Method for investigating and monitoring esculent swift population and habitat by means of unmanned aerial vehicle

Abstract

The invention provides a esculent swift population and habitat investigation monitoring method by means of an unmanned aerial vehicle, and relates to the technical field of poultry population investigation and monitoring, and the method comprises the following steps: releasing the unmanned aerial vehicle at a potential distribution place of esculent swifts, and collecting environment data information and position information of the esculent swifts; according to the position information of the esculent swiftlets, confirming habitats of the esculent swiftlets; the unmanned aerial vehicle is controlled to enter the range of the habitat, multiple times of chirp attraction are carried out, and meanwhile quantity information and esculent swift behavior information are collected; ending the attraction, and collecting the flying azimuth information of the esculent swiftlet; according to the flying azimuth information of the esculent swiftlet, the unmanned aerial vehicle is controlled to find potential nesting points in the habitat; monitoring points are set according to the positions of the potential nesting points, and activity data information of the esculent swiftlets is collected. According to the technical scheme, the flexibility of the unmanned aerial vehicle can be utilized to attract esculent swiftlets and then find potential nesting points of the esculent swiftlets, and a basis is provided for subsequent accurate fixed-point monitoring.

Description

Technical Field

[0001] The present application relates to the technical field of poultry population survey and monitoring, and in particular to a method for swiftlet population survey and habitat monitoring using unmanned aerial vehicles. Background Art

[0002] The swiftlet belongs to the genus swiftlet of the family Apodidae. It is a small bird. The salivary glands of some species swell during the breeding season and can secrete a large amount of sticky saliva, which condenses into solid in the air. It is the main material for the swiftlet to build its nest. The nest it builds is called a bird's nest, which has high nutritional value and economic value. The Java swiftlet, which can produce bird's nests, was officially listed as a national second-level key protected wild animal by my country in 2021.

[0003] Under natural conditions, swiftlets live in rock caves. They usually go out to hunt insects during the day and return to their nests to rest in the evening. Since the four toes of swiftlets are all facing forward, they are small climbing birds and cannot grasp branches or stand on the ground, so they will not stay on branches or the ground. Therefore, swiftlets are always in flight after going out to live in caves, and their flying speed is very fast. In addition, due to their small size, it is usually difficult to observe swiftlets directly at close range. Conventional bird survey and monitoring methods are difficult to effectively implement the survey and monitoring of swiftlet populations and habitats. At the same time, swiftlets have singing behavior. The singing of swiftlets of different species is specific, and swiftlets have a phenomenon of gathering the singing of individuals of the same species. Therefore, the use of singing attraction technology to investigate and monitor swiftlet populations is an effective method.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present application, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] The purpose of this application is to overcome the deficiencies of the above-mentioned prior art and to provide a method for investigating and monitoring the population and habitat of swiftlets using drones. By taking advantage of drone flight, potential nesting sites of swiftlets can be found and targeted monitoring can be performed to provide better protection.

[0006] According to one aspect of the present application, a method for surveying and monitoring swiftlet populations and habitats using a drone is provided, comprising the following steps:

[0007] Release drones in potential swiftlet distribution areas to collect environmental data and swiftlet location information;

[0008] Determine at least one habitat based on the location information of the swiftlet;

[0009] Controlling the drone to enter the habitat and perform multiple calls to attract swiftlets, while collecting attraction monitoring data, wherein the attraction monitoring data at least includes quantity information and behavior information of swiftlets;

[0010] Stop playing the call, end the attraction, and collect the swiftlet's flight location information;

[0011] According to the directional information of the swiftlet flying away, the drone is controlled to search for potential nesting sites in the habitat;

[0012] Monitoring points are set up according to the locations of potential nesting sites to collect activity data information of swiftlets.

[0013] According to some embodiments of the present application, based on the above scheme, the performing of multiple calls to attract further includes the following steps:

[0014] Construct the target swiftlet attracting call based on the pre-corrected swiftlet test call;

[0015] The target swiftlet attracting sound is played repeatedly in a loop with a preset first single playing time, so as to collect the swiftlet attracting situation within the attracting range and obtain the attracting monitoring data.

[0016] According to some embodiments of the present application, based on the above scheme, the performing of multiple calls to attract further includes the following steps:

[0017] Acquire pre-corrected swiftlet test calls, wherein the swiftlet test calls include calls of swiftlets during group activities, calls during pursuit and courtship, calls during nesting, calls during predation, and calls during feeding of young birds;

[0018] The target swiftlet attracting sound is constructed based on a combination of sounds from the group activities of the swiftlet, the chasing and courting sounds, the nesting sounds, the predation sounds and the feeding sounds of the young birds, and by playing the multiple sound combinations simultaneously or in a loop.

[0019] According to some embodiments of the present application, based on the above solution, the data information also includes behavior data information, and after the sound playing is stopped, the following steps are also included:

[0020] Playing the preset swiftlet test call once for a preset second single play time, and recording the single behavior data information;

[0021] The swiftlet test sound includes one of the pre-collected sounds of swiftlets during group activities, sounds during chasing and courting, sounds during nesting, sounds during predation, or sounds during feeding of young birds.

[0022] According to some embodiments of the present application, based on the above scheme, the performing of multiple calls to attract the birds in the habitat further includes the following steps:

[0023] The method uses multiple calls to attract the swiftlets during the period when the swiftlets return to their nests after hunting.

[0024] According to some embodiments of the present application, based on the aforementioned scheme, the time period for returning to the nest by predators includes at least 5:30 to 7:30 pm, or the time period for returning to the nest by predators includes at least 6:00 to 7:00 pm.

[0025] According to some embodiments of the present application, based on the above scheme, the end time of the chirping attraction is controlled to be after sunset;

[0026] Infrared imaging is used to collect the directional information of the swiftlets flying away;

[0027] Use infrared imaging to find potential nesting sites.

[0028] According to some embodiments of the present application, based on the aforementioned solution, after confirming the habitat of the swiftlet, the environmental data information of the habitat is continuously collected;

[0029] According to the different environmental data information, multiple calls are made to attract swiftlets, and the number information and behavior information of swiftlets are collected.

[0030] According to some embodiments of the present application, based on the above scheme, the establishment of monitoring points according to the location of potential nesting points also includes the following steps:

[0031] Collect the location and shape information of the monitoring points to find the equipment placement points;

[0032] Transporting the monitoring equipment to the equipment placement point by the unmanned transport;

[0033] The monitoring equipment at the equipment placement point is replaced by the drone with a unit time as a period.

[0034] According to some embodiments of the present application, based on the aforementioned scheme, the environmental data information includes time information, weather information, temperature information, wind information, humidity information, location information, vegetation information, topography information, etc.

