Multifunctional mammal ecological monitoring system and method based on unmanned aerial vehicle

Abstract

The invention discloses a multifunctional mammal ecological monitoring system and method based on an unmanned aerial vehicle, and belongs to the technical field of ecological monitoring. The system comprises an unmanned aerial vehicle platform configured to provide a flight function and provide a mounting platform for other modules; the multi-sensor integration module is configured to be capable of collecting information of mammals and living areas of the mammals; the intelligent control module is configured to identify a target, navigate and control the work of the unmanned aerial vehicle platform; and the data processing module is configured to perform edge calculation on the collected data, fuse the data of the multiple sensors and generate an ecological behavior monitoring result and a habitat environment monitoring result of the mammals. According to the invention, high-precision, intelligent, low-interference and large-range real-time monitoring of ecological behaviors, population distribution, habitat environment and the like of mammals can be realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of ecological monitoring, and in particular relates to a multifunctional mammal ecological monitoring system and method based on an unmanned aerial vehicle. Background Art

[0002] Traditional mammal ecological monitoring mainly relies on manual inspections, infrared cameras, GPS collars, etc. However, with the deepening of ecological research and the continuous improvement of monitoring accuracy and scope requirements, the inherent shortcomings of traditional mammal ecological monitoring methods have become increasingly obvious.

[0003] Manual inspections, as the most basic monitoring method, rely on professionals to conduct field observations and records in the habitats of mammals. Although this method can intuitively obtain behavioral information about animals, it is limited by manpower, time and geographical conditions. In severe weather or complex, large-scale terrain conditions, it is almost impossible to carry out work or only work can be carried out within a certain range, making it impossible to guarantee the continuity of data collection. More importantly, the intervention of human activities may interfere with the normal behavior of mammals, resulting in deviations in observation results.

[0004] Infrared cameras make up for some of the shortcomings of manual inspections to a certain extent. They can automatically capture images of animals without human supervision. However, the monitoring range of infrared cameras is also limited. Each camera can only cover a specific area, and the appropriate installation location needs to be selected in advance. Once installed, it is difficult to adjust flexibly. There are a large number of monitoring blind spots between different cameras, making it difficult to achieve seamless monitoring of large areas of habitat. In addition, the data collection of infrared cameras depends on animals actively entering their shooting range. If the animal's activity trajectory is relatively scattered or there is alertness to the camera, some animals may not be recorded for a long time, and the integrity of the data will be greatly reduced.

[0005] GPS collars track the movements of mammals through satellite positioning technology, providing strong data support for studying animal migration, territorial range, etc. However, putting a collar on an animal is itself an invasive operation, which may have potential effects on the animal's behavior and health. For example, the weight of the collar may affect the animal's ability to move, especially for some small mammals. Moreover, the battery life of GPS collars is limited, and signal transmission is easily affected by terrain and weather, resulting in interrupted or inaccurate data. At the same time, due to the high cost, it is difficult to apply it on a large scale to monitor multiple species and a large range of mammals.

[0006] In recent years, drone technology has gradually emerged in the field of ecological monitoring due to its unique advantages. Drones can quickly reach areas that are difficult for humans to access and achieve large - area low - altitude monitoring. Devices such as high - definition cameras and thermal imagers carried by drones can, to a certain extent, obtain information on the distribution and behavior of mammals. However, existing drone systems are unable to fully meet the requirements for comprehensive monitoring of mammalian ecological behavior. In terms of functionality, most drones currently used for ecological monitoring only have simple shooting and image transmission functions. They cannot perform real - time and accurate analysis on the acquired images and videos, are difficult to identify different species of mammals, and are even less able to deeply analyze complex information such as animal behavior patterns and social structures. In a complex ecological environment, such as when multiple herbivores live in mixed groups on the grassland, it is difficult for existing drones to accurately distinguish each individual animal and continuously track its behavior. In terms of intelligence level, existing drones lack the ability of autonomous decision - making and adaptive adjustment. When encountering sudden situations such as weather changes or animals suddenly changing their movement directions, they cannot automatically adjust the monitoring strategy. For example, when encountering rainy weather, drones may not be able to automatically adjust the flight altitude and shooting parameters according to the reduced visibility, resulting in a serious decline in the quality of monitoring data.

