Acousto-optic fusion bird repelling efficiency evaluation method and system

Abstract

The invention discloses an acousto-optic fusion bird repelling efficiency evaluation method and system, and the method comprises the steps: enabling a bird repelling device to recognize a target through an AI image, and enabling the bird repelling device to repel the target through the sound and light capability; collecting data and synchronously transmitting the data to a data analysis module; the behavior state of the birds is automatically analyzed based on image recognition and video processing technologies; comprehensively evaluating the bird repelling effect by using the efficiency evaluation index; according to historical data, a bird repelling strategy is optimized through an efficiency evaluation result; intelligent learning is introduced, and a bird repelling strategy is automatically adjusted; the system generates a regular efficiency evaluation report and feeds back data to the user; the system comprises a data acquisition module, a behavior identification and analysis module, an efficiency evaluation module and a strategy optimization module. According to the method, quantitative evaluation is carried out on the bird repelling effect, and the efficiency performance of bird repelling equipment is clarified; the effectiveness of a bird repelling strategy can be analyzed according to behaviors of birds; the bird repelling strategy is adjusted and optimized according to the data, and the bird repelling efficiency is greatly improved.

Description

Technical Field

[0001] The present invention relates to the field of intelligent bird-repelling, and in particular to a method and system for evaluating the effectiveness of bird-repelling by sound and light fusion based on video image data. Background Art

[0002] At present, bird-repellent equipment widely used in agriculture, power facilities, airports and other places mostly uses sound and light to interfere with birds to achieve repelling. However, existing bird-repellent equipment mainly focuses on the short-term performance of bird-repellent effects, and there is no effective recording data. There is a lack of effective means for long-term statistics and evaluation of the effectiveness of bird-repellent equipment. It is impossible to determine whether each repellent has achieved the desired effect, nor is it possible to make refined strategy adjustments based on different bird habits or specific environmental conditions. It is impossible to quantitatively evaluate the effect of bird repellent and it is difficult to clarify the performance of bird repellent equipment. With the development of intelligent technology, there is an urgent need for a method that can quantitatively evaluate the effect of bird repellent in order to improve the intelligence level of equipment and optimize bird repellent strategies. Summary of the invention

[0003] Purpose of the invention: The purpose of the present invention is to provide a method and system for evaluating the effectiveness of bird-repelling by sound and light fusion based on video image data.

[0004] Technical solution: The method for evaluating the effectiveness of bird-repelling by combining sound and light in the present invention comprises the following steps: S1: The bird repellent device uses AI image recognition to drive away the target using sound and light capabilities; S2: Collect data through high-definition cameras and transmit them to the data analysis module synchronously; S3: Based on image recognition and video processing technology, the system automatically analyzes the behavior of birds; S4: Comprehensively evaluate the bird repellent effect using the effectiveness evaluation index; S5: Optimizing the bird-repelling strategy based on the performance evaluation result obtained in step S4 according to the historical data; S6: Introducing intelligent learning to automatically adjust bird-repelling strategies; S7: The system generates regular performance evaluation reports and feeds the data back to the user.

[0005] Furthermore, in step (2), when the bird-repelling device performs the bird-repelling task, the camera captures pictures and records videos to automatically capture the dynamic behavior of the bird as data, and synchronously transmits it to the data analysis module. Furthermore, the dynamic behavior of the bird includes the state of the bird flying away, moving, and continuing to stay.

[0006] Furthermore, in step (3), the system automatically analyzes the behavior status of birds, including: detecting whether the birds fly away immediately after the bird-repelling behavior is triggered; whether there are birds that move briefly but do not completely fly away after the device intervenes; and whether there are birds that continue to stay in the area. By identifying different behavior patterns, a data report on the repelling effect is generated.

[0007] Furthermore, the performance evaluation indicators of step (4) include expulsion success rate, residence time and secondary expulsion success rate.

[0008] Furthermore, the driving away success rate is the ratio of the number of birds that fly away immediately after the bird driving away strategy is implemented to the total number of target birds.

[0009] Furthermore, the secondary expulsion success rate is the ratio of the number of birds finally expelled to the total number of target birds when the system triggers the device again through a subsequent bird expelling strategy if the initial expulsion fails.

[0010] Furthermore, in step (5), the system analyzes the performance of different bird-repelling strategies in different environments and time periods based on historical data, and optimizes the bird-repelling strategies through performance evaluation results. When the success rate of using sound to repel birds is low, the system will give priority to using laser strategies in the future, or adjust the switching frequency of laser and sound.