[0035] The present application provides a method for investigating and monitoring swiftlet populations and habitats with the aid of drones, which comprises the following steps: releasing drones in potential distribution areas of swiftlets, and collecting environmental data information and location information of swiftlets; confirming the habitat of swiftlets based on the location information of swiftlets; controlling the drones to enter the range of the habitat, and making multiple calls to attract swiftlets, while collecting quantity information and behavior information of swiftlets; ending the attraction, and collecting the directional information of swiftlets flying away; based on the directional information of swiftlets flying away, controlling the drones to search for potential nesting points in the habitat; and setting up monitoring points based on the locations of the potential nesting points to collect activity data information of swiftlets.

[0036] When swiftlets are found in potential distribution areas, further efforts will be made to attract them to determine the population size of the swiftlet in the area and to delineate the approximate range of the habitat, so that subsequent investigations can be conducted directly within the habitat.

[0037] The method of attracting swiftlets by calling out is to make use of the fact that swiftlets are sensitive to the calls of their own kind. This allows swiftlets that are far away or in their nests to be attracted out, making it easier to survey the number of swiftlets in their habitats. In addition, the location of the attraction can be used as a starting point to observe the direction of the swiftlets and find their foraging grounds, drinking water areas and other living places.

[0038] In addition, drones can find potential nesting sites and set up monitoring points to facilitate subsequent monitoring and obtain more information about swiftlets. Drones can also go to places that are difficult for humans to reach, such as large open waters, woodlands, farmlands, reefs and caves on islands and coasts, which is conducive to the comprehensiveness of the swiftlet population survey.

[0039] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0041] Figure 1 The flowchart of the method for investigating and monitoring swiftlet populations and habitats by means of drones according to some embodiments of the present application is schematically shown.

[0042] Figure 2 The following schematically shows a flow chart of collecting attraction monitoring data according to some embodiments of the present application. DETAILED DESCRIPTION

[0043] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this specification. Instead, they are merely examples of devices and methods consistent with some aspects of this specification as detailed in the appended claims.

[0044] Furthermore, the drawings are only schematic illustrations and are not necessarily drawn to scale. The block diagrams shown in the drawings are only functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0045] In some exemplary embodiments of the present application, a method for investigating and monitoring swiftlet populations and habitats using drones is provided, which uses the flexible properties of drones to investigate and monitor swiftlet populations and habitats. Figure 1 As shown, the swiftlet population survey and monitoring method may include the following steps:

[0046] S110, release the drone in the potential distribution area of ​​swiftlets and collect environmental data and location information of swiftlets;

[0047] S120, determining at least one habitat according to the location information of the swiftlet;

[0048] S130, controlling the drone to enter the habitat, and performing multiple calls to attract swiftlets, while collecting attraction monitoring data, wherein the attraction monitoring data at least includes quantity information and behavior information of swiftlets;

[0049] S140, stop playing the chirping sound, end the attraction, and collect the swiftlet's flying position information;

[0050] S150, controlling the drone to search for potential nesting sites near the habitat according to the azimuth information of the swiftlet flying away;

[0051] S160, monitoring points are set up according to the locations of potential nesting sites to collect activity data information of swiftlets.

[0052] When swiftlets are found through direct observation in potential distribution areas, further attraction is then carried out to determine the population size of the swiftlet in the area and to delineate the approximate range of the habitat, so that subsequent investigations can be conducted directly within the habitat.

[0053] The method of attracting swiftlets by calling out is to make use of the fact that swiftlets are sensitive to the calls of their own kind. This allows swiftlets that are far away or in their nests to be attracted out, making it easier to survey the number of swiftlets in their habitats. In addition, the location of the attraction can be used as a starting point to observe the direction of the swiftlets and find their foraging grounds, drinking water areas and other living places.

[0054] In addition, drones can find potential nesting sites and set up monitoring points to facilitate subsequent monitoring and obtain more information about swiftlets. Drones can also go to places that are difficult for humans to reach, such as large open waters, woodlands, farmlands, reefs and caves on islands and coasts, which is conducive to the comprehensiveness of the swiftlet population survey.

[0055] In some exemplary embodiments of the present application, drones can also collect data more effectively and accurately on terrains that are difficult to reach or have complex landforms. For example, when conducting a survey and monitoring of swiftlets on an island, aerial photography can be used to survey the terrain of the entire island. The effect of aerial photography is clearer and more comprehensive than the actual effect of satellite maps, and is more convenient and reliable than traditional collection methods.

[0056] Drones can also collect environmental parameters, topography and landforms, as well as details of swiftlets' activities.

[0057] Potential distribution areas refer to areas where swiftlets are found to be active through reference to relevant literature, historical distribution records and ecological research results or through preliminary surveys.

[0058] Specifically, according to relevant literature, geographical areas such as forests, wetlands or farmlands in tropical and subtropical coastal areas can be determined as potential distribution areas of swiftlet populations. Of course, this is only a schematic example. The potential distribution area can be determined specifically based on the local activities or habitat characteristics of the swiftlet population under study, and this embodiment is not limited to this.

[0059] The preliminary survey can be conducted by driving in a specific time period, such as the time period when swiftlets are out foraging, or at sunrise, and visually observing or attracting surveys along a certain route, and recording the areas where swiftlets are found. The areas are marked as potential distribution areas, and the potential distribution areas where swiftlets exist are directly recorded, and then supplemented with literature records.

[0060] The selection of potential distribution areas can also be adjusted according to the season. For example, in summer and autumn, the potential distribution areas can be distributed more evenly, while in winter or spring, the potential distribution areas close to the equator are investigated in a focused manner. Seasons are often accompanied by changes in temperature and food abundance, and the distribution of swiftlet populations will change to a certain extent with the change of seasons. Below, the swiftlet population survey and monitoring method in this example embodiment will be further described.

[0061] In step S110, the potential distribution area refers to a geographical area where swiftlets may be active or inhabited, which is preliminarily screened out based on the known habitat characteristics and biological laws of swiftlets.

[0062] Before implementing the survey and monitoring of swiftlets, the target area needs to be divided in detail in order to screen out areas where swiftlets are active and inhabiting, or areas that are consistent with the activities and inhabiting habits of swiftlets. By conducting detailed investigations on potential distribution areas, not only can the monitoring efficiency be improved, but also the waste of resources can be effectively reduced and the scope of the investigation can be narrowed.

