Intelligent collaborative system and method for detecting and repelling birds

Abstract

The invention provides an intelligent cooperative system and method for detecting and repelling birds. The system comprises a bird detecting device for detecting bird conditions; after the bird repelling equipment works, a bird repelling action is executed to repel birds; the intelligent background adopts a reinforcement learning framework for learning, and the optimal bird repelling action is improved; the method specifically comprises the steps of controlling bird repelling equipment to execute different bird repelling actions, and obtaining execution effects of all the bird repelling equipment after the bird repelling actions are executed; evaluating the execution effect to obtain an evaluation result; according to the evaluation result and the intelligent adjustment strategy, bird repelling actions executed by the bird repelling devices are adjusted; and receiving a manual adjustment strategy, and adjusting each bird repelling device according to the manual adjustment strategy. According to the bird-detecting and bird-repelling intelligent cooperative system, the execution effect of the bird-repelling device is evaluated by using a reinforcement learning method, and the bird-repelling action of the bird-repelling device is adjusted according to the evaluation result, so that the bird-repelling effect is improved. In this way, the bird repelling action can be adjusted in time in the process that the birds establish adaptability, and the birds are prevented from establishing adaptability.

Description

Technical Field

[0001] The present invention belongs to the technical field of bird repelling, and in particular relates to an intelligent collaborative system and method for bird detection and repelling. Background Art

[0002] In order to reduce the probability of collision between birds and aircraft, it is necessary to drive away birds active in the flight area and reduce the number of birds. Visual, auditory and olfactory sensory stimulation and frightening techniques are often used to drive away birds. However, how can a method be implemented to achieve the best effect? ​​Which of the various bird-repelling methods is effective? After the bird-repelling method is implemented, how can birds gradually build adaptability, and how to avoid birds building adaptability? There are no quantifiable standard answers to these questions in the industry. Summary of the invention

[0003] In view of the defects in the prior art, the present invention provides an intelligent collaborative system and method for bird detection and bird repelling, which improves the bird repelling effect, adjusts the bird repelling action in time, and avoids the birds from building adaptability.

[0004] A bird detection and bird repelling intelligent collaborative system, comprising:

[0005] A variety of bird detection equipment; bird detection equipment is used to detect bird conditions;

[0006] A variety of bird-repelling equipment; bird-repelling equipment is used to perform bird-repelling actions to repel birds after work;

[0007] Intelligent background: adopts reinforcement learning framework for learning to improve the optimal bird-repelling action; specifically includes: controlling the bird-repelling equipment to perform different bird-repelling actions, obtaining the execution effect of all bird-repelling equipment after performing the bird-repelling action, evaluating the execution effect to obtain the evaluation result, and adjusting the bird-repelling action performed by each bird-repelling equipment according to the evaluation result and intelligent adjustment strategy; receiving the manual adjustment strategy, and adjusting each bird-repelling equipment according to the manual adjustment strategy.

[0008] Furthermore, the bird-repelling action includes:

[0009] Method A: All bird repellent devices work at the same time at fixed time intervals, where the time interval is used as a learning parameter;

[0010] Method B: All bird repellent devices work in turn at fixed time intervals, where the time interval and working order are used as learning parameters;

[0011] Method C: Set a warning area; when N1 birds enter the warning area, the bird-repelling device corresponding to the warning area works in method A or method B; the warning area range, the corresponding relationship between the warning area and the bird-repelling device, and N1 are used as learning parameters;

[0012] Method D: Set warning areas for takeoff and landing aircraft respectively; when the aircraft enters the warning area, the bird-repellent equipment corresponding to the warning area works in method A or method B; the range of the warning area, the range of the warning area, and the correspondence between the warning area and the bird-repellent equipment are used as learning parameters.

[0013] Furthermore, the bird-repelling action further includes:

[0014] When there are multiple setting schemes for the bird-repelling device, each setting scheme serves as a bird-repelling action; wherein the adjustment parameters in each setting scheme serve as learning parameters.

