CN114638975A - Bird and non-bird repelling method and system for airport - Google Patents
Bird and non-bird repelling method and system for airport Download PDFInfo
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Abstract
The application relates to a bird and non-bird repelling method and a system for an airport, relating to the technical field of airport repelling, wherein the method comprises the steps of detecting the position of an invader in a designated area in real time by a radar and capturing the motion track of the invader; the detection equipment carries out real-time tracking shooting on the position and the motion track of the invader and acquires the image information of the invader; analyzing the image information of the invader to judge whether the invader is a bird or not; if the invader is a bird, controlling driving equipment corresponding to the invader of the bird to drive the invader; and if the invader is non-bird, controlling driving equipment corresponding to the non-bird invader to drive the invader. The application can realize the targeted driving of birds and non-bird invaders, improve the success rate of driving and improve the driving effect.
Description
Technical Field
The application relates to the technical field of airport driving, in particular to a bird and non-bird driving method and system for an airport.
Background
In recent years, with the rapid development of aviation industry, many thousands of bird-hit events (hereinafter referred to as bird-hit events) occur every year around the world, so that the parts of the airplane are damaged by light people, and the people are destroyed by heavy people. According to international authorities, the direct loss caused by the annual aviation events of the bird strike events in recent years is more than 20 billion dollars, and the indirect loss caused by the annual aviation events of the bird strike events is more immeasurable. Therefore, the international aviation union has classified the damage caused by bird strike as a class a aviation disaster, and besides the threat of birds to airplane flight, some low and slow non-birds similar to kites, aircrafts and the like also pose a certain threat to airplane flight, so that the driving of birds and non-birds (hereinafter referred to as invaders) by airports has become an important research content of airport work to ensure the safety of airplane flight.
The mode of driving away to airport invading thing among the prior art is mostly the position through surveying the invading thing, and then uses the equipment of driving away to the invading thing and drives, but such mode of driving away has blindness nature, and the success rate of driving away is lower, and the effect of driving away is relatively poor.
Disclosure of Invention
The application provides a bird and non-bird repelling method and system for an airport, which can realize targeted repelling of birds and non-bird invaders, improve the success rate of repelling and improve the repelling effect.
In a first aspect, the present application provides a method for bird and non-bird repelling in an airport, using the following technical solution:
a method of avian and non-avian repellency for airports comprising:
detecting the position of an invader in a designated area in real time by a radar and capturing the motion track of the invader;
the detection equipment carries out real-time tracking shooting on the position and the motion track of the invader and acquires the image information of the invader;
analyzing the image information of the invader to judge whether the invader is a bird or not;
if the invader is a bird, controlling driving equipment corresponding to the invader of the bird to drive the invader;
and if the invader is non-bird, controlling driving equipment corresponding to the non-bird invader to drive the invader.
By adopting the technical scheme, the radar detects the position of the invader in the designated area in real time and captures the motion track of the invader; the detection equipment is right the position and the motion track of the invader are tracked and shot in real time, the image information of the invader is collected, then the image information of the invader is analyzed, whether the invader is a bird is judged, if the invader is a bird, the driving equipment corresponding to the invader of the bird is controlled, if the invader is a non-bird, the driving equipment corresponding to the invader of the non-bird is controlled, the invader is driven, by adopting the method, the invader can be positioned by radar, the detection equipment is shot, the bird and the non-bird invader are judged by image analysis, the driving equipment corresponding to the bird and the non-bird is matched, a passive driving mode is changed into active detection and targeted driving, and in conclusion, the airport bird and non-bird driving method can realize targeted driving of the bird and the non-bird, the driving success rate is improved, and the driving effect is improved.
In another possible implementation manner, if the invader is a bird, controlling a driving device corresponding to the bird invader, driving the invader, and then further including:
further judging the specific bird species of the invaders based on the fact that the invaders are birds;
and controlling driving equipment corresponding to the bird species based on the specific bird species of the invader to drive the invader in a targeted manner.
Through adopting above-mentioned technical scheme, based on the concrete bird species of invader, the pertinence match with the equipment of driving that the bird looks corresponds can abandon traditional different bird species but has relative unified equipment of driving, the mode of driving, and the pertinence of driving the bird is stronger, and it is better to drive the bird effect, and the potential safety hazard that causes the airport is lower.
In another possible implementation manner, the radar detects the position of the intruding object in the designated area in real time and captures a motion track of the intruding object, and the method includes:
establishing a space coordinate system for a driving area, wherein the driving area is an area along two sides of an airport runway, the center of the airport runway is taken as an original point, the direction along the airport runway is a y axis, the horizontal direction vertical to the airport runway is an x axis, and the direction vertical to the airport runway and pointing to the sky is a z axis;
dividing the driving area into a plurality of blocks on the basis of the space coordinate system;
and determining the deployment modes of the N driving devices in the blocks based on the blocks and by combining the device types and the optimal working radiuses of the N driving devices.
