Bird exploration methods, devices, electronic equipment and storage media

Abstract

This invention provides a method, apparatus, electronic device, and storage medium for bird observation, relating to the field of bird observation technology. The method includes: acquiring image data collected by a bird feeder; sending the image data to a bird observation server for identification and analysis to obtain identification results containing at least the bird species and their appearance times; based on the bird species and appearance times in the identification results, cumulatively calculating the number of visits and dwell time for each bird species to generate activity statistics; extracting video segments for each bird species from the original video clips corresponding to the identification results and synthesizing them into a condensed video summary; and pushing the activity statistics and / or condensed video summary to a mobile client. This method achieves automatic bird identification, statistics, and video summarization without the need for manual monitoring or playback, significantly improving observation efficiency and accurately grasping bird activity patterns.

Description

Technical Field

[0001] This invention relates to the field of bird exploration technology, and in particular to a bird exploration method, device, electronic device, and storage medium. Background Technology

[0002] Birdwatching is an important activity for ecological researchers and nature enthusiasts. Currently, there are two main methods: one is manual field observation, which requires carrying equipment such as binoculars to record birds at dawn or dusk, which is labor-intensive and difficult to cover all weather conditions; the other is setting up cameras to record for a long time, and then reviewing the video to select bird clips. However, with several hours or even days of video, it takes several times longer to manually review the footage, which is extremely inefficient.

[0003] The aforementioned technologies lack automated means to extract bird appearance times, species, and activity patterns, forcing researchers to expend a great deal of effort on video browsing, making it difficult to quickly obtain structured population dynamic data. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a bird exploration method, device, electronic device and storage medium, which realizes automatic bird identification, statistics and video condensation, without the need for manual supervision or playback, significantly improves observation efficiency and accurately grasps the bird activity patterns.

[0005] In a first aspect, embodiments of the present invention provide a bird exploration method, the method comprising: acquiring image data collected by a bird feeder; sending the image data to a bird exploration server for identification and analysis to obtain identification results containing at least bird species and appearance times; accumulating and statistically analyzing the number of visits and duration of stay for each bird species based on the bird species and appearance times in the identification results to generate activity statistics; extracting video segments for each bird species based on the original video segments corresponding to the identification results and synthesizing them into a condensed video summary; and pushing the activity statistics and / or condensed video summary to a mobile client.

[0006] In a preferred embodiment of the present invention, the above-mentioned sending of image data to a bird detection server for identification and analysis includes: determining whether there are birds in the field of vision by a detection algorithm built into the bird feeder; when birds are detected, triggering the acquisition of images or videos, and uploading the acquired data to the bird detection server; the bird detection server performing identification and analysis on the uploaded data, and outputting bird species classification and time tags.

[0007] In a preferred embodiment of the present invention, the above-mentioned method of accumulating and statistically analyzing the number of visits and the duration of stay for each type of bird based on the bird species and appearance time in the identification results to generate activity statistics includes: calculating the first appearance time, the last appearance time, and the total number of visits for each type of bird in a preset period; determining the frequency of bird appearance within a preset time period to form activity statistics.

[0008] In a preferred embodiment of the present invention, the above-mentioned generation of activity statistics further includes: summarizing the data of the day at midnight every day to generate a daily report; the daily report includes a list of bird species, the number of visits for each bird species and the peak period; weekly reports and monthly reports are generated weekly and monthly respectively; the weekly and monthly reports include the ranking of the birds with the most visits and the recommended best observation time interval.

[0009] In a preferred embodiment of the present invention, the above-mentioned extraction of video segments of each bird species and synthesis of a condensed video summary based on the original video segments corresponding to the recognition results includes: extracting original video segments before and after the appearance of each bird species from the original video recording based on the timestamps in the recognition results; arranging all the extracted original video segments in chronological order; and if the total duration of the spliced ​​original video segments exceeds a preset time threshold, then compressing the spliced ​​original video segments at double speed to obtain a condensed video summary.

[0010] In a preferred embodiment of the present invention, the method further includes: generating a real-time notification message when the identification result confirms the presence of birds; sending the notification message to a mobile client; the notification message includes the bird species name and the time of appearance.