[0015] Furthermore, the evaluation result V is defined as:

[0016] V=C 1 V 1 +C 2 V 2 +C 3 V 3 ;

[0017] Among them, V 1 is the short-term effect value, V 2 is the long-term effect value, V 3 is the side effect value, C 1 , C 2 , C 3 is the weight coefficient;

[0018] V 1 =C 4 (N 0 -N 1 )+C 5 (N 0 -N 2 )+C 6 (N 0 -N 3 );

[0019] Among them, N 0 is the number of birds in the evaluation area before the bird-repelling action is performed in the bird-repelling device, N 1 、N 2 、N 3 They are T 1 、T 2 、T 3 Always evaluate the number of birds in the area, T 1 、T 2 、T 3 The value ranges from 1 second to 30 seconds. 4 , C 5 , C 6 is the weight coefficient;

[0020]

[0021] Among them, N 4 N is the total number of birds in the evaluation area during the long-term cumulative execution time T of the bird-repelling action, 5 is the total number of birds flying towards the runway, C 7 , C 8 is the weight coefficient;

[0022] V 3 Affected by the economic cost, noise pollution, and environmental pollution factors of the bird-repelling action, it is set to a negative value.

[0023] Furthermore, the intelligent adjustment strategy includes:

[0024] Define the bird-repelling action of the bird-repelling device initially set by humans as the optimal bird-repelling action;

[0025] Continuously evaluate the performance of the bird-repelling device and take the latest evaluation result as the benchmark value;

[0026] Switching the bird-repelling device to an exploration mode at specific time intervals or when the latest evaluation result is lower than a set threshold;

[0027] When the bird-repelling device is in the exploration mode, the bird-repelling action of the bird-repelling device is changed, and the execution effect of the bird-repelling device is continuously evaluated; when the latest evaluation result is higher than the benchmark value, the optimal bird-repelling action is replaced with the current bird-repelling action of the bird-repelling device;

[0028] When the exploration mode of the bird-repelling device ends, the bird-repelling device is switched to the optimal bird-repelling action.

[0029] Furthermore, the intelligent backend is specifically used for:

[0030] When the bird repellent device is in exploration mode, the learning parameters are randomly configured according to the probability weights;

[0031] Evaluate the performance of bird repellent equipment configured with learning parameters;

[0032] The probability weights of different learning parameters are adjusted according to the evaluation results, where the better the evaluation result, the greater the probability weight;

[0033] The evaluation results of all learning parameters are curve fitted, and the probability weights are readjusted according to the fitting results.

[0034] Furthermore, the manual adjustment strategy includes:

[0035] Adjust the range of adjustment parameters in each bird-repelling action;

[0036] Add or delete bird-repelling actions;

[0037] Adjust the layout of the bird repellent equipment according to the activity patterns of birds;

[0038] Remove bird-repellent equipment that is difficult to drive away birds, and add new bird-repellent equipment.

[0039] In the second aspect, a bird detection and bird repelling intelligent collaborative method includes:

[0040] Bird detection equipment detects bird activity;

[0041] After the bird-repelling device is working, the bird-repelling action is performed to repel the birds;

[0042] The intelligent background adopts the reinforcement learning framework to learn and improve the optimal bird-repelling action; specifically, it includes: controlling the bird-repelling equipment to perform different bird-repelling actions, obtaining the execution effects of all bird-repelling equipment after performing the bird-repelling actions, evaluating the execution effects to obtain the evaluation results, and adjusting the bird-repelling actions performed by each bird-repelling equipment according to the evaluation results and the intelligent adjustment strategy; receiving the manual adjustment strategy, and adjusting each bird-repelling equipment according to the manual adjustment strategy.

[0043] Furthermore, the bird-repelling action includes:

[0044] Method A: All bird repellent devices work at the same time at fixed time intervals, where the time interval is used as a learning parameter;

[0045] Method B: All bird repellent devices work in turn at fixed time intervals, where the time interval and working order are used as learning parameters;

[0046] Method C: Set a warning area; when N1 birds enter the warning area, the bird-repelling device corresponding to the warning area works in method A or method B; the warning area range, the corresponding relationship between the warning area and the bird-repelling device, and N1 are used as learning parameters;

[0047] Method D: Set warning areas for takeoff and landing aircraft respectively; when the aircraft enters the warning area, the bird-repellent equipment corresponding to the warning area works in method A or method B; the range of the warning area, the range of the warning area, and the correspondence between the warning area and the bird-repellent equipment are used as learning parameters.