[0011] Furthermore, step (6) includes introducing a machine learning model, and based on previous bird-repelling effectiveness data, the system learns which strategy works best under different lighting, wind speed, and bird species conditions, and intelligently selects the best strategy in the next bird-repelling operation.

[0012] The sound and light fusion bird-repelling effectiveness evaluation system of the present invention comprises: The data collection module is used for the equipment to automatically capture the dynamic behavior of birds, including the status of birds flying away, moving and staying; Behavior recognition and analysis module, used to automatically analyze the behavior status of birds based on image recognition and video processing technology; The effectiveness evaluation module is used to comprehensively evaluate the bird repellent effect, including the evaluation of the bird repellent effect on stubborn targets; The strategy optimization module is used to analyze the performance of different bird-repelling strategies in different environments and time periods based on historical data, and optimize the bird-repelling strategies through performance evaluation results.

[0013] Beneficial effects: Compared with the prior art, the present invention has the following significant advantages: it conducts quantitative evaluation on the bird-repelling effect and clarifies the performance of the bird-repelling equipment; while repelling birds, it has the functions of collecting and analyzing image and video data, and can analyze the effectiveness of the bird-repelling strategy according to the specific behavior of birds; the equipment can adjust and optimize the bird-repelling strategy according to the data, and the bird-repelling efficiency is greatly improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0015] The technical solution of the present invention is further described below in conjunction with the accompanying drawings.

[0016] like Figure 1 As shown, the sound and light fusion bird-repelling effectiveness evaluation method of the present invention comprises: S1: The bird-repellent device uses AI image recognition to identify the target and uses sound and light capabilities to drive the target away; The bird-repellent device uses AI image recognition to detect the target and uses sound and light capabilities to drive the target away.

[0017] S2: Collect data through high-definition cameras and transmit them to the data analysis module synchronously; When the bird-repelling device is performing the bird-repelling task, it captures pictures and records videos through the camera. The device can automatically capture the dynamic behavior of birds, including their flying away, moving and staying. These data are captured by high-definition cameras and synchronously transmitted to the data analysis module.

[0018] S3: Based on image recognition and video processing technology, the system automatically analyzes the behavior of birds; Based on image recognition and video processing technology, the system can automatically analyze the behavior of birds. The module can detect: After the bird-repelling behavior is triggered, do the birds fly away immediately? Are there any birds that move briefly but do not completely fly away after the device intervenes? Whether there are birds that continue to stay in the area. By identifying different behavior patterns, the system can generate data reports on the effectiveness of the repellent.

[0019] S4: Comprehensively evaluate the bird repellent effect using the effectiveness evaluation index; Performance evaluation indicators include: Repellent success rate: The ratio of the number of birds that fly away immediately after the implementation of the bird repellent strategy to the total number of target birds is counted as the core indicator of bird repellent success.

[0020] Stay time: record the length of time birds stay after the bird repellent strategy is implemented. If the birds fly away in a shorter time, it is considered to be a good bird repellent effect.

[0021] Secondary bird repellent effect: If the initial repellent fails, the system will trigger the device again through the subsequent bird repellent strategy and count the success rate after the secondary repellent to evaluate the comprehensive bird repellent effect of the device on stubborn targets.

[0022] S5: Optimizing the bird-repelling strategy based on the performance evaluation result obtained in step S4 according to the historical data; The system analyzes the performance of different bird-repelling strategies in different environments and time periods based on historical data, and optimizes bird-repelling strategies through performance evaluation results. For example, if the success rate of using sound to repel birds is low during a certain period of time, the system can give priority to the laser strategy in the future, or adjust the switching frequency between laser and sound.

[0023] S6: Introducing intelligent learning to automatically adjust bird-repelling strategies; The system introduces a machine learning model that can automatically adjust the bird-repelling strategy based on past bird-repelling effectiveness data. For example, the system can learn which strategy works best under different lighting, wind speed, bird species, etc., and intelligently select the best solution for the next bird-repelling operation.

[0024] S7: The system generates regular performance evaluation reports and feeds the data back to the user.

[0025] The system can generate regular performance evaluation reports, including the number of successful bird repellent attempts each time, etc. These reports can be provided to users to help them further optimize equipment settings and bird repellent strategies.

