Bird repelling method and system for airport bird information based on intelligent detection

Abstract

The application discloses a bird driving method and system based on intelligent detection of airport bird information, the method comprising: acquiring current bird information data of an airport; determining an initial bird driving strategy; inputting the initial bird driving strategy and the bird information data into a driving time estimation model to predict an estimated driving time; calculating a time gap between the estimated driving end time and the scheduled take-off and landing time of an airplane; if the time gap is greater than a preset threshold, driving the birds according to the initial bird driving strategy, otherwise, adjusting the laser wavelength or the sound wave frequency on the basis of the initial bird driving strategy to generate a new bird driving strategy, re-predicting the estimated driving time in combination with the new bird driving strategy and acquiring the time gap, and stopping adjusting the laser wavelength and / or the sound wave frequency until the time gap is greater than the preset threshold, and driving the birds according to the new bird driving strategy. The application realizes automatic bird driving under consideration of airplane take-off and landing, and reduces the occurrence probability of bird strike events of airplanes.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of airport bird driving, aviation safety and wildlife management, in particular to a method and system for driving birds based on airport bird information detected by an intelligent probe. BACKGROUND

[0002] With the rapid development of the aviation industry, the threat of airport bird activity to aviation safety has attracted increasing attention. Currently, various bird driving technologies have been applied in airports, such as sound wave driving, visual driving, etc. These technologies have reduced the occurrence of bird strike events to some extent, but still have problems such as unstable effect, insensitivity to specific birds, etc.

[0003] Traditional airport bird driving methods mainly include using high-frequency loudspeakers to play the sounds of bird predators, setting bird nets, using chemical reagents, etc. These methods can drive birds to some extent, but often have problems such as short-lasting driving effect, environmental pollution, and impact on the surrounding ecology of the airport. In order to solve the above problems, existing technologies also disclose visual driving methods, ultrasonic driving methods, and combined driving methods of multiple methods, but most bird driving methods do not comprehensively consider the impact on aircraft takeoff and landing, and cannot automatically adjust the driving strategy to reduce the probability of aircraft being struck by birds. SUMMARY

[0004] In order to achieve automatic and intelligent bird driving considering aircraft takeoff and landing and reduce the probability of aircraft being struck by birds, the present application provides a method and system for driving birds based on airport bird information detected by an intelligent probe.

[0005] In a first aspect, the present application provides a method for driving birds based on airport bird information detected by an intelligent probe, comprising:

[0006] obtaining current bird information data in each region of the airport;

[0007] determining an initial bird driving strategy for each region according to the current bird information data of each region; the initial bird driving strategy includes a sound wave driving strategy of a certain frequency, a laser driving strategy of a certain wavelength, or a combined driving strategy of a certain frequency of sound wave and a certain wavelength of laser;

[0008] inputting the initial bird driving strategy in each region and the bird information data into a driving time estimation model to obtain the estimated driving time of the corresponding region; the driving time estimation model selects a neural network model trained based on historical bird driving information, the historical bird driving information including historical bird driving strategies, historical bird information data and corresponding historical driving times; and determining an estimated driving end time according to the estimated driving time of each region;

[0009] The estimated driving end time of each area is compared with the aircraft predicted takeoff and landing time. If the time difference between the estimated driving end time and the aircraft predicted takeoff and landing time is greater than a preset threshold, the bird is driven according to the initial bird driving strategy. Otherwise, the laser wavelength or the sound wave frequency is adjusted on the basis of the initial bird driving strategy to generate a new bird driving strategy. The new bird driving strategy is used to replace the initial bird driving strategy to re-predict the estimated driving time and obtain the estimated driving end time. The adjustment of the laser wavelength and / or the sound wave frequency is stopped until the estimated driving end time obtained is greater than the preset threshold. The bird is driven according to the new bird driving strategy.

[0010] By using the above scheme, the driving time estimation model is generated by using the historical bird driving strategy, the historical bird data and the historical driving time. The completion driving time of the bird driving strategy is determined by combining the current bird data. If the completion driving time does not meet the requirement of not affecting the takeoff and landing of the aircraft, the bird driving strategy is adjusted to shorten the bird driving time and further reduce the occurrence probability of the bird strike event of the aircraft.

[0011] Preferably, the method further comprises:

[0012] The current environment data in each area of the airport is obtained.

[0013] The historical bird driving information further comprises historical environment data. The environment data of each area, the initial bird driving strategy and the bird data are input into the driving time estimation model to obtain the estimated driving time of the corresponding area.

