CN116225070A - Environment monitoring method and system based on unmanned aerial vehicle automatic patrol - Google Patents
Environment monitoring method and system based on unmanned aerial vehicle automatic patrol Download PDFInfo
- Publication number
- CN116225070A CN116225070A CN202310473803.8A CN202310473803A CN116225070A CN 116225070 A CN116225070 A CN 116225070A CN 202310473803 A CN202310473803 A CN 202310473803A CN 116225070 A CN116225070 A CN 116225070A
- Authority
- CN
- China
- Prior art keywords
- aerial vehicle
- unmanned aerial
- environment monitoring
- area
- monitoring area
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 293
- 238000000034 method Methods 0.000 title claims abstract description 42
- 238000003915 air pollution Methods 0.000 claims abstract description 60
- 230000007613 environmental effect Effects 0.000 claims abstract description 33
- 238000005265 energy consumption Methods 0.000 claims abstract description 32
- 239000013618 particulate matter Substances 0.000 claims description 23
- 230000008033 biological extinction Effects 0.000 claims description 18
- 238000012545 processing Methods 0.000 claims description 17
- 238000001514 detection method Methods 0.000 claims description 15
- 230000009467 reduction Effects 0.000 claims description 11
- 230000001133 acceleration Effects 0.000 claims description 6
- 230000008859 change Effects 0.000 claims description 6
- 238000013507 mapping Methods 0.000 claims description 6
- 238000007689 inspection Methods 0.000 claims description 4
- 230000005484 gravity Effects 0.000 claims description 3
- 230000006870 function Effects 0.000 description 13
- 238000004891 communication Methods 0.000 description 10
- 238000010586 diagram Methods 0.000 description 5
- 238000000605 extraction Methods 0.000 description 5
- 238000007726 management method Methods 0.000 description 5
- 238000013473 artificial intelligence Methods 0.000 description 4
- 238000004422 calculation algorithm Methods 0.000 description 4
- 238000004590 computer program Methods 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000004458 analytical method Methods 0.000 description 2
- 239000004973 liquid crystal related substance Substances 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 239000002028 Biomass Substances 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000012512 characterization method Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000000802 evaporation-induced self-assembly Methods 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 230000031700 light absorption Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000013077 scoring method Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
- 238000002834 transmittance Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/10—Simultaneous control of position or course in three dimensions
- G05D1/101—Simultaneous control of position or course in three dimensions specially adapted for aircraft
- G05D1/106—Change initiated in response to external conditions, e.g. avoidance of elevated terrain or of no-fly zones
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Engineering & Computer Science (AREA)
- Aviation & Aerospace Engineering (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Automation & Control Theory (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention relates to the technical field of environmental monitoring, and discloses an environmental monitoring method and system based on unmanned aerial vehicle automatic patrol, wherein the method comprises the following steps: extracting regional characteristics of an environment monitoring region, making an automatic patrol route of unmanned aerial vehicle equipment, calculating energy consumption of the unmanned aerial vehicle corresponding to the automatic patrol route, and determining an optimal patrol route of the unmanned aerial vehicle equipment; image acquisition of the unmanned aerial vehicle equipment on the environment monitoring area is executed, an area acquisition image is obtained, and the air pollution coefficient of the environment monitoring area is calculated; transmitting sonar waves to an environment monitoring area by using a sonar detector preset by unmanned aerial vehicle equipment, receiving feedback results of the transmitted sonar waves, and calculating the biological density of the environment monitoring area to obtain the surface pollution coefficient of the environment monitoring area; and confirming the pollution level of the environment monitoring area, respectively detecting pollution sources corresponding to the air pollution and the ground surface pollution, and generating a monitoring report of the environment monitoring area. The invention aims to improve the accuracy of environmental monitoring based on unmanned aerial vehicle automatic patrol.
Description
Technical Field
The invention relates to the technical field of environmental monitoring, in particular to an environmental monitoring method and system based on unmanned aerial vehicle automatic patrol.
Background
With the continuous development of the industrialization process, environment monitoring needs to be performed on a specific area, and as the labor amount of manual monitoring is too large, unmanned plane equipment is combined with environment monitoring equipment to perform environment monitoring on the specific area at present, manual monitoring steps are reduced, and the accuracy of data is improved.
However, in the existing unmanned aerial vehicle detection method, air is collected through an environment monitoring instrument fixed on unmanned aerial vehicle equipment, the collected air is detected and analyzed, and an environment monitoring result is obtained according to an analysis result.
Disclosure of Invention
The invention provides an environment monitoring method and system based on unmanned aerial vehicle automatic patrol, and mainly aims to improve the accuracy of environment monitoring based on unmanned aerial vehicle automatic patrol.
In order to achieve the above purpose, the invention provides an environment monitoring method based on unmanned aerial vehicle automatic patrol, comprising the following steps:
Acquiring unmanned aerial vehicle equipment and an environment monitoring area to be patrolled, extracting area characteristics of the environment monitoring area, formulating an automatic patrolling route of the unmanned aerial vehicle equipment according to the area characteristics, calculating energy consumption of an unmanned aerial vehicle corresponding to the automatic patrolling route, and determining an optimal patrolling route of the unmanned aerial vehicle equipment according to energy consumption of the unmanned aerial vehicle;
according to the optimal patrol route, the unmanned aerial vehicle equipment performs image acquisition on the environment monitoring area to obtain an area acquisition image, and according to the area acquisition image, the air pollution coefficient of the environment monitoring area is calculated;
transmitting sonar waves to the environment monitoring area by using a sonar detector preset by the unmanned aerial vehicle equipment, receiving a feedback result of the transmitted sonar waves, calculating the biological density of the environment monitoring area according to the feedback result, and obtaining the surface pollution coefficient of the environment monitoring area according to the biological density;
and confirming the pollution level of the environment monitoring area by combining the air pollution coefficient, the surface pollution coefficient and the area characteristics, respectively detecting pollution sources corresponding to air pollution and surface pollution, and generating a monitoring report of the environment monitoring area by combining the pollution level and the pollution sources.
Optionally, the extracting the area feature of the environment monitoring area includes:
acquiring surface data corresponding to the environment monitoring area, and acquiring an area map corresponding to the environment monitoring area;
extracting topographic indexes in the regional map, and calculating an index value of each index in the topographic indexes by combining the surface data to obtain topographic index values;
extracting features of the regional map according to the topographic index value and the topographic index value to obtain map features;
and determining the regional characteristics of the environment monitoring region according to the map characteristics.
Optionally, the making an automatic routing of the unmanned aerial vehicle device according to the regional characteristics includes:
acquiring a monitoring task corresponding to the environment monitoring area, extracting a task requirement of the monitoring task, and detecting a meteorological environment of the environment monitoring area;
according to the task requirements and the meteorological environment, an initial route for the unmanned aerial vehicle equipment is established;
and extracting characteristic parameters of the regional characteristics, and carrying out route adjustment on the initial routing inspection route according to the characteristic parameters to obtain an automatic routing inspection route.
