点处于接收面上)以及接收点和接收点的间距。进而，控制单元508可以将上述树木电阻抗断层成像装置中的声波发射换能器(图6中未画出)固定在x轴(或者y轴)上的第一目标发射点，并控制该第一目标发射点发射声波，并使得与第一目标发射点所在发射面对应的接受面中所有接收点进行声波接收(需要说明的是，该发射-接收的测试过程可类比为扇形测试)；进而，控制单元508可以把上述树木电阻抗断层成像装置中的声波发射换能器固定在x轴(或者y轴)上的第二目标发射点，并重复上述扇形测试，直到控制单元508把上述树木电阻抗断层成像装置中的声波发射换能器固定在x轴(或者y轴)上的最后一 个目标发射点，并完成扇形测试为止；控制单元508还可以采集上述所有扇形测试的测试结果，并控制处理器将该测试结果进行计算分析，最终得到包括树干横断面的高速率声波区域以及低速率声波区域声波图像。所以，执行控制单元508能够通过控制树木电阻抗断层成像装置对目标树木进行声波层析，得到包括树干横断面的高速率声波区域以及低速率声波区域声波图像，以便及时针对目标树木出现的问题调整养护方案，延长目标树木的寿命，改善城市绿化监测的效果。
本发明实施例中，超声层析成像(超声CT)是指根据物体周围的散射波反演物体内部结构图像的技术。由于超声波具有无电离辐射、对人体无害、设备价格便宜等特点，广泛应用于生物医学工程、无损检测、地球物理以及模式识别等领域。
第一确定单元503，还用于在第一确定单元503根据电阻抗断层图像确定出目标树木的即时健康状况程度之后，确定目标树木的目标树干部分的即时具体健康状况程度。
本发明实施例中，目标树干部分的即时具体健康状况程度可以为分为健康、轻度腐烂、中度腐烂以及重度腐烂并且死亡。
第一确定单元503，还用于当目标树木的目标树干部分既属于高速率声波区域又属于高电阻指示区域时，确定目标树干部分的即时具体健康状况程度为健康；当目标树木的目标树干部分既属于高速率声波区域又属于低电阻指示区域时，确定目标树干部分的即时具体健康状况程度为轻度腐烂；当目标树木的目标树干部分既属于低速率声波区域又属于高电阻指示区域时，确定目标树干部分的即时具体健康状况程度为重度腐烂并且死亡；当目标树木的目标树干部分既属于低速率声波区域又属于低电阻指示区域时，确定目标树干部分的即时具体健康状况程度为中度腐烂。
电阻抗检测单元502，可以包括：
第一控制子单元5021，用于控制树木电阻抗断层成像装置向目标树木中输入电流。
本发明实施例中，在第一控制子单元5021控制树木电阻抗断层成像装置向目标树木中输入电流之后，触发第二控制子单元5022启动。
第二控制子单元5022，用于控制树木电阻抗断层成像装置测量目标树木中的电流变化得到测量结果，并得到以电阻抗断层图像的形式表示的测量结果；其中，电阻抗断层图像包括目标树木的树干横断面的高电阻指示区域、低电阻指示区域以及增长电阻指示区域；其中，高电阻指示区域对应的目标树木的树干部分含水量低于正常含水量范围的最小值，低电阻指示区域对应的目标树木的树干部分含水量处于正常含水量范围内，增长电阻指示区域对应的目标树木的树干部分含水量处于变化状态。
本发明实施例中，第一控制子单元5021和第二控制子单元5022可以通过自动控制树木电阻抗断层成像装置测量目标树木中的电流变化，得到目标树木中具体的水分含量分布，降低了人工成本，提高了城市绿化监测的效率。
可见，实施图6所描述的智能监测机器人中，控制单元508能够通过控制树木电阻抗断层成像装置对目标树木进行声波层析，得到包括树干横断面的高速率声波区域以及低速率声波区域声波图像，以便及时针对目标树木出现的问题调整养护方案，延长目标树木的寿命，改善城市绿化监测的效果；第一控制子单元5021 和第二控制子单元5022可以通过自动控制树木电阻抗断层成像装置测量目标树木中的电流变化，得到目标树木中具体的水分含量分布，降低了人工成本，提高了城市绿化监测的效率。所以，实施图6所描述的智能监测机器人能够进一步降低人工成本，并提高绿化监测效率。
实施例六
请参阅图7，图7是本发明实施例公开的又一种智能监测机器人的结构示意图。其中，图7所示的智能监测机器人是由图6所示的智能监测机器人进行优化得到的。与图6所示的智能监测机器人相比较，图7所示的智能监测机器人还可以包括：