[0063] In the example embodiment of the present application, the step of collecting environmental data information is performed when the swiftlet is observed for the first time and no attraction is carried out. The purpose of this step is to effectively record the environmental conditions of the swiftlet's activities without interfering with the swiftlet's natural activities, thereby reducing the changes in environmental data that may be caused by attraction activities and avoiding misleading the survey results.

[0064] The location information of swiftlets is collected within the visual range of the drone, aiming to capture the areas where swiftlets are active and record the surrounding environmental characteristics of these areas in detail. These characteristics include but are not limited to topography, vegetation, buildings, and water sources. By recording these key environmental conditions, detailed environmental parameters can be provided for analyzing the habitat selection model of swiftlets, providing more concentrated and scientific basic data for the study of swiftlet populations. This method not only enhances the accuracy of the data, but also provides solid data support for the protection and management of swiftlets.

[0065] In step S120, at least one habitat is determined according to the location information of the swiftlet.

[0066] In an exemplary embodiment of the present application, the habitat is obtained by comparing multiple locations where swiftlets appear and analyzing the areas around which they fly, and the location where swiftlets are more likely to be found is usually the location where swiftlets are likely to forage, stay or nest. For example, the habitat can be a grassland rich in insect food, a wetland near a water source, or an open farmland or woodland.

[0067] By further dividing and refining the distribution area, we can more accurately calibrate the specific areas where swiftlets may be active. Through statistical comparative analysis of different habitat environments and swiftlet distribution conditions, we can avoid the randomness and uncertainty in traditional methods, significantly improve our ability to grasp the activity patterns of swiftlet groups, improve monitoring accuracy, and thus ensure the efficiency of swiftlet survey and monitoring.

[0068] In step S130, the drone is controlled to enter the habitat and perform multiple calls to attract swiftlets, while collecting attraction monitoring data, which at least includes quantity information and behavior information of swiftlets.

[0069] In an example embodiment of the present application, sound attraction refers to a technical means of attracting swiftlets by playing specific swiftlet sounds. Multiple sound attraction refers to repeatedly playing specific swiftlet sounds at multiple time points or environmental conditions to obtain monitoring data on swiftlet activities and flight trajectories to the greatest extent. The sound attraction device is a special player or a group of players on the drone. The volume and frequency of the playback need to be adjusted to cover a reasonable range. For example, the playback range of the sound attraction device can be set to a circular area with a radius of 4100 to 1000 meters.

[0070] It is understandable that this propagation range refers to the maximum range of sound information that the swiftlet can obtain, not the range of sound that humans can hear.

[0071] In an exemplary embodiment of the present application, the playback range of the device for attracting different environmental sounds can be set to a circular area with a radius of 500 to 1000 meters, such as areas with environmental noise such as the seaside and islands.

[0072] In an exemplary embodiment of the present application, the playback range of the device for attracting different environmental sounds can be set to a circular area with a radius of 100 to 300 meters, such as a wetland park near a residential area, and the impact on the surrounding residents needs to be considered.

[0073] It should be noted that due to the noise caused by the rotation of the drone's own rotor, in order to ensure the attraction effect, the playback range of the sound attraction device needs to be larger than the playback range of the fixed point attraction device. The playback range of the fixed point sound attraction device is set in a circular area of ​​300m to 500m. The playback range here and the playback range of the above drone refer to the extreme position where sound transmission can have an attraction effect.

[0074] Attraction monitoring data may include quantity information (referring to the number of swiftlets appearing within the attraction range), environmental information (referring to dynamic data such as weather, temperature, humidity, wind speed, etc. related to the attraction environment, as well as static data such as topography, vegetation, water sources, etc.), and directional information of swiftlets flying away (referring to the flight direction and trajectory of swiftlets leaving after attraction). Attraction monitoring data may be collected by taking photos, video recording, capturing with infrared sensors, or manually recording, and stored in a database for subsequent analysis.

[0075] The attraction monitoring data also includes the changes in the number of swiftlets in different time periods after the call, such as the number of swiftlets within one minute after the call, the number of swiftlets within 1 minute to 1.5 minutes after the call, and the number of swiftlets within 3 minutes to 5 minutes after the call. This setting can determine the time and distance of the swiftlets after hearing the call, that is, the size of the effective attraction range. In addition, it can more accurately determine the effect of attraction and the impact of the continuous playback of the attraction sound on the swiftlet's stay.

[0076] In an exemplary embodiment of the present application, the duration of the sound attraction is at least 15 minutes.

[0077] The method of attracting can gather nearby swiftlet populations into a certain area, which is convenient for observing the movements and postures of swiftlets on the one hand, and can also be used as a starting point to record the direction in which the swiftlets leave, providing a basic direction for finding the nesting points of swiftlets. Therefore, in S140, after a period of continuous sound attraction, the sound is stopped, the attraction is ended, and the directional information of the swiftlets flying away is collected.

[0078] In step S150, based on the azimuth information of the swiftlet flying away, the drone is controlled to search for potential nesting sites near the habitat.

[0079] In an example embodiment of the present application, based on the collected quantity information and the directional information of the swiftlets flying away, a population distribution map is drawn through spatial analysis technology. In addition, potential nesting sites can be further identified through correlation analysis between environmental information and swiftlet behavior data. For example, locations with suitable environmental conditions can be screened by matching habitat characteristics. Data analysis methods can include statistical analysis, machine learning modeling, or rule-based reasoning algorithms, and data results can be used to dynamically adjust the monitoring area to form an iteratively optimized monitoring strategy.

[0080] The flexibility of drones allows them to go directly to verify after recording the directional information of the swiftlets’ flight, and then determine the location of potential nesting sites, providing a basis for capturing the behavioral characteristics and distribution patterns of swiftlets in a systematic and comprehensive manner.

[0081] In step S160, monitoring points are set up according to the location of potential nesting sites to collect swiftlet activity data information. The establishment of monitoring points is used to monitor the activity data information of swiftlets near potential nesting sites for a long time, provide data information for comprehensive investigation and protection of swiftlet populations, support dynamic evaluation and long-term monitoring of swiftlet populations, and further ensure the accuracy and effectiveness of swiftlet population distribution and potential nesting site monitoring.

[0082] It should be noted that the purpose of the investigation in the above embodiments is based on the research and protection of the swiftlet population. First, the data of the swiftlet population is collected, and the variable parameters affecting the swiftlet population and population density are obtained based on the data analysis. Secondly, the distribution of the swiftlet is understood, including the distribution quantity information, distribution pattern, etc., and the factors affecting its distribution pattern are comprehensively considered. Thirdly, the habitat suitable for the swiftlet is comprehensively analyzed, including topographic and geomorphic characteristics, vegetation characteristics, climate characteristics, human interference, etc. Finally, the swiftlet's nesting site is found to observe the swiftlet's living habits to confirm the swiftlet's habit parameters.