Optionally, the calculating the energy consumption of the unmanned aerial vehicle corresponding to the automatic patrol route includes:
The energy consumption of the unmanned aerial vehicle corresponding to the automatic routing is calculated through the following formula:
wherein T represents the maximum time value of the time slot T, C f Representing the wing area of unmanned aerial vehicle equipment, bt]Representing the corresponding speed of unmanned aerial vehicle equipment at the moment t, D 2 Representing the ratio of the resultant force of corresponding external forces of unmanned aerial vehicle equipment to the gravity of unmanned aerial vehicle equipment, A [ t ]]The acceleration corresponding to the unmanned plane equipment at the time t is represented, g represents the gravitational acceleration, and beta i Indicating the distance corresponding to the ith automatic patrol route, and Δp indicates the change of energy of the unmanned aerial vehicle device.
Optionally, the performing image acquisition of the unmanned aerial vehicle device on the environment monitoring area according to the optimal patrol route, to obtain an area acquisition image, includes:
scheduling camera equipment of the unmanned aerial vehicle equipment, and acquiring images of the environment monitoring area by using the camera equipment according to the optimal patrol route to obtain initial acquired images;
carrying out noise reduction treatment on the initial acquisition image to obtain a noise reduction acquisition image;
performing de-duplication treatment on the noise reduction acquisition image to obtain a target acquisition image;
and performing image enhancement processing on the target acquisition image to obtain an area acquisition image.
Optionally, the calculating the air pollution coefficient of the environment monitoring area according to the area acquired image includes:
extracting image pixel points of the region acquisition image, and calculating brightness values corresponding to the image pixel points to obtain first brightness values;
acquiring a historical acquisition image of the environment monitoring area, extracting an image brightness value and a historical air pollution coefficient of the historical acquisition image, and calculating a proportionality coefficient of the image brightness value and the first brightness value to obtain a brightness proportionality coefficient;
calculating an extinction coefficient of the area acquisition image, and calculating the suspended particulate matter concentration of the environment monitoring area by combining the brightness proportion coefficient and the extinction coefficient;
determining an air pollution coefficient of the environment monitoring area by combining the suspended particulate matter concentration
Optionally, the calculating the suspended particulate matter concentration of the environmental monitoring area by combining the brightness proportionality coefficient and the extinction coefficient includes:
calculating the suspended particulate matter concentration of the environment monitoring area by the following formula:
wherein F represents suspended particulate matter concentration of an environment monitoring area, n represents brightness proportionality coefficient, v represents RGB color channels of an area acquisition image, U v The light intensity attenuation coefficient of the v-th channel is represented by W, the diameter average value corresponding to the particulate matter is represented by T, the extinction coefficient is represented by T (vs), and the relationship function of the extinction coefficient T under the v-th channel with respect to the diameter average value W of the particulate matter is represented by T.
Optionally, the calculating the biological density of the environment monitoring area according to the feedback result includes:
calculating an initial intensity value of biological contact between the sonar wave and the environment monitoring area, obtaining a feedback intensity value of the sonar wave and a contact area of the sonar wave according to the feedback result, and measuring the area of the environment monitoring area;
calculating a distance value between the unmanned aerial vehicle equipment and organisms in the environment monitoring area, inquiring a feedback loss coefficient corresponding to the sonar wave through a preset sonar wave loss coefficient table according to the distance value, and calculating a real feedback intensity value of the sonar wave by combining the initial intensity value, the feedback intensity value and the feedback loss coefficient;
calculating the intensity difference between the real feedback intensity value and the initial intensity value, and calculating the ratio of the contact area corresponding to the feedback intensity value to the area of the area when the intensity difference is larger than a preset threshold value to obtain an area proportionality coefficient;
And carrying out weighted summation on the area proportionality coefficients to obtain target coefficients, and taking the target coefficients as the biological density of the environment monitoring area.
Optionally, said determining a pollution level of said environmental monitoring area in combination with said air pollution coefficient, said surface pollution coefficient, and said area characteristic comprises:
according to the regional characteristics, distributing the weight coefficients of the air pollution coefficient and the surface pollution coefficient;
according to the weight coefficient, carrying out weighted summation on the air pollution coefficient and the surface pollution coefficient to obtain a target pollution coefficient;
inquiring the pollution level corresponding to the target pollution coefficient from a preset pollution level-coefficient mapping table, and confirming the pollution level of the environment monitoring area according to the pollution level.
In order to solve the above problems, the present invention further provides an environment monitoring system based on unmanned aerial vehicle automatic patrol, the system comprising:
the route making module is used for obtaining unmanned aerial vehicle equipment and an environment monitoring area to be patrolled, extracting area characteristics of the environment monitoring area, making an automatic patrolling route of the unmanned aerial vehicle equipment according to the area characteristics, calculating unmanned aerial vehicle energy consumption corresponding to the automatic patrolling route, and determining an optimal patrolling route of the unmanned aerial vehicle equipment according to the unmanned aerial vehicle energy consumption;
The image processing module is used for executing image acquisition of the unmanned aerial vehicle equipment on the environment monitoring area according to the optimal patrol route to obtain an area acquisition image, and calculating the air pollution coefficient of the environment monitoring area according to the area acquisition image;
the sonar detection module is used for transmitting sonar waves to the environment monitoring area by using a sonar detector preset by the unmanned aerial vehicle equipment, receiving a feedback result of the transmitted sonar waves, calculating the biological density of the environment monitoring area according to the feedback result, and obtaining the surface pollution coefficient of the environment monitoring area according to the biological density;
the pollution source detection module is used for combining the air pollution coefficient, the surface pollution coefficient and the regional characteristics, confirming the pollution level of the environment monitoring region, respectively detecting pollution sources corresponding to air pollution and surface pollution, and generating a monitoring report of the environment monitoring region by combining the pollution level and the pollution sources.
According to the invention, the unmanned aerial vehicle equipment and the environment monitoring area to be patrolled are obtained, the area characteristics of the environment monitoring area are extracted, the characteristics of the environment monitoring area can be known, the automatic patrolling route of the unmanned aerial vehicle equipment is conveniently formulated subsequently, the image acquisition of the unmanned aerial vehicle equipment on the environment monitoring area is carried out according to the optimal patrolling route, the understanding of the environment monitoring area is conveniently increased through the acquired image, wherein the area acquisition image is an image obtained by shooting and acquiring the environment monitoring area by shooting equipment such as the unmanned aerial vehicle equipment, and the like; in addition, the invention combines the air pollution coefficient, the surface pollution coefficient and the regional characteristics to confirm the pollution level of the environment monitoring region, thereby facilitating the subsequent generation of the monitoring report of the environment monitoring region. Therefore, the environment monitoring method and system based on the unmanned aerial vehicle automatic patrol can improve the accuracy of the environment monitoring based on the unmanned aerial vehicle automatic patrol.
Drawings
Fig. 1 is a schematic flow chart of an environment monitoring method based on automatic unmanned aerial vehicle patrol according to an embodiment of the invention;
fig. 2 is a functional block diagram of an environment monitoring system based on automatic unmanned aerial vehicle patrol according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of an electronic device for implementing the environmental monitoring method based on unmanned aerial vehicle automatic patrol according to an embodiment of the present invention.