发送单元509，用于在计算单元507根据即时健康状况程度、即时稳定程度以及即时受病虫害侵害程度以及预设比例值，计算得出目标树木的综合健康程度之后，将目标树木的检测报告发送至管理人员的移动终端；其中，检测报告包括目标树木的即时健康状况程度、即时稳定程度、即时受病虫害侵害程度、基本数据以及综合健康程度。
本发明实施例中，发送单元509可以将包含目标树木即时健康状况程度、即时稳定程度、即时受病虫害侵害程度、基本数据以及综合健康程度的检测报告发送至管理人员的移动终端，以便管理人员针对目标树木的综合健康程度进行有针对性的养护。所以，执行发送单元509能够通过将目标树木的检测报告发送至管理人员的移动终端，提高了城市绿化监测的便捷性和及时性，与此同时提高了城市绿化监测效率。
病虫害检测单元505，可以包括：
获取子单元5051，用于获取目标树木的随机样本。
第三控制子单元5052，用于控制病虫害检测装置对随机样本进行检测。
判断子单元5053，用于判断随机样本中是否存在病虫害。
比对子单元5054，用于在判断子单元5053判断出随机样本中存在病虫害之后，将病虫害的形态与数据库中现有的病虫害的形态进行比对，得到病虫害的种类，并将病虫害的种类发送至移动终端。
本发明实施例中，获取子单元5051、第三控制子单元5052、判断子单元5053以及比对子单元5054通过智能监测机器人对目标树木进行病虫害的检测，并且当目标树木存在病虫害时对该病虫害的种类进行确定，更进一步的增加了城市绿化监测的便捷性。
可见，实施图7所描述的智能监测机器人，发送单元509能够通过将目标树木的检测报告发送至管理人员的移动终端，提高了城市绿化监测的便捷性和及时性，与此同时提高了城市绿化监测效率；获取子单元5051、第三控制子单元5052、判断子单元5053以及比对子单元5054通过智能监测机器人对目标树木进行病虫害的检测，并且当目标树木存在病虫害时对该病虫害的种类进行确定，更进一步的增加了城市绿化监测的便捷性。所以，实施图7所描述的智能监测机器人能够更进一步降低人工成本，并提高绿化监测效率。
实施例七
请参阅图8，图8是本发明实施例公开的又一种智能监测机器人的结构示意图。如图8所示，该智能监测机器人可以包括：
存储有可执行程序代码的存储器801；
与存储器801耦合的处理器802；
其中，处理器802调用存储器801中存储的可执行程序代码，执行图1～图3任意一种应用于智慧城市的绿化监测方法。
本发明实施例公开一种计算机可读存储介质，其存储计算机程序，其中，该计算机程序使得计算机执行图1～图3任意一种应用于智慧城市的绿化监测方法。
本领域普通技术人员可以理解上述实施例的各种方法中的全部或部分步骤是可以通过程序来指令相关的硬件来完成，该程序可以存储于一计算机可读存储介质中，存储介质包括只读存储器(Read-Only Memory，ROM)、随机存储器(Random Access Memory，RAM)、可编程只读存储器(Programmable Read-only Memory，PROM)、可擦除可编程只读存储器(Erasable Programmable Read Only Memory，EPROM)、一次可编程只读存储器(One-time Programmable Read-Only Memory，OTPROM)、电子抹除式可复写只读存储器(Electrically-Erasable Programmable Read-Only Memory，EEPROM)、只读光盘(Compact Disc Read-Only Memory，CD-ROM)或其他光盘存储器、磁盘存储器、磁带存储器、或者能够用于携带或存储数据的计算机可读的任何其他介质。
以上所述，以上实施例仅用以说明本申请的技术方案而非对其限制；尽管参照前述实施例对本申请进行了详细的说明，然而本领域的普通技术人员应当理解；其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本申请各实施例技术方案的精神和范围。

Claims (10)

  1. 一种应用于智慧城市的绿化监测方法，其特征在于，所述方法包括：