[0007] In summary, traditional means of mammalian ecological monitoring have many deficiencies, and existing drone systems cannot meet the requirements for comprehensive monitoring. Developing a multi - functional, intelligent, and low - interference drone system for mammalian ecological monitoring has become an urgent task. Summary of the Invention

[0008] The present invention aims to solve at least one of the technical problems in the above - mentioned related technologies to a certain extent.

[0009] For this reason, the object of the present invention is to provide a multi - functional mammalian ecological monitoring system and method based on drones, which can perform high - precision, intelligent, low - interference, and large - range real - time monitoring on the ecological behavior, population distribution, habitat environment, etc. of mammals.

[0010] To solve the above - mentioned technical problems, the present invention is implemented as follows:

[0011] The embodiment of the present invention provides a multi - functional mammalian ecological monitoring system based on drones, and the system includes:

[0012] A drone platform, configured to be able to provide a flight function and provide an installation platform for other modules;

[0013] A multi - sensor integration module, configured to be able to collect information on mammals and their living areas;

[0014] An intelligent control module, configured to be able to identify targets and navigate, and control the operation of the drone platform; and,

[0015] A data processing module, configured to be able to perform edge computing on the collected data, fuse multi-sensor data, and generate ecological behavior monitoring results and habitat environment monitoring results of mammals.

[0016] In addition, the multi-functional mammalian ecological monitoring system based on an unmanned aerial vehicle according to the present invention may further have the following additional technical features:

[0017] In some embodiments, the multi-sensor integration module includes a camera, a thermal imager, a lidar, an acoustic sensor, and an environmental sensor;

[0018] The high-definition camera is configured to be able to capture behavior images and videos of mammals;

[0019] The thermal imager is configured to be able to identify the body temperature characteristics of mammals;

[0020] The lidar is configured to be able to perform topographic mapping and three-dimensional modeling of the habitat;

[0021] The acoustic sensor is configured to be able to collect sound signals of mammals;

[0022] The environmental sensor is configured to be able to monitor environmental parameters of the habitat.

[0023] In some embodiments, the environmental sensor includes a temperature and humidity sensor, a barometric pressure sensor, and an air quality sensor.

[0024] In some embodiments, the intelligent control module includes:

[0025] An autonomous navigation system, configured to be able to perform path planning and flight control of the unmanned aerial vehicle;

[0026] A target recognition and tracking system, configured to be able to identify and track mammals in real time, and adjust the flight path and sensor parameters on the original path; and,

[0027] An obstacle avoidance system, configured to be able to perform obstacle avoidance during flight through ultrasonic and infrared obstacle avoidance sensor data, and ensure the safe flight of the unmanned aerial vehicle in a complex environment.

[0028] In some embodiments, the data processing module includes:

[0029] An edge computing unit, configured to be able to perform edge computing on the collected data, process sensor data in real time, and reduce data transmission latency;

[0030] A data compression and encryption unit, configured to be able to compress and encrypt the collected data to ensure data security and transmission efficiency; and,

[0031] A data fusion and analysis unit, configured to be able to fuse multi-sensor data to generate an ecological behavior map of mammals and a habitat environment data report.

[0032] In some embodiments thereof, the ground station system includes:

[0033] A remote monitoring and control unit, communicatively connected to the intelligent control module, configured to be able to monitor the flight status and sensor data of the unmanned aerial vehicle in real time, and be able to remotely control the unmanned aerial vehicle and adjust tasks;

[0034] A data storage and management unit, configured to be able to provide a large-capacity data storage and database management function, and support long-term data preservation and query; and,

[0035] A visualization display unit, configured to be able to display the monitoring data in various forms to facilitate data analysis and decision-making by relevant personnel.

[0036] In some embodiments thereof, the multi-sensor integration module further includes a multi-spectral camera; the multi-spectral camera is configured to be able to collect mammalian fur data and water pollution data.

[0037] An embodiment of the present invention further provides a multi-functional mammalian ecological monitoring method based on an unmanned aerial vehicle, which is implemented based on the multi-functional mammalian ecological monitoring system based on an unmanned aerial vehicle as described in any one of the above; the content of the method includes:

[0038] S1. Start the unmanned aerial vehicle system and initialize the parameters related to flight and monitoring;

[0039] S2. Autonomous flight and monitoring of the unmanned aerial vehicle; the content includes:

[0040] Generate an optimal flight path according to the preset monitoring area and obstacles within the area, and perform flight of the unmanned aerial vehicle and data collection of multi-sensors; during the flight, according to the recognition result of the mammalian target, adjust the flight path and flight parameters in real time to achieve tracking and monitoring of mammals.

