CN-122004197-A - Intelligent accurate bird repelling system and method based on voiceprint recognition and bionic natural enemy

CN122004197ACN 122004197 ACN122004197 ACN 122004197ACN-122004197-A

Abstract

The invention relates to the technical field of bird repelling, and discloses an intelligent accurate bird repelling system and method based on voiceprint recognition and bionic natural enemies, wherein the system comprises a voiceprint acquisition recognition module; the bird driving system comprises a bird driving strategy making module, a bird driving strategy executing feedback module, an optimizing strategy module, a bird driving strategy optimizing module and a bird driving strategy optimizing module, wherein the bird driving strategy making module is used for collecting bird stress response data and environment parameters in the bird driving strategy when judging to optimize the bird driving strategy, and optimizing the bird driving strategy based on real-time bird sound signals, bird stress response data and environment parameters to obtain the optimized bird driving strategy. According to the bird-repellent method, accurate identification of bird types and behavior states in a target area is achieved through the voiceprint acquisition and identification module, scientific basis is provided for formulation of a differentiated bird-repellent strategy, and blindness of a traditional bird-repellent method to all birds is avoided.

Inventors

GONG XIAODI
ZHANG QINGWEI
WANG MIN
ZHAO QINGSONG
YANG LONG
ZHANG CHUNXIANG
Fan Pinghua
XIE YANYAN

Assignees

泰安市泰山林业科学研究院

Dates

Publication Date: 20260512
Application Date: 20260209

Claims (10)