By adopting the technical scheme, the space coordinate system is built for the airport, the airport driving area is divided into blocks, and corresponding driving equipment is deployed in each block in a targeted manner, so that the N types of driving equipment can fully cover the driving area.
In another possible implementation manner, the image information of the intruding object comprises a body state contour, an activity area and the number of the intruding objects.
By adopting the technical scheme, the image information of the invader comprises the body state contour, the activity area and the number of the invader, so that the image information of the invader can be analyzed more dimensionally and more comprehensively, and a theoretical basis is provided for the subsequent judgment of the invader.
In another possible implementation manner, the analyzing the image information of the intruding object to determine whether the intruding object is a bird specifically includes:
extracting image information of the invader;
calculating a characteristic value based on the image information of the invader;
if the characteristic value is smaller than a first preset value, determining that the invader is a non-bird;
and if the characteristic value is not less than a first preset value, determining that the invader is a bird.
By adopting the technical scheme, the image information of the invader is extracted, the characteristic value is calculated based on the image information of the invader, if the characteristic value is smaller than the first preset value, the invader is determined to be non-birds, if the characteristic value is not smaller than the first preset value, the invader is determined to be birds, whether the invader is birds or not is determined, different driving equipment is adopted, and the driving pertinence is stronger.
In another possible implementation manner, if the characteristic value is not less than the first preset value, it is determined that the invader is a bird, and then the method further includes:
and if the invader is determined to be the bird, determining the specific bird species of the invader according to the convolutional neural network.
By adopting the technical scheme, after the invader is determined to be the bird, the specific bird species of the invader is determined according to the convolutional neural network, and the driving equipment corresponding to the specific bird species is matched through further subdividing the bird species, so that the driving effect is better.
In another possible implementation manner, if it is determined that the invader is a bird, determining a specific bird species of the invader according to a convolutional neural network, and then further including:
determining a risk level for the bird species based on the specific bird species of the invader;
matching a corresponding driving device based on the hazard level.
By adopting the technical scheme, after the specific bird species of the invader is determined, the danger level of the bird species is determined, wherein the danger level refers to the danger level of the danger probability caused to the airplane, which is divided according to the habit, flight area, flight height, intelligence quotient and the like of the bird species, and the adopted driving equipment is determined according to the danger level of the bird species.
In a second aspect, the present application provides a bird and non-bird repelling system for airports, employing the following technical solution:
a bird and non-bird repelling system for an airport comprising:
the acquisition module is used for acquiring the position of the invader and the motion track of the invader;
the information receiving module is used for receiving the image information of the invader;
the first analysis module is used for analyzing the image information of the invader and judging whether the invader is a bird or not;
the first driving module is used for controlling driving equipment corresponding to the bird invaders to drive the invaders if the invaders are birds;
and the second driving module is used for controlling the driving equipment corresponding to the non-bird invaders if the invaders are non-birds, and driving the invaders.
Through adopting above-mentioned technical scheme, the acquisition module acquires the position of invading thing and the motion trail of invading thing, information receiving module receives the image information of invading thing, first analysis module carries out the analysis to the image information of invading thing, judge whether the invading thing is birds, if the invading thing is birds, then first module of driving drives birds invading thing, if the invader is non-birds, then the second module of driving drives non-birds invading thing, use this method can distinguish birds invading thing and non-birds invading thing, and match corresponding driving equipment, realize the pertinence driving to birds and non-birds invading thing.
In another possible implementation manner, the system further includes:
the second analysis module is used for further judging the specific bird species of the invaders based on the fact that the invaders are birds;
and the third driving module is used for controlling driving equipment corresponding to the bird species based on the specific bird species of the invader, and performing targeted driving on the invader.
In another possible implementation manner, the system further includes:
the modeling module is used for establishing a space coordinate system for the driving area, the center of the airport runway is taken as an original point, the direction along the airport runway is taken as an axis y, the horizontal direction vertical to the airport runway is taken as an axis x, the direction vertical to the airport runway and pointing to the sky is taken as an axis z, and the driving area is the area along the two sides of the airport runway;
the dividing module is used for dividing the driving area into a plurality of blocks on the basis of a space coordinate system;
and the deployment module is used for determining the deployment modes of the N driving devices in the blocks based on the blocks and by combining the device types and the optimal working radiuses of the N driving devices.
In another possible implementation manner, the information receiving module is specifically configured to:
and acquiring the body state contour, the activity area and the quantity of the invaders based on the acquired image information of the invaders.
In another possible implementation manner, the first analysis module is used for analyzing the image information of the invader and judging whether the invader is a bird, and is specifically used for:
extracting image information of the invader;
calculating a characteristic value based on the image information of the invader;
if the characteristic value is smaller than a first preset value, determining that the invader is a non-bird;
and if the characteristic value is not less than a first preset value, determining that the invader is a bird.