[0041] S3. Data processing and analysis: Process the collected various types of data, and perform fusion and analysis of multi-data to obtain the ecological behavior monitoring result and habitat environment monitoring result of mammals.

[0042] In addition, according to the multi-functional mammalian ecological monitoring method based on an unmanned aerial vehicle of the present invention, the following additional technical features may also be included:

[0043] In some of these embodiments, the method further includes:

[0044] Communicating with the unmanned aerial vehicle (UAV) through the ground station system, monitoring the flight status and sensor data of the UAV, and presenting the monitoring data in various forms by the ground station system for relevant personnel to query, analyze, and make decisions on the data.

[0045] In some of these embodiments, in step S3, the ecological behavior monitoring results and habitat environment monitoring results of mammals include:

[0046] An ecological behavior atlas capable of showing the activity trajectories and behavior patterns of mammals;

[0047] A habitat environment report containing a three-dimensional terrain model and changes in environmental parameters; and,

[0048] Species identification results based on the classification of image and acoustic data.

[0049] Compared with the prior art, the present invention has at least the following beneficial effects:

[0050] In the embodiments of the present invention, the provided multi-functional mammalian ecological monitoring system based on UAV integrates multiple sensors on the UAV platform, realizes the omni-directional monitoring of the ecological behavior of mammals, and overcomes the shortcoming of the single function of traditional monitoring means;

[0051] In the embodiments of the present invention, the provided multi-functional mammalian ecological monitoring system based on UAV adopts deep learning algorithms and autonomous navigation technologies, realizes the intelligent flight and target tracking of the UAV, and improves the monitoring efficiency and accuracy;

[0052] In the embodiments of the present invention, the provided multi-functional mammalian ecological monitoring system based on UAV reduces the interference to mammals by optimizing the UAV structure and flight strategy, and ensures the authenticity and reliability of the monitoring data;

[0053] In the embodiments of the present invention, the provided multi-functional mammalian ecological monitoring system based on UAV integrates an edge computing unit on the UAV, realizes the real-time processing and analysis of data, and improves the response speed of the monitoring system.

[0054] The multi-functional mammalian ecological monitoring method based on UAV of the present invention is implemented by using the multi-functional mammalian ecological monitoring system based on UAV, and thus has at least all the features and advantages of the multi-functional mammalian ecological monitoring system based on UAV, which will not be elaborated here. The additional aspects and advantages of the present invention will be partially given in the following description, partially become obvious from the following description, or be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 Structural block diagram of a multi-functional mammalian ecological monitoring system based on an unmanned aerial vehicle disclosed in an embodiment of the present invention. Detailed implementation manners

[0056] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0057] Next, the embodiments of the present invention will be described in detail with reference to the accompanying drawings, through specific embodiments and their application scenarios.

[0058] Please refer to Figure 1 As shown, in some embodiments of the present invention, a multi-functional mammalian ecological monitoring system based on an unmanned aerial vehicle is provided, including an unmanned aerial vehicle platform, a multi-sensor integration module, an intelligent control module, a data processing module, and a ground station system.

[0059] In some embodiments of the present invention, the unmanned aerial vehicle platform adopts a quadcopter or a hexacopter unmanned aerial vehicle, which has a long endurance (endurance time ≥ 60 minutes) and wind resistance (wind resistance level ≥ 6). It is equipped with foldable arms and a waterproof housing to adapt to monitoring tasks in complex terrains and harsh weather conditions.

[0060] In some embodiments of the present invention, the multi-sensor integration module is equipped with a high-definition camera, a thermal imager, a lidar, an acoustic sensor, and an environmental sensor. The high-definition camera is a high-definition camera with a 4K resolution, supporting optical zoom and night vision functions, and is used to capture the behavior images and videos of mammals. The thermal imager is used for detecting mammals at night or in densely vegetated areas and identifying the body temperature characteristics of animals. The lidar (LiDAR) is used for terrain mapping and three-dimensional modeling of habitats, providing high-precision environmental data. The acoustic sensor is used to collect the sound signals of mammals and support species identification and behavior analysis. The environmental sensor includes a temperature and humidity sensor, a barometric pressure sensor, an air quality sensor, etc., and is used to monitor the environmental parameters of the habitat.