    智能监测机器人检测预设区域内目标树木的基本数据，并将所述基本数据与数据库中的现有数据进行比对，确定出所述目标树木的树木品种；其中，所述基本数据包括所述目标树木的位置数据以及样本数据；
    所述智能监测机器人对所述目标树木进行电阻抗检测，得到所述目标树木的电阻抗断层图像，并根据所述电阻抗断层图像确定所述目标树木的即时健康状况程度；其中，所述即时健康状况程度包括所述目标树木的树木水分；
    所述智能监测机器人对所述目标树木进行侧向拉伸测试，得到所述目标树木的即时稳定程度，并对所述目标树木进行病虫害检测得到所述目标树木的即时受病虫害侵害程度；
    所述智能监测机器人确定所述目标树木的树木品种对应的预设比例值，所述预设比例值是预设健康状况程度、预设稳定程度以及预设受病虫害侵害程度三者的比例值；
    所述智能监测机器人根据所述即时健康状况程度、所述即时稳定程度以及所述即时受病虫害侵害程度以及所述预设比例值，计算得出所述目标树木的综合健康程度。
  2. 根据权利要求1所述的方法，其特征在于，所述智能监测机器人对所述目标树木进行电阻抗检测，得到所述目标树木的电阻抗断层图像，包括：
    所述智能监测机器人控制树木电阻抗断层成像装置向所述目标树木中输入电流；
    所述智能监测机器人控制所述树木电阻抗断层成像装置测量所述目标树木中的电流变化得到测量结果，并得到以电阻抗断层图像的形式表示的所述测量结果；其中，所述电阻抗断层图像包括所述目标树木的树干横断面的高电阻指示区域、低电阻指示区域以及增长电阻指示区域；其中，所述高电阻指示区域对应的所述目标树木的树干部分含水量低于正常含水量范围的最小值，所述低电阻指示区域对应的所述目标树木的树干部分含水量处于正常含水量范围内，所述增长电阻指示区域对应的所述目标树木的树干部分含水量处于变化状态。
  3. 根据权利要求2所述的方法，其特征在于，所述智能监测机器人得到所述目标树木的电阻抗断层图像之后，所述方法还包括：
    所述智能监测机器人控制所述树木电阻抗断层成像装置对所述目标树木进行声波层析，得到声波图像；其中，所述声波图像包括所述树干横断面的高速率声波区域以及低速率声波区域；
    所述智能监测机器人根据所述电阻抗断层图像确定所述目标树木的即时健康状况程度之后，所述方法还包括：
    所述智能监测机器人确定所述目标树木的目标树干部分的即时具体健康状况程度；
    若所述目标树木的目标树干部分既属于所述高速率声波区域又属于所述高电阻指示区域，所述智能监测机器人确定所述目标树干部分的即时具体健康状况程度为健康；若所述目标树木的目标树干部分既属于所述高速率声波区域又属于所述低电阻指示区域，所述智能监测机器人确定所述目标树干部分的即时具体健康状况程度为轻度腐烂；若所述目标树木的目标树干部分既属于所述低速率声波区域又属于所述高电阻指示区域，所述智能监测机器人确定所述目标树干部分的即时具体健康状况程度为重度腐烂并且死亡；若所述目标树木的目标树干部分既属于所述低速率声波区域又属于所述低电阻指示区域，所述智能监测机器人确定 所述目标树干部分的即时具体健康状况程度为中度腐烂。
  4. 根据权利要求3所述的方法，其特征在于，所述智能监测机器人根据所述即时健康状况程度、所述即时稳定程度以及所述即时受病虫害侵害程度以及所述预设比例值，计算得出所述目标树木的综合健康程度之后，所述方法还包括：
    所述智能监测机器人将所述目标树木的检测报告发送至管理人员的移动终端；其中，所述检测报告包括所述目标树木的所述即时健康状况程度、所述即时稳定程度、所述即时受病虫害侵害程度、所述基本数据以及所述综合健康程度。
  5. 根据权利要求4所述的方法，其特征在于，所述智能监测机器人对所述目标树木进行病虫害检测得到所述目标树木的即时受病虫害侵害程度，包括：
    所述智能监测机器人获取所述目标树木的随机样本；
    所述智能监测机器人控制病虫害检测装置对所述随机样本进行检测，并判断所述随机样本中是否存在病虫害；
    如果是，所述智能监测机器人将所述病虫害的形态与所述数据库中现有的病虫害的形态进行比对，得到所述病虫害的种类，并将所述病虫害的种类发送至所述移动终端。
  6. 一种智能监测机器人，其特征在于，所述智能监测机器人包括：