[0048] Furthermore, the bird-repelling action further includes:

[0049] When there are multiple setting schemes for the bird-repelling device, each setting scheme serves as a bird-repelling action; wherein the adjustment parameters in each setting scheme serve as learning parameters.

[0050] It can be seen from the above technical solutions that the bird detection and bird repelling intelligent collaborative system and method provided by the present invention can realize the collaborative operation between bird detection equipment, bird repelling equipment, and bird repelling operators, use reinforcement learning methods to evaluate the execution effect of bird repelling equipment, and adjust the bird repelling action of the bird repelling equipment according to the evaluation results, thereby improving the bird repelling effect. In this way, the bird repelling action can be adjusted in time during the process of birds establishing adaptability, avoiding birds from establishing adaptability. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for the specific embodiments or the description of the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.

[0052] Figure 1 A module block diagram of the bird detection and bird repelling intelligent collaborative system provided in the embodiment.

[0053] Figure 2 A flow chart of the intelligent collaborative method for bird detection and bird repelling provided in an embodiment. DETAILED DESCRIPTION

[0054] The embodiments of the technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and are therefore only used as examples, and the protection scope of the present invention cannot be limited thereto. It should be noted that, unless otherwise specified, the technical terms or scientific terms used in this application should be the common meanings understood by those skilled in the art to which the present invention belongs.

[0055] It should be understood that when used in this specification and the appended claims, the terms "include" and "comprises" indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0056] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0057] As used in this specification and the appended claims, the term "if" may be interpreted as "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrases "if it is determined" or "if [described condition or event] is detected" may be interpreted as meaning "upon determination" or "in response to determining" or "upon detection of [described condition or event]" or "in response to detecting [described condition or event]," depending on the context.

[0058] Example:

[0059] A bird detection and bird repelling intelligent collaborative system, see Figure 1 ,include:

[0060] A variety of bird detection equipment; bird detection equipment is used to detect bird conditions;

[0061] A variety of bird-repelling equipment; bird-repelling equipment is used to perform bird-repelling actions to repel birds after work;

[0062] Intelligent background: adopts reinforcement learning framework for learning to improve the optimal bird-repelling action; specifically includes: controlling the bird-repelling equipment to perform different bird-repelling actions, obtaining the execution effect of all bird-repelling equipment after performing the bird-repelling action, evaluating the execution effect to obtain the evaluation result, and adjusting the bird-repelling action performed by each bird-repelling equipment according to the evaluation result and intelligent adjustment strategy; receiving the manual adjustment strategy, and adjusting each bird-repelling equipment according to the manual adjustment strategy.

[0063] In the present embodiment, the bird detection and bird repelling intelligent collaborative system is composed of bird detection equipment, bird repelling equipment, and intelligent background. The bird detection equipment may include radar bird detection equipment, optical bird detection equipment, and the like. The bird repelling equipment may be operated remotely, including unmanned bird repelling vehicles, sonic bird repelling equipment, laser bird repelling equipment, gas cannons, chemical spraying devices, and other equipment that stimulates the visual, auditory, and olfactory senses of birds. The intelligent background has functions such as information display, reinforcement learning, and remote control of bird repelling equipment. Bird repelling operators can remotely log in to the intelligent background through personal terminals, view real-time or historical bird conditions, and carry out bird repelling operations in a targeted manner under the guidance of the intelligent background. Expert knowledge can also be used to adjust bird repelling equipment and parameters.

[0064] In this embodiment, the bird-detecting and bird-repelling intelligent collaborative system can perform a variety of bird-repelling actions, evaluate the execution effect, and intelligently adjust the bird-repelling actions according to the evaluation results. The system can also feed back the evaluation results to experts, and manually adjust the system based on experience. In this way, the system continuously cycles through learning, so that the optimal bird-repelling action is continuously improved to avoid birds from establishing adaptability. The reinforcement learning method of the system includes five key elements: intelligent agent, environment, action, reward and state. The bird-detecting and bird-repelling intelligent collaborative system is the intelligent agent, the birds in the flight zone are the environment, the various bird-repelling actions are the actions, the accurate evaluation of the execution effect of the bird-repelling action is the reward, and the adjustment of the bird-repelling equipment is the state.