[0014] By using the above scheme, it is considered that the environment in the area (such as rainfall, wind direction data and wind speed data) also affects the driving time of the bird in addition to the sound wave frequency and the size of the laser wavelength. By considering the environment data, a more accurate driving time is predicted.

[0015] Preferably, the initial bird driving strategy of each area is determined according to the current bird data of each area, and the initial bird driving strategy of each area comprises:

[0016] When the number of birds in the area is less than a first preset number, a laser driving strategy of emitting a certain wavelength is selected. When the number of birds in the area is greater than the first preset number and less than a second preset number, a sound wave driving strategy of emitting a certain frequency is selected. When the number of birds in the area is greater than the second preset number, a combined driving strategy of emitting a certain frequency of sound wave and a certain wavelength of laser is selected.

[0017] The most common bird species in the area is counted. The laser wavelength or the sound wave frequency more sensitive to the counted bird species is selected from the laser wavelength range or the sound wave frequency range sensitive to the bird species as the laser wavelength or the sound wave frequency used in the initial bird driving strategy.

[0018] By adopting the above scheme, considering that the coverage of the sound wave driving strategy is wider than that of the laser driving strategy, more birds can be driven, so the driving strategy is selected according to the number of birds in the region to shorten the driving time; and since birds are typical representatives of gregarious animals, more birds affected by laser or sound waves will produce a chain reaction to speed up the driving time, so the bird species with the largest number is selected to be more sensitive to the laser wavelength or sound wave frequency.

[0019] Preferably, the determining of the initial bird driving strategy for each region according to the current bird data of each region comprises:

[0020] calculating the similarity between the current bird data of each region and the historical bird data corresponding to the successful bird driving before the scheduled take-off time of the aircraft in the same region in the same season, and selecting the historical bird data with the similarity within a preset similarity range;

[0021] obtaining the historical bird driving strategy corresponding to the selected historical bird data;

[0022] selecting the historical bird driving strategy with the highest repetition rate from the obtained historical bird driving strategies as the initial bird driving strategy.

[0023] By adopting the above scheme, considering that the bird migration in the same season has population commonality, the historical bird data with high similarity in the same season is selected, and the historical bird driving strategy corresponding to the successful bird driving before the scheduled take-off time of the aircraft is selected as the initial bird driving strategy to shorten the estimated driving time.

[0024] Preferably, the determining of the initial bird driving strategy for each region according to the current bird data of each region further comprises:

[0025] determining whether the sound wave driving strategy execution device and the laser driving strategy execution device in each region are in a fault state;

[0026] If the sound wave driving strategy execution device or the laser driving strategy execution device is in a fault state, the laser driving strategy or the sound wave driving strategy or the combined sound wave driving strategy is not selected according to the number of birds in the region, but the laser driving strategy or the sound wave driving strategy is determined according to the sound wave driving strategy execution device not in the fault state or the laser driving strategy execution device not in the fault state.

[0027] By adopting the above scheme, considering that the sound wave driving strategy execution device and the laser driving strategy execution device may fail, the driving strategy is directly set according to the device not in the fault state, and the actual execution feasibility of the driving strategy is ensured.

[0028] Preferably, the determining the initial bird driving strategy of each area according to the current bird data of each area further comprises:

[0029] checking the running state of the sound wave driving strategy execution device and the laser driving strategy execution device in each area;

[0030] if the corresponding sound wave driving strategy execution device and / or laser driving strategy execution device is in a running state and the running state is normal, and the bird species with the largest number in the statistical area is not sensitive to the laser wavelength range or the sound wave frequency range, the laser wavelength or the sound wave frequency more sensitive to the bird species is selected as the laser wavelength or the sound wave frequency used in the initial bird driving strategy, and the sound wave frequency emitted by the sound wave driving strategy execution device currently in the running state and the running state is normal and / or the laser wavelength emitted by the laser driving strategy execution device currently in the running state and the running state is normal is directly used as the laser wavelength and / or sound wave frequency used in the initial bird driving strategy;

[0031] otherwise, the bird species with the largest number in the statistical area is continuously counted, and the laser wavelength or the sound wave frequency more sensitive to the counted bird species is selected as the laser wavelength or the sound wave frequency used in the initial bird driving strategy.

[0032] By using the above scheme, the possibility of not timely closing the driving strategy execution device is considered, and the laser wavelength and / or sound wave frequency used by the last execution device is directly used to shorten the time for determining the initial bird driving strategy.