In another possible implementation manner, after the first analysis module analyzes the image information of the invader and determines that the invader is a bird, the second analysis module further determines the bird species, and is specifically configured to:
and if the invader is determined to be the bird, determining the specific bird species of the invader according to the convolutional neural network.
In another possible implementation manner, the system further includes:
a first determining module, configured to determine a risk level of the bird species based on a specific bird species of the invader;
and the fourth driving module is used for matching the corresponding driving equipment based on the danger level.
In a third aspect, the present application provides an electronic device, which adopts the following technical solutions:
an electronic device, comprising:
one or more processors;
a memory;
one or more application programs, wherein the one or more application programs are stored in the memory and configured to be executed by the one or more processors, the one or more application programs configured to: a method of bird and non-bird repelling for an airport according to any one of the possible implementations of the first aspect is performed.
In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solutions:
a computer-readable storage medium, comprising: there is stored a computer program that can be loaded by a processor and that executes a method for bird and non-bird repelling for airports, as shown in any one of the possible implementations of the first aspect.
In summary, the present application includes at least one of the following beneficial technical effects:
1. the electronic equipment acquires the position of an invader in an appointed area and captures the motion track of the invader, then shoots the position and the motion track of the invader, acquires the image information of the invader, then analyzes the image information of the invader, judges whether the invader is a bird, if the invader is a bird, controls the driving equipment corresponding to the bird invader, drives the invader if the invader is a non-bird, controls the driving equipment corresponding to the non-bird invader, drives the invader, can carry out radar positioning and detection equipment shooting on the invader by adopting the method, judges the bird and the non-bird invader by image analysis, and matches the corresponding driving equipment with the image analysis, changes a passive driving mode into active detection and targeted driving, in conclusion, the bird and non-bird repelling method for the airport can realize the targeted repelling of the invaders of birds and non-birds, improve the success rate of the repelling and improve the repelling effect;
2. electronic equipment is based on the invading thing is birds, further judges the concrete bird species of invading thing, based on the concrete bird species of invading thing, the pertinence match with the equipment of driving that the bird looks correspondence can abandon traditional different bird species but has the equipment of driving of relative unity, drive the mode, and the pertinence of driving the bird is stronger, drives the bird effect better, and the potential safety hazard that causes the airport is lower.
Drawings
FIG. 1 is a schematic flow diagram of a bird and non-bird repelling method for an airport according to an embodiment of the present application;
FIG. 2 is a schematic flow diagram of a bird and non-bird repelling system for an airport according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
The present application is described in further detail below with reference to figures 1-3.
A person skilled in the art, after reading the present specification, may make modifications to the present embodiments as necessary without inventive contribution, but only within the scope of the claims of the present application are protected by patent laws.
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
In addition, the term "and/or" herein is only one kind of association relationship describing the association object, and means that there may be three kinds of relationships, for example, a and/or B, and may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship, unless otherwise specified.
The embodiments of the present application will be described in further detail with reference to the drawings attached hereto.
The embodiment of the application provides a bird and non-bird repelling method for an airport, which is executed by electronic equipment, wherein the electronic equipment can be a server or terminal equipment, the server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, and a cloud server for providing cloud computing service. The terminal device may be a smart phone, a tablet computer, a notebook computer, a desktop computer, etc., but is not limited thereto, the terminal device and the server may be directly or indirectly connected through a wired or wireless communication manner, and the embodiment of the present application is not limited thereto, as shown in fig. 1, the method includes step S101, step S102, step S103, step S104, and step S105, wherein,
and S101, detecting the position of the invader in the designated area in real time by using a radar and capturing the motion track of the invader.
For the embodiment of the application, the position of the invader in the designated area is detected in real time through a radar and the motion trail of the invader is captured, wherein the designated area refers to the universe where the aircraft can affect the flight in the take-off and landing processes of the aircraft, and can include areas where the aircraft can or can possibly approach, such as an aircraft runway, a runway safety belt and the like, and can also include airspace such as a wasteland at the periphery of an airport, a farmland and the like; the radar provides comprehensive detection from the ground to the range of the flying height of the airplane, the detection comprises omnibearing invader detection in the horizontal direction and the vertical direction, the position of the invader is tracked and locked, one or a plurality of radars can be adopted in the embodiment, and the airport situation and the economic cost comprehensive evaluation are specifically required to be combined.
And S102, the detection equipment tracks and shoots the position and the motion track of the invader in real time and collects the image information of the invader.
For the embodiment of the application, the detection device can receive the position condition of the invader transmitted by the radar in real time through a 5G network or a wireless network, track the position and the motion track of the invader in real time and acquire the image information of the shot invader, and then transmit the image information of the invader to the electronic device in real time through the 5G network and transmit the image information of the invader to the electronic device in real time through the wireless network, which is not limited herein; in addition, the detection device can be a photoelectric detection device based on three cameras, the tracking lens can adopt a wide-angle lens and a zoom lens, and meanwhile, the tracking lens is also provided with an infrared detector for ensuring the working capacity in the daytime and at night.