[0065] The intelligent bird detection and bird repelling collaborative system can realize the collaborative operation between bird detection equipment, bird repelling equipment, and bird repelling operators, use reinforcement learning methods to evaluate the execution effect of bird repelling equipment, and adjust the bird repelling action of the bird repelling equipment according to the evaluation results, thereby improving the bird repelling effect. In this way, the bird repelling action can be adjusted in time during the process of birds building adaptability, avoiding birds from building adaptability.

[0066] Further, in some embodiments, the bird-repelling action includes:

[0067] Method A: All bird repellent devices work at the same time at fixed time intervals, where the time interval is used as a learning parameter;

[0068] Method B: All bird repellent devices work in turn at fixed time intervals, where the time interval and working order are used as learning parameters;

[0069] Method C: Set a warning area; when N1 birds enter the warning area, the bird-repelling device corresponding to the warning area works in method A or method B; the warning area range, the corresponding relationship between the warning area and the bird-repelling device, and N1 are used as learning parameters;

[0070] Method D: Set warning areas for takeoff and landing aircraft respectively; when the aircraft enters the warning area, the bird-repellent equipment corresponding to the warning area works in method A or method B; the range of the warning area, the range of the warning area, and the correspondence between the warning area and the bird-repellent equipment are used as learning parameters.

[0071] In this embodiment, the bird-repelling device has a variety of bird-repelling actions, including mode A, mode B, mode C and mode D. The time intervals in mode A and mode B can be set specifically according to actual conditions. The learning parameters of each bird-repelling action in the bird-repelling device can be configured with different values ​​in the exploration mode to achieve the evaluation of different bird-repelling actions. The typical work is as follows:

[0072] Method A: At fixed time intervals, all bird-repelling devices work simultaneously to drive away birds using a coordinated sense of shock; the time interval can be set to any number of minutes;

[0073] Method B: At fixed time intervals, all bird repellent devices work in turn, creating a sense of gradual advancement and improving the directional effect of repelling. The time interval of each device can be set to any number of minutes, and the time difference between devices is determined by the installation location.

[0074] Mode C: Set a warning area; when N1 birds enter the warning area, the bird repellent device corresponding to the warning area works in mode A or mode B; the warning area is generally set to be between 100 meters and 500 meters from the runway, and the corresponding relationship of the bird repellent device is generally set to be the bird repellent device within 50-200 meters on both sides of the vertical line between the bird and the runway, and N1 is generally set between 1-100;

[0075] Mode D: Set warning areas for takeoff and landing aircraft respectively; when an aircraft enters the warning area, the bird-repelling equipment corresponding to the warning area works in mode A or mode B; the warning area is generally set to be between 1km and 5km from the aircraft to the end of the runway.

[0076] Furthermore, in some embodiments, the bird-repelling action further includes:

[0077] When there are multiple setting schemes for the bird-repelling device, each setting scheme is used as a bird-repelling action; wherein the adjustment parameters in each setting scheme are used as learning parameters.

[0078] In this embodiment, the bird-repelling device has a variety of adjustment parameters. When adjustment settings are made, each setting scheme can be used as a bird-repelling action, wherein the adjustment parameters in each setting scheme are used as learning parameters. For example, the adjustment parameters include volume, sound content, light intensity, gas usage, release agent dosage, etc.

[0079] Further, in some embodiments, the evaluation result V is defined as:

[0080] V=C 1 V 1 +C 2 V 2 +C 3 V 3 ;

[0081] Among them, V 1 is the short-term effect value, V 2 is the long-term effect value, V 3 is the side effect value, C 1 , C 2 , C 3 is the weight coefficient;

[0082] V 1 =C 4 (N 0 -N 1 )+C 5 (N 0 -N 2 )+C 6 (N 0 -N 3 );

[0083] Among them, N 0 is the number of birds in the evaluation area before the bird repelling action is performed in the bird repelling device, N 1 、N 2 、N 3 They are T 1 、T 2 、T 3 Always evaluate the number of birds in the area, T 1 、T 2 、T 3 The value ranges from 1 second to 30 seconds. 4 , C 5 , C 6 is the weight coefficient;

[0084]

[0085] Among them, N 4 N is the total number of birds in the evaluation area during the long-term cumulative execution time T of the bird-repelling action, 5 is the total number of birds flying towards the runway, C 7 , C 8 is the weight coefficient;

[0086] V 3 Affected by the economic cost, noise pollution, and environmental pollution factors of the bird-repelling action, it is set to a negative value.