[0033] Preferably, the adjusting the laser wavelength and / or sound wave frequency on the basis of the initial bird driving strategy to generate a new bird driving strategy comprises:

[0034] counting the bird species with the largest number in the statistical area, and determining the laser wavelength and the sound wave frequency most sensitive to the bird species based on the biological characteristics of the bird species, and recording the laser wavelength and the sound wave frequency as the reference laser wavelength and the reference sound wave frequency, respectively;

[0035] correspondingly calculating the difference between the laser wavelength and / or sound wave frequency emitted in the initial bird driving strategy and the reference laser wavelength and the reference sound wave frequency, and recording the difference as the difference frequency and / or the difference wavelength;

[0036] setting the sound wave frequency for one-time adjustment and / or the laser wavelength for one-time adjustment according to the difference frequency and / or the difference wavelength, and completing the one-time adjustment of the laser wavelength and / or the sound wave frequency according to the sound wave frequency for one-time adjustment and / or the laser wavelength for one-time adjustment.

[0037] By adopting the above scheme, the adjustment benchmark of the sound wave frequency and the laser wavelength is determined according to the biological characteristics of the birds, so that the frequency or the wavelength is adjusted to be close to the benchmark each time, and the cost of emitting a stronger sound wave frequency and a stronger laser wavelength is reduced as much as possible, while the driving time requirement is met.

[0038] In a second aspect, the present application provides a bird driving method and system based on intelligent detection of airport bird information, comprising:

[0039] A bird data acquisition module acquires current bird data in each area of the airport.

[0040] An initial bird driving strategy determination module is configured to determine an initial bird driving strategy for each area according to the current bird data of each area. The initial bird driving strategy includes a sound wave driving strategy of a certain frequency, a laser driving strategy of a certain wavelength, or a combined driving strategy of a certain frequency of sound wave and a certain wavelength of laser.

[0041] A predicted driving end time acquisition module is configured to input the initial bird driving strategy and the bird data in each area into a driving time prediction model to obtain a predicted driving time for the corresponding area. The driving time prediction model is a neural network model trained based on historical bird driving information, including historical bird driving strategies, historical bird data, and corresponding historical driving times. The predicted driving end time is determined according to the predicted driving time of each area.

[0042] A final bird driving strategy selection module is configured to compare the predicted driving end time of each area with the scheduled takeoff and landing time of the aircraft. If the time difference between the predicted driving end time and the scheduled takeoff and landing time of the aircraft is greater than a preset threshold, the initial bird driving strategy is used to drive the birds. Otherwise, the laser wavelength and / or the sound wave frequency are adjusted based on the initial bird driving strategy to generate a new bird driving strategy. The new bird driving strategy is used to replace the initial bird driving strategy to re-predict the predicted driving time and obtain the predicted driving end time. The adjustment of the laser wavelength and / or the sound wave frequency is stopped until the time difference between the obtained predicted driving end time and the scheduled takeoff and landing time of the aircraft is greater than the preset threshold. The birds are driven according to the new bird driving strategy.

[0043] By adopting the above scheme, the bird driving strategy that does not affect the takeoff and landing of the aircraft is automatically generated considering the scheduled takeoff and landing time, and the probability of bird strike events is reduced.

[0044] In a third aspect, the present application provides a computer readable storage medium comprising a stored computer program, wherein the computer readable storage medium controls the device where the computer readable storage medium is located to execute the method as described above when the computer program is running.

[0045] In a fourth aspect, the present application provides a computer device, comprising a memory, a processor, and a program stored in the memory and executable by the processor, wherein the program, when executed by the processor, implements the steps of the method described above.

[0046] In summary, the present application has the following advantages:

[0047] 1. An initial bird driving strategy sensitive to bird species and quantity in current bird data is generated, and the driving time is predicted based on the initial bird driving strategy, bird data, and environmental data, and the initial bird driving strategy is adjusted to meet the bird driving strategy without affecting the scheduled takeoff and landing of the aircraft.

[0048] 2. The most sensitive laser wavelength and sound frequency of the bird species with the largest quantity in the current bird data are found based on the biological characteristics of the bird species, which are used as the adjustment direction to determine the adjustment scheme, so as to reduce the emission power as much as possible to save costs while meeting the adjusted bird driving strategy without affecting the scheduled takeoff and landing of the aircraft. BRIEF DESCRIPTION OF DRAWINGS

[0049] Figure 1 A flowchart of the bird driving method based on intelligent detection of airport bird information in the specific embodiment is shown.

[0050] Figure 2 A structural schematic diagram of the bird driving system based on intelligent detection of airport bird information in the specific embodiment is shown. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is further described in detail below in combination with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0052] As shown in Figure 1 The present application discloses a bird driving method based on intelligent detection of airport bird information, and the specific steps include:

[0053] S1, acquiring current bird data in each region of the airport.

