Digital bird control monitoring and early warning methods and systems
By using a digital bird prevention monitoring and early warning method, bird deterrence equipment is initialized using regional and bird activity data, and bird detection combination equipment is configured to generate intrusion data and perform early warning management. This solves the problem of time-consuming and labor-intensive existing bird prevention monitoring methods and achieves efficient and accurate bird prevention monitoring.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- UHVDC CENT OF STATE GRID SICHUAN ELECTRIC POWER CO
- Filing Date
- 2023-10-23
- Publication Date
- 2026-06-30
AI Technical Summary
Existing bird monitoring methods are time-consuming and labor-intensive, making it difficult to accurately grasp bird dynamics and numbers, and unable to provide timely and effective early warnings of potential hazards, resulting in high costs and low technical suitability for various scenarios.
A digital bird prevention monitoring and early warning method is adopted. Bird deterrence equipment is initialized by collecting regional data and bird activity data, bird detection combination equipment is configured, intrusion data is generated and bird deterrence equipment is invoked to perform early warning management, and a feedback space is constructed to implement compensation strategies, thereby achieving efficient bird prevention monitoring.
It achieves efficient and accurate bird monitoring, reduces costs, improves the compatibility of technology with various scenarios, and reduces negative environmental impacts.
Smart Images
Figure CN117671917B_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of bird monitoring technology, specifically to a digital bird monitoring and early warning method and system. Background Technology
[0002] The area outside the converter station is densely covered with vegetation and trees, attracting a large number of birds. Bird activity within the station area, particularly around the AC filter field and capacitor towers, can cause equipment tripping. Furthermore, twigs, thatch, and bird droppings carried by birds while nesting in areas like gantry cranes can fall onto equipment, potentially reducing insulation and causing further tripping, posing a safety hazard. Traditional bird control methods typically involve visual observation by lookouts and manual recording. These methods are not only time-consuming and labor-intensive but also struggle to accurately track bird activity and numbers, and fail to provide timely and effective warnings of potential hazards. Moreover, some traditional bird control methods, such as the use of shotguns and fireworks, have been proven to have negative impacts on both the environment and the birds themselves.
[0003] Existing bird monitoring technologies suffer from high costs and low compatibility with various scenarios due to insufficient rigor and completeness, ultimately hindering the efficient implementation of bird monitoring. Summary of the Invention
[0004] This application provides a digital bird prevention monitoring and early warning method and system, which solves the problems of high cost and low technical scenario matching caused by insufficient rigor and completeness in existing bird prevention monitoring work, and realizes the efficient deployment of bird prevention monitoring work.
[0005] In view of the above problems, this application provides a digital bird prevention monitoring and early warning method.
[0006] Firstly, this application provides a digital bird control monitoring and early warning method, the method comprising: collecting regional data of a monitoring area and reading historical data of the monitoring area; establishing environmental data and bird situation data of the monitoring area based on the collection results; initializing and configuring bird deterrence equipment based on the environmental data and the bird situation data, wherein the bird deterrence equipment includes high sound pressure level directional bird deterrence equipment and low sound pressure level directional bird deterrence equipment; configuring a bird detection combination device, wherein the bird detection combination device includes bird detection photoelectric and bird detection radar, receiving feedback signals from the bird detection combination device, generating intrusion data based on the authentication results of the feedback signals, wherein the intrusion data includes intrusion location, intrusion type and intrusion quantity; generating monitoring and early warning information based on the intrusion data, and invoking the bird deterrence equipment according to the monitoring and early warning information to perform initial early warning management of digital bird control; configuring a feedback space, performing feedback supervision of early warning processing in the feedback space, and generating a compensation strategy based on the feedback supervision results to complete the early warning management.
[0007] Secondly, this application provides a digital bird control monitoring and early warning system, comprising: a data acquisition module: collecting regional data of the monitoring area and reading historical data of the monitoring area, and establishing environmental data and bird situation data of the monitoring area based on the acquisition results; a device initialization module: initializing and configuring bird deterrent devices based on the environmental data and the bird situation data, wherein the bird deterrent devices include high sound pressure level directional bird deterrent devices and low sound pressure level directional bird deterrent devices; a device configuration module: configuring bird detection combination devices, wherein the bird detection combination devices include bird detection photoelectric devices and bird detection radar devices, receiving feedback signals from the bird detection combination devices, and generating intrusion data based on the authentication results of the feedback signals, wherein the intrusion data includes intrusion location, intrusion type, and intrusion quantity; an early warning generation module: generating monitoring and early warning information based on the intrusion data, and calling the bird deterrent devices according to the monitoring and early warning information to perform initial early warning management of digital bird control; and a feedback space module: configuring a feedback space, performing feedback supervision of early warning processing in the feedback space, and generating compensation strategies based on the feedback supervision results to complete early warning management.