[0087] In this embodiment, the intelligent backend uses the above method to evaluate and reward the performance of the bird removal device. 4 It reflects the bird population density control ability, N 5 It reflects the ability to drive away, V 3 It can be set manually. It can be seen that the evaluation result can be evaluated from multiple factors such as the various capabilities of the driving equipment and the length of time the bird-repelling equipment is used, making the evaluation learning effect more comprehensive.

[0088] Furthermore, in some embodiments, the intelligent adjustment strategy includes:

[0089] Define the bird-repelling action of the bird-repelling device initially set by humans as the optimal bird-repelling action;

[0090] Continuously evaluate the effectiveness of bird repellent equipment and use the latest evaluation results as the baseline value;

[0091] At specific time intervals (ranging from 1 day to 1 month) or when the latest evaluation result is below the set threshold, the bird repellent device will be switched to exploration mode;

[0092] When the bird-repelling device is in the exploration mode, the bird-repelling action of the bird-repelling device is changed, and the execution effect of the bird-repelling device is continuously evaluated; when the latest evaluation result is higher than the benchmark value, the optimal bird-repelling action is replaced with the current bird-repelling action of the bird-repelling device;

[0093] When the exploration mode of the bird-repelling device ends, the bird-repelling device is switched to the optimal bird-repelling action.

[0094] In this embodiment, when the intelligent background switches the bird-repelling device to the exploration mode, it is necessary to keep the bird-repelling device working in the exploration mode for a period of time (1 hour to 1 day), and switch back to the optimal bird-repelling action after the exploration mode ends. For example, when the bird-repelling device is in the exploration mode, the bird-repelling device executes bird-repelling action A, evaluates the execution effect of bird-repelling action A, and obtains evaluation result A, but evaluation result A is lower than the benchmark value, and bird-repelling action A is not the optimal bird-repelling action. Then the bird-repelling device switches to execute bird-repelling action B, evaluates the execution effect of bird-repelling action B, and obtains evaluation result B, but evaluation result B is higher than the benchmark value, and bird-repelling action B is set as the optimal bird-repelling action. The system can explore different bird-repelling actions in different bird-repelling technical means, and find the optimal combination of technical means through comparison of multiple bird-repelling technical means to further enhance the bird-repelling ability.

[0095] Furthermore, in some embodiments, the intelligent backend is specifically used for:

[0096] When the bird repellent device is in exploration mode, the learning parameters are randomly configured according to the probability weights;

[0097] Evaluate the performance of bird repellent equipment configured with learning parameters;

[0098] The probability weights of different learning parameters are adjusted according to the evaluation results, where the better the evaluation result, the greater the probability weight;

[0099] The evaluation results of all learning parameters are curve fitted, and the probability weights are readjusted according to the fitting results.

[0100] In this embodiment, in order to minimize the use of unreasonable parameter settings in the exploration mode, when the bird-repelling device is in the exploration mode, learning parameters are randomly extracted according to the probability weight. After completing the evaluation of the group of learning parameters, the evaluation results are recorded, and the probability weights of each learning parameter are adjusted according to the principle that the better the evaluation result, the greater the weight. In this way, when the system continues to run for a long time, curve fitting can be performed based on the evaluation results of a large number of learning parameters, and the probability weights can be readjusted to eliminate the influence of accidental factors on the evaluation results.

[0101] Furthermore, in some embodiments, the manual adjustment strategy includes:

[0102] Adjust the range of adjustment parameters in each bird-repelling action;

[0103] Add or delete bird-repelling actions;

[0104] Adjust the layout of bird repellent equipment according to the activity patterns of birds;

[0105] Remove bird-repellent equipment that is difficult to drive away birds, and add new bird-repellent equipment.

[0106] In this embodiment, the system uses expert manual analysis of the bird activity big data detected, combined with expert experience, to make the following adjustments: (1) Adjust the range of the adjustment parameters in the bird repellent action AX, and add or delete bird repellent actions. (2) Adjust the layout of the bird repellent equipment according to the bird activity patterns. (3) Remove the bird repellent equipment that has been proven to be difficult to repel birds after a long period of time, and add new bird repellent equipment.

