Wild boar activity intelligent early warning and grading prevention and control method based on AI and thermal imaging

Abstract

The invention discloses a wild boar activity intelligent early warning and grading prevention and control method based on AI and thermal imaging, a sensing system carries out thermal imaging processing and camera shooting monitoring on wild boars in corresponding areas in the air through thermal imaging and camera shooting functions of an unmanned aerial vehicle, and a ground infrared camera array carries out infrared imaging processing on the wild boars around the ground; the sound sensor recognizes the sound of the wild boars, and the ground vibration sensor detects the running of the wild boars and the digging of the ground, and relates to the technical field of early warning, prevention and control of the activities of the wild boars. According to the wild boar activity intelligent early warning and grading prevention and control method based on AI and thermal imaging, a sensing module is arranged in a system, and an unmanned aerial vehicle module, a ground infrared imaging module, a sound recognition processing module and a ground vibration sensing module are matched with one another to perform thermal imaging processing on wild boars so as to obtain specific information of a wild boar group; subsequent driving and marking operations are facilitated while continuous monitoring is carried out, and the danger level of the wild boar herd is analyzed through the analysis module.

Description

TECHNICAL FIELD

[0001] The application relates to a wild boar activity early warning and prevention and control technical field, in particular to a wild boar activity intelligent early warning and hierarchical prevention and control method based on AI and thermal imaging. BACKGROUND

[0002] When the wild boar activity early warning and prevention and control is carried out, the corresponding AI and thermal imaging technology needs to be used, the Chinese patent number "CN107301753A" discloses an intelligent security monitoring system and method, the security state information in the security area is detected by the security monitoring device, and the server group generates a security state hierarchical early warning result according to the security state information, as shown in the above patent, the existing wild boar activity intelligent early warning and hierarchical prevention and control method and device are difficult to acquire and continuously monitor the specific information of the wild boar group in the corresponding area according to the needs of the user, and the hierarchical prevention and control processing is carried out according to the action track of the wild boar group, which is easy to cause a safety hazard, in addition, the system is difficult to kill the wild boar according to the needs of the ecology when the wild boar group reaches the corresponding quantity and density, which is easy to cause the ecological imbalance and cause great economic losses. SUMMARY

[0003] In view of the defects of the prior art, the application provides a wild boar activity intelligent early warning and hierarchical prevention and control method based on AI and thermal imaging, which solves the problems that the system is difficult to monitor the wild boar group in the corresponding area, acquire data, and carry out hierarchical prevention and control processing according to the track of the wild boar.

[0004] To achieve the above purpose, the application is implemented by the following technical scheme: a wild boar activity intelligent early warning and hierarchical prevention and control method based on AI and thermal imaging, specifically comprising the following steps: Step one, the sensing system carries out thermal imaging processing and camera monitoring on the wild boar in the corresponding area in the air through the thermal imaging and camera functions of the unmanned aerial vehicle, the ground infrared camera array carries out infrared imaging processing on the wild boar around the ground, and the sound sensor identifies the call of the wild boar, and the ground vibration sensor detects the running and digging of the wild boar, and the external analysis system analyzes the above data and evaluates and processes the danger level of the wild boar; Step two, in step one, when the wild boar danger level is rated as level one, the wild boar is driven away by the sound wave driver in the unmanned aerial vehicle, when the wild boar danger level is rated as level two, the wild boar is driven away by the light of the unmanned aerial vehicle, when the wild boar danger level is rated as level three, the wild boar is frightened by the pheromone of the wild boar natural enemy released by the unmanned aerial vehicle, whether the wild boar needs to be killed is judged according to the number and density of the wild boar in the corresponding area, when the wild boar does not need to be killed, when the wild boar needs to be killed, an alarm is given, the wild boar data is transmitted to the regional chain storage system, and at the same time the corresponding task of the professional hunter is distributed, after confirming the accuracy of the wild boar distribution information data, the ecological compensation smart contract is generated, and the professional hunter carries out hunting operation according to the real-time dynamic data of the wild boar distribution, the unmanned aerial vehicle dynamically monitors, marks and drives the wild boar group to the hunting range of the hunter; Step three, in step two, when the alarm is given, the AI center estimates the wild boar activity through the wild boar group information and transmits it to the mobile phone APP of the surrounding personnel to remind the risk avoidance planning, and the corresponding area is blocked by the prevention and control fence and is electrified to be closed, when it is confirmed that the wild boar distribution information is not accurate, the hunting action is temporarily terminated, and after the wild boar distribution information is reconfirmed to be accurate, the hunting step is reperformed.