In the figure, 1-an electronic device; 10-a processor; 11-memory; 12-a communication bus; 13-a communication interface;
100-an environment monitoring system based on unmanned aerial vehicle automatic patrol; 101-a route establishment module; 102-an image processing module; 103-a sonar detection module; 104-a pollution source detection module.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
The embodiment of the application provides an environment monitoring method based on unmanned aerial vehicle automatic patrol. In the embodiment of the present application, the execution body of the environment monitoring method based on unmanned aerial vehicle automatic patrol includes, but is not limited to, at least one of a server, a terminal, and the like, which can be configured to execute the method provided in the embodiment of the present application. In other words, the environment monitoring method based on unmanned aerial vehicle automatic patrol can be executed by software or hardware installed in a terminal device or a server device, wherein the software can be a blockchain platform. The service end includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, and the like. The server may be an independent server, or may be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.
Referring to fig. 1, a flow chart of an environment monitoring method based on automatic unmanned aerial vehicle patrolling according to an embodiment of the present invention is shown. In this embodiment, the method for monitoring the environment based on the unmanned aerial vehicle automatic patrol includes steps S1 to S4.
S1, acquiring unmanned aerial vehicle equipment and an environment monitoring area to be patrolled, extracting regional characteristics of the environment monitoring area, formulating an automatic patrolling route of the unmanned aerial vehicle equipment according to the regional characteristics, calculating unmanned aerial vehicle energy consumption corresponding to the automatic patrolling route, and determining an optimal patrolling route of the unmanned aerial vehicle equipment according to the unmanned aerial vehicle energy consumption.
According to the invention, the unmanned aerial vehicle equipment and the environment monitoring area to be patrolled are obtained, the area characteristics of the environment monitoring area are extracted, the characteristics of the environment monitoring area can be known, and the automatic patrolling route of the unmanned aerial vehicle equipment is conveniently formulated subsequently.
The unmanned aerial vehicle equipment is equipment which is not provided with a cockpit but can fly, and is tracked, positioned and remotely controlled by an operator through a radar on the ground, a naval vessel or a master remote control station, and has the characteristics that: the system has the advantages of small volume, low cost, convenience in use and the like, the environment monitoring area is a region space needing environment monitoring, the area is characterized in that the environment monitoring area is provided with a representation meaning part, further, unmanned aerial vehicle equipment to be patrolled and protected and the environment monitoring area can be obtained through a man-machine interaction mode, such as manual inquiry of the environment monitoring area, and scheduling of the unmanned aerial vehicle equipment through an equipment manager.
As one embodiment of the present invention, the extracting the area feature of the environment monitoring area includes: acquiring surface data corresponding to the environment monitoring area, acquiring an area map corresponding to the environment monitoring area, extracting terrain indexes in the area map, calculating index values of each index in the terrain indexes in combination with the surface data to obtain terrain index values, extracting features of the area map according to the terrain index values and the terrain indexes to obtain map features, and determining the area features of the environment monitoring area according to the map features.
The surface data are data corresponding to the surface of the environment monitoring area, such as objects or buildings and the like existing on the surface, the area map is a map corresponding to the environment monitoring area, the terrain indexes are basic natural geographic elements in the area map, such as gradient change rate, slope change rate, terrain relief degree, ground roughness and the like, the terrain index values are numerical values corresponding to each index in the terrain indexes, such as the numerical value of gradient change rate, and the map features are characterization parts in the area map.
Furthermore, the data acquisition of the earth surface data corresponding to the environment monitoring area can be realized through a data acquisition device, the data acquisition device is compiled by a script language, the acquisition of the area map corresponding to the environment monitoring area can be realized through map software, such as a hundred-degree map, the extraction of the topographic index in the area map can be realized through a corresponding index extraction tool, the index extraction tool is compiled by Java language, the index value of each index in the topographic index can be obtained through calculation of a digital elevation model, and the feature extraction of the area map can be realized through an lbp algorithm.
According to the method, the automatic routing of the unmanned aerial vehicle equipment is formulated according to the regional characteristics, so that the follow-up unmanned aerial vehicle equipment can regularly monitor the environment monitoring region, wherein the automatic routing is an automatic running route for the unmanned aerial vehicle equipment to monitor the environment monitoring region.
As one embodiment of the present invention, the making an automatic routing of the unmanned aerial vehicle device according to the regional characteristics includes: acquiring a monitoring task corresponding to the environment monitoring area, extracting a task requirement of the monitoring task, detecting the meteorological environment of the environment monitoring area, making an initial routing of the unmanned aerial vehicle equipment according to the task requirement and the meteorological environment, extracting characteristic parameters of the area characteristics, and carrying out route adjustment on the initial routing according to the characteristic parameters to obtain an automatic routing.
The monitoring task is the monitoring work of the unmanned aerial vehicle equipment on the environment monitoring area, the task requirement is a condition corresponding to the monitoring task, the meteorological environment is the weather environment of the environment monitoring area, the initial patrol route is an initial route of the unmanned aerial vehicle equipment formulated according to the task requirement and the meteorological environment, and the characteristic parameter is parameter information corresponding to the area characteristic.
Further, the monitoring task corresponding to the environment monitoring area can be obtained through a task viewer, the meteorological environment of the environment monitoring area can be detected through a meteorological detector, the initial routing of the unmanned aerial vehicle equipment can be established through a voronoi diagram method, and the characteristic parameters for extracting the characteristics of the area can be achieved through a parameter extraction tool, such as a Parsehub tool.
According to the invention, the energy consumption condition of the unmanned aerial vehicle equipment corresponding to the automatic patrol route can be known by calculating the energy consumption of the unmanned aerial vehicle corresponding to the automatic patrol route, so that the follow-up determination of the optimal patrol route of the unmanned aerial vehicle equipment is facilitated, wherein the unmanned aerial vehicle energy consumption is the energy consumption of the unmanned aerial vehicle equipment corresponding to the unmanned aerial vehicle equipment after completing the corresponding task according to the automatic patrol route.
As an embodiment of the present invention, the calculating the energy consumption of the unmanned aerial vehicle corresponding to the automatic patrol route includes:
the energy consumption of the unmanned aerial vehicle corresponding to the automatic routing is calculated through the following formula:
wherein T represents the maximum time value of the time slot T, C f Representing the wing area of unmanned aerial vehicle equipment, bt]Representing the corresponding speed of unmanned aerial vehicle equipment at the moment t, D 2 Representing the ratio of the resultant force of corresponding external forces of unmanned aerial vehicle equipment to the gravity of unmanned aerial vehicle equipment, A [ t ]]The acceleration corresponding to the unmanned plane equipment at the time t is represented, g represents the gravitational acceleration, and beta i Indicating the distance corresponding to the ith automatic patrol route, and Δp indicates the change of energy of the unmanned aerial vehicle device.
According to the unmanned aerial vehicle energy consumption monitoring method, the optimal patrol route of the unmanned aerial vehicle equipment is determined according to the unmanned aerial vehicle energy consumption, so that the energy consumption of the unmanned aerial vehicle equipment is reduced to the minimum, the optimal patrol route is the route with the lowest energy consumption of the unmanned aerial vehicle equipment in the automatic patrol route, energy sources can be saved, and further, the optimal patrol route of the unmanned aerial vehicle equipment can be determined according to the numerical value of the unmanned aerial vehicle energy consumption.
S2, according to the optimal patrol route, image acquisition of the unmanned aerial vehicle equipment on the environment monitoring area is executed, an area acquisition image is obtained, and according to the area acquisition image, the air pollution coefficient of the environment monitoring area is calculated.