[0107] An intelligent collaborative method for bird detection and bird repelling, see Figure 2 ,include:

[0108] Bird detection equipment detects bird activity;

[0109] After the bird-repelling device is working, the bird-repelling action is performed to repel the birds;

[0110] The intelligent background adopts the reinforcement learning framework to learn and improve the optimal bird-repelling action; specifically, it includes: controlling the bird-repelling equipment to perform different bird-repelling actions, obtaining the execution effects of all bird-repelling equipment after performing the bird-repelling actions, evaluating the execution effects to obtain the evaluation results, and adjusting the bird-repelling actions performed by each bird-repelling equipment according to the evaluation results and the intelligent adjustment strategy; receiving the manual adjustment strategy, and adjusting each bird-repelling equipment according to the manual adjustment strategy.

[0111] Further, in some embodiments, the bird-repelling action includes:

[0112] Method A: All bird repellent devices work at the same time at fixed time intervals, where the time interval is used as a learning parameter;

[0113] Method B: All bird repellent devices work in turn at fixed time intervals, where the time interval and working order are used as learning parameters;

[0114] Method C: Set a warning area; when N1 birds enter the warning area, the bird-repelling device corresponding to the warning area works in method A or method B; the warning area range, the corresponding relationship between the warning area and the bird-repelling device, and N1 are used as learning parameters;

[0115] Method D: Set warning areas for takeoff and landing aircraft respectively; when the aircraft enters the warning area, the bird-repellent equipment corresponding to the warning area works in method A or method B; the range of the warning area, the range of the warning area, and the correspondence between the warning area and the bird-repellent equipment are used as learning parameters.

[0116] Furthermore, in some embodiments, the bird-repelling action further includes:

[0117] When there are multiple setting schemes for the bird-repelling device, each setting scheme serves as a bird-repelling action; wherein the adjustment parameters in each setting scheme serve as learning parameters.

[0118] The method provided in the embodiment of the present invention is briefly described. For matters not mentioned in the embodiment part, reference can be made to the corresponding contents in the aforementioned embodiment.

[0119] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents. These modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and specification of the present invention.

Claims

1. A bird detection and bird repelling intelligent collaborative system, characterized in that: include: A variety of bird detection equipment; bird detection equipment is used to detect bird conditions; A variety of bird repellent equipment; The bird repelling equipment is used to perform bird repelling actions to repel birds after work; Intelligent background: adopts reinforcement learning framework for learning to improve the optimal bird-repelling action; specifically includes: controlling the bird-repelling equipment to perform different bird-repelling actions, obtaining the execution effect of all bird-repelling equipment after performing the bird-repelling action, evaluating the execution effect to obtain the evaluation result, and adjusting the bird-repelling action performed by each bird-repelling equipment according to the evaluation result and intelligent adjustment strategy; receiving the manual adjustment strategy, and adjusting each bird-repelling equipment according to the manual adjustment strategy.

2. The bird detection and bird repelling intelligent collaborative system according to claim 1 is characterized in that: The bird-repelling action includes: Method A: All bird repellent devices work at the same time at fixed time intervals, where the time interval is used as a learning parameter; Method B: All bird repellent devices work in turn at fixed time intervals, where the time interval and working order are used as learning parameters; Method C: Set a warning area; when N1 birds enter the warning area, the bird-repelling device corresponding to the warning area works in method A or method B; the warning area range, the corresponding relationship between the warning area and the bird-repelling device, and N1 are used as learning parameters; Method D: Set warning areas for takeoff and landing aircraft respectively; when the aircraft enters the warning area, the bird-repellent equipment corresponding to the warning area works in method A or method B; the range of the warning area, the range of the warning area, and the correspondence between the warning area and the bird-repellent equipment are used as learning parameters.

3. The bird detection and bird repelling intelligent collaborative system according to claim 2 is characterized in that: The bird-repelling action also includes: When there are multiple setting schemes for the bird-repelling device, each setting scheme serves as a bird-repelling action; wherein the adjustment parameters in each setting scheme serve as learning parameters.