1. Accurate bird system that drives of intelligence based on voiceprint discernment and bionical natural enemy, its characterized in that includes: The bird voice signal acquisition and recognition module is used for acquiring bird voice signals before the bird repelling strategy is implemented in a target area, extracting characteristics of the bird voice signals and obtaining bird voice characteristics, and matching and recognizing the bird voice characteristics with a preset bird voice characteristic library to determine the types and behavior states of the birds; the bird-repellent strategy formulation module is used for acquiring a comprehensive risk evaluation value of a target bird to the target area according to the types and behavior states of the birds, and determining the bird-repellent strategy based on the comprehensive risk evaluation value; The bird repelling strategy execution feedback module is used for repelling target birds in the target area by the bird repelling strategy, collecting real-time bird sound signals in the target area after a preset time interval, and evaluating bird repelling effects according to the change condition of the real-time bird sound signals so as to judge whether the bird repelling strategy needs to be optimized; The bird driving strategy optimizing module is used for acquiring bird stress response data and environment parameters in the bird driving strategy when judging to optimize the bird driving strategy, and optimizing the bird driving strategy based on the real-time bird sound signals, the bird stress response data and the environment parameters to obtain the optimized bird driving strategy.
2. The intelligent precision bird repellent system based on voiceprint recognition and simulated natural enemies of claim 1, wherein the bird species include rag birds, medium-sized and large-sized populated birds, small-sized singing birds, water birds and nocturnal birds, and the behavioral states include foraging states, nesting states, migration passing states, field defense states and clustered hover states.
3. The intelligent accurate bird repellent system based on voiceprint recognition and bionic natural enemies according to claim 2, wherein when obtaining the comprehensive risk assessment value of the target bird to the target area according to the kind and behavior state of the bird, the intelligent accurate bird repellent system comprises: determining corresponding bird base risk parameters based on the types of birds, wherein the base risk parameters comprise body type risk coefficients, social risk coefficients and activity time risk coefficients; Extracting behavior characteristic parameters corresponding to the behavior state, wherein the behavior characteristic parameters comprise stay time, activity frequency and behavior aggregation degree; weighting and fusing the basic risk parameters and the behavior characteristic parameters to obtain a behavior risk evaluation value of the target birds; Acquiring region attribute parameters of the target region; and carrying out association analysis on the behavior risk evaluation value and the regional attribute parameter to obtain an association influence value, and obtaining a comprehensive risk evaluation value of influence of the target birds on the target region according to the association influence value.
4. The intelligent accurate bird repellent system based on voiceprint recognition and bionic natural enemies according to claim 3, wherein the performing the association analysis on the behavior risk assessment value and the regional attribute parameter to obtain an association influence value comprises: Performing time dimension standardization processing on the behavior risk evaluation value to obtain a behavior risk time sequence; Performing parameter decoupling processing on the regional attribute parameters, and dividing the regional attribute parameters into static regional parameters and dynamic regional parameters, wherein the static regional parameters comprise regional function types and environment sensitivity levels, and the dynamic regional parameters comprise real-time environment change parameters and historical bird activity frequency parameters; Performing time sequence correlation analysis based on the behavior risk time sequence and the dynamic region parameters to obtain a correlation index between the behavior change of the target birds and the region environment change; calculating a risk amplification factor based on the behavioral risk assessment value and the static region parameter; and carrying out weighted fusion on the relevance index and the risk amplification factor to obtain a relevant influence value of the target bird behavior on the target area.
5. The intelligent accurate bird repellent system based on voiceprint recognition and bionic natural enemies according to claim 4, wherein when obtaining the comprehensive risk assessment value of the influence of the target bird on the target area according to the associated influence value, the intelligent accurate bird repellent system comprises: Comparing the association influence value with a first association influence value and a second association influence value, and determining the comprehensive risk assessment value according to the comparison result, wherein the first association influence value is smaller than the second association influence value; When the association influence value is smaller than or equal to the first association influence value, determining the comprehensive risk evaluation value as a first comprehensive risk evaluation value; when the association influence value is greater than the first association influence value and less than or equal to the second association influence value, determining the comprehensive risk assessment value as a second comprehensive risk assessment value; And when the association influence value is larger than the second association influence value, determining the comprehensive risk evaluation value as a third comprehensive risk evaluation value.
6. The intelligent precision bird repellent system based on voiceprint recognition and simulated natural enemies of claim 5, wherein when determining the bird repellent strategy based on the integrated risk assessment value, comprising: And comparing the comprehensive risk evaluation value with a preset bird repellent strategy mapping set, and determining the bird repellent strategy according to the comparison result.
7. The intelligent precise bird repellent system based on voiceprint recognition and bionic natural enemies according to claim 6, wherein the evaluating the bird repellent effect according to the change condition of the real-time bird sound signal to determine whether the bird repellent strategy needs to be optimized comprises: Performing characteristic alignment processing on the bird sound signals before implementing the bird repellent strategy and the real-time bird sound signals after implementing the bird repellent strategy, and extracting voiceprint intensity characteristics, voiceprint occurrence frequency characteristics and voiceprint duration characteristics in corresponding time periods; Constructing bird activity change indexes before and after bird repellent based on the voiceprint intensity characteristic, the voiceprint occurrence frequency characteristic and the voiceprint duration characteristic; Comparing the bird activity change index with a bird activity change index threshold, and judging whether the bird repelling strategy needs to be optimized according to the comparison result; When the bird activity change index is smaller than or equal to the bird activity change index threshold, judging that the bird repellent effect reaches the expected value, and optimizing a bird repellent strategy is not needed; When the bird activity change index is larger than the bird activity change index threshold, judging that the bird repelling effect is not expected, and optimizing a bird repelling strategy is needed.
8. The intelligent precision bird repellent system based on voiceprint recognition and bionic natural enemies of claim 7, wherein when optimizing the bird repellent strategy based on the real-time bird sound signal, bird stress response data and environmental parameters to obtain an optimized bird repellent strategy, comprising: extracting stress characteristics of the real-time bird sound signals to obtain voiceprint stress characteristic parameters, wherein the voiceprint stress characteristic parameters comprise alarm sound proportion change, voiceprint frequency spectrum change amplitude and voiceprint continuity change characteristics; Constructing an optimized feature group according to the bird activity change index, the voiceprint stress feature parameter and the environmental parameter level; Comparing the optimized feature set with a historical bird-repellent optimized set, and determining optimized parameters of the bird-repellent strategy according to the comparison result; If the history bird repellent optimization group has a history optimization feature group matched with the optimization feature group, taking a history optimization parameter corresponding to the history optimization feature group as the optimization parameter; and if the history bird repellent optimization group does not have the history optimization feature group matched with the optimization feature group, determining the optimization parameters according to the optimization feature group.
9. The intelligent precision bird repellent system based on voiceprint recognition and bionic natural enemies of claim 8, wherein determining the optimization parameters from the set of optimization features comprises: Normalizing the bird activity change index, the voiceprint stress characteristic parameter and the environment parameter; Based on the normalized bird activity change index, the voiceprint stress characteristic parameter and the environment parameter, respectively constructing a behavior change sub-state value, a voiceprint stress sub-state value and an environment correction sub-state value, and obtaining a comprehensive stress-adaptation state value of the target bird to the current bird driving strategy in a weighted fusion mode; According to the comprehensive stress-adaptation state value and a preset stress-adaptation state threshold value interval, determining a stress reaction stage where a current target bird is located, wherein the stress reaction stage comprises a low stress adaptation stage, a moderate stress resistance stage and a high stress avoidance stage; and determining the optimization parameters according to the stress reaction stage.
10. An intelligent accurate bird repellent method based on voiceprint recognition and bionic natural enemies, applied to the intelligent accurate bird repellent system based on voiceprint recognition and bionic natural enemies as set forth in any one of claims 1 to 9, comprising: The bird voice signal processing method comprises the steps of collecting bird voice signals before bird repelling strategies are implemented in a target area, extracting characteristics of the bird voice signals to obtain bird voice characteristics, and carrying out matching recognition on the bird voice characteristics and a preset bird voice characteristic library to determine the types and behavior states of the birds; Acquiring a comprehensive risk assessment value of a target bird to the target area according to the type and behavior state of the bird, and determining the bird repelling strategy based on the comprehensive risk assessment value; The bird repelling strategy is used for repelling target birds in the target area, real-time bird sound signals in the target area are collected after a preset time interval, and bird repelling effects are evaluated according to the change condition of the real-time bird sound signals so as to judge whether the bird repelling strategy needs to be optimized; When the bird driving strategy is judged to be optimized, bird stress response data and environmental parameters in the bird driving strategy are collected, and the bird driving strategy is optimized based on the real-time bird sound signals, the bird stress response data and the environmental parameters so as to obtain the optimized bird driving strategy.