According to the invention, the unmanned aerial vehicle equipment performs image acquisition of the environment monitoring area according to the optimal patrol route, so that the acquired image is convenient for increasing the knowledge of the environment monitoring area, wherein the area acquisition image is obtained by shooting and acquiring the environment monitoring area by shooting equipment such as the unmanned aerial vehicle equipment.
As an embodiment of the present invention, the performing, according to the optimal patrol route, image acquisition of the environmental monitoring area by the unmanned aerial vehicle device, to obtain an area acquisition image includes: and scheduling camera equipment of the unmanned aerial vehicle equipment, carrying out image acquisition on the environment monitoring area by utilizing the camera equipment according to the optimal patrol route to obtain an initial acquisition image, carrying out noise reduction processing on the initial acquisition image to obtain a noise reduction acquisition image, carrying out de-duplication processing on the noise reduction acquisition image to obtain a target acquisition image, and carrying out image enhancement processing on the target acquisition image to obtain an area acquisition image.
The camera device is used for shooting an image of the environment monitoring area on the unmanned aerial vehicle device, the initial acquisition image is an initial image obtained by the camera device on the environment monitoring area according to the optimal routing, the noise reduction acquisition image is an image obtained by removing noise in the initial acquisition image, and the target acquisition image is an image obtained by removing repeated images in the noise reduction acquisition image.
Further, as an optional embodiment of the present invention, the scheduling of the camera device of the unmanned aerial vehicle device may be implemented by a device scheduling algorithm, for example, a polling algorithm, the denoising processing of the initial acquired image may be implemented by an average filter, the deduplication processing of the denoising acquired image may be implemented by calculating a similarity in the denoising acquired image, removing a repeated image in the denoising acquired image according to the magnitude of the similarity value, and the image enhancement processing of the target acquired image may be implemented by a gray scale transformation enhancement method.
According to the method, the air pollution coefficient of the environment monitoring area is calculated according to the area acquired image, so that the air pollution degree of the environment monitoring area can be known conveniently through the air pollution coefficient, wherein the air pollution coefficient is the air pollution degree of the environment monitoring area.
As one embodiment of the present invention, the calculating the air pollution coefficient of the environmental monitoring area according to the area acquired image includes: extracting image pixel points of the area acquisition image, calculating a brightness value corresponding to the image pixel points to obtain a first brightness value, acquiring a history acquisition image of the environment monitoring area, extracting an image brightness value and a history air pollution coefficient of the history acquisition image, calculating a proportion coefficient of the image brightness value and the first brightness value to obtain a brightness proportion coefficient, calculating an extinction coefficient of the area acquisition image, calculating suspended particulate matter concentration of the environment monitoring area by combining the brightness proportion coefficient and the extinction coefficient, and determining the air pollution coefficient of the environment monitoring area by combining the suspended particulate matter concentration.
The first brightness value represents the brightness of the image pixel point, the history collected image is an image collected during environment monitoring before the environment monitoring area, the history monitoring result is a result obtained during environment monitoring before the environment monitoring area, the brightness proportionality coefficient is a ratio of the image brightness value to the first brightness value, the extinction coefficient is a relative transmittance of light absorption of the area collected image, and the suspended particulate matter concentration represents the content of particulate matters in air of the environment monitoring area.
Further, as an optional embodiment of the present invention, the extracting of the image pixel point of the area collected image may be implemented by an extracting pixel method, the calculating of the brightness value corresponding to the image pixel point may be implemented by l=r×0.30+g×0.59+b×0.11, R represents a red color channel in the image pixel point, G represents a green color channel in the image pixel point, B represents a blue color channel in the image pixel point, the calculating of the brightness proportionality coefficient may be implemented by a ratio of the image brightness value to the first brightness value, and the extinction coefficient of the area collected image may be calculated by the formula: t=e-kb, T represents the extinction coefficient, e is the base of the natural logarithm, k is the brightness constant, b is the optical path length, and the air pollution coefficient for determining the environment monitoring area can be set by the value of the suspended particulate matter concentration.
Further, as an alternative embodiment of the present invention, the calculating the suspended particulate matter concentration of the environmental monitoring area by combining the brightness proportionality coefficient and the extinction coefficient includes:
calculating the suspended particulate matter concentration of the environment monitoring area by the following formula:
wherein F represents suspended particulate matter concentration of an environment monitoring area, n represents brightness proportionality coefficient, v represents RGB color channels of an area acquisition image, U v The light intensity attenuation coefficient of the v-th channel is represented by W, the diameter average value corresponding to the particulate matter is represented by T, the extinction coefficient is represented by T (vs), and the relationship function of the extinction coefficient T under the v-th channel with respect to the diameter average value W of the particulate matter is represented by T.
S3, transmitting sonar waves to the environment monitoring area by using a sonar detector preset by the unmanned aerial vehicle equipment, receiving a feedback result of the transmitted sonar waves, calculating the biological density of the environment monitoring area according to the feedback result, and obtaining the surface pollution coefficient of the environment monitoring area according to the biological density.
According to the invention, sonar waves are transmitted to the environment monitoring area by using a sonar detector preset by the unmanned aerial vehicle equipment, and a feedback result of the transmitted sonar waves is received, so that the biomass condition of the environment monitoring area can be known through the feedback result, wherein the feedback result is a sonar wave result returned after the sonar detector transmits the sonar waves to the environment monitoring area.
According to the invention, the biological density of the environment monitoring area is calculated according to the feedback result, so that the biological quantity condition of the environment monitoring area can be solved, and the surface pollution coefficient of the environment monitoring area can be calculated conveniently, wherein the biological density is the quantity of organisms in a unit area in the environment monitoring area.
As an embodiment of the present invention, the calculating the biological density of the environmental monitoring area according to the feedback result includes: calculating an initial intensity value of biological contact between the sonar wave and the environment monitoring area, obtaining a feedback intensity value of the sonar wave and a contact area of the sonar wave according to the feedback result, measuring the area of the environment monitoring area, calculating a distance value between the unmanned aerial vehicle equipment and the biological contact area of the environment monitoring area, inquiring a feedback loss coefficient corresponding to the sonar wave according to the distance value through a preset sonar wave loss coefficient table, calculating a real feedback intensity value of the sonar wave by combining the initial intensity value, the feedback intensity value and the feedback loss coefficient, calculating an intensity difference between the real feedback intensity value and the initial intensity value, calculating a ratio of the contact area corresponding to the feedback intensity value to the area when the intensity difference is larger than a preset threshold value, obtaining an area proportion coefficient, carrying out weighted summation on the area proportion coefficient, and obtaining a target coefficient as the biological density of the environment monitoring area.
The initial intensity value represents the intensity of the sonar wave before contacting the living things in the environment detection area, the feedback intensity value is the intensity of the sonar wave fed back after the sonar wave contacts the living things in the environment detection area, the contact area is the contact area of the sonar wave and the living things, the preset sonar wave loss coefficient table is a mapping table of the distance and loss coefficient corresponding to the sonar wave, the real feedback intensity value is a real value obtained after the sonar wave passes through the living things, and the preset threshold value is a judging standard value of the intensity difference, which can be 0.8, and can also be set according to an actual service scene.