[0083] Next, the contents of step S110 to step S150 are described in detail.

[0084] In an exemplary embodiment of the present application, Figure 2 The steps in S130 are used to perform multiple beeps to attract birds and collect attracting monitoring data. Figure 2 As shown, the following steps may be specifically included:

[0085] Step S210, constructing a target swiftlet attracting call according to the pre-corrected swiftlet test call;

[0086] Step S220, the target swiftlet attracting sound is played repeatedly in a loop for a preset first single playing time, so as to collect the swiftlet attracting situation within the attracting range and obtain the attracting monitoring data.

[0087] The pre-corrected swiftlet test sound refers to an audio signal obtained by collecting the original sound emitted by swiftlets at different physiological and behavioral stages and processing them to optimize the sound quality and signal characteristics. The source of the swiftlet test sound may include the sound of swiftlets during group activities, the sound of chasing and courting, the sound of nesting, the sound of predation, and the sound of feeding young birds. Of course, it can also be the sound of swiftlets in other behavioral activities. This exemplary embodiment does not specifically limit the type of swiftlet test sound.

[0088] The target swiftlet attracting call is an induced audio signal generated based on the pre-corrected swiftlet test call according to the set playback mode and call combination. This attracting call can be an induced audio signal obtained by looping any one of the calls of swiftlets during group activities, chasing and courting, nesting, predation or feeding young birds. At the same time, the induced audio signal can also be obtained by simultaneously playing or looping at least two combinations of the calls of swiftlets in these different behavior stages. This embodiment is not limited to a specific playback combination.

[0089] The construction of the target swiftlet attraction call can be done by using audio processing software such as Audacity or other professional audio editing tools to edit, adjust the frequency and enhance the signal of the pre-corrected swiftlet test call. In addition, the machine learning model can also be used to construct the attraction call, and by analyzing a large number of swiftlet call samples, an audio signal that meets the specific goal can be automatically generated. During the construction process, it may be necessary to dynamically adjust the type and intensity of the attraction call according to changes in the monitoring environment. For example, in the breeding season, the call of chasing and courtship can be given priority; during the period of frequent swiftlet activities, the call of group activities can be selected. In some cases, mixed audio technology can also be used to superimpose different calls and adjust the volume ratio to optimize the attraction effect. This method provides flexibility and can be adjusted according to the behavior and environmental conditions of the swiftlet to achieve the best attraction effect.

[0090] In an optional embodiment, considering that the noise generated by the rotor of the drone during flight may interfere with the recording of the swiftlet's call, the drone can be parked at a high point and the rotation of the rotor can be stopped when the sound is sounded to attract the swiftlets. In this way, the drone can sound and attract the swiftlets at a fixed point, reduce noise interference, and improve the clarity and accuracy of the recorded swiftlet's call. This method helps to effectively attract and monitor the swiftlets without interfering with their natural behavior.

[0091] In the process of attracting swiftlets, the first single playback duration refers to the continuous playback time of each target swiftlet's call in one playback cycle. This duration can be determined based on the swiftlet's auditory sensitivity and reaction time to ensure that the call can be effectively perceived by the swiftlet and attract their attention. Usually, the preset first single playback duration can be set within the range of 10 to 15 minutes. This duration can not only give the swiftlet enough time to recognize and respond to the played call, but also avoid long playback causing their auditory fatigue or habituation. By accurately controlling the playback duration, the attraction efficiency can be improved while reducing interference with the swiftlet's natural behavior.

[0092] Loop playback means repeatedly playing the target swiftlet attracting sound during the entire monitoring process to ensure the continuity and stability of the attracting signal during the monitoring period. There is no limit on the stop time of the target swiftlet calling sound, only continuous playback is required.

[0093] In an optional embodiment, the playback process can also be combined with sound wave directional technology to enhance the directionality of the signal and improve the attraction effect in a specific area. During the monitoring period, in order to avoid interference with other birds, the audio signal can be adjusted to retain only the unique sound characteristics of the swiftlet or amplify the unique sound frequency of the swiftlet.

[0094] By constructing the target swiftlet attracting call based on the pre-corrected swiftlet test call, the problems of single attracting sound and insensitive response to swiftlet behavior in traditional technology are solved. The pre-corrected call can optimize the frequency range, volume and playback mode to make the played target attracting call more in line with the physiological characteristics and behavioral habits of swiftlets, which can significantly improve the propagation effect of sound signals and enhance the ability to attract target swiftlets in complex environments. By adopting the method of multiple loop playback of the target swiftlet attracting call, combined with the preset single playback time, the problems of insufficient sound coverage and poor playback continuity in traditional monitoring are further solved. The loop playback mode ensures the stability and consistency of the audio signal during long-term monitoring, avoids the defect of inaccurate monitoring results caused by behavioral deviations of swiftlets in different time periods, and can capture the behavioral data of swiftlets more comprehensively under diverse time nodes and environmental conditions.

[0095] Optionally, when collecting the information on attracting swiftlets within the attraction range and obtaining the attraction monitoring data, the number of house martins, lesser white-rumped swifts and passing swiftlets can be distinguished and excluded. The distinction can be made by including the body shape, flight posture, tail spread status and abdominal feather color of the swiftlet or house martins.

[0096] Among them, the flight state refers to the dynamic performance of the target bird when it is moving in the air. The flight of the swiftlet is mainly fast straight or curved flight, usually accompanied by a small tail swing, while the flight state of the house martin is more flexible, with obvious turning and emergency stops. By analyzing the flight trajectory, the species of the target bird can be inferred. For example, the flight trajectory curve model in the video can be used to identify whether it conforms to the typical flight pattern of the swiftlet. When shooting, it can be combined with the continuous shooting mode to record multiple key nodes during the flight process for trajectory reproduction and comparative analysis.

[0097] Tail spread is a method of classification by observing the shape and spread angle of the tail feathers of the target bird. During flight, the tail of the swiftlet is narrow and long, forming an arc when spread and with a sharp tail end, while the tail of the house martin is wider, deeply forked when spread and with a relatively blunt tail end. In order to obtain a clear tail shape, the bird can be photographed at a specific angle during flight. For example, a wide-angle lens can be used to capture flight images from the dorsal side, or slow video playback technology can be used to observe the dynamic changes of the tail.