[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:
[0009] The digital bird prevention monitoring and early warning method and system provided in this application collects regional data of the monitoring area and reads historical data of the monitoring area to establish environmental data and bird situation data of the monitoring area. Then, based on the environmental data and bird situation data, it initializes and configures bird deterrence equipment and bird detection combination equipment, receives feedback signals from the bird detection combination equipment, generates intrusion data based on the authentication results of the feedback signals, generates monitoring and early warning information based on the intrusion data, and calls bird deterrence equipment to perform initial early warning management of digital bird prevention. Finally, it configures a feedback space, performs feedback supervision of early warning processing in the feedback space, and generates compensation strategies based on the feedback supervision results to complete early warning management. This solves the problems of high cost and low technical scenario matching caused by insufficient rigor and completeness in existing bird prevention monitoring work, and realizes efficient deployment of bird prevention monitoring work. Attached Figure Description
[0010] Figure 1 This application provides a schematic diagram of the digital bird prevention monitoring and early warning method.
[0011] Figure 2 This application provides a schematic diagram of the structure of a digital bird prevention monitoring and early warning system.
[0012] Explanation of reference numerals in the attached diagram: Data acquisition module 11, Device initialization module 12, Device configuration module 13, Early warning generation module 14, Feedback space module 15. Detailed Implementation
[0013] This application provides a digital bird control monitoring and early warning method and system. It collects regional data of the monitoring area and reads historical data to establish environmental and bird activity data. Based on this data, it initializes and configures bird deterrence equipment and bird detection devices, receives feedback signals from these devices, generates intrusion data based on the authentication results, and then generates monitoring and early warning information. The system then invokes the bird deterrence equipment to perform initial digital bird control early warning management. Finally, it configures a feedback space for monitoring the early warning process and generates compensation strategies based on the monitoring results to complete the early warning management. This solution addresses the problems of high costs and low technical scenario compatibility in existing bird control monitoring methods due to insufficient rigor and completeness, enabling efficient deployment of bird control monitoring.
[0014] Example 1
[0015] like Figure 1 As shown, this application provides a digital bird-prevention monitoring and early warning method and system, the method including:
[0016] Collect regional data of the monitoring area and read historical data of the monitoring area; establish environmental data and bird activity data of the monitoring area based on the collection results.
[0017] The regional data for the monitoring area includes environmental data and bird activity data. Environmental data includes the actual distribution of various power facilities and office areas within the converter station; bird activity data includes the number and species of birds appearing within the monitoring area. Environmental data is obtained through actual measurements, and bird activity data is acquired using bird detection equipment, including bird-detecting radar and photoelectric sensors. By collecting regional data from the monitoring area and retrieving historical data from the system, corresponding data is generated based on the historical data, ensuring consistency between the collected regional data and historical data, thus providing a data foundation for subsequent data collection.
[0018] The bird deterrence device is initialized and configured based on the environmental data and the bird situation data, wherein the bird deterrence device includes a high sound pressure level directional bird deterrence device and a low sound pressure level directional bird deterrence device;
[0019] High-sound-pressure-level directional bird deterrent equipment refers to equipment with a peak sound pressure level ≥140dB@1m (metering method: fast (F), A-weighted, output sound pressure level adjustable); low-sound-pressure-level directional bird deterrent equipment refers to equipment with a peak sound pressure level ≥130dB@1m. Bird deterrent equipment is configured based on environmental and bird activity data. High-sound-pressure-level equipment is deployed in areas with a large number of birds and strong resistance to interference, while low-sound-pressure-level equipment is deployed in areas with fewer birds and weak resistance to interference. The number of bird deterrent devices is determined based on environmental data to ensure coverage of the entire converter station. The sound pressure emission level is adjusted according to the distance from the main control building to minimize the impact on staff while achieving the best bird deterrent effect.