[0054] Specifically, the airport is divided into several regions, and each region has a corresponding monitoring system. The monitoring system of each region collects images of the current region in real time, and monitors the bird data appearing in combination with image recognition technology.

[0055] The bird data includes information data such as the species of the bird, the quantity of the bird, the flight speed of the bird, and the flight position of the bird.

[0056] S2, determining an initial bird driving strategy for each region according to the current bird data of each region.

[0057] Specifically, the initial bird driving strategy of each area includes: a sound wave driving strategy of a certain frequency, a laser driving strategy of a certain wavelength, or a combination driving strategy of a certain frequency of sound wave and a certain wavelength of laser, etc.; wherein the certain sound wave frequency or the certain laser wavelength selected to occur is in the sensitive laser wavelength range or the sensitive sound wave frequency range of birds.

[0058] Considering that the coverage range of the sound wave driving strategy is wider than that of the laser driving strategy, when the number of birds is small, the laser driving strategy can be selected to drive the birds, so in the embodiment, determining the initial bird driving strategy of each area specifically includes:

[0059] Comparing the number of birds in the area with the first preset number and the second preset number; when the number of birds in the area is less than the first preset number, a laser driving strategy of a certain wavelength is selected; when the number of birds in the area is more than the first preset number and less than the second preset number, a sound wave driving strategy of a certain frequency is selected; when the number of birds in the area is more than the second preset number, a combination driving strategy of a certain frequency of sound wave and a certain wavelength of laser is selected; for example, the first preset number is selected as 20; the second preset number is selected in the range of 50.

[0060] Considering that birds have a certain sensitive laser wavelength range or sound wave frequency range, but the sensitive laser wavelength range or sound wave frequency range of each bird is different, and when more birds are affected by laser or sound wave and escape, it will correspondingly affect other birds to escape, so in the embodiment, determining the initial bird driving strategy of each area specifically includes:

[0061] The most common bird species in the area is counted, and the laser wavelength or sound wave frequency more sensitive to the counted bird species from the sensitive laser wavelength range or sound wave frequency range of birds is selected as the initial bird driving strategy. For example, the counted bird species is sparrow, and the sensitive sound wave range of sparrow is 1.3KHZ-2.5KHZ, and a sound wave frequency of 1.5KHZ is randomly selected in the range as the sound wave frequency of the initial bird driving strategy.

[0062] S3, based on the initial bird driving strategy and bird data prediction in each area at present, the driving time of the corresponding area is predicted.

[0063] Specifically, the initial bird driving strategy in each region and the bird data are input into the driving time estimation model to obtain the estimated driving time of the corresponding region. The driving time estimation model selects a neural network model, the input of which is the bird driving strategy and the bird data, and the output is the driving time. The driving time estimation model is specifically generated by training historical bird driving information, including historical bird driving strategies, historical bird data, and historical driving times corresponding to the historical bird driving strategies and the historical bird data. For example: a sound wave driving strategy of emitting a sound wave frequency of 1.5KHZ, 10 sparrows, a distance within a range of 5 meters from the boundary of the region, and a driving time of 3 minutes.

[0064] S4, determining the estimated driving end time of the corresponding region according to the estimated driving time of each region;

[0065] S5, comparing the estimated driving end time of each region with the estimated take-off and landing time of the aircraft to determine whether it affects the normal operation of the aircraft according to the estimated take-off and landing time.

[0066] Specifically, the estimated driving end time of each region is compared with the estimated take-off and landing time of the aircraft. If the time gap between the estimated driving end time and the estimated take-off and landing time of the aircraft is greater than a preset threshold, it is determined that it does not affect the normal operation of the aircraft according to the estimated take-off and landing time, and step S6 is turned to. Otherwise, it is determined that it affects the normal operation of the aircraft according to the estimated take-off and landing time, and step S7 is turned to.

[0067] In this embodiment, the preset threshold is set to 5 minutes.

[0068] S6, driving birds according to the initial bird driving strategy, and turning to S8 after completing the bird driving task.

[0069] S7, adjusting the laser wavelength or the sound wave frequency on the basis of the initial bird driving strategy to generate a new bird driving strategy, and turning to step S3 and replacing the initial bird driving strategy with the new bird driving strategy.