[0011] In a preferred embodiment of the present invention, the method further includes: the mobile client sending a request to the bird exploration server, specifying the target time period for the query; the bird exploration server returning a pie chart of bird occurrences, species distribution, and a suggestion for the best observation time based on activity statistics within the target time period; the mobile client displaying the data in chart form and responding to the user's click on a specific bird species by playing back the corresponding condensed video clip.

[0012] Secondly, embodiments of the present invention also provide a bird exploration device, the device comprising: acquiring image data collected by a bird feeder; sending the image data to a bird exploration server for identification and analysis to obtain identification results containing at least bird species and appearance times; accumulating and statistically analyzing the number of visits and duration of stay for each bird species based on the bird species and appearance times in the identification results to generate activity statistics data; extracting video segments for each bird species based on the original video segments corresponding to the identification results and synthesizing them into a condensed video summary; and pushing the activity statistics data and / or condensed video summary to a mobile client.

[0013] Thirdly, embodiments of the present invention also provide an electronic device, including a processor and a memory, wherein the memory stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the bird exploration method of the first aspect described above.

[0014] Fourthly, embodiments of the present invention also provide a computer-readable storage medium storing computer-executable instructions, which, when invoked and executed by a processor, cause the processor to implement the bird exploration method of the first aspect described above.

[0015] The embodiments of the present invention bring the following beneficial effects: This invention provides a method, apparatus, electronic device, and storage medium for bird detection. By acquiring image data from a bird feeder, the image data is sent to a bird detection server for identification and analysis, resulting in identification results that include at least the bird species and their appearance times. Based on the bird species and appearance times in the identification results, the number of visits and the duration of stay for each bird species are accumulated and statistically analyzed to generate activity statistics. Based on the original video clips corresponding to the identification results, video segments for each bird species are extracted and synthesized into a condensed video summary. The activity statistics and / or condensed video summary are then pushed to a mobile client. This method achieves automatic bird identification, statistics, and video summarization without the need for manual monitoring or playback, significantly improving observation efficiency and accurately grasping bird activity patterns.

[0016] Other features and advantages of this disclosure will be set forth in the following description, or some features and advantages may be inferred from the description or determined without doubt, or may be learned by practicing the techniques described above.

[0017] To make the above-mentioned objects, features and advantages of this disclosure more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0018] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0019] Figure 1 A flowchart of a bird exploration method provided in an embodiment of the present invention; Figure 2 An overall flowchart of bird exploration provided in an embodiment of the present invention; Figure 3A flowchart of another bird exploration method provided in an embodiment of the present invention; Figure 4 A signaling diagram for bird exploration provided in an embodiment of the present invention; Figure 5 This is a schematic diagram of the structure of a bird exploration device provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] Currently, birdwatching enthusiasts or researchers who want to understand the bird populations and activity patterns in a certain area usually use two methods: one is traditional manual field observation, carrying equipment such as binoculars and guidebooks to observe and record during specific time periods; the other is setting up video equipment to record for a long time and then reviewing the recordings afterward.

[0022] These two methods have the following significant drawbacks: First, there's the efficiency bottleneck of manual observation. Birds are most active at dawn or dusk, requiring observers to dedicate significant time and energy to on-site surveillance. Limited by human energy and patience, prolonged continuous observation is nearly impossible, easily missing many fleeting moments of bird appearance. This method is extremely labor-intensive and cannot cover the needs of round-the-clock monitoring.

[0023] Secondly, the post-event review process is inefficient and delayed. While camera recording enables 24 / 7 recording, it shifts the observation work from real-time surveillance to post-event review. Faced with hours or even days' worth of video footage, observers need to spend several times the recording time manually reviewing and filtering to find the segments where birds appeared. This passive review method is extremely inefficient, causing a significant amount of valuable observation time to be wasted on video browsing rather than actual analysis.

[0024] Secondly, extracting temporal patterns is difficult. Current technology lacks effective automated methods to understand the core pattern of when birds appear. Observers need to manually record the time points when birds are seen during each playback and then manually compile and summarize the data. For long-term monitoring, this data is highly fragmented, making it difficult to quickly generate a visualized report on the temporal distribution of population activity.