    基本数据检测单元，用于检测预设区域内目标树木的基本数据，并将所述基本数据与数据库中的现有数据进行比对，确定出所述目标树木的树木品种；其中，所述基本数据包括所述目标树木的位置数据以及样本数据；
    电阻抗检测单元，用于对所述目标树木进行电阻抗检测，得到所述目标树木的电阻抗断层图像；
    第一确定单元，用于根据所述电阻抗断层图像确定所述目标树木的即时健康状况程度；其中，所述即时健康状况程度包括所述目标树木的树木水分；
    侧向拉伸测试单元，用于对所述目标树木进行侧向拉伸测试，得到所述目标树木的即时稳定程度；
    病虫害检测单元，用于对所述目标树木进行病虫害检测得到所述目标树木的即时受病虫害侵害程度；
    第二确定单元，用于确定所述目标树木的树木品种对应的预设比例值，所述预设比例值是预设健康状况程度、预设稳定程度以及预设受病虫害侵害程度三者的比例值；
    计算单元，用于根据所述即时健康状况程度、所述即时稳定程度以及所述即时受病虫害侵害程度以及所述预设比例值，计算得出所述目标树木的综合健康程度。
  7. 根据权利要求6所述的智能监测机器人，其特征在于，所述电阻抗检测单元包括：
    第一控制子单元，用于控制树木电阻抗断层成像装置向所述目标树木中输入电流；
    第二控制子单元，用于控制所述树木电阻抗断层成像装置测量所述目标树木中的电流变化得到测量结果，并得到以电阻抗断层图像的形式表示的所述测量结果；其中，所述电阻抗断层图像包括所述目标树木的树干横断面的高电阻指示区域、低电阻指示区域以及增长电阻指示区域；其中，所述高电阻指示区域对应的所述目标树木的树干部分含水量低于正常含水量范围的最小值，所述低电阻指示区域对应的所述目标树木的树干部分含水量处于正常含水量范围内，所述增长电阻指示区域对应的所述目标树木的树干部分含水量处于变化状态。
  8. 根据权利要求7所述的智能监测机器人，其特征在于，所述智能监测机器人还包括：
    控制单元，用于在所述电阻抗检测单元得到所述目标树木的电阻抗断层图像之后，控制所述树木电阻抗断层成像装置对所述目标树木进行声波层析，得到声波图像；其中，所述声波图像包括所述树干横断面的高速率声波区域以及低速率声波区域；
    所述第一确定单元，还用于在执行所述的根据所述电阻抗断层图像确定出所述目标树木的即时健康状况程度之后，确定所述目标树木的目标树干部分的即时具体健康状况程度；
    所述第一确定单元，还用于当所述目标树木的目标树干部分既属于所述高速率声波区域又属于所述高电阻指示区域时，确定所述目标树干部分的即时具体健康状况程度为健康；当所述目标树木的目标树干部分既属于所述高速率声波区域又属于所述低电阻指示区域时，确定所述目标树干部分的即时具体健康状况程度为轻度腐烂；当所述目标树木的目标树干部分既属于所述低速率声波区域又属于所述高电阻指示区域时，确定所述目标树干部分的即时具体健康状况程度为重度腐烂并且死亡；当所述目标树木的目标树干部分既属于所述低速率声波区域又属于所述低电阻指示区域时，确定所述目标树干部分的即时具体健康状况程度为中度腐烂。
  9. 根据权利要求8所述的智能监测机器人，其特征在于，所述智能监测机器人还包括：
    发送单元，用于在所述计算单元根据所述即时健康状况程度、所述即时稳定程度以及所述即时受病虫害侵害程度以及所述预设比例值，计算得出所述目标树木的综合健康程度之后，将所述目标树木的检测报告发送至管理人员的移动终端；其中，所述检测报告包括所述目标树木的所述即时健康状况程度、所述即时稳定程度、所述即时受病虫害侵害程度、所述基本数据以及所述综合健康程度。
  10. 根据权利要求9所述的智能监测机器人，其特征在于，所述病虫害检测单元包括：
    获取子单元，用于获取所述目标树木的随机样本；
    第三控制子单元，用于控制病虫害检测装置对所述随机样本进行检测；
    判断子单元，用于判断所述随机样本中是否存在病虫害；
    比对子单元，用于在所述判断子单元判断出所述随机样本中存在病虫害之后，将所述病虫害的形态与所述数据库中现有的病虫害的形态进行比对，得到所述病虫害的种类，并将所述病虫害的种类发送至所述移动终端。
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