[0070] Specifically, the replacement means that the content of the initial bird driving strategy is replaced by the new bird driving strategy. Considering the biological characteristics of each bird, it is known that each bird is more sensitive to the range of laser wavelengths and the range of sound wave frequencies. The adjustment of the laser wavelength and / or the sound wave frequency on the basis of the initial bird driving strategy to generate a new bird driving strategy includes:

[0071] The most common bird species in the statistical area is determined based on the biological characteristics of the bird species to determine the most sensitive laser wavelength and sound frequency, respectively, as the reference laser wavelength and the reference sound frequency; for example: the most sensitive laser wavelength range of the sparrow is the green laser with a wavelength of 532 nm, and the wavelength of 532 nm is recorded as the reference laser wavelength. In addition, if some bird species only query the more sensitive laser wavelength range and the sound frequency range, the center value of the more sensitive laser wavelength range and the sound frequency range is respectively determined as the most sensitive laser wavelength and the sound frequency.

[0072] The difference between the laser wavelength and / or sound frequency emitted in the initial bird driving strategy and the reference laser wavelength and the reference sound frequency is calculated, and the difference frequency and / or the difference wavelength are recorded; for example: the laser wavelength emitted in the initial bird driving strategy is a red laser with a wavelength of 645 nm, and the difference wavelength is 13 nm.

[0073] According to the difference frequency and / or the difference wavelength, the adjusted sound frequency and / or the adjusted laser wavelength are set, and the adjustment of the laser wavelength and / or the sound frequency is completed according to the adjusted sound frequency and / or the adjusted laser wavelength. Wherein, the adjusted sound frequency and / or the adjusted laser wavelength can be set according to the fractional multiple (such as 1 / 2 times) of the difference frequency and / or the difference wavelength.

[0074] S8, record the bird driving strategy and bird data generated area bird driving record information taken by each successful bird driving before the predicted take-off and landing time of the aircraft in the area.

[0075] Specifically, for generating area bird driving record information, grouping is performed according to the species and quantity in the bird data, and the bird data and the bird driving strategy are stored according to the grouping, which is convenient for subsequent query.

[0076] In one specific embodiment, considering that environmental factors are also influencing factors for completing the bird driving task, in order to further accurately obtain the driving time, the method further comprises:

[0077] Obtain the current environmental data in each area of the airport; the environmental data includes: wind speed data, wind direction data, rainfall data and visibility data, etc.

[0078] The input of the driving time estimation model is adjusted to the bird driving strategy, the bird data and the environmental data, and the output is the driving time; the historical bird driving information is adjusted to: the historical bird driving strategy, the historical bird data, the historical environmental data and the historical driving time corresponding to the historical bird driving strategy, the historical bird data and the historical environmental data.

[0079] inputting the current environmental data of each area, the initial bird driving strategy and the bird data into the driving time estimation model to obtain the estimated driving time of the corresponding area.

[0080] In one specific embodiment, the bird species that usually complete migration in the same quarter are considered based on the bird species belonging to the same species or the same genus. The similar bird data can be selected from the historical bird data of the same quarter, and the driving strategy adopted according to the similar bird data that meets the requirement of not affecting the take-off and landing of the aircraft is taken as the initial bird driving strategy, so as to reduce the necessity of subsequent adjustment. In the method, the initial bird driving strategy of each area is determined according to the current bird data of each area, which specifically includes:

[0081] The similarity between the current bird data of each area and the historical bird data corresponding to the bird driving completed before the scheduled take-off time of the aircraft in the same quarter of the same area is calculated, and the historical bird data with the similarity within a preset similarity range is selected. In this embodiment, the preset similarity is set to 70%.

[0082] The historical bird driving strategy corresponding to the selected historical bird data is obtained.

[0083] The historical bird driving strategy with the highest repetition rate is selected as the initial bird driving strategy from the obtained historical bird driving strategies.

[0084] Among the selected historical bird driving strategies, the historical bird driving strategy with the highest repetition rate is selected as the initial bird driving strategy. If there are multiple historical bird driving strategies with the highest repetition rate, one of them can be randomly selected as the initial bird driving strategy.

[0085] In one specific embodiment, when determining the initial bird driving strategy, it is also necessary to consider whether the driving strategy execution device can be normally used to prevent the situation that the corresponding strategy cannot be executed. In the method, the initial bird driving strategy of each area is determined according to the current bird data of each area, which further includes:

[0086] It is determined whether the sound wave driving strategy execution device and the laser driving strategy execution device of each area are in a fault state.