4. The bird detection and bird repelling intelligent collaborative system according to claim 3 is characterized in that: The evaluation result V is defined as: V=C1V1+C2V2+C3V3; Among them, V1 is the short-term effect value, V2 is the long-term effect value, V3 is the side effect value, and C1, C2, and C3 are weight coefficients; V1=C4(N0-N1)+C5(N0-N2)+C6(N0-N3); Wherein, N0 is the number of birds in the evaluation area before the bird-repelling action is executed in the bird-repelling device, N1, N2, and N3 are the number of birds in the evaluation area at T1, T2, and T3 after the bird-repelling action is executed, respectively, T1, T2, and T3 are between 1 second and 30 seconds, and C4, C5, and C6 are weight coefficients; Among them, N4 is the total number of birds in the evaluation area within the long-term cumulative execution time T of the bird-repelling action, N5 is the total number of birds flying towards the runway, and C7 and C8 are weight coefficients; V3 is affected by the economic cost, noise pollution, and environmental pollution factors of the bird-repelling action and is set to a negative value.

5. The bird detection and bird repelling intelligent collaborative system according to claim 4 is characterized in that: The intelligent adjustment strategy includes: Define the bird-repelling action of the bird-repelling device initially set by humans as the optimal bird-repelling action; Continuously evaluate the performance of the bird-repelling device and take the latest evaluation result as the benchmark value; Switching the bird-repelling device to an exploration mode at specific time intervals or when the latest evaluation result is lower than a set threshold; When the bird-repelling device is in the exploration mode, the bird-repelling action of the bird-repelling device is changed, and the execution effect of the bird-repelling device is continuously evaluated; when the latest evaluation result is higher than the benchmark value, the optimal bird-repelling action is replaced with the current bird-repelling action of the bird-repelling device; When the exploration mode of the bird-repelling device ends, the bird-repelling device is switched to the optimal bird-repelling action.

6. The bird detection and bird repelling intelligent collaborative system according to claim 5 is characterized in that: The intelligent backend is specifically used for: When the bird repellent device is in exploration mode, the learning parameters are randomly configured according to the probability weights; Evaluate the performance of bird repellent equipment configured with learning parameters; The probability weights of different learning parameters are adjusted according to the evaluation results, where the better the evaluation result, the greater the probability weight; The evaluation results of all learning parameters are curve fitted, and the probability weights are readjusted according to the fitting results.

7. The bird detection and bird repelling intelligent collaborative system according to claim 6, characterized in that: The manual adjustment strategy includes: Adjust the range of adjustment parameters in each bird-repelling action; Add or delete bird-repelling actions; Adjust the layout of the bird repellent equipment according to the activity patterns of birds; Remove bird-repellent equipment that is difficult to drive away birds, and add new bird-repellent equipment.

8. An intelligent collaborative method for bird detection and bird repelling, characterized in that: include: Bird detection equipment detects bird activity; After the bird-repelling device is working, the bird-repelling action is performed to repel the birds; The intelligent background adopts the reinforcement learning framework to learn and improve the optimal bird-repelling action; specifically, it includes: controlling the bird-repelling equipment to perform different bird-repelling actions, obtaining the execution effects of all bird-repelling equipment after performing the bird-repelling actions, evaluating the execution effects to obtain the evaluation results, and adjusting the bird-repelling actions performed by each bird-repelling equipment according to the evaluation results and the intelligent adjustment strategy; receiving the manual adjustment strategy, and adjusting each bird-repelling equipment according to the manual adjustment strategy.

9. The intelligent collaborative method for bird detection and bird repelling according to claim 8, characterized in that: The bird-repelling action includes: Method A: All bird repellent devices work at the same time at fixed time intervals, where the time interval is used as a learning parameter; Method B: All bird repellent devices work in turn at fixed time intervals, where the time interval and working order are used as learning parameters; Method C: Set a warning area; when N1 birds enter the warning area, the bird-repelling device corresponding to the warning area works in method A or method B; the warning area range, the corresponding relationship between the warning area and the bird-repelling device, and N1 are used as learning parameters; Method D: Set warning areas for takeoff and landing aircraft respectively; when the aircraft enters the warning area, the bird-repellent equipment corresponding to the warning area works in method A or method B; the range of the warning area, the range of the warning area, and the correspondence between the warning area and the bird-repellent equipment are used as learning parameters.

10. The intelligent collaborative method for bird detection and bird repelling according to claim 9, characterized in that: The bird-repelling action also includes: When there are multiple setting schemes for the bird-repelling device, each setting scheme serves as a bird-repelling action; wherein the adjustment parameters in each setting scheme serve as learning parameters.

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