And step S103, analyzing the image information of the invader, and judging whether the invader is a bird or not.
For the embodiment of the application, the electronic device analyzes the image information of the invader, wherein the image information specifically includes the body state contour, the activity area and the number of the invader, and may further include the motion speed, the motion attitude and the behavior, the analysis result judges whether the invader is a bird, taking the bird as an example, the image information of the bird just includes the body state contour of the bird, the flight speed of the bird, the flight attitude of the bird, the activity area of the bird, the gathering number of the bird and the behavior of the bird (perching, foraging, flying through and the like).
And step S104, if the invader is a bird, controlling driving equipment corresponding to the invader of the bird, and driving the invader.
For the embodiment of the application, if the invaders are birds, the electronic equipment controls the driving equipment corresponding to the invaders of the birds to drive the invaders, and here, if the birds are used as the invaders, the driving equipment is divided into sound driving, ultrasonic driving, visual driving and physical driving according to different driving types, and the main driving equipment for driving by corresponding sound comprises a gas cannon bird repeller and a whistle bird repeller; the main driving equipment for ultrasonic driving comprises a directional sound wave bird repeller and an omnidirectional sound wave bird repeller; the main driving equipment for visual driving comprises an eagle model and a dummy model; the main driving equipment for physical driving, including bird nets and bird-preventing electric fences, may be more selected, but not limited thereto.
And S105, if the invader is non-bird, controlling driving equipment corresponding to the non-bird invader to drive the invader.
For the embodiment of the application, if the invaders are non-birds, the electronic device controls the driving device corresponding to the non-bird invaders to drive the invaders, and here, if the non-birds are used as the invaders, the driving device is divided into chemical driving and driving vehicles (manual intervention) according to different driving types, and it needs to be explained that the non-bird invaders comprise ground organisms and manually controlled flyers; can take the mode of driving that drives car (manual intervention) to artificial type of controlling flight thing, for example drive the on-vehicle personnel of driving of transporting, the manual work is hit the kite off, can adopt radio frequency interference's mode to unmanned aerial vehicle to reach the purpose of driving, above-mentioned equipment of driving can have more choices, is not limited to this.
In a possible implementation manner of the embodiment of the present application, the method further includes step S106 (not shown in the figure) and step S107 (not shown in the figure), wherein,
and step S106, further judging the specific bird species of the invaders based on the invaders as the birds.
For the embodiment of the application, based on that the invader is a bird, the electronic device judges the specific bird species of the invader, such as crow, sparrow, and the like, and the electronic device inputs the acquired image information of the bird species into the trained convolutional neural network model to perform contour feature recognition on the image of the bird species, so that the contour feature of the bird species is obtained, the specific identity information of the bird species is determined, and the specific bird species is determined.
For example: the electronic equipment inputs the acquired image information of the current bird species into the trained convolutional neural network model, carries out contour feature recognition on the image of the current bird species so as to obtain contour features of the current bird species, compares the contour features of the current bird species with a plurality of bird species models in the trained convolutional neural network model according to the contour features of the bird species, and determines that the current bird species is crow if the contour features of the current bird species are overlapped with the contour features of a certain specific bird species in the convolutional neural network model, for example, the contour features of the current bird species are overlapped with the contour features of the crow.
And S107, controlling driving equipment corresponding to the bird species based on the specific bird species of the invader, and performing targeted driving on the invader.
For the embodiment of the application, the electronic equipment controls the driving equipment corresponding to the specific bird species based on the specific bird species of the invader to drive the invader in a targeted manner, and here, the connection between the specific bird species and the corresponding driving equipment is explained, and according to the difference of the bird species, part of the bird species are sensitive to sound, so that the bird species are driven by matching with a gas gun bird repeller or a whistle bird repeller, and the driving effect is better; part of bird species are sensitive to sound waves, so that the bird repeller is matched with the directional sound wave repeller or the omnidirectional sound wave repeller to repel, and the repelling effect is better; some bird species are sensitive in vision, so that the bird species are driven by matching with a vision threatening mode such as an eagle model or a dummy model, and the driving effect is better; and part of bird species can be directly intercepted by the bird-preventing net or the bird-preventing electric fence.
In a possible implementation manner of the embodiment of the present application, the method further includes step S108 (not shown in the figure), step S109 (not shown in the figure), and step S110 (not shown in the figure), wherein,
and step S108, establishing a space coordinate system for the driving area, wherein the driving area is an area along two sides of the airport runway, the center of the airport runway is taken as an original point, the direction along the airport runway is taken as an axis y, the horizontal direction vertical to the airport runway is taken as an axis x, and the direction vertical to the airport runway and pointing to the sky is taken as an axis z.