[0026] The sound and light fusion bird-repelling effectiveness evaluation system of the present invention comprises: The data collection module is used for the equipment to automatically capture the dynamic behavior of birds, including the status of birds flying away, moving and staying; Behavior recognition and analysis module, used to automatically analyze the behavior status of birds based on image recognition and video processing technology; The effectiveness evaluation module is used to comprehensively evaluate the bird repellent effect, including the evaluation of the bird repellent effect on stubborn targets; The strategy optimization module is used to analyze the performance of different bird-repelling strategies in different environments and time periods based on historical data, and optimize the bird-repelling strategies through performance evaluation results.

[0027] The present invention is applicable to places where birds need to be driven away, such as agriculture, airports, wind farms, photovoltaic power stations, etc. The main problems it solves are: how to quantitatively evaluate the effectiveness of bird-repelling equipment through image and video data; how to optimize bird-repelling strategies through data feedback to achieve a higher success rate of bird-repelling; and to provide flexible and intelligent bird-repelling strategy adjustment methods for different environments and target birds.

Claims

1. A method for evaluating the effectiveness of bird-repelling by combining sound and light, characterized in that: The steps include: S1: The bird repellent device uses AI image recognition to drive away the target using sound and light capabilities; S2: Collect data through high-definition cameras and transmit them to the data analysis module synchronously; S3: Based on image recognition and video processing technology, the system automatically analyzes the behavior of birds; S4: Comprehensively evaluate the bird repellent effect using the effectiveness evaluation index; S5: Optimizing the bird-repelling strategy based on the performance evaluation result obtained in step S4 according to the historical data; S6: Introducing intelligent learning to automatically adjust bird-repelling strategies; S7: The system generates regular performance evaluation reports and feeds the data back to the user.

2. The method for evaluating the effectiveness of bird repelling by combining sound and light according to claim 1, characterized in that: In step (2), when the bird-repelling device performs the bird-repelling task, it automatically captures the dynamic behavior of the birds as data by taking pictures and recording videos through the camera, and synchronously transmits it to the data analysis module.

3. The method for evaluating the effectiveness of bird repelling by combining sound and light according to claim 2, characterized in that: The dynamic behaviors of the bird include the states of the bird flying away, moving and continuing to stay.

4. The method for evaluating the effectiveness of bird repelling by combining sound and light according to claim 1, characterized in that: The system automatically analyzes the behavior status of birds in step (3), including: detecting whether the birds fly away immediately after the bird-repelling behavior is triggered; whether the birds move briefly but do not completely fly away after the device intervenes; and whether the birds continue to stay in the area. By identifying different behavior patterns, a data report on the repelling effect is generated.

5. The method for evaluating the effectiveness of bird repelling by combining sound and light according to claim 1, characterized in that: The performance evaluation indicators of step (4) include expulsion success rate, residence time and secondary expulsion success rate.

6. The method for evaluating the effectiveness of bird repelling by combining sound and light according to claim 5, characterized in that: The driving away success rate is the ratio of the number of birds that fly away immediately after the bird driving away strategy is implemented to the total number of target birds.

7. The method for evaluating the effectiveness of bird-repelling by combining sound and light according to claim 5, characterized in that: The secondary expulsion success rate is the ratio of the number of birds finally expelled to the total number of target birds when the system triggers the device again through a subsequent bird expulsion strategy if the initial expulsion fails.

8. The method for evaluating the effectiveness of bird repelling by combining sound and light according to claim 1, characterized in that: In step (5), the system analyzes the performance of different bird-repelling strategies in different environments and time periods based on historical data, and optimizes the bird-repelling strategies through performance evaluation results. When the success rate of using sound to repel birds is low, the system will give priority to using laser strategies in the future, or adjust the switching frequency between laser and sound.

9. The method for evaluating the effectiveness of bird repelling by combining sound and light according to claim 1, characterized in that: The step (6) includes introducing a machine learning model, based on previous bird-repelling effectiveness data, the system learns which strategy works best under different lighting, wind speed, and bird species conditions, and intelligently selects the best strategy in the next bird-repelling operation.

10. An acoustic-optical fusion bird-repellent effectiveness evaluation system, characterized in that: include: The data collection module is used for the equipment to automatically capture the dynamic behavior of birds, including the status of birds flying away, moving and staying; Behavior recognition and analysis module, used to automatically analyze the behavior status of birds based on image recognition and video processing technology; The effectiveness evaluation module is used to comprehensively evaluate the bird repellent effect, including the evaluation of the bird repellent effect on stubborn targets; The strategy optimization module is used to analyze the performance of different bird-repelling strategies in different environments and time periods based on historical data, and optimize the bird-repelling strategies through performance evaluation results.

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