[0087] If the sound wave driving strategy execution device or the laser driving strategy execution device is in a fault state, the laser driving strategy or the sound wave driving strategy or the combined sound wave driving strategy determined according to the number of birds in the area is not executed, but the laser driving strategy or the sound wave driving strategy is determined according to the sound wave driving strategy execution device not in a fault state or the laser driving strategy execution device not in a fault state.

[0088] In one specific embodiment, in addition to determining as accurate an initial bird repelling strategy as possible to reduce subsequent adjustments, the time for the final repelling strategy can be shortened by shortening the time for the initial bird repelling strategy as much as possible under the condition that the repelling device is not turned off in time after the previous repelling task is completed. In the method, determining the initial bird repelling strategy for each region according to the current bird data of each region further includes:

[0089] checking the operating states of the sound wave repelling strategy execution device and the laser repelling strategy execution device in each region;

[0090] According to the number of birds in the current bird data of each region, if the corresponding sound wave repelling strategy execution device and / or laser repelling strategy execution device is in an operating state and the operating state is normal, and the bird species with the largest number in the statistical region is not sensitive to the laser wavelength range or the sound wave frequency range, the laser wavelength or the sound wave frequency that is more sensitive to the bird species selected for statistics is selected as the laser wavelength or the sound wave frequency used in the initial bird repelling strategy. Instead, the sound wave frequency emitted by the sound wave repelling strategy execution device that is currently in an operating state and has a normal operating state and / or the laser wavelength emitted by the laser repelling strategy execution device that is currently in an operating state and has a normal operating state is directly used as the laser wavelength and / or the sound wave frequency used in the initial bird repelling strategy.

[0091] Otherwise, the laser wavelength or the sound wave frequency that is more sensitive to the bird species selected for statistics is selected as the laser wavelength or the sound wave frequency used in the initial bird repelling strategy.

[0092] As shown in Figure 2 , the embodiment of the present application provides a bird repelling system based on intelligent detection of airport bird information, which specifically includes:

[0093] A bird data acquisition module 101 acquires current bird data in each region of the airport;

[0094] An initial bird repelling strategy determination module 102 is configured to determine an initial bird repelling strategy for each region according to the current bird data of each region. The initial bird repelling strategy includes a sound wave repelling strategy with a certain frequency, a laser repelling strategy with a certain wavelength, or a combined repelling strategy with a sound wave with a certain frequency and a laser with a certain wavelength.

[0095] The estimated driving end time obtaining module 103 is configured to input the initial bird driving strategy in each region and the bird information data into a driving time estimation model to obtain an estimated driving time of the corresponding region, and the driving time estimation model is a neural network model trained based on historical bird driving information, and the historical bird driving information includes historical bird driving strategies, historical bird information data, and corresponding historical driving times; and the estimated driving end time is determined according to the estimated driving time of each region.

[0096] The final bird driving strategy selection module 104 is configured to compare the estimated driving end time of each region with the scheduled takeoff and landing time of the aircraft, if the time difference between the estimated driving end time and the scheduled takeoff and landing time of the aircraft is greater than a preset threshold, the initial bird driving strategy is used to drive the birds, otherwise, the wavelength of the laser and / or the frequency of the sound wave are adjusted based on the initial bird driving strategy to generate a new bird driving strategy, the new bird driving strategy is used to replace the initial bird driving strategy to re-predict the estimated driving time and obtain the estimated driving end time, and the wavelength of the laser and / or the frequency of the sound wave are stopped from being adjusted until the time difference between the obtained estimated driving end time and the scheduled takeoff and landing time of the aircraft is greater than the preset threshold, and the birds are driven according to the new bird driving strategy.

[0097] The system further comprises:

[0098] The environment data obtaining module 105 is configured to obtain current environment data in each region of the airport.

[0099] The estimated driving end time obtaining module 103 is further configured to input the environment data, the initial bird driving strategy, and the bird information data of each region into the driving time estimation model to obtain the estimated driving time of the corresponding region.

[0100] The embodiment of the application further discloses a computer readable storage medium.

[0101] Specifically, the computer readable storage medium stores a computer program capable of being loaded and executed by a processor to perform the bird driving method based on intelligent detection of airport bird information as described above, and the computer readable storage medium includes, for example, a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and various storage program code media.

[0102] The embodiment of the application further discloses a computer device.

[0103] Specifically, the computer device includes a memory and a processor, and the memory stores a computer program capable of being loaded and executed by the processor to perform the bird driving method based on intelligent detection of airport bird information as described above.

[0104] The above are only preferred embodiments of the present application, not intended to limit the protection scope of the present application, any one feature disclosed in the specification (including the abstract and the drawings) can be replaced by other equivalent or similar features with similar purposes unless specifically described. That is, each feature is only an example of a series of equivalent or similar features unless specifically described.