[0005] Preferably, in the step one, after the analysis system analyzes the wild boar data, the wild boar data is stored by the storage system.

[0006] The application also discloses a wild boar activity intelligent early warning and grading prevention and control method based on AI and thermal imaging.

[0007] Preferably, the grading intervention module is connected with the sensing module, the ground vibration sensing module comprises a ground vibration sensor, and the sound recognition processing module comprises a sound sensor.

[0008] Preferably, the unmanned aerial vehicle module comprises a flight module, the flight module is connected with a camera module and a thermal radiation module respectively, and the camera module and the thermal radiation module are respectively connected with a sound wave module, a compression module, a release module and a marking module.

[0009] Preferably, the flight module, the camera module, the thermal radiation module, the sound wave module, the compression module, the release module and the marking module are all connected with the AI center.

[0010] Preferably, the camera module is used for taking pictures of the external environment, the thermal radiation module is used for external infrared imaging processing, the sound wave module and the compression module are used for driving wild boars, the release module is used for releasing pheromones, and the marking module is used for identifying wild boars.

[0011] Preferably, the hunting module comprises an alarm module connected with the judgment module, the alarm module is respectively connected with a distribution module and an induction module, the distribution module and the induction module are both connected with a confirmation module, and the confirmation module is connected with a hunting module.

[0012] Beneficial effects The application provides a wild boar activity intelligent early warning and grading prevention and control method based on AI and thermal imaging. (1) The wild boar activity intelligent early warning and grading prevention and control method based on AI and thermal imaging sets a perception module in the system, so that the unmanned aerial vehicle module, the ground infrared imaging module, the sound recognition processing module and the ground vibration sensing module cooperate with each other to perform thermal imaging processing on wild boars and acquire the scale and distribution information of the wild boars, so as to obtain specific information of the wild boar group, which is helpful for subsequent driving and marking operations while continuously monitoring. The analysis module analyzes the danger level of the wild boar group, the grading intervention module cooperates with the unmanned aerial vehicle module, according to the danger level of the wild boar group, cooperates with the flight module, the camera module, the thermal radiation module, the sound wave module, the compression module and the marking module, drives and scares the wild boar group, and controls the moving track of the wild boar group by marking the corresponding head pig and the track guide, thereby reducing the security risks.

[0013] (2) The wild boar activity intelligent early warning and grading prevention and control method based on AI and thermal imaging sets a camera module and a release module in the system. The camera module cooperates with the thermal radiation module to improve the detection effect on wild boars, and records the surrounding environment to prevent unmanned aerial vehicles from colliding and plan flight routes. The release module releases corresponding pheromones to prevent the wild boar group from entering the corresponding area to cause corresponding damage, thereby improving the prevention and control effect.

[0014] (3) The wild boar activity intelligent early warning and grading prevention and control method based on AI and thermal imaging sets a hunting module in the system. When wild boars need to be hunted, an alarm is sent, wild data is transmitted to a regional chain notarization system, and a professional hunter is assigned a corresponding task. After confirming that the wild boar distribution information data is accurate, an ecological compensation smart contract is generated, so that the professional hunter can hunt according to the real-time dynamic data of the wild boar distribution. The unmanned aerial vehicle dynamically monitors, marks and drives the wild boar group to the hunting range of the hunter. This setting reduces false judgments, ensures hunting accuracy, helps to accurately hunt a corresponding number of wild boars, maintains ecological balance, and reduces the labor intensity and personal risks of hunters. BRIEF DESCRIPTION OF DRAWINGS

[0015] Figure 1 is the main flowchart of the present application; Figure 2 is the main principle block diagram of the present application; Figure 3 is the principle block diagram of the internal loss analysis module of the present application; Figure 4 is the principle block of the internal monitoring module of the present application. DETAILED DESCRIPTION