[0020] Configure a bird detection combination device, which includes a bird detection photoelectric device and a bird detection radar device. Receive feedback signals from the bird detection combination device and generate intrusion data based on the authentication results of the feedback signals. The intrusion data includes the intrusion location, intrusion type, and intrusion quantity.
[0021] Bird detection radar is a radar device specifically designed for studying bird migration. It monitors and analyzes radar signals from migratory birds to acquire information such as their movement trajectories, numbers, distribution, altitude, and speed in the sky. Bird detection optoelectronic devices are photoelectric detection equipment. In bird control operations, bird detection radar first detects suspicious targets through all-around monitoring and early warning. It receives feedback signals from these suspicious targets and then guides the optoelectronic detection equipment to confirm the target, generating intrusion data. The optoelectronic detection system uses deep learning algorithms to distinguish flying birds from other low-altitude small targets. The bird detection radar display software displays real-time bird information acquired by the radar, including target size, orientation, distance, and number, on polar coordinates or a map—that is, the intrusion location, intrusion type, and intrusion quantity. This provides the data foundation for subsequent monitoring and early warning information generation based on the intrusion data, and for calling upon bird control equipment to perform initial early warning management for digital bird control.
[0022] Based on the intrusion data, monitoring and early warning information is generated, and the bird deterrent device is invoked according to the monitoring and early warning information to perform initial early warning management of digital bird prevention;
[0023] The intrusion data, including intrusion location, type, and quantity, is organized and mapped. These three data points are then integrated into a single composite information item, outputting monitoring and early warning information. This monitoring and early warning information undergoes a transformation, converting the information representation on a map or polar coordinate system into a data format used by bird control devices. The bird control devices are then activated, and the monitoring and early warning information is sent to them. Upon receiving the monitoring and early warning information, the bird control devices execute digital bird control early warning management. In the current digital bird control management, directly using monitoring and early warning information as bird control data introduces certain errors, requiring subsequent error correction. Therefore, the current early warning management is called initialization early warning management. This initialization prepares the feedback space for subsequent configuration, performs feedback supervision of early warning processing within the feedback space, and generates compensation strategies based on the feedback supervision results, providing a data foundation for completing early warning management.
[0024] Configure a feedback space, perform feedback supervision of early warning processing in the feedback space, and generate a compensation strategy based on the feedback supervision results to complete early warning management.
[0025] In practice, error adjustment and compensation are cumbersome and inefficient, making it difficult to adjust to the current bird control situation in a timely manner, resulting in poor timeliness. However, by constructing a bird control feedback model in a three-dimensional simulation space, inputting relevant data, simulating the situation in the three-dimensional simulation space, performing corresponding compensation based on the simulation data, and outputting the compensation results, early warning management can be implemented based on the output compensation results. A feedback space is constructed based on environmental and bird activity data of the monitoring area, and bird control equipment parameters are input to obtain the completed feedback space. Bird control simulation is performed based on the feedback space, and the output data is recorded. The output data is analyzed to obtain compensation analysis results, and compensation strategies are generated based on the compensation analysis results. The compensation strategies are then output to complete early warning management. By constructing a feedback space to generate compensation strategies, early warning management can be made more efficient.
[0026] Furthermore, the method also includes:
[0027] The intrusion data is analyzed, and the bird deterrent device is located and responded to based on the analysis results. Response parameters are set, including response audio and response decibels.
[0028] The sound pollution is evaluated using the aforementioned response parameters;
[0029] If the noise pollution assessment results do not meet the preset threshold, an adjustment strategy will be generated.
[0030] Initial early warning management is completed according to the adjustment strategy described above.
[0031] First, obtain the intrusion data, parse the intrusion data to obtain the intrusion location in the intrusion data, select the bird repellent device at the corresponding location according to the intrusion location, and then further screen in the bird repellent device according to the type of intrusion in the intrusion data to select the bird repellent device for the type of intrusion. Then, further screen the eligible bird repellent devices according to the number of intrusions in the intrusion data to obtain the responsive bird repellent device and complete the positioning of the responsive bird repellent device. And set parameters for the responsive bird repellent device, and set parameters for the response audio and response decibels based on the intrusion data. And conduct a sound pollution evaluation on the corresponding parameters, detect the response audio and the response device through a noise detection device to obtain the sound pollution evaluation result. Set a preset threshold. When the biological evaluation result can meet the preset threshold, it is determined to be qualified. If the sound pollution evaluation result cannot be met, it means that the responsive bird repellent device needs to be adjusted, generate an adjustment strategy, and complete the initial warning management according to the adjustment strategy to control the impact of the bird repellent device on the surrounding environment.