[0061] In some embodiments of the present invention, the intelligent control module includes an autonomous navigation system, a target recognition and tracking system, and an obstacle avoidance system. The autonomous navigation system, based on GPS and visual SLAM (Simultaneous Localization and Mapping) technology, realizes the autonomous flight and path planning of the unmanned aerial vehicle (UAV). The target recognition and tracking system adopts deep learning algorithms to identify and track mammals in real time, and automatically adjusts the flight path and sensor parameters. The obstacle avoidance system is equipped with ultrasonic and infrared obstacle avoidance sensors to ensure the safe flight of the UAV in complex environments.

[0062] In some embodiments of the present invention, the data processing module includes an edge computing unit, a data compression and encryption unit, and a data fusion and analysis unit. The edge computing unit integrates high-performance edge computing devices on the UAV to process sensor data in real time and reduce data transmission latency. The data compression and encryption unit compresses and encrypts the collected data to ensure data security and transmission efficiency. The data fusion and analysis unit fuses multi-sensor data to generate ecological behavior maps of mammals and habitat environment reports.

[0063] In some embodiments of the present invention, the ground station system includes a remote monitoring and control unit, a data storage and management unit, and a visualization display unit. The remote monitoring and control unit, through the ground station software, monitors the flight status and sensor data of the UAV in real time, and supports remote control and task adjustment. The data storage and management unit provides large-capacity data storage and database management functions, and supports long-term data preservation and query. The visualization display unit displays the monitoring data in the form of charts, 3D models, etc., facilitating data analysis and decision-making for scientific research personnel.

[0064] In some embodiments of the present invention, a multi-functional mammalian ecological monitoring method based on a UAV is provided, and the steps include:

[0065] Step 1. System startup and initialization:

[0066] Step 1.1: UAV system inspection. Before the task starts, conduct a comprehensive inspection of the UAV platform, multi-sensor integration module, battery status, communication link, etc. to ensure that the system is in a normal working state.

[0067] Step 1.2: Task parameter setting. Set the monitoring task parameters through the ground station system, including: monitoring area range (delimited by GPS coordinates or maps), flight altitude (usually 20 - 100 meters, adjusted according to the monitoring target), flight speed (usually 5 - 10 m / s, adjusted according to the task requirements), and sensor working modes (such as the resolution of the high-definition camera, the sensitivity of the thermal imager, the scanning frequency of the lidar, etc.).

[0068] Step 1.3: Environmental Parameter Calibration. Start the environmental sensor and calibrate parameters such as temperature, humidity, and air pressure to ensure the accuracy of data collection.

[0069] Step 2: UAV Autonomous Flight and Monitoring:

[0070] Step 2.1: Autonomous Navigation and Path Planning. The UAV generates an optimal flight path based on the preset monitoring area, combining GPS and visual SLAM technologies. The path planning should avoid obstacles (such as trees and mountains) and cover the target area.

[0071] Step 2.2: Target Recognition and Tracking. During flight, the high-definition camera and thermal imager collect image data in real time, and identify mammalian targets through deep learning algorithms. Once a target is detected, the UAV automatically adjusts the flight path and sensor parameters for tracking and monitoring.

[0072] Step 2.3: Synchronized Multi-Sensor Data Collection. During monitoring, start the following sensors synchronously:

[0073] High-definition camera: Take behavioral images and videos of the target;

[0074] Thermal imager: Record the body temperature distribution of the target;

[0075] LiDAR: Scan the terrain and habitat structure to generate a 3D model;

[0076] Acoustic sensor: Collect the sound signals of the target;

[0077] Environmental sensor: Record environmental data such as temperature, humidity, air pressure, and air quality.

[0078] Step 3: Data Processing and Analysis:

[0079] Step 3.1: Edge Computing and Real-Time Processing. The edge computing unit on the UAV performs real-time processing on the collected data, including:

[0080] Compression and target recognition of images and videos;

[0081] Temperature analysis of thermal imaging data;

[0082] 3D modeling of LiDAR data;

[0083] Spectrum analysis and species recognition of acoustic signals;

[0084] Standardization processing of environmental data.

[0085] Step 3.2: Data Encryption and Transmission. The processed data is encrypted through encryption algorithms (such as AES-256) and transmitted to the ground station system through wireless communication links (such as 4G / 5G or satellite communication).