For the embodiment of the application, the electronic device establishes a spatial coordinate system for the driving area, specifically, the driving area is an area along both sides of the airport runway, and the driving area is a part of the designated area in step S101, that is, the designated area completely covers the driving area and covers more areas except the driving area, with the center of the airport runway as an origin, the direction along the airport runway as a y-axis, the horizontal direction perpendicular to the airport runway as an x-axis, and the direction perpendicular to the airport runway and pointing to the sky as a z-axis.
Step S109, dividing the driving area into a plurality of blocks based on the space coordinate system.
For the embodiment of the application, after the spatial coordinate system is established in step S108, the driving area is divided into a plurality of blocks based on the spatial coordinate system, so as to deploy corresponding driving equipment in each block.
And step S110, determining the deployment modes of the N driving devices in the blocks based on the blocks and by combining the device types and the optimal working radiuses of the N driving devices.
For the embodiment of the present application, based on the N types of driving devices mentioned in the above steps S104 and S105 but not limited thereto, the driving devices are deployed in each block correspondingly based on the plurality of blocks, and the deployment manner may be deployed according to the device types and the optimal working radii of the N types of driving devices, and may also be deployed correspondingly according to the flight trajectory of the intruder (taking bird intruder as an example), where the flight trajectory refers to the conventional flight path of birds under a large data sample, for example: taking the waiting bird as an example, in the relatively fixed time quantum of every year, the waiting bird can pass through the airport with relatively fixed flight route, and for this embodiment, the waiting bird can pass through the designated area with relatively fixed flight route, more specifically can pass through the driving area, from this, based on big data sample, can dispose corresponding equipment of driving (voice drives, ultrasonic wave drives, vision drives and physics drives) in the block that the driving area of waiting bird route corresponds, realizes better driving effect.
In a possible implementation manner of the embodiment of the present application, the analyzing is performed in step S103 based on the image information of the intruding object to determine whether the intruding object is a bird, and the method specifically includes step S1031 (not shown in the figure), step S1032 (not shown in the figure), step S1033 (not shown in the figure), and step S1034 (not shown in the figure), wherein,
step S1031 extracts image information of the intruding object.
For the embodiment of the application, the electronic equipment acquires the image information of an invader, when the invader has posture change, the image corresponding to the posture change moment is obviously different from the image corresponding to the previous moment, the electronic equipment calculates the similarity of the two images at the moment, each image can generate a gray image histogram, if the gray image histograms of the two images are very close, the similarity of the two images is determined to be very high, and at the moment, the electronic equipment randomly selects any one of the two images and extracts the image information of the image; and if the difference of the gray level image histograms of the two images is large, determining that the similarity of the two images is low, and at the moment, respectively acquiring the image information of the two images by the electronic equipment to jointly serve as the image sample of the invader.
In step S1032, a feature value is calculated based on the image information of the intruding object.
For the embodiment of the application, the electronic device inputs image information into a trained convolutional neural network model for image recognition, color filtering is performed on an invader in the image information through the gray value of the image information, the boundary contour of the invader is extracted, contour information of the invader is obtained, feature extraction is performed on the contour information, the contour information is divided into 5 contour blocks, and feature values are calculated based on the 5 contour blocks. For example:
the first contour block eigenvalue is 10;
the second contour block eigenvalue is 10;
the third macroblock eigenvalue is 10;
the fourth macroblock eigenvalue is 10;
the fifth macroblock feature value is 10.
And step S1033, if the characteristic value is smaller than the first preset value, determining that the invader is a non-bird.
For the embodiment of the present application, assuming that the first preset value is 25, taking step S1032 as an example, if the first feature value of the profile block is 4, the second feature value of the profile block is 5, the third feature value of the profile block is 4, the fourth feature value of the profile block is 5, and the fifth feature value of the profile block is 4, the current feature value is: 4+5+4+5+4=22, and the eigenvalue 22 is less than the first preset value 25, then the electronic device determines that the intruder is a non-bird.
And S1034, if the characteristic value is not less than the first preset value, determining that the invader is a bird.
For the embodiment of the present application, assuming that the first preset value is 25, taking step S1032 as an example,
if the first contour block eigenvalue is 4, the second contour block eigenvalue is 6, the third contour block eigenvalue is 5, the fourth contour block eigenvalue is 5, and the fifth contour block eigenvalue is 5, then the current eigenvalue is: 4+6+5+5+5=25, and the eigenvalue 25 is equal to the first preset value 25, the electronic device determines that the invader is a bird;
if the first contour block eigenvalue is 6, the second contour block eigenvalue is 8, the third contour block eigenvalue is 7, the fourth contour block eigenvalue is 9, and the fifth contour block eigenvalue is 7, then the current eigenvalue is: 6+8+7+9+7=37, and the eigenvalue 37 is greater than the first preset value 25, the electronic device determines that the invader is a bird.