[0032] Furthermore, the method further includes:
[0033] Determine a key area according to the regional data, where the key area is a sound pollution sensitive area, and establish a time-sharing noise constraint for the key area;
[0034] Establish a sound distance attenuation factor for the monitoring area;
[0035] Set the preset threshold through the time-sharing noise constraint and the sound distance attenuation factor.
[0036] When determining the preset threshold, it is necessary to consider the sound attenuation situation to ensure that when the interference noise reaches the specified location, its various data are not lower than the corresponding intrusion data, and use the corresponding lowest intrusion data as the lowest value. And limit it as the highest value according to the noise impact situation, set the threshold within a range interval, and select within the range interval. Select important areas according to the regional data. Important areas are areas such as the working areas of staff. For this area, the noise needs to be strictly restricted. Regard the important area as the key area, and establish a time-sharing noise constraint for the key area to control the noise in different time periods. And confirm the distance attenuation degree according to the various monitoring data of the monitoring area. That is, the parameters affecting the distance attenuation are the sound distance attenuation factors. Set the upper and lower limits of the threshold through the time-sharing noise constraint and the sound distance attenuation factor, and continuously adjust the parameters of the time-sharing noise constraint and the sound distance attenuation factor to gradually narrow the range of the preset threshold until a numerical point is obtained, and obtain this numerical point, that is, the preset threshold. Setting the preset threshold through the time-sharing noise constraint and the sound distance attenuation factor can minimize the impact of the bird repellent device on important areas and ensure the bird repellent effect.
[0037] Furthermore, the method also includes:
[0038] If the noise pollution assessment results do not meet the preset threshold, the device matching of the bird deterrent equipment is carried out according to the analysis results.
[0039] Configure matching bird deterrence devices based on the aforementioned response parameters;
[0040] A working path is generated, and the working path and the configured matching bird deterrent devices are used as adjustment strategies to perform initial early warning management.
[0041] If the noise pollution assessment result does not meet the preset threshold, it indicates that the noise pollution of that response parameter is too high and cannot be used directly, requiring corresponding adjustments. Based on the analysis results, equipment matching for mobile bird deterrent devices is performed, selecting suitable mobile bird deterrent devices. These mobile bird deterrent devices can flexibly adjust their position and response parameters. Mobile bird deterrent devices are matched through response parameter configuration. The appropriate mobile bird deterrent device is selected based on the response parameter, and a workflow is generated based on the mobile bird deterrent device. The workflow and the matched mobile bird deterrent devices are output, i.e., the work path and the configured matched mobile bird deterrent devices, to obtain the adjustment strategy. Initial warning management is then performed based on the adjustment strategy. Configuring corresponding mobile bird deterrent devices for response parameters that do not meet the preset threshold allows the initial warning management to achieve the goal of bird deterrence while minimizing pollution.
[0042] Furthermore, the method also includes:
[0043] Detection analysis was conducted on both photoelectric bird detection and radar bird detection methods, and the species sensitivity factors and distance sensitivity factors for both methods were established.
[0044] The feedback signal is analyzed, and the accuracy of the feedback result is evaluated using the type sensitivity factor and the distance sensitivity factor.
[0045] The feedback signal authentication is completed based on the accuracy evaluation results.
[0046] Accuracy analysis was conducted on bird detection photoelectric sensors and radar, and evaluation factors for these sensors were constructed, including bird species and distance sensitivity factors. The accuracy of bird identification and distance judgment was assessed. Different bird species have varying resistance to interference, and different distances require different sound pressure levels; therefore, the accuracy of these two judgments by the bird detection sensors and radar needed to be analyzed and evaluated. The test device was used to detect birds using the sensors and radar, and the detection results were output as test results. Influencing factors were constructed for the detection results, namely the species sensitivity factors and distance sensitivity factors of the bird detection sensors and radar. The detection results were compared with the parameters of the test device to obtain the result difference. Data tracing was performed using the species sensitivity factors and distance sensitivity factors of the bird detection sensors and radar to obtain the corresponding parameter differences. The accuracy of these parameter differences was evaluated to obtain the accuracy evaluation of the feedback results. Based on the accuracy evaluation results, the feedback signal was authenticated. By analyzing the feedback signal using the species sensitivity factor and distance sensitivity factor of bird detection photoelectric and bird detection radar, more reasonable and accurate interference signals can be obtained.