[0086] Step 3.3: Data Fusion and Report Generation. After receiving the data, the ground station system performs multi-source data fusion and generates the following reports:

[0087] Ecological Behavior Map: showing the activity trajectories, behavior patterns, etc. of mammals;

[0088] Habitat Environment Report: including 3D terrain models, changes in environmental parameters, etc.;

[0089] Species Identification Results: species classification and quantity statistics based on image and acoustic data.

[0090] Step 4: Task Completion and Data Storage:

[0091] Step 4.1: UAV Return and Landing. After the monitoring task is completed, the UAV automatically returns to the take-off point according to the preset return path and lands safely.

[0092] Step 4.2: Data Storage and Management. The ground station system stores the monitoring data in a local database or a cloud server, supporting long-term data preservation and query. The data storage formats include:

[0093] Image and video files (JPEG, MP4 formats), thermal imaging data (TIFF format), lidar data (LAS format), acoustic data (WAV format), environmental data (CSV format).

[0094] Step 4.3: Data Visualization and Display. Through the visualization module of the ground station system, the monitoring data is displayed in the form of charts, 3D models, etc., facilitating analysis and decision-making by scientific researchers.

[0095] Parameter Setting Example:

[0096] 1. Flight Parameters:

[0097] The flight altitude is set to 50 meters (can be adjusted according to the target size).

[0098] The flight speed is set to 8 m / s. The endurance time is set to 60 minutes.

[0099] 2. Sensor Parameters:

[0100] High-definition camera: 4K resolution, 30 frames per second.

[0101] Thermal imager: sensitivity ≤ 0.05 °C, frame rate 25 Hz.

[0102] Lidar: scanning frequency 100 Hz, accuracy ±2 cm.

[0103] Acoustic sensor: Sampling rate 44.1 kHz, frequency range 20 Hz - 20 kHz.

[0104] Environmental sensor: Temperature and humidity accuracy ±0.5 °C / ±3% RH, air pressure accuracy ±0.5 hPa.

[0105] 3. Data processing parameters:

[0106] Edge computing unit: Computing power ≥10 TOPS (for deep learning algorithms).

[0107] Data compression rate: Image and video compression rate ≥80%.

[0108] Encryption algorithm: AES - 256.

[0109] Example of data processing flow:

[0110] 1. Image data processing:

[0111] Collect image data → Object recognition (based on YOLOv5 algorithm) → Behavior analysis (such as movement trajectory, activity frequency) → Generate ecological behavior map.

[0112] 2. Thermal imaging data processing:

[0113] Collect thermal imaging data → Temperature distribution analysis → Object recognition (based on body temperature characteristics) → Generate body temperature distribution.

[0114] 3. LiDAR data processing:

[0115] Collect point cloud data → 3D modeling → Terrain analysis → Generate 3D habitat model.

[0116] 4. Acoustic data processing:

[0117] Collect sound signal → Spectrum analysis → Species recognition (based on convolutional neural network) → Generate acoustic feature report.

[0118] 5. Environmental data processing:

[0119] Collect environmental data → Standardization processing → Generate environmental parameter change curve.

[0120] In some embodiments of the present invention, a multispectral camera can also be equipped on the drone for collecting multispectral images for analysis. The multispectral camera can simultaneously obtain image information in multiple different spectral bands, which can be used to monitor the fur condition of mammals. Through the reflection information in specific bands, it is possible to infer whether the animal is healthy, whether there is parasite infection or malnutrition, etc., because changes in these physiological states may cause subtle differences in the spectral reflection of the fur; it can also detect the pollution degree of water bodies. By analyzing the absorption and scattering of light by water bodies in different bands, it is possible to determine whether there are pollutants in the water and the type and concentration of the pollutants. For the habitats of mammals, understanding the health condition of water bodies is crucial for evaluating the suitability of the entire ecosystem.

[0121] For the parts not described in detail in the present invention, reference can be made to the prior art or the well-known techniques to those skilled in the art. This embodiment does not make any limitations in this regard and will not be described in detail herein.

[0122] The embodiments of the present invention have been described above in conjunction with the accompanying drawings. However, the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative rather than restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many forms without departing from the purpose of the present invention and the scope protected by the claims, and all of them fall within the protection scope of the present invention.

Claims

1. A multi-functional mammalian ecological monitoring system based on drones, characterized in that, The system includes: A drone platform, configured to be able to provide flight functions and provide an installation platform for other modules; A multi-sensor integration module, configured to be able to collect information on mammals and their living areas; An intelligent control module, configured to be able to identify targets and navigate, and control the operation of the drone platform; and, A data processing module, configured to be able to perform edge computing on the collected data, fuse multi-sensor data, and generate ecological behavior monitoring results and habitat environment monitoring results of mammals.