[0016] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0017] Reference Figures 1-4 The AI and thermal imaging based intelligent early warning and hierarchical prevention and control method for wild boar activities specifically includes the following steps: Step one, the sensing system performs thermal imaging processing and camera monitoring on the wild boars in the corresponding area in the air through the thermal imaging and camera functions of the unmanned aerial vehicle. At the same time, the ground infrared camera array performs infrared imaging processing on the wild boars around the ground, and the sound sensor identifies the wild boar calls, and the ground vibration sensor detects the wild boar running and digging behaviors, thereby analyzing the position, number, size, leader, and running trajectory of the wild boars. The external analysis system analyzes the above data and evaluates and processes the danger level of the wild boars. Step two, in step one, when the wild boar danger level is rated as level one, the wild boars are driven away by the sound wave driver in the unmanned aerial vehicle. When the wild boar danger level is rated as level two, the wild boars are driven away by the light of the unmanned aerial vehicle. When the wild boar level is rated as level three, the pheromone of the natural enemy of the wild boar is released by the unmanned aerial vehicle to scare the wild boar and guide the direction of the wild boar. At the same time, the information of the wild boar group is marked, and whether the wild boar needs to be killed is determined according to the number and density of the wild boars in the corresponding area. When the wild boar does not need to be killed, the system transmits a signal to the surrounding area to display the number and movement range of the wild boar. When the wild boar needs to be killed, an alarm is first given, the wild data is transmitted to the regional chain notarization system, and at the same time, the corresponding task of the professional hunter is distributed. After confirming the accuracy of the wild boar distribution information data, an ecological compensation smart contract is generated, and the professional hunter performs hunting operation according to the real-time dynamic data of the wild boar distribution. In this process, the unmanned aerial vehicle dynamically monitors, marks, and drives the wild boar group to the hunting range of the hunter. Step three, in step two, when the alarm, the AI hub estimates the boar activity by the boar information and transmits it to the surrounding personnel's mobile phone APP for risk planning reminder, and blocks the corresponding area through the prevention and control fence and electrifies to close the processing, when confirming that the boar distribution information is inaccurate, temporarily terminate the hunting action, and after reconfirming that the boar distribution information is accurate, re-perform the hunting step.

[0018] In step one, after the analysis system analyzes the boar data, the boar data is stored by the storage system.

[0019] Reference Figures 1-4 The application also discloses a boar activity intelligent early warning and hierarchical prevention and control method based on AI and thermal imaging. The first embodiment comprises a sensing module, the sensing module comprises a UAV module, a ground infrared imaging module, a ground vibration sensing module and a sound recognition processing module, the UAV module, the ground infrared imaging module, the ground vibration sensing module and the sound recognition processing module are connected with an analysis module for boar information summary and analysis, the analysis module is connected with a storage module and a risk grading module, the risk grading module is connected with a grading intervention module for risk grading, the risk grading module is connected with a judgment module, and the judgment module is connected with a protection module and a killing module; the grading intervention module is connected with the sensing module, the ground vibration sensing module comprises a ground vibration sensor, and the sound recognition processing module comprises a sound sensor. The UAV module comprises a flight module, and the flight module is connected with a camera module and a thermal radiation module; the camera module and the thermal radiation module are connected with a sound wave module, a compression module, a release module and a marking module; the flight module, the camera module, the thermal radiation module, the sound wave module, the compression module, the release module and the marking module are connected with an AI hub; the sound wave module comprises a sound wave driver, and the compression module comprises a light lamp; the UAV module, the ground infrared imaging module, the sound recognition processing module and the ground vibration sensing module cooperate with each other to perform thermal imaging processing on the boar and acquire the scale and distribution information of the boar, so as to obtain specific information of the boar group; the analysis module analyzes the danger level of the boar group; the grading intervention module cooperates with the UAV module to drive and intimidate the boar group according to the danger level of the boar group, and controls the moving track of the boar group through marking the corresponding head boar and track guidance. The second embodiment differs from the first embodiment mainly in that: The camera module is used for taking pictures of the external environment, the thermal radiation module is used for external infrared imaging processing, the sound wave module and the compression module are used for driving wild boars, the release module is used for releasing the pheromone of natural enemies of wild boars, and the marking module is used for identifying wild boars. The camera module takes pictures of the external environment to improve the detection effect on wild boars in cooperation with the thermal radiation module, and the release module prevents the wild boar group from entering the corresponding area by releasing the corresponding pheromone. The third embodiment is mainly different from the second embodiment in that: The hunting module includes an alarm module connected with the judgment module, the alarm module is respectively connected with a distribution module and an induction module, the induction module is used for inducing wild boar distribution information data, the distribution module and the induction module are both connected with a confirmation module, the confirmation module is connected with a hunting module, the distribution module is used for distributing hunter tasks, and the confirmation module is used for confirming the accuracy of wild boar distribution information data. When wild boars need to be hunted, an alarm is sent, wild data is transmitted to the regional chain notarization system, and at the same time, professional hunters are distributed with corresponding tasks. After confirming the accuracy of the wild boar distribution information data, an ecological compensation smart contract is generated, and the professional hunters hunt according to the real-time dynamic data of the wild boar distribution. The unmanned aerial vehicle dynamically monitors, marks and drives the wild boar group to the hunting range of the hunter.

[0020] Meanwhile, the contents not described in detail in the specification are all prior art known to those skilled in the art, and the model parameters of each electric appliance are not specifically limited, and conventional equipment can be used.