[0098] The color of the abdominal feathers is an important means of distinguishing the target birds based on their appearance. The abdominal feathers of the swiftlet are usually dark gray or gray, showing a single tone, while the abdominal feathers of the house martin are usually white or light yellow markings. The difference in color distribution can significantly distinguish the two. During the collection process, the lighting conditions of the target area can be enhanced by combining sunlight or artificial light to obtain higher quality image data. In the video recording, the aperture size and exposure time are adjusted to ensure that the abdominal details of the swiftlet and the house martin are still clearly visible in motion.

[0099] By comprehensively capturing the characteristic data of house martins and golden swiftlets and excluding the number of house martins and passing golden swiftlets, the accuracy and reliability of the monitoring data can be further improved.

[0100] The Little White-waisted Bird is larger than the Golden-winged Swiftlet, has a wider wingspan, and is a little stronger. The adult bird has very obvious bright white spots on its waist. It flaps its wings more vigorously and at a higher frequency when flying. The chirping sounds it makes are obviously different from those of the Golden-winged Swiftlet. The Little White-waisted Bird tends to fly at a higher altitude, and will not fly low when playing the chirping sounds of the Golden-winged Swiftlet, let alone approach or hover around the player.

[0101] Optionally, the following steps may be used to implement the construction of the target swiftlet attracting sound according to the pre-corrected swiftlet test sound in step S210, which may specifically include:

[0102] Pre-corrected swiftlet test calls can be obtained, and the swiftlet test calls can include the calls of swiftlets during group activities, the calls of chasing and courting, the calls of nesting, the calls during predation, and the calls when feeding young birds; and then, based on the calls of swiftlets during group activities, the calls of chasing and courting, the calls of nesting, the calls during predation, and the calls when feeding young birds, a target swiftlet attracting call can be constructed in the form of simultaneous or looped playback of multiple call combinations.

[0103] The swiftlet test calls refer to the sound signals obtained by collecting and preliminarily processing the original calls of swiftlets in different behavioral states. The source of the swiftlet test calls can be natural sounds recorded by on-site recording equipment or swiftlet audio data obtained from existing audio databases. Highly sensitive directional microphones or professional wildlife recording equipment can be used during the recording process to reduce environmental noise interference and improve the clarity of the audio signal.

[0104] The collected swiftlet test calls may include, but are not limited to, calls during group activities of swiftlets (such as interactive calls during roosting), calls during pursuit and courtship (such as high-frequency short calls in courtship rituals), calls during nesting (such as calls used to consolidate the nest position), calls during the process of predation (such as low-frequency calls during circling flight), and calls during feeding of young birds (such as short calls during feeding).

[0105] After obtaining the swiftlet test calls, the original audio can be preprocessed, and the processing content may include noise removal, signal enhancement, and audio editing, etc. Of course, other types of audio preprocessing methods can also be used, and this embodiment is not limited to this. Noise removal can be achieved through spectrum analysis technology to separate background noise from the target call; signal enhancement can increase the volume of the target signal through gain adjustment; audio editing can be time-cut and organized according to behavior-specific segments. Of course, artificial intelligence algorithms can also be used to automatically separate mixed audio in a natural environment and extract representative swiftlet call segments. This example embodiment does not specifically limit the preprocessing method of the collected swiftlet test calls.

[0106] The target swiftlet attracting call refers to the induced audio signal generated by processing the pre-corrected test call according to certain combination rules. The combination rules are formulated based on the sensitivity and response intensity of swiftlets to different types of calls. For example, swiftlets may respond more strongly to the calls of chasing and courting and the calls during nesting during the breeding season, while they are more sensitive to the calls of group activities and the calls during the predation process during foraging activities. Therefore, the target swiftlet attracting calls in different situations can be dynamically adjusted according to monitoring needs.

[0107] For example, the target swiftlet attracting call can be at least two combinations of the calls of swiftlets during group activities, the calls of chasing and courting, the calls of nesting, the calls during the predation process, and the calls of feeding young birds. For example, the target swiftlet attracting call is an audio combination of the calls of swiftlets during group activities and the calls of chasing and courting, or it can be an audio combination of the calls of nesting and the calls of feeding young birds that are played simultaneously or in a loop; the target swiftlet attracting call can be the calls of swiftlets during group activities, the calls of chasing and courting, the calls of nesting, the calls during the predation process, and the calls of feeding young birds. At least three combinations of the calls, such as the target swiftlet attracting call can be an audio that simultaneously plays or loops the combined calls of swiftlets’ group activities, calls when chasing and courting, and calls when building nests; it can also be an audio that simultaneously plays or loops the combined calls of nesting, calls during the predation process, and calls when feeding young birds; the target swiftlet attracting call can also be an audio that simultaneously plays or loops the calls of swiftlets’ group activities, calls when chasing and courting, calls when building nests, calls during the predation process, and calls when feeding young birds, at least four combinations, or at least five combinations, and examples are not given here one by one.

[0108] The realization of the combination of sounds can be operated through audio editing software, including the synthesis and mixing of multi-track audio. Multiple sounds can be played simultaneously in parallel, for example, the sounds of group activities and the sounds of nesting can be superimposed; they can also be played in a loop in a time series, for example, the sounds of predation can be played first, and then the sounds of feeding young birds can be played. The playback mode can be optimized according to the activity patterns of swiftlets. For example, the playback interval and the number of repetitions can be set to improve the attraction effect. The above settings can be customized according to the actual scenario, and this embodiment is not limited to the description here.

[0109] In some optional implementations, a specific combination of attracting calls can be generated by training models based on machine learning audio generation technology, and complex audio structures can be achieved without manual editing. In addition, a method of real-time collection and processing of on-site audio can be used to dynamically integrate the actual calls of swiftlets in the environment into target swiftlet attracting calls, thereby better fitting the natural habits and environmental characteristics of swiftlets.

[0110] Optionally, the following steps may be used to implement the construction of the target swiftlet attracting call according to the pre-corrected swiftlet test call in step S210, which may specifically include:

[0111] Pre-corrected swiftlet test calls can be obtained, and the swiftlet test calls include the calls of swiftlets during group activities, the calls of chasing and courting, the calls of nesting, the calls during predation, and the calls when feeding young birds. According to any one of the calls of swiftlets during group activities, the calls of chasing and courting, the calls of nesting, the calls during predation, and the calls when feeding young birds, a target swiftlet attracting call is constructed in the form of looping any one of the selected calls.

[0112] For example, the target swiftlet attracting sound can be the sound of swiftlets' group activities played in a loop, or the sound of swiftlets chasing and courting played in a loop, or the sound of swiftlets building nests played in a loop, or the sound of swiftlets feeding their young played in a loop. The specific type of sound to be used can be determined based on the actual scene requirements.