Further, as an optional embodiment of the present invention, measuring the area of the environmental monitoring area may be implemented by an area measuring apparatus, calculating the distance value between the unmanned aerial vehicle device and the living being in the environmental monitoring area may be implemented by a euclidean distance algorithm, querying the feedback loss coefficient corresponding to the sonar wave may be implemented by a query function, such as a find function, and calculating the real feedback intensity value of the sonar wave may be obtained by subtracting the ratio of the feedback intensity value to the feedback loss coefficient by combining the initial intensity value.
Further, as an alternative embodiment of the present invention, the calculating the initial intensity value of the biological contact between the sonar wave and the environment monitoring area includes:
calculating an initial intensity value of biological contact between the sonar wave and the environment monitoring area through the following formula:
wherein Q represents an initial intensity value of biological contact between a sonar wave and an environment monitoring area, Y represents medium density in air, P represents sound frequency of the sonar wave, K represents sonar amplitude corresponding to the sonar wave, and X represents wave speed of sonar wave emission.
According to the invention, the surface pollution coefficient of the environment monitoring area is obtained according to the biological density, so that the surface pollution severity of the environment monitoring area can be obtained, and the pollution level of the environment monitoring area can be conveniently confirmed later, wherein the surface pollution coefficient represents the surface pollution degree of the environment monitoring area, and further, the value of the biological density can be used as the surface pollution coefficient of the environment monitoring area.
S4, confirming the pollution level of the environment monitoring area by combining the air pollution coefficient, the surface pollution coefficient and the area characteristics, respectively detecting pollution sources corresponding to air pollution and surface pollution, and generating a monitoring report of the environment monitoring area by combining the pollution level and the pollution sources.
The invention combines the air pollution coefficient, the surface pollution coefficient and the area characteristics to confirm the pollution level of the environment monitoring area, so as to facilitate the subsequent generation of a monitoring report of the environment monitoring area, wherein the pollution level represents the pollution level of the environment monitoring area.
As one embodiment of the present invention, the determining the pollution level of the environmental monitoring area by combining the air pollution coefficient, the surface pollution coefficient and the area characteristic includes: and according to the regional characteristics, distributing the weight coefficients of the air pollution coefficient and the surface pollution coefficient, carrying out weighted summation on the air pollution coefficient and the surface pollution coefficient according to the weight coefficients to obtain a target pollution coefficient, inquiring a pollution level corresponding to the target pollution coefficient from a preset pollution level-coefficient mapping table, and determining the pollution level of the environment detection region according to the pollution level.
The weight coefficient is the importance degree corresponding to the air pollution coefficient and the surface pollution coefficient, the target pollution coefficient is a numerical value obtained by weighted summation of the air pollution coefficient and the surface pollution coefficient, and the preset pollution level-coefficient mapping table is a relation mapping table corresponding to the pollution level and the coefficient.
Further, the air pollution coefficient and the weight coefficient of the surface pollution coefficient can be distributed through the feature quantity occupied by the air part and the surface part in the regional feature, and the weighted summation of the air pollution coefficient and the surface pollution coefficient can be achieved through a weighted summation scoring method.
The invention combines the pollution level and the pollution source by respectively detecting the pollution sources corresponding to the air pollution and the ground surface pollution so as to generate the monitoring report of the environment monitoring area, so that the pollution condition of the environment monitoring area can be more intuitively known, wherein the pollution sources are the sources corresponding to the air pollution and the ground surface pollution, further, the pollution sources corresponding to the air pollution and the ground surface pollution can be respectively detected by an on-site investigation method and a geological analysis method, and the generation of the monitoring report of the environment monitoring area can be realized by a report generator which is compiled by a programming language.
According to the invention, the unmanned aerial vehicle equipment and the environment monitoring area to be patrolled are obtained, the area characteristics of the environment monitoring area are extracted, the characteristics of the environment monitoring area can be known, the automatic patrolling route of the unmanned aerial vehicle equipment is conveniently formulated subsequently, the image acquisition of the unmanned aerial vehicle equipment on the environment monitoring area is carried out according to the optimal patrolling route, the understanding of the environment monitoring area is conveniently increased through the acquired image, wherein the area acquisition image is an image obtained by shooting and acquiring the environment monitoring area by shooting equipment such as the unmanned aerial vehicle equipment, and the like; in addition, the invention combines the air pollution coefficient, the surface pollution coefficient and the regional characteristics to confirm the pollution level of the environment monitoring region, thereby facilitating the subsequent generation of the monitoring report of the environment monitoring region. Therefore, the environment monitoring method based on the unmanned aerial vehicle automatic patrol can improve the accuracy of the environment monitoring based on the unmanned aerial vehicle automatic patrol.
Fig. 2 is a functional block diagram of an environment monitoring system based on automatic unmanned aerial vehicle patrol according to an embodiment of the present invention.
The environment monitoring system 100 based on unmanned aerial vehicle automatic patrol can be installed in electronic equipment. According to the functions implemented, the environment monitoring system 100 based on unmanned aerial vehicle automatic patrol may include a route formulation module 101, an image processing module 102, a sonar detection module 103, and a pollution source detection module 104. The module of the invention, which may also be referred to as a unit, refers to a series of computer program segments, which are stored in the memory of the electronic device, capable of being executed by the processor of the electronic device and of performing a fixed function.
In the present embodiment, the functions concerning the respective modules/units are as follows:
the route making module 101 is configured to obtain an unmanned aerial vehicle device to be patrolled and an environment monitoring area, extract an area characteristic of the environment monitoring area, make an automatic patrolling route of the unmanned aerial vehicle device according to the area characteristic, calculate energy consumption of the unmanned aerial vehicle corresponding to the automatic patrolling route, and determine an optimal patrolling route of the unmanned aerial vehicle device according to the energy consumption of the unmanned aerial vehicle;
The image processing module 102 is configured to perform image acquisition of the environmental monitoring area by the unmanned aerial vehicle device according to the optimal patrol route, obtain an area acquisition image, and calculate an air pollution coefficient of the environmental monitoring area according to the area acquisition image;
the sonar detection module 103 is configured to transmit a sonar wave to the environmental monitoring area by using a sonar detector preset by the unmanned aerial vehicle device, receive a feedback result of the transmitted sonar wave, calculate a biological density of the environmental monitoring area according to the feedback result, and obtain a surface pollution coefficient of the environmental monitoring area according to the biological density;
the pollution source detection module 104 is configured to combine the air pollution coefficient, the surface pollution coefficient and the regional characteristics, confirm a pollution level of the environmental monitoring region, detect pollution sources corresponding to air pollution and surface pollution, and generate a monitoring report of the environmental monitoring region by combining the pollution level and the pollution sources.
In detail, each module in the environment monitoring system 100 based on the automatic unmanned aerial vehicle in the embodiment of the present application adopts the same technical means as the above-mentioned environment monitoring method based on the automatic unmanned aerial vehicle in fig. 1 when in use, and can produce the same technical effects, which are not repeated here.
Fig. 3 is a schematic structural diagram of an electronic device 1 for implementing an environment monitoring method based on unmanned aerial vehicle automatic patrol according to an embodiment of the present invention.