[0047] Furthermore, the method also includes:
[0048] Record the intrusion data and extract common intrusion data;
[0049] Bird situation data is updated using the intrusion common data, and the configuration of bird deterrence equipment is updated based on the updated bird situation data.
[0050] During seasonal changes, bird populations undergo corresponding shifts. This necessitates on-site technical personnel to upgrade the audio database, collect intrusion data, extract relevant records (i.e., common intrusion data), and update bird activity data and equipment accordingly. Key tasks include: proactively expanding the bird deterrence audio library based on bird monitoring and information published by relevant departments, ensuring that bird deterrence operations do not increase bird adaptability, and guaranteeing effective deterrence. After backend software system upgrades, the on-site system will be updated to the latest version quarterly to ensure bird deterrence effectiveness.
[0051] Example 2
[0052] Based on the same inventive concept as the digital bird-prevention monitoring and early warning method in the foregoing embodiments, such as Figure 2 As shown, this application provides a digital bird-prevention monitoring and early warning system, the system comprising:
[0053] Data acquisition module 11: The data acquisition module 11 is used to collect regional data of the monitoring area, read historical data of the monitoring area, and establish environmental data and bird activity data of the monitoring area based on the acquisition results;
[0054] Device initialization module 12: The device initialization module 12 is used to initialize and configure the bird deterrent device based on the environmental data and the bird situation data, wherein the bird deterrent device includes a high sound pressure level directional bird deterrent device and a low sound pressure level directional bird deterrent device;
[0055] Device configuration module 13: The device configuration module 13 is used to configure the bird detection combination device, wherein the bird detection combination device includes bird detection photoelectric and bird detection radar, receives the feedback signal of the bird detection combination device, and generates intrusion data based on the authentication result of the feedback signal, wherein the intrusion data includes intrusion location, intrusion type and intrusion quantity;
[0056] Early warning generation module 14: The early warning generation module 14 is used to generate monitoring and early warning information based on the intrusion data, and to call the bird deterrent device according to the monitoring and early warning information to perform initial early warning management of digital bird prevention;
[0057] Feedback Space Module 15: The feedback space module 15 is used to configure the feedback space, perform feedback supervision of early warning processing in the feedback space, and generate compensation strategies based on the feedback supervision results to complete early warning management.
[0058] Furthermore, the system also includes:
[0059] The intrusion data is analyzed, and the bird deterrent device is located and responded to based on the analysis results. Response parameters are set, including response audio and response decibels.
[0060] The sound pollution is evaluated using the aforementioned response parameters;
[0061] If the noise pollution assessment results do not meet the preset threshold, an adjustment strategy will be generated.
[0062] Initial early warning management is completed according to the adjustment strategy described above.
[0063] Furthermore, the system also includes:
[0064] Based on the regional data, key regions are identified, including noise pollution-sensitive areas within the key regions, and time-division noise constraints are established for the key regions.
[0065] Establish the sound distance attenuation factor for the monitoring area;
[0066] The preset threshold is set using the time-division noise constraint and the sound distance attenuation factor.
[0067] Furthermore, the system also includes:
[0068] If the noise pollution assessment results do not meet the preset threshold, the device matching of the bird deterrent equipment is carried out according to the analysis results.
[0069] Configure matching bird deterrence devices based on the aforementioned response parameters;
[0070] A working path is generated, and the working path and the configured matching bird deterrent devices are used as adjustment strategies to perform initial early warning management.
[0071] Furthermore, the system also includes:
[0072] Detection analysis was conducted on both photoelectric bird detection and radar bird detection methods, and the species sensitivity factors and distance sensitivity factors for both methods were established.
[0073] The feedback signal is analyzed, and the accuracy of the feedback result is evaluated using the type sensitivity factor and the distance sensitivity factor.
[0074] The feedback signal authentication is completed based on the accuracy evaluation results.