[0025] Based on this, the bird detection method, apparatus, electronic device, and storage medium provided in this invention can acquire image data collected by a bird feeder, send the image data to a bird detection server for identification and analysis, and obtain identification results that include at least the bird species and their appearance time points. Based on the bird species and appearance time points in the identification results, the number of visits and the duration of stay for each bird species are accumulated and statistically analyzed to generate activity statistics. Based on the original video segments corresponding to the identification results, video segments of each bird species are extracted and synthesized into a condensed video summary. The activity statistics and / or condensed video summary are then pushed to a mobile client. This method achieves automatic bird identification, statistics, and video summarization without the need for manual monitoring or playback, significantly improving observation efficiency and accurately grasping bird activity patterns.

[0026] To facilitate understanding of this embodiment, a bird exploration method disclosed in this embodiment of the invention will first be described in detail.

[0027] Example 1 This invention provides a method for bird exploration. Figure 1 A flowchart illustrating a bird exploration method provided in an embodiment of the present invention. Figure 1 As shown, this bird exploration method may include the following steps: Step S101: Acquire image data collected by the bird feeder.

[0028] Among them, bird feeders are used to observe birds, provide them with food, and acquire bird image data.

[0029] Image data can include static images and dynamic videos.

[0030] For example, a user can set up a bird feeder in the garden. The built-in camera uses motion detection or a lightweight AI detection algorithm. When a dove lands on the feeder, the camera automatically starts recording a 10-second video and generates a high-definition image.

[0031] Step S102: Send the image data to the bird exploration server for identification and analysis to obtain identification results that include at least the bird species and the time of appearance.

[0032] The bird exploration server can be a cloud-based or local server, containing AI recognition services and data statistics services. It is responsible for receiving image data, calling recognition algorithms, storing analysis results, providing configuration information storage interfaces and displaying statistical information interfaces to mobile clients, providing interfaces to obtain AIcloud analysis results, and storing relevant data in a database.

[0033] The bird feeder contains a camera with built-in AI algorithms. When a bird is detected, the acquired video stream or image is pushed to a bird exploration server for further in-depth analysis.

[0034] For example, the feeder uploads images and videos to a bird detection server via WiFi. The server calls a pre-trained deep learning model (such as ResNet or YOLO) and outputs the recognition result: bird species = Spotted Dove, appearance time = 2025-05-21 06:58:22, stay duration = 12 seconds.

[0035] Specifically, sending image data to a bird detection server for identification and analysis can include: the detection algorithm built into the bird feeder determining whether there are birds in the field of vision; when birds are detected, triggering the acquisition of images or videos and uploading the acquired data to the bird detection server; the bird detection server identifying and analyzing the uploaded data and outputting bird species classification and time tags.

[0036] The detection algorithm can be an AI algorithm, and the time tag is a timestamp added by the bird exploration server after receiving the data, which is used for subsequent statistics and video capture.

[0037] The identification results can be structured information output by the AI ​​model, including at least the bird species name, such as sparrow or magpie, and the timestamp of the bird's first entry into the field of vision, as well as the duration of stay and confidence level.

[0038] Step S103: Based on the bird species and appearance time points in the identification results, the number of visits and stay time of each bird species are accumulated and statistically analyzed to generate activity statistics.

[0039] The number of visits refers to the number of times the same bird species enters the field of vision and is recorded within a unit of time. Usually, each consecutive appearance is counted as one visit.

[0040] The dwell time period is the time interval from when a bird enters the field of vision to when it leaves the field of vision.

[0041] The activity statistics, such as daily, weekly, and monthly reports, include the distribution of visit frequency, peak periods, and best observation times. These are structured JSON data or Excel spreadsheets, containing heatmaps of the first, last, and most frequent visits for each bird species, as well as frequency across different time periods.

[0042] For example, the server's daily midnight statistics show that spotted doves visited 8 times that day, mainly between 6:30-8:00 and 16:00-17:30; sparrows visited 23 times, concentrated throughout the day. This data is stored in the database to generate a bar chart of visit frequency and a heat map of time periods.

[0043] Specifically, based on the bird species and appearance times in the identification results, the number of visits and stay periods of each bird species are accumulated and statistically analyzed to generate activity statistics. This may include: calculating the first appearance time, last appearance time, and total number of visits for each bird species in a preset period; determining the frequency of bird appearances within a preset time period to form activity statistics.