[0021] It should be noted that, in the present document, the relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations. Moreover, the terms "include", "contain" or any other variants thereof are intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements not only includes those elements, but also includes other elements not explicitly listed or inherent to such process, method, article or equipment.

[0022] Although the embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to the embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A method for intelligent early warning and hierarchical control of wild boar activity based on AI and thermal imaging, characterized by: Specifically, the following steps are included: Step 1: The perception system uses the thermal imaging and video recording functions of the UAV to perform thermal imaging processing and video monitoring of wild boars in the corresponding area from the air. The ground infrared camera array performs infrared imaging processing of wild boars around the ground, while the sound sensor identifies the calls of wild boars, and the ground vibration sensor detects the running and digging behavior of wild boars. The above data is analyzed by the external analysis system and the danger level of wild boars is assessed. Step Two: In Step One, when the wild boar danger level is Level One, the drone uses a sonic deterrent to drive the wild boar away. When the wild boar danger level is Level Two, the drone uses lights to drive the wild boar away. When the wild boar danger level is Level Three, the drone releases pheromones from the wild boar's natural enemies to scare the wild boar away. The drone determines whether to kill the wild boar based on the number and density of wild boars in the corresponding area. When it is not necessary to kill the wild boar, an alarm is triggered. When it is necessary to kill the wild boar, the wild boar data is transmitted to the blockchain evidence storage system and professional hunters are assigned corresponding tasks. After confirming that the wild boar distribution information is accurate, an ecological compensation smart contract is generated, allowing professional hunters to carry out hunting operations based on the real-time dynamic data of wild boar distribution. The drone dynamically monitors, marks, and drives the wild boar herd to the hunters' hunting range. Step 3: In step 2, when an alarm is triggered, the AI ​​hub summarizes the wild boar activity estimate based on the wild boar herd information and transmits it to the mobile APP of people in the vicinity for evacuation planning reminders. It also isolates the corresponding area through protective fences and energizes it for closure. If the wild boar distribution information is confirmed to be inaccurate, the hunting operation is temporarily suspended. The hunting steps are resumed after the wild boar distribution information is reconfirmed to be accurate.

2. The method for intelligent early warning and hierarchical control of wild boar activity based on AI and thermal imaging as described in claim 1, characterized in that: In step one, after the analysis system finishes analyzing the wild boar data, the data is stored and processed through the storage system.

3. The system for intelligent early warning and hierarchical control of wild boar activity based on AI and thermal imaging as described in claim 2, comprising a sensing module, characterized in that: The perception module includes a drone module, a ground infrared imaging module, a ground vibration sensing module, and a sound recognition and processing module. The drone module, ground infrared imaging module, ground vibration sensing module, and sound recognition and processing module are all connected to an analysis module for summarizing and analyzing wild boar information. The analysis module is connected to a storage module and a risk classification module. The risk classification module is connected to a risk classification intervention module and a judgment module. The judgment module is connected to a protection module and a capture module.

4. The system of intelligent early warning and hierarchical control method for wild boar activity based on AI and thermal imaging as described in claim 3, characterized in that: The graded intervention module is connected to the sensing module, the ground vibration sensing module includes a ground vibration sensor, and the sound recognition and processing module includes a sound sensor.

5. The system of intelligent early warning and hierarchical control method for wild boar activity based on AI and thermal imaging as described in claim 3, characterized in that: The drone module includes a flight module, which is connected to a camera module and a thermal radiation module. The camera module and the thermal radiation module are respectively connected to a sound wave module, a pressure module, a release module, and a marking module.

6. The system of intelligent early warning and hierarchical control method for wild boar activity based on AI and thermal imaging as described in claim 5, characterized in that: The flight module, camera module, thermal radiation module, acoustic wave module, pressure module, release module, and marking module are all connected to the AI ​​hub.

7. The system for intelligent early warning and hierarchical control of wild boar activity based on AI and thermal imaging as described in claim 6, characterized in that: The camera module is used to capture images of the external environment, the thermal radiation module is used for external infrared imaging processing, the sound wave module and the pressure module are both used to drive away wild boars, the release module is used to release pheromones, and the marking module is used to identify wild boars.

8. The system of intelligent early warning and hierarchical control method for wild boar activity based on AI and thermal imaging as described in claim 7, characterized in that: The hunting module includes an alarm module connected to the judgment module. The alarm module is connected to an allocation module and a summarization module. Both the allocation module and the summarization module are connected to a confirmation module. The confirmation module is connected to the hunting module.

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