Claims

1. A bird-repelling method based on intelligent detection of airport bird information, characterized in that, include: Obtain current bird activity data for each area of ​​the airport; Determine the initial bird deterrence strategy for each region based on the current bird situation data for each region; The initial bird deterrence strategy includes a strategy of emitting sound waves of a certain frequency, a strategy of emitting lasers of a certain wavelength, or a combination of sound waves of a certain frequency and lasers of a certain wavelength. The determination of the initial bird deterrence strategy for each area based on the current bird situation data includes: if the number of birds in the area is less than a first preset number, then a strategy of emitting lasers of a certain wavelength is selected; if the number of birds in the area exceeds the first preset number but is less than a second preset number, then a strategy of emitting sound waves of a certain frequency is selected; if the number of birds in the area exceeds the second preset number, then a combination of sound waves of a certain frequency and lasers of a certain wavelength is selected. The most numerous bird species in the statistical area are selected from the range of laser wavelengths or sound frequencies that birds are sensitive to, and the laser wavelengths or sound frequencies that birds are more sensitive to are selected as the initial laser wavelengths or sound frequencies used for bird deterrence strategies. The initial bird deterrence strategy and bird situation data for each current region are input into the deterrence time prediction model to obtain the estimated deterrence time for the corresponding region. The deterrence time prediction model is a neural network model trained based on historical bird deterrence information, which includes: historical bird deterrence strategies, historical bird situation data and corresponding historical deterrence times. The estimated end time of deterrence is determined based on the estimated deterrence time for each region. The estimated bird deterrence end time for each region is compared with the estimated take-off and landing times of the aircraft. If the time difference between the estimated bird deterrence end time and the estimated take-off and landing times of the aircraft is greater than a preset threshold, the birds are deterred according to the initial bird deterrence strategy. Otherwise, the laser wavelength or sound wave frequency is adjusted based on the initial bird deterrence strategy to generate a new bird deterrence strategy. The new bird deterrence strategy is used to replace the initial bird deterrence strategy to re-predict the estimated bird deterrence time and obtain the estimated bird deterrence end time. The adjustment of the laser wavelength and / or sound wave frequency is stopped when the time difference between the obtained estimated bird deterrence end time and the estimated take-off and landing times of the aircraft is greater than the preset threshold, and the birds are deterred according to the new bird deterrence strategy.

2. The bird-repelling method based on intelligent detection of airport bird information according to claim 1, characterized in that, Also includes: Obtain current environmental data for each area within the airport; The historical bird deterrence information also includes: historical environmental data; Input the current environmental data, initial bird deterrence strategy, and bird activity data of each region into the deterrence time prediction model to obtain the predicted deterrence time for the corresponding region.

3. The bird-repelling method based on intelligent detection of airport bird information according to claim 1, characterized in that, The initial bird deterrence strategy for each region, determined based on the current bird situation data for each region, includes: Calculate the similarity between the current bird activity data for each region and the historical bird activity data for the same region for all successful bird removals completed before the scheduled take-off and landing times of aircraft in the current season, and select the historical bird activity data with similarity within the preset similarity range; Obtain the historical bird deterrence strategies corresponding to the selected historical bird activity data; The historical bird deterrence strategy with the highest repetition rate is selected as the initial bird deterrence strategy.

4. The bird-repelling method based on intelligent detection of airport bird information according to claim 1, characterized in that, The method of determining the initial bird deterrence strategy for each region based on the current bird situation data of each region also includes: Determine whether the current acoustic and laser drive-away strategy execution devices in each area are in a faulty state; If the acoustic repelling strategy execution device or the laser repelling strategy execution device is in a faulty state, the laser repelling strategy, acoustic repelling strategy, or a combination of acoustic repelling strategies determined based on the number of birds in the area will not be executed. Instead, the laser repelling strategy or acoustic repelling strategy will be determined based on the acoustic repelling strategy execution device or the laser repelling strategy execution device that is not in a faulty state.