[0075] Furthermore, the system also includes:
[0076] Record the intrusion data and extract common intrusion data;
[0077] Bird situation data is updated using the intrusion common data, and the configuration of bird deterrence equipment is updated based on the updated bird situation data.
[0078] Through the foregoing detailed description of the digital bird-prevention monitoring and early warning method, those skilled in the art can clearly understand the digital bird-prevention monitoring and early warning method in this embodiment. As for the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and relevant parts can be referred to the method section description.
[0079] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A digital bird-prevention monitoring and early warning method, characterized in that, The method includes: Collect regional data of the monitoring area and read historical data of the monitoring area; establish environmental data and bird activity data of the monitoring area based on the collection results. The bird deterrence device is initialized and configured based on the environmental data and the bird situation data, wherein the bird deterrence device includes a high sound pressure level directional bird deterrence device and a low sound pressure level directional bird deterrence device; Configure a bird detection combination device, which includes a bird detection photoelectric device and a bird detection radar device. Receive feedback signals from the bird detection combination device and generate intrusion data based on the authentication results of the feedback signals. The intrusion data includes the intrusion location, intrusion type, and intrusion quantity. Based on the intrusion data, monitoring and early warning information is generated, and the bird deterrent device is invoked according to the monitoring and early warning information to perform initial early warning management of digital bird prevention; Configure a feedback space, perform feedback supervision of early warning processing in the feedback space, and generate a compensation strategy based on the feedback supervision results to complete early warning management; The method further includes: The intrusion data is analyzed, and the bird deterrent device is located and responded to based on the analysis results. Response parameters are set, including response audio and response decibels. Noise pollution is evaluated using the aforementioned response parameters; If the noise pollution assessment results do not meet the preset threshold, an adjustment strategy will be generated. Initial early warning management is completed according to the aforementioned adjustment strategy; The method further includes: Based on the regional data, key regions are identified, including noise pollution-sensitive areas within the key regions, and time-division noise constraints are established for the key regions. Establish the sound distance attenuation factor for the monitoring area; The preset threshold is set using the time-division noise constraint and the sound distance attenuation factor.
2. The method as described in claim 1, characterized in that, The method further includes: If the noise pollution assessment results do not meet the preset threshold, the device matching of the bird deterrent equipment is carried out according to the analysis results. Configure matching bird deterrence devices based on the aforementioned response parameters; A working path is generated, and the working path and the configured matching bird deterrent devices are used as adjustment strategies to perform initial early warning management.
3. The method as described in claim 1, characterized in that, The method further includes: Detection analysis was conducted on both photoelectric bird detection and radar bird detection methods, and the species sensitivity factors and distance sensitivity factors for both methods were established. The feedback signal is analyzed, and the accuracy of the feedback result is evaluated using the type sensitivity factor and the distance sensitivity factor. The feedback signal authentication is completed based on the accuracy evaluation results.
4. The method as described in claim 1, characterized in that, The method further includes: Record the intrusion data and extract common intrusion data; Bird situation data is updated using the intrusion common data, and the configuration of bird deterrence equipment is updated based on the updated bird situation data.
5. A digital bird-prevention monitoring and early warning system, characterized in that, The system for implementing the method of any one of claims 1-4, the system comprising: Data acquisition module: Collects regional data of the monitoring area and reads historical data of the monitoring area, and establishes environmental data and bird activity data of the monitoring area based on the acquisition results; Equipment initialization module: Initializes and configures bird deterrence equipment based on the environmental data and the bird situation data, wherein the bird deterrence equipment includes high sound pressure level directional bird deterrence equipment and low sound pressure level directional bird deterrence equipment; Equipment configuration module: Configures a bird-detecting combination device, which includes a bird-detecting photoelectric device and a bird-detecting radar device. Receives feedback signals from the bird-detecting combination device and generates intrusion data based on the authentication results of the feedback signals. The intrusion data includes the intrusion location, intrusion type, and intrusion quantity. Early warning generation module: Generates monitoring and early warning information based on the intrusion data, and calls the bird deterrent device according to the monitoring and early warning information to perform initial early warning management of digital bird prevention; Feedback Space Module: Configures the feedback space, performs feedback supervision on early warning processing in the feedback space, and generates compensation strategies based on the feedback supervision results to complete early warning management.