In a possible implementation manner of the embodiment of the present application, the method further includes a step S111 (not shown in the figure) and a step S112 (not shown in the figure), wherein,
and step S111, determining the danger level of the bird species based on the specific bird species of the invader.
For the embodiment of the application, taking step S106 as an example, after the specific bird species of the invader is determined, the electronic device inputs the image information of the specific bird species into the trained convolutional neural network model to perform danger level identification, and determines the danger level of the current bird species, where the danger level of the bird species refers to a danger degree causing a substantial threat to the take-off and landing flight of the aircraft, and is divided into a first level and a second level, where the first level indicates that the danger level is high, and the second level indicates that the danger level is low.
And step S112, matching the corresponding driving equipment based on the danger level.
To this application embodiment, the electronic equipment drives the bird species based on the corresponding equipment of driving of danger level control of bird species, for example: similar to bird species such as pigeons, sparrows, swallows and the like, the bird species like flying back and forth at medium and low altitude, so the bird species easily threaten the safety of the airplane, the bird species are first-level danger levels, and based on the danger levels, the electronic equipment controls the driving equipment corresponding to the danger levels to drive the bird species; similar to bird species such as magpies, the bird species are better than low-altitude ground flying, so that the threat to the safety of the airplane by the bird species is relatively low, the bird species are secondary danger levels, and based on the danger levels, the electronic equipment controls the driving equipment corresponding to the danger levels to drive the bird species.
In addition, the corresponding driving modes are different according to the difference of the intelligence quotient of the bird species, such as: some birds with higher intelligence quotient take crow as an example, the crow can not actively impact an airplane, and when the airplane takes off and lands for flying, the birds similar to the crow have independent judgment consciousness or stronger danger judgment consciousness on danger, so the birds similar to the crow belong to a second-level danger level, and more birds with the second-level danger level are mainly threatened and are driven to be assisted; the quail is taken as an example of part of bird species with lower intelligence quotient, and the bird species have poor judgment consciousness on danger and disordered activities, so the bird species similar to the quail belongs to a first-level danger level, and the bird species with the first-level danger level should be mainly driven and assisted by frightening.
The above embodiments describe a bird and non-bird repelling method for airports from the perspective of the method flow, and the following embodiments describe a bird and non-bird repelling system for airports from the perspective of the virtual modules or virtual units, as described in detail in the following embodiments.
The present embodiment provides a bird and non-bird repelling system 20 for an airport, as shown in fig. 2, which the bird and non-bird repelling system 20 for an airport may specifically include:
an obtaining module 201, configured to obtain a position of an intruding object and a motion trajectory of the intruding object;
an information receiving module 202, configured to receive image information of an intruding object;
the first analysis module 203 is used for analyzing the image information of the invader and judging whether the invader is a bird or not;
the first driving module 204 is used for controlling driving equipment corresponding to the bird invaders to drive the invaders if the invaders are birds;
and the second driving module 205 is used for controlling driving equipment corresponding to the non-bird invaders to drive the invaders if the invaders are non-birds.
To this application embodiment, the position that module 201 obtained the invading thing and the motion track of invading thing, information receiving module 202 receives the image information of invading thing, first analysis module 203 carries out the analysis to the image information of invading thing, judge whether the invading thing is birds, if the invading thing is birds, first module 204 of driving drives birds invading thing, if the invading thing is non-birds, second module 205 of driving drives non-birds invading thing, use this method can distinguish birds invading thing and non-birds invading thing, and match corresponding equipment of driving, realize the pertinence and drive the bird, improve and drive the bird effect.
In a possible implementation manner of the embodiment of the present application, the system 20 further includes:
the second analysis module is used for further judging the specific bird species of the invaders based on the invaders as the birds;
and the third driving module is used for controlling driving equipment corresponding to the bird species based on the specific bird species of the invader to drive the invader in a targeted manner.
In a possible implementation manner of the embodiment of the present application, the system 20 further includes:
the modeling module is used for establishing a space coordinate system for the driving area, the center of the airport runway is taken as an original point, the direction along the airport runway is taken as an axis y, the horizontal direction vertical to the airport runway is taken as an axis x, the direction vertical to the airport runway and pointing to the sky is taken as an axis z, and the driving area is the area along the two sides of the airport runway;
the dividing module is used for dividing the driving area into a plurality of blocks on the basis of a space coordinate system;
and the deployment module is used for determining the deployment modes of the N driving devices in the blocks based on the blocks and by combining the device types and the optimal working radiuses of the N driving devices.
In a possible implementation manner of the embodiment of the present application, the information receiving module 202 is specifically configured to:
and acquiring the image information of the invader, including the body state contour, the activity area and the number of the invader, based on the acquired image information of the invader.
In a possible implementation manner of the embodiment of the application, the first analysis module 203 analyzes the image information of the invader, and determines whether the invader is a bird, and is specifically configured to:
extracting image information of an invader;
calculating a characteristic value based on the image information of the invader;
if the characteristic value is smaller than the first preset value, determining that the invader is a non-bird;
and if the characteristic value is not less than the first preset value, determining that the invader is a bird.