2. The multi-functional mammalian ecological monitoring system based on an unmanned aerial vehicle according to claim 1, wherein The multi-sensor integration module includes a camera, a thermal imager, a lidar, an acoustic sensor, and an environmental sensor; The high-definition camera is configured to be able to capture behavior images and videos of mammals; The thermal imager is configured to be able to identify the body temperature characteristics of mammals; The lidar is configured to be able to perform topographic mapping and three-dimensional modeling of the habitat; The acoustic sensor is configured to be able to collect sound signals of mammals; The environmental sensor is configured to be able to monitor environmental parameters of the habitat.

3. The multi-functional mammalian ecological monitoring system based on an unmanned aerial vehicle according to claim 2, characterized in that The environmental sensor includes a temperature and humidity sensor, a barometric pressure sensor, and an air quality sensor.

4. The multi-functional mammalian ecological monitoring system based on an unmanned aerial vehicle according to claim 1, characterized in that, The intelligent control module includes: An autonomous navigation system, configured to be able to perform path planning and flight control of the drone; A target recognition and tracking system, configured to be able to identify and track mammals in real time, and adjust the flight path and sensor parameters on the basis of the original path; and, An obstacle avoidance system, configured to be able to achieve obstacle avoidance during flight through ultrasonic and infrared obstacle avoidance sensor data, and ensure the safe flight of the drone in a complex environment.

5. The multi-functional mammalian ecological monitoring system based on an unmanned aerial vehicle according to claim 1, wherein The data processing module includes: An edge computing unit, configured to be able to perform edge computing on the collected data, process sensor data in real time, and reduce data transmission latency; A data compression and encryption unit, configured to be able to compress and encrypt the collected data, and ensure data security and transmission efficiency; and, A data fusion and analysis unit, configured to be able to fuse multi-sensor data and generate an ecological behavior map of mammals and a habitat environment data report.

6. The multi-functional mammalian ecological monitoring system based on an unmanned aerial vehicle according to claim 1, wherein, The ground station system includes: A remote monitoring and control unit, communicatively connected to the intelligent control module, configured to be able to monitor the flight status and sensor data of the drone in real time, and be able to remotely control the drone and adjust tasks; A data storage and management unit, configured to be able to provide a large-capacity data storage and database management function, and support long-term data storage and query; and, A visualization display unit, configured to be able to display the monitoring data in various forms, facilitating data analysis and decision-making by relevant personnel.

7. The multi-functional mammalian ecological monitoring system based on an unmanned aerial vehicle according to claim 2, wherein, The multi-sensor integration module further includes a multi-spectral camera; the multi-spectral camera is configured to be able to collect mammal fur data and water pollution data.

8. A multi-functional mammalian ecological monitoring method based on drones, characterized in that, Implemented based on the drone-based multi-functional mammal ecological monitoring system according to any one of claims 1-7; the content of the method includes: S1. Start the drone system and initialize flight and monitoring related parameters; S2. Autonomous flight and monitoring of the drone; the content includes: Generate an optimal flight path based on a preset monitoring area and obstacles within the area, and conduct drone flight and multi-sensor data collection; during the flight, adjust the flight path and flight parameters in real time according to the recognition results of mammalian targets to achieve tracking and monitoring of mammals. S3. Data processing and analysis: Process various collected data, and conduct multi-data fusion and analysis to obtain the ecological behavior monitoring results and habitat environment monitoring results of mammals.

9. The method for multifunctional mammalian ecological monitoring based on an unmanned aerial vehicle according to claim 8, characterized in that, The method further includes: Communicate with the drone through the ground station system, monitor the flight status and sensor data of the drone, and display the monitoring data in various forms by the ground station system for relevant personnel to query, analyze, and make decisions on the data.

10. The method for multifunctional mammalian ecological monitoring based on an unmanned aerial vehicle according to claim 8, wherein In step S3, the ecological behavior monitoring results and habitat environment monitoring results of mammals include: An ecological behavior map that can display the activity trajectories and behavior patterns of mammals; A habitat environment report containing a three-dimensional terrain model and changes in environmental parameters; and, Species recognition results based on image and acoustic data classification.

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