The electronic device 1 may comprise a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may further comprise a computer program stored in the memory 11 and executable on the processor 10, such as an environment monitoring method program based on unmanned aerial vehicle automatic patrol.
The processor 10 may be formed by an integrated circuit in some embodiments, for example, a single packaged integrated circuit, or may be formed by a plurality of integrated circuits packaged with the same function or different functions, including one or more central processing units (Central Processing Unit, CPU), a microprocessor, a digital processing chip, a graphics processor, a combination of various control chips, and so on. The processor 10 is a Control Unit (Control Unit) of the electronic device 1, connects respective parts of the entire electronic device using various interfaces and lines, executes or executes programs or modules stored in the memory 11 (for example, executes an environment monitoring method program based on unmanned aerial vehicle automatic patrol, etc.), and invokes data stored in the memory 11 to perform various functions of the electronic device and process data.
The memory 11 includes at least one type of readable storage medium including flash memory, a removable hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, etc. The memory 11 may in some embodiments be an internal storage unit of the electronic device, such as a mobile hard disk of the electronic device. The memory 11 may in other embodiments also be an external storage device of the electronic device, such as a plug-in mobile hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the electronic device. Further, the memory 11 may also include both an internal storage unit and an external storage device of the electronic device. The memory 11 may be used to store not only application software installed in an electronic device and various data, such as a code of an environment monitoring method program based on automatic unmanned aerial vehicle patrol, but also temporarily store data that has been output or is to be output.
The communication bus 12 may be a peripheral component interconnect standard (Peripheral Component Interconnect, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The bus may be classified as an address bus, a data bus, a control bus, etc. The bus is arranged to enable a connection communication between the memory 11 and at least one processor 10 etc.
The communication interface 13 is used for communication between the electronic device 1 and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and/or a wireless interface (e.g., WI-FI interface, bluetooth interface, etc.), typically used to establish a communication connection between the electronic device and other electronic devices. The user interface may be a Display (Display), an input unit such as a Keyboard (Keyboard), or alternatively a standard wired interface, a wireless interface. Alternatively, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light-Emitting Diode) touch, or the like. The display may also be referred to as a display screen or display unit, as appropriate, for displaying information processed in the electronic device and for displaying a visual user interface.
Fig. 3 shows only an electronic device with components, it being understood by a person skilled in the art that the structure shown in fig. 3 does not constitute a limitation of the electronic device 1, and may comprise fewer or more components than shown, or may combine certain components, or may be arranged in different components.
For example, although not shown, the electronic device 1 may further include a power source (such as a battery) for supplying power to each component, and preferably, the power source may be logically connected to the at least one processor 10 through a power management device, so that functions of charge management, discharge management, power consumption management, and the like are implemented through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The electronic device 1 may further include various sensors, bluetooth modules, wi-Fi modules, etc., which will not be described herein.
It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.
An environment monitoring method program based on unmanned aerial vehicle automatic patrol stored in the memory 11 of the electronic device 1 is a combination of a plurality of instructions, and when running in the processor 10, it can be implemented:
acquiring unmanned aerial vehicle equipment and an environment monitoring area to be patrolled, extracting area characteristics of the environment monitoring area, formulating an automatic patrolling route of the unmanned aerial vehicle equipment according to the area characteristics, calculating energy consumption of an unmanned aerial vehicle corresponding to the automatic patrolling route, and determining an optimal patrolling route of the unmanned aerial vehicle equipment according to energy consumption of the unmanned aerial vehicle;
According to the optimal patrol route, the unmanned aerial vehicle equipment performs image acquisition on the environment monitoring area to obtain an area acquisition image, and according to the area acquisition image, the air pollution coefficient of the environment monitoring area is calculated;
transmitting sonar waves to the environment monitoring area by using a sonar detector preset by the unmanned aerial vehicle equipment, receiving a feedback result of the transmitted sonar waves, calculating the biological density of the environment monitoring area according to the feedback result, and obtaining the surface pollution coefficient of the environment monitoring area according to the biological density;
and confirming the pollution level of the environment monitoring area by combining the air pollution coefficient, the surface pollution coefficient and the area characteristics, respectively detecting pollution sources corresponding to air pollution and surface pollution, and generating a monitoring report of the environment monitoring area by combining the pollution level and the pollution sources.
In particular, the specific implementation method of the above instructions by the processor 10 may refer to the description of the relevant steps in the corresponding embodiment of the drawings, which is not repeated herein.
Further, the modules/units integrated in the electronic device 1 may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as separate products. The computer readable storage medium may be volatile or nonvolatile. For example, the computer readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM).
The present invention also provides a computer readable storage medium storing a computer program which, when executed by a processor of an electronic device, can implement:
acquiring unmanned aerial vehicle equipment and an environment monitoring area to be patrolled, extracting area characteristics of the environment monitoring area, formulating an automatic patrolling route of the unmanned aerial vehicle equipment according to the area characteristics, calculating energy consumption of an unmanned aerial vehicle corresponding to the automatic patrolling route, and determining an optimal patrolling route of the unmanned aerial vehicle equipment according to energy consumption of the unmanned aerial vehicle;
according to the optimal patrol route, the unmanned aerial vehicle equipment performs image acquisition on the environment monitoring area to obtain an area acquisition image, and according to the area acquisition image, the air pollution coefficient of the environment monitoring area is calculated;
transmitting sonar waves to the environment monitoring area by using a sonar detector preset by the unmanned aerial vehicle equipment, receiving a feedback result of the transmitted sonar waves, calculating the biological density of the environment monitoring area according to the feedback result, and obtaining the surface pollution coefficient of the environment monitoring area according to the biological density;
And confirming the pollution level of the environment monitoring area by combining the air pollution coefficient, the surface pollution coefficient and the area characteristics, respectively detecting pollution sources corresponding to air pollution and surface pollution, and generating a monitoring report of the environment monitoring area by combining the pollution level and the pollution sources.
In the several embodiments provided in the present invention, it should be understood that the disclosed apparatus, device and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.
The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof.
The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference signs in the claims shall not be construed as limiting the claim concerned.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Furthermore, it is evident that the word "comprising" does not exclude other elements or steps, and that the singular does not exclude a plurality. A plurality of units or means recited in the system claims can also be implemented by means of software or hardware by means of one unit or means. The terms first, second, etc. are used to denote a name, but not any particular order.
Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.
Claims (10)
1. An environment monitoring method based on unmanned aerial vehicle automatic patrol, which is characterized by comprising the following steps:
acquiring unmanned aerial vehicle equipment and an environment monitoring area to be patrolled, extracting area characteristics of the environment monitoring area, formulating an automatic patrolling route of the unmanned aerial vehicle equipment according to the area characteristics, calculating energy consumption of an unmanned aerial vehicle corresponding to the automatic patrolling route, and determining an optimal patrolling route of the unmanned aerial vehicle equipment according to energy consumption of the unmanned aerial vehicle;
according to the optimal patrol route, the unmanned aerial vehicle equipment performs image acquisition on the environment monitoring area to obtain an area acquisition image, and according to the area acquisition image, the air pollution coefficient of the environment monitoring area is calculated;
transmitting sonar waves to the environment monitoring area by using a sonar detector preset by the unmanned aerial vehicle equipment, receiving a feedback result of the transmitted sonar waves, calculating the biological density of the environment monitoring area according to the feedback result, and obtaining the surface pollution coefficient of the environment monitoring area according to the biological density;
And confirming the pollution level of the environment monitoring area by combining the air pollution coefficient, the surface pollution coefficient and the area characteristics, respectively detecting pollution sources corresponding to air pollution and surface pollution, and generating a monitoring report of the environment monitoring area by combining the pollution level and the pollution sources.