In a possible implementation manner of the embodiment of the application, the first analysis module 203 analyzes the image information of the invader, and after determining that the invader is a bird, the second analysis module further determines the bird species, which is specifically used for:
and if the invader is determined to be the bird, determining the specific bird species of the invader according to the convolutional neural network.
In a possible implementation manner of the embodiment of the present application, the system 20 further includes:
the first determination module is used for determining the danger level of the bird species based on the specific bird species of the invader;
and the fourth driving module is used for matching the corresponding driving equipment based on the danger level.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In an embodiment of the present application, an electronic device is provided, and as shown in fig. 3, an electronic device 30 shown in fig. 3 includes: a processor 301 and a memory 303. Wherein processor 301 is coupled to memory 303, such as via bus 302. Optionally, the electronic device 30 may also include a transceiver 304. It should be noted that the transceiver 304 is not limited to one in practical applications, and the structure of the electronic device 30 is not limited to the embodiment of the present application.
The Processor 301 may be a CPU (Central Processing Unit), a general-purpose Processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other Programmable logic device, a transistor logic device, a hardware component, or any combination thereof. Which may implement or perform the various illustrative logical blocks, modules, and circuits described in connection with the disclosure. The processor 301 may also be a combination of computing functions, e.g., comprising one or more microprocessors, a combination of a DSP and a microprocessor, or the like.
The Memory 303 may be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), a magnetic Disc storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired application code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to these.
The memory 303 is used for storing application program codes for executing the scheme of the application, and the processor 301 controls the execution. The processor 301 is configured to execute application program code stored in the memory 303 to implement the aspects illustrated in the foregoing method embodiments.
Among them, electronic devices include but are not limited to: mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. But also a server, etc. The electronic device shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
The present application provides a computer-readable storage medium, on which a computer program is stored, which, when running on a computer, enables the computer to execute the corresponding content in the foregoing method embodiments. Compared with the prior art, in the embodiment of the application, the electronic equipment acquires the position of the invader and the motion track of the invader, receives the image information of the invader, analyzes the image information of the invader, judges whether the invader is a bird or not, if the invader is a bird, drives the bird invader, and if the invader is a non-bird, drives the non-bird invader.
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and may be performed in other orders unless explicitly stated herein. Moreover, at least a portion of the steps in the flow chart of the figure may include multiple sub-steps or multiple stages, which are not necessarily performed at the same time, but may be performed at different times, which are not necessarily performed in sequence, but may be performed alternately or alternately with other steps or at least a portion of the sub-steps or stages of other steps.
The foregoing is only a few embodiments of the present application and it should be noted that those skilled in the art can make various improvements and modifications without departing from the principle of the present application, and that these improvements and modifications should also be considered as the protection scope of the present application.
Claims (10)
1. A method of bird and non-bird repelling for an airport comprising:
detecting the position of an invader in a designated area in real time by a radar and capturing the motion track of the invader;
the detection equipment carries out real-time tracking shooting on the position and the motion track of the invader and acquires the image information of the invader;
analyzing the image information of the invader to judge whether the invader is a bird or not;
if the invader is a bird, controlling driving equipment corresponding to the invader of the bird to drive the invader;
and if the invader is non-bird, controlling driving equipment corresponding to the non-bird invader to drive the invader.
2. A bird and non-bird repelling method for an airport according to claim 1 wherein if the invader is a bird, controlling a repelling device corresponding to the bird invader to repel the invader, and thereafter further comprising:
further judging the specific bird species of the invaders based on the fact that the invaders are birds;
and controlling driving equipment corresponding to the bird species based on the specific bird species of the invader to drive the invader in a targeted manner.
3. The method of claim 1, wherein the radar detects the location of the intruding object in a designated area and captures the trajectory of the intruding object in real time, and further comprising:
establishing a space coordinate system for a driving area, wherein the driving area is an area along two sides of an airport runway, the center of the airport runway is taken as an original point, the direction along the airport runway is taken as an axis y, the horizontal direction vertical to the airport runway is taken as an axis x, and the direction vertical to the airport runway and pointing to the sky is taken as an axis z;
dividing the driving area into a plurality of blocks on the basis of the space coordinate system;
and determining the deployment modes of the N driving devices in the blocks based on the blocks and by combining the device types and the optimal working radiuses of the N driving devices.
4. The method of claim 1, wherein the image information of the intruding object comprises a configuration profile, an activity area and a number of the intruding object.
5. The method according to claim 1, wherein the analyzing the image information of the invader to determine whether the invader is a bird comprises:
extracting image information of the invader;
calculating a characteristic value based on the image information of the invader;
if the characteristic value is smaller than a first preset value, determining that the invader is a non-bird;
and if the characteristic value is not less than a first preset value, determining that the invader is a bird.