[0113] By using any one or a combination of the sounds of swiftlets during group activities, chasing and courting, building nests, preying, and feeding their young, the problem of insufficient behavioral stimulation and low response rate of single sound signals in traditional technologies is solved. By playing a combination of one or more sounds, especially in simultaneous or looped playback modes, a sound scene that is closer to the natural environment of the swiftlet can be simulated, thereby attracting more swiftlets to approach the target area, effectively improving the pertinence of attraction signals during the breeding season, foraging time, and roosting period, and improving the accuracy and reliability of swiftlet behavior research in various environments.

[0114] In an exemplary embodiment of the present application, the recruitment monitoring data may also include behavior data information. After the recruitment is completed, the collection of behavior data information may be achieved through the following steps, which may specifically include:

[0115] The preset second single playback duration is used to play the preset swiftlet test sound once, and the single behavioral data information is recorded; wherein the swiftlet test sound includes one of the pre-collected sounds of swiftlets during group activities, chasing and courting, nesting, predation, or feeding young birds.

[0116] The second single play duration refers to the duration of the audio during the single audio play process of the sound test. The second single play duration can be set in combination with the swiftlet's reaction time to the sound signal and its behavioral characteristics. For example, the second single play duration can be set to 5 to 8 minutes to ensure that the swiftlet's behavioral response to a specific sound can be fully recorded. Of course, it can also be 4 to 10 minutes, and this embodiment is not limited to this.

[0117] The pre-collected swiftlet test calls refer to the audio signals of swiftlets in different behavioral scenarios obtained from the natural environment, which have been screened and modified to optimize their attraction ability. Each call has specific acoustic characteristics. For example, the calls during group activities usually have a lower frequency and a long rhythm, which is suitable for attracting swiftlets at a distance; the calls during chasing and courting are high-frequency and short signals, which are usually used to attract breeding individuals; the calls during nesting have continuous rhythmic changes, which can have a strong attraction to individuals in the nesting stage; the calls during the predation process are intermittent low-frequency signals, which are more suitable for reflecting the foraging activities of swiftlets; the calls when feeding young birds have a higher frequency and a soft rhythm, which are used to monitor nesting activities during the breeding season.

[0118] The collection of swiftlet test calls can be completed by a high-sensitivity recording device, such as a directional microphone, a wireless acoustic collection device, or a portable recorder with noise reduction function. The collected audio signal can be filtered, denoised, and frequency adjusted by professional audio processing software to improve the clarity and recognizability of the audio. Optionally, an audio signal with similar characteristics to the actual test call can be generated by analog synthesis to replace the naturally collected call to meet specific experimental conditions.

[0119] Behavioral data information refers to the record of the swiftlet's action response, flight position and other behavioral characteristics during the broadcast. Specific collection methods may include direct observation by the operator of the drone when attracting birds with calls, image capture, video recording, infrared detection or automated equipment recording. Manual observation can use telescopes or high-magnification photography equipment to observe and manually record the swiftlet's activity trajectory and behavioral characteristics; image capture, video recording or infrared detection can use high-resolution cameras or infrared cameras to capture in poor light environments; automated equipment such as intelligent monitoring systems can automatically generate behavioral data information records in combination with image recognition algorithms.

[0120] By setting the second single playback duration, the problem of playback time not matching the behavioral response characteristics of swiftlets is avoided, and the preset single playback duration is optimized according to the swiftlet's reaction time to the sound signal and its behavioral patterns, so that the playback process can fully attract the swiftlet to approach the sound source within a reasonable time, thereby avoiding the situation where the swiftlet fails to respond completely due to too short playback time, and also avoiding the waste of resources due to too long playback time, thereby improving the efficiency and pertinence of attraction and monitoring data collection within a specific time window; the single playback mode combined with the recording of behavioral data information can realize the efficient identification of individual responses of swiftlets, especially capturing key behavioral characteristics in a short time, and can quickly obtain high-quality monitoring data with limited resources; by recording single behavioral data information, it lays the foundation for the comprehensive evaluation of swiftlet behavior patterns, effectively improving the accuracy and comprehensiveness of attraction and monitoring data.

[0121] Optionally, the recorded behavioral data information includes at least the swiftlet's action response, flight position, and call response.

[0122] Action response refers to the dynamic behavior characteristics of swiftlets in response to the target sound played, which may include approaching the sound source, moving away from the sound source, hovering at close range, or changing the flight direction. The method of collecting action response can be achieved through manual observation or video recording. Manual observation can use high-magnification telescopes or telephoto lenses to clearly capture the behavior of swiftlets; video recording can use high-definition video equipment or thermal imaging cameras. Especially in poor light environments, thermal imaging technology can effectively capture the movement trajectory of swiftlets.

[0123] The flight position refers to the flight altitude, flight path, flight radius and its distribution in space when the swiftlet plays its call. The flight altitude can be calibrated by multiple ranges, such as 1-15 meters, 15-30 meters, etc. The flight radius can also be calibrated by multiple ranges, such as within 15 meters, within 25 meters, within 35 meters, etc. The determination of the specific flight position can be deduced through video analysis and demonstration.

[0124] Call response refers to the characteristic information of the call signal emitted by the swiftlet when it receives the target call. The collection of call response can be combined with a directional microphone or acoustic sensor to capture the call of the swiftlet within the target range and perform signal analysis. The specific analysis content may include characteristic parameters such as the frequency, amplitude and rhythm of the call. The processing of audio data can be completed through spectrum analysis software to separate the response signal of the swiftlet from the environmental noise and further optimize the signal characteristics. As an alternative implementation method, multi-channel acoustic monitoring equipment can also be used to realize the collection of calls from different directions in the space, thereby improving the efficiency of capturing call responses.

[0125] By recording and analyzing the action reaction, flight position and call response, the behavioral characteristics of the swiftlet to the target call can be fully reflected. These behavioral data not only provide a reliable basis for subsequent monitoring and research, but also provide a scientific basis for optimizing the call attraction effect. To ensure the accuracy and consistency of data collection, multiple recording devices can be combined to collect information synchronously, and integrated and analyzed through data fusion technology to maximize the monitoring accuracy.

[0126] In an exemplary embodiment of the present application, the correction of the swiftlet test call can be achieved by the following steps:

[0127] The action response and flight position of the swiftlet can be analyzed based on the preset swiftlet test call to determine the impact of the swiftlet test call on the swiftlet's behavior and the impact on the attraction effect; based on the impact on the swiftlet's behavior and the impact on the attraction effect, the swiftlet test call is corrected to obtain a pre-corrected swiftlet test call.