2. The method for environmental monitoring based on automatic patrol of unmanned aerial vehicle according to claim 1, wherein the extracting the regional characteristics of the environmental monitoring region comprises:
acquiring surface data corresponding to the environment monitoring area, and acquiring an area map corresponding to the environment monitoring area;
extracting topographic indexes in the regional map, and calculating an index value of each index in the topographic indexes by combining the surface data to obtain topographic index values;
extracting features of the regional map according to the topographic index value and the topographic index value to obtain map features;
and determining the regional characteristics of the environment monitoring region according to the map characteristics.
3. The method for monitoring the environment based on the automatic patrol of the unmanned aerial vehicle according to claim 1, wherein the step of making the automatic patrol route of the unmanned aerial vehicle device according to the regional characteristics comprises the following steps:
Acquiring a monitoring task corresponding to the environment monitoring area, extracting a task requirement of the monitoring task, and detecting a meteorological environment of the environment monitoring area;
according to the task requirements and the meteorological environment, an initial route for the unmanned aerial vehicle equipment is established;
and extracting characteristic parameters of the regional characteristics, and carrying out route adjustment on the initial routing inspection route according to the characteristic parameters to obtain an automatic routing inspection route.
4. The method for monitoring the environment based on the automatic patrol of the unmanned aerial vehicle according to claim 1, wherein the calculating the energy consumption of the unmanned aerial vehicle corresponding to the automatic patrol route comprises:
the energy consumption of the unmanned aerial vehicle corresponding to the automatic routing is calculated through the following formula:
wherein T represents the maximum time value of the time slot T, C f Representing the wing area of unmanned aerial vehicle equipment, bt]Representing the corresponding speed of unmanned aerial vehicle equipment at the moment t, D 2 Representing the ratio of the resultant force of corresponding external forces of unmanned aerial vehicle equipment to the gravity of unmanned aerial vehicle equipment, A [ t ]]The acceleration corresponding to the unmanned plane equipment at the time t is represented, g represents the gravitational acceleration, and beta i Indicating the distance corresponding to the ith automatic patrol route, and Δp indicates the change of energy of the unmanned aerial vehicle device.
5. The method for monitoring the environment based on the automatic patrol of the unmanned aerial vehicle according to claim 1, wherein the performing the image acquisition of the unmanned aerial vehicle device on the environment monitoring area according to the optimal patrol route to obtain an area acquisition image comprises:
scheduling camera equipment of the unmanned aerial vehicle equipment, and acquiring images of the environment monitoring area by using the camera equipment according to the optimal patrol route to obtain initial acquired images;
carrying out noise reduction treatment on the initial acquisition image to obtain a noise reduction acquisition image;
performing de-duplication treatment on the noise reduction acquisition image to obtain a target acquisition image;
and performing image enhancement processing on the target acquisition image to obtain an area acquisition image.
6. The method for environmental monitoring based on unmanned aerial vehicle automatic patrol according to claim 1, wherein the calculating the air pollution coefficient of the environmental monitoring area according to the area acquired image comprises:
extracting image pixel points of the region acquisition image, and calculating brightness values corresponding to the image pixel points to obtain first brightness values;
acquiring a historical acquisition image of the environment monitoring area, extracting an image brightness value and a historical air pollution coefficient of the historical acquisition image, and calculating a proportionality coefficient of the image brightness value and the first brightness value to obtain a brightness proportionality coefficient;
Calculating an extinction coefficient of the area acquisition image, and calculating the suspended particulate matter concentration of the environment monitoring area by combining the brightness proportion coefficient and the extinction coefficient;
and determining the air pollution coefficient of the environment monitoring area by combining the suspended particulate matter concentration.
7. The method for environmental monitoring based on automatic drone cruising according to claim 6, wherein said calculating the suspended particulate matter concentration of the environmental monitoring area by combining the brightness scale factor and the extinction coefficient comprises:
calculating the suspended particulate matter concentration of the environment monitoring area by the following formula:
wherein F represents suspended particulate matter concentration of an environment monitoring area, n represents brightness proportionality coefficient, v represents RGB color channels of an area acquisition image, U v The light intensity attenuation coefficient of the v-th channel is represented by W, the diameter average value corresponding to the particulate matter is represented by T, the extinction coefficient is represented by T (vs), and the relationship function of the extinction coefficient T under the v-th channel with respect to the diameter average value W of the particulate matter is represented by T.
8. The method for environmental monitoring based on automatic unmanned aerial vehicle patrol according to claim 1, wherein the calculating the biological density of the environmental monitoring area according to the feedback result comprises:
Calculating an initial intensity value of biological contact between the sonar wave and the environment monitoring area, obtaining a feedback intensity value of the sonar wave and a contact area of the sonar wave according to the feedback result, and measuring the area of the environment monitoring area;
calculating a distance value between the unmanned aerial vehicle equipment and organisms in the environment monitoring area, inquiring a feedback loss coefficient corresponding to the sonar wave through a preset sonar wave loss coefficient table according to the distance value, and calculating a real feedback intensity value of the sonar wave by combining the initial intensity value, the feedback intensity value and the feedback loss coefficient;
calculating the intensity difference between the real feedback intensity value and the initial intensity value, and calculating the ratio of the contact area corresponding to the feedback intensity value to the area of the area when the intensity difference is larger than a preset threshold value to obtain an area proportionality coefficient;
and carrying out weighted summation on the area proportionality coefficients to obtain target coefficients, and taking the target coefficients as the biological density of the environment monitoring area.
9. The method for environmental monitoring based on unmanned aerial vehicle automatic patrol as claimed in claim 1, wherein said combining the air pollution coefficient, the surface pollution coefficient and the area characteristics to confirm the pollution level of the environmental monitoring area comprises:
According to the regional characteristics, distributing the weight coefficients of the air pollution coefficient and the surface pollution coefficient;
according to the weight coefficient, carrying out weighted summation on the air pollution coefficient and the surface pollution coefficient to obtain a target pollution coefficient;
inquiring the pollution level corresponding to the target pollution coefficient from a preset pollution level-coefficient mapping table, and confirming the pollution level of the environment monitoring area according to the pollution level.