[0044] The preset period can be a day, an hour, or a custom time period, which is a time window used for statistics.

[0045] The first appearance time is the point in time when a certain bird is first identified within the period.

[0046] The last appearance time is the time point at which the bird was last identified within the period.

[0047] The total number of visits refers to the number of independent events in which the bird is detected within the period. A minimum interval is usually set between two visits (e.g., consecutive occurrences within 30 seconds are counted as one visit).

[0048] The frequency of occurrence refers to the number of times or the proportion of times the bird is recorded per unit of time (e.g., per hour).

[0049] Furthermore, the generation of activity statistics can also include: summarizing the data of the day at midnight every day to generate a daily report; the daily report includes a list of bird species, the number of visits for each bird species and the peak time period; weekly and monthly reports are generated respectively; the weekly and monthly reports include the ranking of the birds with the most visits and the recommended best observation time interval.

[0050] For example, at midnight on the first day of each week (month), data from the previous week (month) is summarized, providing bird diversity change curves, rankings of common bird species, and first-time sightings of rare bird species. Users can then adjust feeding locations or food types to attract more birds.

[0051] Step S104: Based on the original video segments corresponding to the recognition results, extract video segments for each type of bird and synthesize them into a condensed video summary.

[0052] The condensed video summary is a short video generated by editing, splicing, and compressing the original video clips of all bird sightings throughout the day.

[0053] For example, based on the timestamps of all the identification results for the day, the server extracts 8 segments of spotted doves and 23 segments of sparrows from the original video, splicing them together in chronological order to create a video with a total length of 6 minutes and 30 seconds. Because it exceeds the 5-minute threshold, it is compressed at 1.3x speed to obtain a 5-minute condensed video.

[0054] Specifically, based on the original video segments corresponding to the recognition results, video segments of each bird species are extracted and synthesized into a condensed video summary. This may include: extracting original video segments before and after the appearance of each bird species from the original video recording based on the timestamps in the recognition results; arranging all extracted original video segments in chronological order; and if the total duration of the spliced ​​original video segments exceeds a preset time threshold, then the spliced ​​original video segments are compressed at double speed to obtain a condensed video summary.

[0055] The timestamp is the time point (start time and end time) of each identified event stored on the bird exploration server.

[0056] In this case, the segment before and after the bird's appearance is usually selected within a preset time frame to preserve the complete action, such as 2 seconds. The original recordings are complete surveillance videos (potentially up to 24 hours long) continuously recorded by the feeder and stored on a server or cloud storage.

[0057] The chronological order method involves piecing together all the segments of a day in chronological order, rather than grouping them by bird species, in order to preserve the true sense of the flow of time.

[0058] The preset time threshold, such as 5 minutes, is used. If this time is exceeded, users' patience decreases, and compression is necessary.

[0059] One method is to use tools like FFmpeg to increase the video speed to 1.2x, 1.5x, or 2x for speed compression, while keeping the pitch (if there is audio) unchanged or discarding the audio.

[0060] Step S105: Push activity statistics and / or condensed video summaries to the mobile client.

[0061] The condensed video summary is a short video generated by editing, splicing, and compressing the original video clips of all bird appearances in a day.

[0062] For example, at 8:00 AM the following morning, the server will push the daily report and condensed video summary to the user's mobile phone via an app message. The user can then open the app to view the relevant content.

[0063] For ease of understanding, Figure 2 An overall flowchart of bird exploration provided as an embodiment of the present invention, such as Figure 2As shown, after receiving image data uploaded by the bird feeder, the AI ​​service outputs analysis results. On one hand, the system updates visitor records in real time and immediately pushes notifications to app users. On the other hand, it triggers a statistical and summary task at midnight every day: reading the day's bird records and video clips, generating a condensed video summary and daily report data, and pushing it to the user. Simultaneously, it triggers weekly / monthly cycles, reading statistical data to generate weekly / monthly reports and pushing them to app users. This achieves full automation from AI recognition to real-time notifications, automatic daily generation of condensed video summaries and daily reports, and automatic weekly / monthly generation of comprehensive reports, eliminating the need for manual intervention or post-event playback, significantly improving observation efficiency and data processing capabilities.