6. The method of claim 5, wherein the determination that the invader is a bird is made if the characteristic value is not less than a first predetermined value, further comprising:
and if the invader is determined to be the bird, determining the specific bird species of the invader according to the convolutional neural network.
7. A bird and non-bird repelling method for an airport according to claim 6 wherein if said intruding object is determined to be a bird, then determining the specific species of said intruding object according to a convolutional neural network, further comprising:
determining a risk level for the bird species based on the specific bird species of the invader;
matching a corresponding driving device based on the hazard level.
8. A bird and non-bird repelling system for an airport comprising:
the acquisition module is used for acquiring the position of the invader and the motion track of the invader;
the information receiving module is used for receiving the image information of the invader;
the first analysis module is used for analyzing the image information of the invader and judging whether the invader is a bird or not;
the first driving module is used for controlling driving equipment corresponding to the bird invaders to drive the invaders if the invaders are birds;
and the second driving module is used for controlling the driving equipment corresponding to the non-bird invaders if the invaders are non-birds, and driving the invaders.
9. An electronic device, comprising:
one or more processors;
a memory;
one or more applications, wherein the one or more applications are stored in the memory and configured to be executed by the one or more processors, the one or more applications configured to: carrying out a method of bird and non-bird repelling for an airport according to any one of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, is adapted to carry out a bird and non-bird repelling method for airports as claimed in any one of claims 1 to 7.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115152733A (en) * | 2022-07-11 | 2022-10-11 | 国网江苏省电力有限公司南通市通州区供电分公司 | Bird repelling system based on image recognition |
| CN115868473A (en) * | 2022-11-25 | 2023-03-31 | 首都机场集团有限公司北京大兴国际机场 | Intelligent monitoring and preventing system for bird condition in airport |
| CN117368629A (en) * | 2023-08-24 | 2024-01-09 | 华能会理风力发电有限公司 | Power transmission line fault on-line monitoring system |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108710126A (en) * | 2018-03-14 | 2018-10-26 | 上海鹰觉科技有限公司 | Automation detection expulsion goal approach and its system |
| CN109799760A (en) * | 2019-01-30 | 2019-05-24 | 华通科技有限公司 | The bird-repellent robots control system and control method of power industry |
| CN109964917A (en) * | 2019-03-29 | 2019-07-05 | 芜湖市极星航空科技有限公司 | A kind of airport bird scaring linked system based on Internet of Things |
| CN110033490A (en) * | 2019-04-12 | 2019-07-19 | 南京理工大学 | A kind of low slow Small object preventing control method in airport based on photoelectric image automatic identification |
| CN113030978A (en) * | 2021-02-07 | 2021-06-25 | 中国民用航空总局第二研究所 | Airport ultra-low altitude bird detection and intelligent warning system and method |
| CN113486866A (en) * | 2021-09-06 | 2021-10-08 | 南京天朗防务科技有限公司 | Visual analysis method and system for airport bird identification |
| CN113892479A (en) * | 2021-10-09 | 2022-01-07 | 西安为开化工科技有限公司 | Mobile unmanned bird repelling robot and bird repelling method |
-
2022
- 2022-05-12 CN CN202210515292.7A patent/CN114638975A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108710126A (en) * | 2018-03-14 | 2018-10-26 | 上海鹰觉科技有限公司 | Automation detection expulsion goal approach and its system |
| CN109799760A (en) * | 2019-01-30 | 2019-05-24 | 华通科技有限公司 | The bird-repellent robots control system and control method of power industry |
| CN109964917A (en) * | 2019-03-29 | 2019-07-05 | 芜湖市极星航空科技有限公司 | A kind of airport bird scaring linked system based on Internet of Things |
| CN110033490A (en) * | 2019-04-12 | 2019-07-19 | 南京理工大学 | A kind of low slow Small object preventing control method in airport based on photoelectric image automatic identification |
| CN113030978A (en) * | 2021-02-07 | 2021-06-25 | 中国民用航空总局第二研究所 | Airport ultra-low altitude bird detection and intelligent warning system and method |
| CN113486866A (en) * | 2021-09-06 | 2021-10-08 | 南京天朗防务科技有限公司 | Visual analysis method and system for airport bird identification |
| CN113892479A (en) * | 2021-10-09 | 2022-01-07 | 西安为开化工科技有限公司 | Mobile unmanned bird repelling robot and bird repelling method |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115152733A (en) * | 2022-07-11 | 2022-10-11 | 国网江苏省电力有限公司南通市通州区供电分公司 | Bird repelling system based on image recognition |
| CN115868473A (en) * | 2022-11-25 | 2023-03-31 | 首都机场集团有限公司北京大兴国际机场 | Intelligent monitoring and preventing system for bird condition in airport |
| CN117368629A (en) * | 2023-08-24 | 2024-01-09 | 华能会理风力发电有限公司 | Power transmission line fault on-line monitoring system |
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