Description

Intelligent accurate bird repelling system and method based on voiceprint recognition and bionic natural enemy Technical Field The invention relates to the technical field of bird repelling, in particular to an intelligent accurate bird repelling system and method based on voiceprint recognition and bionic natural enemies. Background The traditional bird repellent method relies on manual repellent, physical barrier or single sound repellent, and has limitations. The bird repellent has the advantages of manual driving, difficult and durable effect, easy adaptation of birds, high installation and maintenance cost, damage to birds and influence on the beauty and functions of areas, fixed single-sound driving factor mode, short-time adaptation of birds, rapid reduction of bird driving effect and difficult long-term bird driving, and can be used for preventing birds from being blocked by a physical barrier such as a bird preventing net. In addition, the existing bird repelling technology lacks of accurately identifying bird species and behavior states, cannot adopt a differential strategy, is blind in bird repelling, wastes resources, and can also interfere non-target birds, so that ecological protection is not favored. Therefore, it is necessary to design an intelligent accurate bird repellent system and method based on voiceprint recognition and bionic natural enemies to solve the problems in the prior art. Disclosure of Invention In view of the above, the invention provides an intelligent accurate bird repelling system and method based on voiceprint recognition and bionic natural enemies, and aims to solve the problems of the prior art that the bird repelling method is not durable in bird repelling effect, strong in bird adaptability and lack of accurate recognition and differentiation strategies. The invention provides an intelligent accurate bird repellent system based on voiceprint recognition and bionic natural enemies, which comprises: The bird voice signal acquisition and recognition module is used for acquiring bird voice signals before the bird repelling strategy is implemented in a target area, extracting characteristics of the bird voice signals and obtaining bird voice characteristics, and matching and recognizing the bird voice characteristics with a preset bird voice characteristic library to determine the types and behavior states of the birds; the bird-repellent strategy formulation module is used for acquiring a comprehensive risk evaluation value of a target bird to the target area according to the types and behavior states of the birds, and determining the bird-repellent strategy based on the comprehensive risk evaluation value; The bird repelling strategy execution feedback module is used for repelling target birds in the target area by the bird repelling strategy, collecting real-time bird sound signals in the target area after a preset time interval, and evaluating bird repelling effects according to the change condition of the real-time bird sound signals so as to judge whether the bird repelling strategy needs to be optimized; The bird driving strategy optimizing module is used for acquiring bird stress response data and environment parameters in the bird driving strategy when judging to optimize the bird driving strategy, and optimizing the bird driving strategy based on the real-time bird sound signals, the bird stress response data and the environment parameters to obtain the optimized bird driving strategy. Further, the bird species include raging birds, medium and large-sized populated birds, small-sized singing birds, water birds and nocturnal birds, and the behavior states include foraging states, nesting states, migration pathway states, field defense states and cluster hover states. Further, when the comprehensive risk assessment value of the target bird to the target area is obtained according to the type and behavior state of the bird, the method comprises the following steps: determining corresponding bird base risk parameters based on the types of birds, wherein the base risk parameters comprise body type risk coefficients, social risk coefficients and activity time risk coefficients; Extracting behavior characteristic parameters corresponding to the behavior state, wherein the behavior characteristic parameters comprise stay time, activity frequency and behavior aggregation degree; weighting and fusing the basic risk parameters and the behavior characteristic parameters to obtain a behavior risk evaluation value of the target birds; Acquiring region attribute parameters of the target region; and carrying out association analysis on the behavior risk evaluation value and the regional attribute parameter to obtain an association influence value, and obtaining a comprehensive risk evaluation value of influence of the target birds on the target region according to the association influence value. Further, performing association analysis on the behavior risk assessment value an