[0064] The method may further include: generating a real-time notification message when the identification results confirm the presence of birds; sending the notification message to a mobile client; the notification message containing the bird species name and the time of appearance.

[0065] The notification messages can be banner notifications within the app, system notification bar messages, or extended to WeChat / SMS, etc.

[0066] Among its features, it can continuously monitor birds and push relevant information to users in real time. Users can click on the notification message at any time to enter the relevant page to obtain bird activity statistics and / or condensed video summaries.

[0067] The bird exploration method provided in this invention includes a bird exploration method, device, electronic device, and storage medium. It acquires image data from a bird feeder, sends the image data to a bird exploration server for identification and analysis, and obtains identification results containing at least the bird species and their appearance times. Based on the bird species and appearance times in the identification results, it accumulates and statistically analyzes the number of visits and dwell time for each bird species to generate activity statistics. Based on the original video clips corresponding to the identification results, it extracts video segments for each bird species and synthesizes them into a condensed video summary. The activity statistics and / or condensed video summary are then pushed to a mobile client. This method achieves automatic bird identification, statistics, and video summarization without manual monitoring or playback, significantly improving observation efficiency and accurately grasping bird activity patterns.

[0068] Example 2 This invention also provides another method for bird exploration; this method is implemented based on the method described in the above embodiments.

[0069] Figure 3 A flowchart of another bird exploration method provided in an embodiment of the present invention, such as... Figure 3 As shown, bird exploration methods may also include the following steps: Step S201: The mobile client sends a request to the bird exploration server, specifying the target time period for the query.

[0070] In step S202, the bird observation server returns a pie chart of bird occurrences, species distribution, and a suggestion for the best observation time based on activity statistics within the target time period.

[0071] Among them, the species distribution pie chart is a circular statistical chart showing the percentage of visits by each bird species.

[0072] Among these features, the system can calculate the time window in which bird activity is most concentrated based on the data within the queried time period, and provide suggestions on the best observation time.

[0073] In step S203, the mobile client displays the information in the form of a chart and responds to the user's click on a specific bird species by replaying the corresponding condensed video clip.

[0074] For example, if a user clicks on a region in a pie chart or the name of a bird in a list, the system will immediately play a representative condensed video clip of that bird species during the query period.

[0075] For ease of understanding, Figure 4 A signaling diagram for bird exploration provided in an embodiment of the present invention, such as... Figure 4 As shown, a user initiates a request to view data statistics via a mobile client. The mobile client requests statistical data from the birdwatching service, the birdwatching service queries the database for the statistical data, the database returns the query results to the birdwatching service, the birdwatching service then returns the statistical data to the mobile client, and finally the mobile client displays the statistical data to the user. This clearly defines the complete interactive chain of users actively querying statistical data via mobile clients, ensuring that users can obtain structured data such as the number of bird visits, species distribution, and optimal observation times at any time.

[0076] Example 3 Corresponding to the above method embodiments, this invention provides a bird exploration device. Figure 4 This is a schematic diagram of the structure of a bird exploration device provided in an embodiment of the present invention, as shown below. Figure 4 As shown, the bird exploration device may include: Image data acquisition module 301 is used to acquire image data collected by bird feeders.

[0077] The identification and analysis module 302 is used to send image data to the bird exploration server for identification and analysis, and obtain identification results that include at least the bird species and the time of appearance.

[0078] The activity statistics generation module 303 is used to accumulate and statistically analyze the number of visits and the duration of stay for each bird species based on the bird species and appearance time points in the identification results, and generate activity statistics.

[0079] The condensed video summary synthesis module 304 is used to extract video segments of each bird species and synthesize them into a condensed video summary based on the original video segments corresponding to the recognition results.

[0080] The push module 305 is used to push activity statistics and / or condensed video summaries to the mobile client.

[0081] The bird detection device provided in this invention can acquire image data collected by a bird feeder, send the image data to a bird detection server for identification and analysis, and obtain identification results that include at least the bird species and their appearance time points. Based on the bird species and appearance time points in the identification results, the number of visits and the duration of stay for each bird species are accumulated and statistically analyzed to generate activity statistics. Based on the original video segments corresponding to the identification results, video segments of each bird species are extracted and synthesized into a condensed video summary. The activity statistics and / or condensed video summary are then pushed to a mobile client. This method achieves automatic bird identification, statistics, and video condensation without the need for manual monitoring or playback, significantly improving observation efficiency and accurately grasping bird activity patterns.