5. The bird-repelling method based on intelligent detection of airport bird information according to claim 1, characterized in that, The method of determining the initial bird deterrence strategy for each region based on the current bird situation data of each region also includes: Check the current operating status of the acoustic and laser deflection strategy execution devices in each area; Based on the number of birds in the current bird situation data for each area, the initial bird deterrence strategy is determined by selecting a laser deterrence strategy, a sound deterrence strategy, or a combination of deterrence strategies. If the corresponding sound deterrence strategy execution device and / or laser deterrence strategy execution device are in operation and functioning normally, the strategy for the bird species with the largest number in the statistical area will no longer be applied. Instead, the laser wavelength or sound frequency that is more sensitive to the statistical bird species will be selected from the range of laser wavelengths or sound frequencies that birds are sensitive to as the laser wavelength or sound frequency used in the initial bird deterrence strategy. Alternatively, the sound frequency emitted by the sound deterrence strategy execution device that is currently in operation and functioning normally and the laser wavelength emitted by the laser deterrence strategy execution device that is currently in operation and functioning normally will be used as the laser wavelength and / or sound frequency used in the initial bird deterrence strategy. Otherwise, continue to count the bird species with the largest number in the area, and select the laser wavelength or sound frequency that the bird species are more sensitive to from the range of laser wavelengths or sound frequencies that birds are sensitive to as the laser wavelength or sound frequency used in the initial bird driving strategy.

6. The bird-repelling method based on intelligent detection of airport bird information according to claim 1, characterized in that, The method of adjusting the laser wavelength and / or sound frequency based on the initial bird deterrence strategy to generate a new bird deterrence strategy includes: The most numerous bird species in the statistical area were identified, and the most sensitive laser wavelength and sound frequency for that bird species were determined based on its biological characteristics. These were denoted as the reference laser wavelength and reference sound frequency, respectively. The difference between the laser wavelength and / or sound frequency emitted in the initial bird deterrence strategy and the reference laser wavelength and reference sound frequency is calculated and recorded as the difference frequency and / or difference wavelength. The acoustic frequency and / or laser wavelength are adjusted once based on the difference frequency and / or difference wavelength, and the laser wavelength and / or acoustic frequency are adjusted once based on the adjusted acoustic frequency and / or laser wavelength.

7. A bird control method system based on intelligent detection of airport bird information, characterized in that, include: The bird data acquisition module obtains current bird data for various areas of the airport. The initial bird deterrence strategy determination module is used to determine the initial bird deterrence strategy for each area based on the current bird situation data of each area. The initial bird deterrence strategy includes a strategy of emitting sound waves of a certain frequency, a strategy of emitting lasers of a certain wavelength, or a combination strategy of emitting sound waves of a certain frequency and lasers of a certain wavelength. The determination of the initial bird deterrence strategy for each area based on the current bird situation data of each area includes: when the number of birds in the area is less than a first preset number, a strategy of emitting lasers of a certain wavelength is selected; when the number of birds in the area exceeds the first preset number but is less than a second preset number, a strategy of emitting sound waves of a certain frequency is selected; when the number of birds in the area exceeds the second preset number, a combination strategy of emitting sound waves of a certain frequency and lasers of a certain wavelength is selected. The module also identifies the bird species with the highest number in the area and selects the laser wavelength or sound frequency that the identified bird species is more sensitive to as the laser wavelength or sound frequency used in the initial bird deterrence strategy from the range of laser wavelengths or sound frequencies that birds are sensitive to. The estimated end time acquisition module is used to input the initial bird deterrence strategy and bird situation data of each area into the deterrence time estimation model to obtain the estimated deterrence time of the corresponding area. The deterrence time estimation model is a neural network model trained based on historical bird deterrence information, which includes: historical bird deterrence strategies, historical bird situation data and corresponding historical deterrence times. The estimated end time of deterrence is determined based on the estimated deterrence time of each area. The final bird deterrence strategy selection module compares the estimated end time of deterrence with the expected take-off and landing times of aircraft in each area. If the time difference between the estimated end time of deterrence and the expected take-off and landing times of aircraft is greater than a preset threshold, the birds are deterred according to the initial bird deterrence strategy. Otherwise, the laser wavelength and / or sound wave frequency are adjusted based on the initial bird deterrence strategy to generate a new bird deterrence strategy. The new bird deterrence strategy replaces the initial bird deterrence strategy to re-predict the estimated deterrence time and obtain the estimated end time of deterrence. The adjustment of the laser wavelength and / or sound wave frequency stops when the time difference between the obtained estimated end time of deterrence and the expected take-off and landing times of aircraft is greater than the preset threshold, and the birds are deterred according to the new bird deterrence strategy.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored computer program, wherein, when the computer program is executed, it controls the device on which the computer-readable storage medium is located to perform the method as described in any one of claims 1 to 6.

9. A computer device, characterized in that, The computer device includes a memory, a processor, and a program stored in and executable on the memory, the program being executed by the processor to implement the steps of the method as described in any one of claims 1 to 6.

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