[0128] Among them, the preset swiftlet test calls refer to typical call signals of swiftlets at different behavioral stages, such as sound samples of scenes such as group activities, courtship, nesting, predation or feeding young birds. The calls are collected by high-sensitivity recording equipment and filtered and frequency optimized to ensure the authenticity and clarity of the audio. The analysis of the swiftlet's action response and flight position is to extract the swiftlet's dynamic performance of the target call through multi-dimensional processing of the monitoring data, which can include the speed of approaching the sound source, trajectory changes, flight altitude adjustment and its repeated response pattern to specific sounds. Data analysis can be completed in combination with manual observation records, video image analysis or computer vision algorithms.

[0129] Through the aggregate analysis of action response and flight position data, the behavioral characteristics of swiftlets can be quantified. For example, the average response time, response intensity and repetition rate can be calculated. Combined with these analysis results, the impact on the attraction effect is evaluated to determine the applicability of the current call in a specific scenario and its shortcomings. The correction process of the call can use professional audio processing software to adjust the volume, frequency range, rhythm and signal duration. The corrected audio can be repeatedly verified through simulation experiments to further optimize the attraction performance.

[0130] Optionally, the swiftlet test call may be corrected according to the call response and the corresponding swiftlet test call to obtain a pre-corrected swiftlet test call.

[0131] Among them, the call response is the acoustic response of the swiftlet after receiving the target call signal. The collected calls are recorded by directional microphones or multi-channel acoustic monitoring equipment and stored as audio data files. The spectral characteristics, amplitude, frequency and time characteristics of the call response can be extracted and annotated by acoustic analysis software. According to the correspondence between the call response and the swiftlet's test call, the intensity and characteristics of the swiftlet's call response to different types of test calls can be determined. For example, the most effective call segment can be screened out by comparing the number of responses and response strength induced by various test calls.

[0132] The correction process can be based on the analysis results, by adjusting the spectral characteristics of the test calls or mixing different types of calls to generate pre-corrected audio signals. For example, the low-frequency component of the predation call can be increased to enhance the attraction to foraging swiftlets, or the interval time of the courtship call can be appropriately shortened to improve the response efficiency. The corrected test call needs to be verified in combination with actual attraction experiments and further adjusted according to feedback data to ensure its effectiveness.

[0133] Performing multiple calls to attract in the habitat also includes the following steps:

[0134] The method uses multiple calls to attract the swiftlets during the period when the swiftlets return to their nests after hunting.

[0135] Since the swiftlet hunts during the day, its nest cannot be tracked. After attracting it in the evening, the location of the swiftlet's nest can be tracked and found, which is convenient for monitoring the habitat. Therefore, multiple calls to attract swiftlets during the hunting and nesting period can improve the success rate of monitoring the population distribution and potential nesting sites.

[0136] The selection of this time period can be combined with the seasonal changes of the region and the living habits of the swiftlets, and can be verified and determined through long-term monitoring data, but this embodiment is not limited thereto.

[0137] In an exemplary embodiment of the present application, the time period for returning to the nest by predators includes at least 5:30 to 7:30 p.m., or the time period for returning to the nest by predators includes at least 6:00 to 7:00 p.m.

[0138] In a specific embodiment, the chirping attraction is performed multiple times between 5:45 and 7:15 pm.

[0139] In a specific embodiment, the chirping attraction is performed multiple times between 5:50 and 7:10 pm.

[0140] In a specific embodiment, the chirping attraction is performed multiple times between 6:15 and 6:45 pm.

[0141] In a specific embodiment, the chirping attraction is performed multiple times between 6:25 and 6:35 pm.

[0142] The above-mentioned sound attraction time means that the start time of the sound attraction is within the above-mentioned time range, and does not limit the end time of the sound attraction to also be within the above-mentioned range. The sound attraction is generally performed multiple times, and here it means that the time of the first sound attraction is within the above-mentioned time range.

[0143] In an exemplary embodiment of the present application, the multiple beeping attracting specifically includes:

[0144] The end time of the calling attraction is controlled to be after sunset. After sunset, the probability of the swiftlets returning to the nest after the calling ends will increase. At this time, further tracking of the swiftlets is conducive to finding a more accurate potential nesting point.

[0145] Infrared imaging is used to collect the directional information of the swiftlets as they fly away. Infrared imaging technology is used to collect the directional information of the swiftlets as they fly away, which helps to track the flight path of the swiftlets in poor visibility conditions such as in the evening or at night.

[0146] Using infrared imaging to find potential nesting sites. Using infrared imaging technology to find potential nesting sites for swiftlets, this method can identify hidden locations that swiftlets may choose in complex environments.

[0147] In an exemplary embodiment of the present application, after the habitat of the swiftlet is confirmed, environmental data information of the area will be continuously collected, including temperature, humidity, light, etc., in order to understand the environmental factors of the swiftlet's choice of habitat, which will help to replicate ideal habitat conditions and discover new swiftlet habitats.

[0148] According to different environmental data information, multiple calls are made to attract swiftlets, and the number and behavior information of swiftlets are collected. After the environmental data information changes, the calls can be made again, which not only helps to increase the understanding of the swiftlet population and obtain more accurate data, but also collects more return calls to make more comprehensive adjustments to the audio signal.

[0149] In an exemplary embodiment of the present application, after confirming the habitat of the swiftlet, monitoring points are set up according to the location of the potential nesting point, and the following steps are also included:

[0150] Collect the location and shape information of the monitoring points to find the equipment placement points.

[0151] The monitoring equipment is transported to the equipment placement point by unmanned means.

[0152] The monitoring equipment at the equipment placement point is replaced by drones on a time basis.

[0153] This embodiment aims to provide an efficient and automated swiftlet monitoring system, which realizes continuous monitoring of swiftlet habitats through precise positioning and automated equipment deployment, so as to collect behavioral data and environmental information of swiftlets, thereby providing a scientific basis for the protection and population management of swiftlets.

[0154] Through the flexibility of drones, after confirming the habitat of the swiftlets, based on the location of potential nesting sites, the location and morphological information of the monitoring points were collected using the Geographic Information System (GIS) and field surveys to determine the best equipment placement points.

[0155] The monitoring equipment is transported to the pre-determined equipment placement points by drones. The use of drones reduces the need for manual handling, improves deployment efficiency, and reduces human interference with the swiftlet habitat.

[0156] Set a periodic time unit and use drones to replace the monitoring equipment at the equipment placement point. This automated maintenance process ensures the continuity of monitoring data and the functionality of the equipment, while reducing the workload of manual inspections and maintenance.

[0157] The above method has the following advantages:

[0158] By accurately collecting monitoring point information, the quality and accuracy of monitoring data are improved.

[0159] The use of drones reduces the need for manual handling of equipment and reduces human interference.