[0082] In some embodiments, the identification and analysis module is further configured to determine whether there are birds in the field of vision using a detection algorithm built into the bird feeder; when birds are detected, image or video acquisition is triggered, and the acquired data is uploaded to the bird exploration server; the bird exploration server performs identification and analysis on the uploaded data and outputs bird species classification and time tags.

[0083] In some embodiments, the activity statistics generation module is further configured to count the first appearance time, last appearance time, and total number of visits for each type of bird in a preset period; determine the frequency of bird appearance within a preset period, and generate activity statistics.

[0084] In some embodiments, the activity statistics generation module is also used to summarize the data of the day at midnight every day to generate a daily report; the daily report includes a list of bird species, the number of visits for each bird species and the peak time period; weekly reports and monthly reports are generated on a weekly and monthly basis respectively; the weekly and monthly reports include the ranking of the birds with the most visits and the recommended best observation time interval.

[0085] In some embodiments, the condensed video summary synthesis module is further configured to extract original video segments before and after the appearance of each bird from the original video recording based on the timestamps in the recognition results; arrange all the extracted original video segments in chronological order; and if the total duration of the spliced ​​original video segments exceeds a preset time threshold, compress the spliced ​​original video segments at double speed to obtain a condensed video summary.

[0086] In some embodiments, the push module is further configured to generate a real-time notification message when the identification results confirm the presence of birds; send the notification message to the mobile client; the notification message includes the bird species name and the time of appearance.

[0087] In some embodiments, the push module is further configured to have the mobile client send a request to the bird exploration server, specifying the target time period for the query; the bird exploration server returns the number of bird occurrences, a pie chart of species distribution, and a suggestion for the best observation time based on the activity statistics within the target time period; the mobile client displays the data in the form of a chart and responds to the user's click on a specific bird species by playing back the corresponding condensed video clip.

[0088] The device provided in this embodiment of the invention has the same implementation principle and technical effect as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in the device embodiment can be referred to the corresponding content in the aforementioned method embodiment.

[0089] Example 5 This invention also provides an electronic device for running the above-described bird exploration method; see [link to related documentation]. Figure 5 The diagram shows the structure of an electronic device, which includes a memory 500 and a processor 501. The memory 500 is used to store one or more computer instructions, which are executed by the processor 501 to implement the bird exploration method described above.

[0090] Furthermore, Figure 5 The electronic device shown also includes a bus 502 and a communication interface 503. The processor 501, the communication interface 503 and the memory 500 are connected via the bus 502.

[0091] The memory 500 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Communication between this system network element and at least one other network element is achieved through at least one communication interface 503 (which can be wired or wireless), such as the Internet, wide area network, local area network, metropolitan area network, etc. The bus 502 can be an ISA bus, PCI bus, or EISA bus, etc. The bus can be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 5 The symbol is represented by a single double-headed arrow, but this does not mean that there is only one bus or one type of bus.

[0092] Processor 501 may be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method can be completed by the integrated logic circuitry in the hardware of processor 501 or by instructions in software form. Processor 501 can be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this invention. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this invention can be directly manifested as execution by a hardware decoding processor, or execution by a combination of hardware and software modules in the decoding processor. The software module can reside in a readily available storage medium in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory 500, and processor 501 reads information from memory 500 and, in conjunction with its hardware, completes the steps of the method described in the foregoing embodiments.

[0093] This invention also provides a computer-readable storage medium storing computer-executable instructions. When these computer-executable instructions are called and executed by a processor, they cause the processor to implement the aforementioned bird exploration method. For specific implementation details, please refer to the method embodiments, which will not be repeated here.

[0094] The computer program product for bird exploration provided in this embodiment of the invention includes a computer-readable storage medium storing non-volatile program code executable by a processor. The instructions included in the program code can be used to execute the methods in the preceding method embodiments. For specific implementation details, please refer to the method embodiments, which will not be repeated here.