10. An environmental monitoring system based on unmanned aerial vehicle automatic patrol, the system comprising:
the route making module is used for obtaining unmanned aerial vehicle equipment and an environment monitoring area to be patrolled, extracting area characteristics of the environment monitoring area, making an automatic patrolling route of the unmanned aerial vehicle equipment according to the area characteristics, calculating unmanned aerial vehicle energy consumption corresponding to the automatic patrolling route, and determining an optimal patrolling route of the unmanned aerial vehicle equipment according to the unmanned aerial vehicle energy consumption;
the image processing module is used for executing image acquisition of the unmanned aerial vehicle equipment on the environment monitoring area according to the optimal patrol route to obtain an area acquisition image, and calculating the air pollution coefficient of the environment monitoring area according to the area acquisition image;
The sonar detection module is used for transmitting sonar waves to the environment monitoring area by using a sonar detector preset by the unmanned aerial vehicle equipment, receiving a feedback result of the transmitted sonar waves, calculating the biological density of the environment monitoring area according to the feedback result, and obtaining the surface pollution coefficient of the environment monitoring area according to the biological density;
the pollution source detection module is used for combining the air pollution coefficient, the surface pollution coefficient and the regional characteristics, confirming the pollution level of the environment monitoring region, respectively detecting pollution sources corresponding to air pollution and surface pollution, and generating a monitoring report of the environment monitoring region by combining the pollution level and the pollution sources.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310473803.8A CN116225070A (en) | 2023-04-28 | 2023-04-28 | Environment monitoring method and system based on unmanned aerial vehicle automatic patrol |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310473803.8A CN116225070A (en) | 2023-04-28 | 2023-04-28 | Environment monitoring method and system based on unmanned aerial vehicle automatic patrol |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116225070A true CN116225070A (en) | 2023-06-06 |
Family
ID=86580837
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310473803.8A Pending CN116225070A (en) | 2023-04-28 | 2023-04-28 | Environment monitoring method and system based on unmanned aerial vehicle automatic patrol |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116225070A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116359218A (en) * | 2023-06-02 | 2023-06-30 | 北京建工环境修复股份有限公司 | Industrial aggregation area atmospheric pollution mobile monitoring system |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104020088A (en) * | 2014-05-15 | 2014-09-03 | 清华大学深圳研究生院 | Method for obtaining concentration of particles in air based on image processing |
| CN104749077A (en) * | 2015-03-31 | 2015-07-01 | 无锡市崇安区科技创业服务中心 | Suspension particle concentration detection system based on ultrasonic waves |
| CN108645769A (en) * | 2018-06-05 | 2018-10-12 | 广州市荣盛环保科技有限公司 | A kind of environmental air quality monitoring method based on unmanned plane |
| CN109631860A (en) * | 2018-12-27 | 2019-04-16 | 南京理工大学 | Reservoir house refuse monitoring method and system based on unmanned plane |
| CN109814598A (en) * | 2019-02-25 | 2019-05-28 | 中国科学院地理科学与资源研究所 | The public airway net design method in unmanned plane low latitude |
| CN110006428A (en) * | 2019-01-21 | 2019-07-12 | 武汉大学 | A kind of overlay path method and device for planning based on unmanned plane energy |
| US10497129B1 (en) * | 2016-08-31 | 2019-12-03 | Amazon Technologies, Inc. | Image-based weather condition detection |
| CN111340804A (en) * | 2020-04-09 | 2020-06-26 | 山东大学 | Unmanned airship-based air quality machine vision online monitoring system and method |
| CN113063401A (en) * | 2021-03-26 | 2021-07-02 | 杨洪 | Unmanned aerial vehicle aerial survey system |
-
2023
- 2023-04-28 CN CN202310473803.8A patent/CN116225070A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104020088A (en) * | 2014-05-15 | 2014-09-03 | 清华大学深圳研究生院 | Method for obtaining concentration of particles in air based on image processing |
| CN104749077A (en) * | 2015-03-31 | 2015-07-01 | 无锡市崇安区科技创业服务中心 | Suspension particle concentration detection system based on ultrasonic waves |
| US10497129B1 (en) * | 2016-08-31 | 2019-12-03 | Amazon Technologies, Inc. | Image-based weather condition detection |
| CN108645769A (en) * | 2018-06-05 | 2018-10-12 | 广州市荣盛环保科技有限公司 | A kind of environmental air quality monitoring method based on unmanned plane |
| CN109631860A (en) * | 2018-12-27 | 2019-04-16 | 南京理工大学 | Reservoir house refuse monitoring method and system based on unmanned plane |
| CN110006428A (en) * | 2019-01-21 | 2019-07-12 | 武汉大学 | A kind of overlay path method and device for planning based on unmanned plane energy |
| CN109814598A (en) * | 2019-02-25 | 2019-05-28 | 中国科学院地理科学与资源研究所 | The public airway net design method in unmanned plane low latitude |
| CN111340804A (en) * | 2020-04-09 | 2020-06-26 | 山东大学 | Unmanned airship-based air quality machine vision online monitoring system and method |
| CN113063401A (en) * | 2021-03-26 | 2021-07-02 | 杨洪 | Unmanned aerial vehicle aerial survey system |
Non-Patent Citations (1)
| Title |
|---|
| 吴邦灿: "《旋翼无人机的建模、规划和控制》", 中国环境科学出版社, pages: 500 - 504 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116359218A (en) * | 2023-06-02 | 2023-06-30 | 北京建工环境修复股份有限公司 | Industrial aggregation area atmospheric pollution mobile monitoring system |
| CN116359218B (en) * | 2023-06-02 | 2023-08-04 | 北京建工环境修复股份有限公司 | Industrial aggregation area atmospheric pollution mobile monitoring system |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107808139B (en) | Real-time monitoring threat analysis method and system based on deep learning | |
| US20220343758A1 (en) | Data Transmission Method and Apparatus | |
| CN109935080B (en) | Monitoring system and method for real-time calculation of traffic flow on traffic line | |
| CN114332977A (en) | Key point detection method and device, electronic equipment and storage medium | |
| CN116225070A (en) | Environment monitoring method and system based on unmanned aerial vehicle automatic patrol | |
| CN116338608B (en) | Method, device, equipment and storage medium for adjusting detection angle of microwave radar | |
| CN116186594B (en) | Method for realizing intelligent detection of environment change trend based on decision network combined with big data | |
| CN113947188A (en) | Training method of target detection network and vehicle detection method | |
| CN113674355A (en) | Target identification and positioning method based on camera and laser radar | |
| CN114092920A (en) | Model training method, image classification method, device and storage medium | |
| CN111369760A (en) | Night pedestrian safety early warning device and method based on unmanned aerial vehicle | |
| CN112613438A (en) | Portable online citrus yield measuring instrument | |
| CN115200554A (en) | Unmanned aerial vehicle photogrammetry supervision system and method based on picture recognition technology | |
| CN114037821A (en) | Pollutant detection method, device, equipment and storage medium | |
| CN112529836A (en) | High-voltage line defect detection method and device, storage medium and electronic equipment | |
| CN112528825A (en) | Station passenger recruitment service method based on image recognition | |
| CN116561509A (en) | Urban vegetation overground biomass accurate inversion method and system considering vegetation types | |
| CN115479946A (en) | Pavement damage detection method, system, device and storage medium | |
| CN115984723A (en) | Road damage detection method, system, device, storage medium and computer equipment | |
| CN112231430A (en) | Map data management method and device | |
| CN116013018B (en) | Forest fire prevention early warning analysis method and system based on unmanned aerial vehicle detection | |
| CN112985823A (en) | Testing device for simulating camera sensor | |
| CN113936134A (en) | Target detection method and device | |
| CN116189023B (en) | Method and system for realizing environment emergency monitoring based on unmanned aerial vehicle | |
| CN117615363B (en) | Method, device and equipment for analyzing personnel in target vehicle based on signaling data |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20230606 |
|
| RJ01 | Rejection of invention patent application after publication |