[0160] The use of drones can achieve periodic equipment replacement, reduce manpower input, and make investigation and monitoring more convenient.

[0161] In addition, fixed-point monitoring also ensures the continuity of monitoring data and avoids monitoring interruptions. It also reduces human entry into the swiftlet's habitat, which helps protect the swiftlet's natural habitat.

[0162] In an example embodiment of the present application, the collected attraction monitoring data may include environmental information, and the specific environmental information may include time information, weather information, temperature information, wind information, humidity information, location information, vegetation information, topography information, etc.

[0163] Among them, environmental information is an important external factor affecting the activities of swiftlets, and its collection and recording are the key to ensuring the integrity and accuracy of monitoring data. Time information is usually recorded by synchronizing device timestamps to ensure the temporal consistency of data.

[0164] The location information can be obtained through the GPS module inside the drone, including the latitude, longitude and altitude of the monitoring location. The collected environmental data needs to be stored synchronously with the behavioral data for subsequent analysis. Of course, the location information can also be obtained by shooting with a watermark camera with a location information tag. Environmental information can also be used to screen and exclude abnormal data. For example, the attraction monitoring data under extreme weather conditions may not have reference value. In order to improve the recording efficiency, the environmental data acquisition module can be integrated into the monitoring equipment to realize automatic recording and uploading. It should be noted that although the various steps of the method in this application are described in a specific order in the accompanying drawings, this does not require or imply that these steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. In addition or alternatively, some steps can be omitted, multiple steps can be combined into one step for execution, and / or one step can be decomposed into multiple steps for execution, etc.

[0165] In an exemplary embodiment of the present application, the location information includes the coordinates of the swiftlet population and the landform information at the coordinates, that is, the terrain information. The possible nesting areas at the coordinate location can be distinguished based on the terrain information to facilitate monitoring.

[0166] Time information, weather information, temperature information, wind information, humidity information, and vegetation information can be acquired in real time using on-site equipment, or simultaneously acquired through nearby meteorological stations, satellite data, etc., to facilitate accurate acquisition of environmental parameters.

[0167] In a specific embodiment, for example, in the coastal area of ​​Hainan Island, the terrain of a certain area can be recorded through the map plate, and effective environmental parameters can be recorded through real-time weather information, etc. For another example, on an island, it is not convenient to collect environmental parameters or an uninhabited island without facilities such as a weather station, so it is necessary to carry a portable device to collect environmental data on the island where swiftlets are distributed.

[0168] In an example embodiment of the present application, the process of attracting and investigating swiftlets is a long process, which requires data collection and scientific monitoring of the population distribution and changes of swiftlets throughout the year. For example, multiple surveys are conducted in winter and summer, and the key survey scope is gradually narrowed to accurately collect swiftlet population data and data changes under different climate and environmental conditions, comprehensively analyze the dynamics of the population, and achieve more scientific investigation and monitoring.

[0169] It should be noted that, although the steps of the method in the present application are described in a specific order in the drawings, this does not require or imply that the steps must be performed in the specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0170] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and embodiments are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims.

[0171] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for investigating and monitoring swiftlet populations and habitats using drones, characterized in that: The steps include: Release drones in potential swiftlet distribution areas to collect environmental data and swiftlet location information; Determine at least one habitat based on the location information of the swiftlet; Controlling the drone to enter the habitat and perform multiple calls to attract swiftlets, while collecting attraction monitoring data, wherein the attraction monitoring data at least includes quantity information and behavior information of swiftlets; Stop playing the call, end the attraction, and collect the swiftlet's flight location information; According to the directional information of the swiftlet flying away, the drone is controlled to search for potential nesting sites near the habitat; Monitoring points are set up according to the locations of potential nesting sites to collect activity data information of swiftlets.

2. The investigation and monitoring method according to claim 1, characterized in that: The method of performing multiple calls to attract people also includes the following steps: Construct the target swiftlet attracting call based on the pre-corrected swiftlet test call; The target swiftlet attracting sound is played repeatedly in a loop with a preset first single playing time, so as to collect the swiftlet attracting situation within the attracting range and obtain the attracting monitoring data.

3. The investigation and monitoring method according to claim 2, characterized in that: The method of performing multiple calls to attract people also includes the following steps: Acquire pre-corrected swiftlet test calls, wherein the swiftlet test calls include calls of swiftlets during group activities, calls during pursuit and courtship, calls during nesting, calls during predation, and calls during feeding of young birds; The target swiftlet attracting sound is constructed based on a combination of sounds from the group activities of the swiftlet, the chasing and courting sounds, the nesting sounds, the predation sounds and the feeding sounds of the young birds, and by playing the multiple sound combinations simultaneously or in a loop.

4. The investigation and monitoring method according to claim 2, characterized in that: The attraction monitoring data also includes behavioral data information. After the sound playing stops, the following steps are also included: Playing the preset swiftlet test call once for a preset second single play time, and recording the single behavior data information; The swiftlet test sound includes one of the pre-collected sounds of swiftlets during group activities, sounds during chasing and courting, sounds during nesting, sounds during predation, or sounds during feeding of young birds.

5. The investigation and monitoring method according to claim 1, characterized in that: The method of performing multiple calls to attract the birds in the habitat also includes the following steps: The method uses multiple calls to attract the swiftlets during the period when the swiftlets return to their nests after hunting.

6. The investigation and monitoring method according to claim 5, characterized in that: The time period for returning to the nest by hunting includes at least 5:30 pm to 7:30 pm, or the time period for returning to the nest by hunting includes at least 6:00 pm to 7:00 pm.

7. The investigation and monitoring method according to claim 6, characterized in that: Control the end time of the sound attraction to be after sunset; Infrared imaging is used to collect the directional information of the swiftlets flying away; Use infrared imaging to find potential nesting sites.

8. The investigation and monitoring method according to claim 1, characterized in that: After confirming the swiftlet, continuously collecting the environmental data information of the habitat; According to the different environmental data information, multiple calls are made to attract swiftlets, and the number information and behavior information of swiftlets are collected.

9. The investigation and monitoring method according to any one of claims 1 to 6, characterized in that: The step of setting up monitoring points according to the location of potential nesting points also includes the following steps: Collect the location and shape information of the monitoring points to find the equipment placement points; Transporting the monitoring equipment to the equipment placement point by the unmanned transport; The monitoring equipment at the equipment placement point is replaced by the drone with a unit time as a period.

10. The investigation and monitoring method according to any one of claims 1 to 6, characterized in that: The environmental data information includes time information, weather information, temperature information, wind information, humidity information, location information, vegetation information, topography information, etc.

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