[0095] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0096] In the several embodiments provided by this invention, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. The apparatus embodiments described above are merely illustrative. For example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. Furthermore, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interface; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0097] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0098] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0099] If the functionality is implemented as a software functional unit and sold or used as an independent product, it can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0100] Finally, it should be noted that the above-described embodiments are merely specific implementations of the present invention, used to illustrate the technical solutions of the present invention, and not to limit it. The scope of protection of the present invention is not limited thereto. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that any person skilled in the art can still modify or easily conceive of changes to the technical solutions described in the foregoing embodiments within the technical scope disclosed in the present invention, or make equivalent substitutions for some of the technical features; and these modifications, changes, or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for bird exploration, characterized in that, The method includes: Acquire image data from bird feeders; The image data is sent to a bird detection server for identification and analysis to obtain identification results that include at least the bird species and the time of appearance. Based on the bird species and appearance times in the identification results, the number of visits and the duration of stay for each bird species are accumulated and statistically analyzed to generate activity statistics. Based on the original video segments corresponding to the recognition results, video segments of each bird species are extracted and synthesized into a condensed video summary; The activity statistics and / or the condensed video summary will be pushed to the mobile client.

2. The method according to claim 1, characterized in that, The step of sending the image data to a bird detection server for identification and analysis includes: The bird feeder uses a built-in detection algorithm to determine whether birds are in the field of vision; When birds are detected, images or videos are captured, and the captured data is uploaded to the bird detection server. The bird exploration server identifies and analyzes the uploaded data, and outputs bird species classifications and time tags.

3. The method according to claim 1, characterized in that, The method involves cumulatively calculating the number of visits and duration of stay for each bird species based on the identification results and the time of appearance, generating activity statistics, including: Using a preset period as the unit, the first appearance time, last appearance time, and total number of visits for each bird species are recorded; Determine the frequency of bird appearances within a preset time period to generate activity statistics.

4. The method according to claim 3, characterized in that, The generated activity statistics also include: At midnight each day, the data for that day is summarized to generate a daily report; the daily report includes a list of bird species, the number of visits for each bird species, and peak times; Weekly and monthly reports are generated, respectively; the weekly and monthly reports include the ranking of the most visited birds and the recommended best observation time intervals.

5. The method according to claim 1, characterized in that, The step of extracting video segments for each bird species and synthesizing them into a condensed video summary based on the original video clips corresponding to the recognition results includes: Based on the timestamps in the identification results, extract the original video clips before and after the appearance of each bird species from the original video recording; Arrange all the extracted original video clips in chronological order; If the total duration of the spliced ​​original video segments exceeds a preset time threshold, the spliced ​​original video segments will be compressed at double speed to obtain a condensed video summary.

6. The method according to claim 1, characterized in that, The method further includes: When the identification results confirm the presence of birds, a real-time notification message is generated; The notification message is sent to the mobile client; the notification message includes the bird species name and the time of appearance.

7. The method according to claim 1, characterized in that, The method further includes: The mobile client sends a request to the bird exploration server, specifying the target time period for the query; Based on the activity statistics within the target time period, the bird observation server returns a pie chart of bird occurrence frequency, species distribution, and suggestions for the best observation time. The mobile client displays information in chart form and responds to user clicks on specific bird species by replaying corresponding condensed video clips.

8. A bird exploration device, characterized in that, The device includes: Image data acquisition module, used to acquire image data collected by bird feeders; The identification and analysis module is used to send the image data to the bird exploration server for identification and analysis, and to obtain identification results that include at least the bird species and the time of appearance; The activity statistics generation module is used to accumulate and statistically analyze the number of visits and the duration of stay for each bird species based on the bird species and appearance time points in the identification results, and generate activity statistics. The condensed video summary synthesis module is used to extract video segments of each bird species and synthesize them into a condensed video summary based on the original video segments corresponding to the recognition results; The push module is used to push the activity statistics and / or the condensed video summary to the mobile client.

9. An electronic device, characterized in that, It includes a processor and a memory, the memory storing computer-executable instructions that can be executed by the processor, the processor executing the computer-executable instructions to implement the bird exploration method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions that, when invoked and executed by a processor, cause the processor to implement the bird exploration method according to any one of claims 1 to 7.

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