Unmanned aerial vehicle forest inspection method and system based on Beidou positioning

Abstract

The invention discloses an unmanned aerial vehicle forest inspection method and system based on Beidou positioning, and relates to the field of forest inspection, and the system comprises an area limiting module which is used for uploading position coordinates and limiting an inspection area based on the uploaded position coordinates; the control module is used for controlling the unmanned aerial vehicle to fly in the inspection area and collecting forest images; the analysis module is used for receiving the forest image collected in the flight process of the unmanned aerial vehicle, storing the forest image and analyzing the forest health situation tendency based on the stored forest image; according to the invention, by defining the inspection area and designing and deploying the analysis logic of the unmanned aerial vehicle, the unmanned aerial vehicle can autonomously and intelligently complete forest image acquisition, and in the forest image acquisition process, the forest image acquisition path is autonomously and randomly generated, so that the diversity of forest image acquisition is ensured; and the result of the system for subsequently evaluating whether the forest ecological environment is healthy is more reliable and effective.

Description

Technical Field

[0001] The present invention relates to the technical field of forest patrol inspection, and specifically provides a method and system for forest patrol inspection by an unmanned aerial vehicle based on Beidou positioning. Background Art

[0002] The key to forest ecological environment management lies in actively preventing and controlling pests and diseases, preventing fires, promoting afforestation and ecological restoration, maintaining the stability of the forest ecosystem in all aspects, and enabling the forest to continuously play its ecological service function.

[0003] The invention patent application with the application number 202411531189.7 discloses a forest fire prevention unmanned aerial vehicle automatic patrol inspection system based on meteorological factors, including: a meteorological data acquisition device, an unmanned airport and an edge computing device, a remote data analysis and flight management system, and an unmanned aerial vehicle; the meteorological data acquisition device is used to collect meteorological factor data under different meteorological conditions, special holidays or different seasons in real time, and the meteorological factor data includes but is not limited to temperature, air humidity, wind speed, rainfall, and snow depth; the unmanned airport and edge computing device includes an edge computing unit and an unmanned airport unit, the edge computing unit is used to receive the meteorological factor data and clean and process the meteorological factor data to obtain processed data; the unmanned airport unit is used to control the unmanned aerial vehicle and cruise the patrol inspection area; the remote data analysis and flight management system is used to receive the processed data, analyze the processed data, judge the forest fire risk meteorological level under different meteorological conditions, special holidays or different seasons, and formulate different cruise tasks for the unmanned aerial vehicle according to the forest fire risk meteorological level, and send the cruise task of the unmanned aerial vehicle to the unmanned airport unit; the unmanned aerial vehicle automatically executes the cruise task according to the control command of the unmanned airport unit to complete the automatic cruise of the patrol inspection area. This application aims to solve the problem that the traditional unmanned aerial vehicle patrol inspection system, either according to a fixed task frequency or manually adjusted by humans, is difficult to meet the actual needs, resulting in waste of resources and reduced efficiency.

[0004] However, for forest ecological environment monitoring, currently, staff usually adopt the method of using an unmanned aerial vehicle to collect forest images for monitoring. However, in the application of this technology at present, during the flight of the unmanned aerial vehicle, manual control is required, and the degree of intelligence is relatively low;

[0005] Therefore, a method and system for forest patrol inspection by an unmanned aerial vehicle based on Beidou positioning are proposed. Summary of the Invention

[0006] In view of the above-mentioned shortcomings of the prior art, the present invention provides a method and system for forest patrol inspection by an unmanned aerial vehicle based on Beidou positioning, which can effectively solve the problems of the prior art.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions;

[0008] The present invention discloses an unmanned aerial vehicle (UAV) forest patrol system based on Beidou positioning, comprising:

[0009] A region limiting module, configured to upload position coordinates and limit a patrol region based on the uploaded position coordinates; a control module, configured to control the UAV to fly in the patrol region and collect forest images; an analysis module, configured to receive the forest images collected during the flight of the UAV, store the forest images, and analyze the tendency of the forest health status based on the stored forest images; an evaluation module, configured to continuously receive the analysis results of the forest health status tendency in the analysis module and evaluate whether the forest ecological environment is healthy based on the analysis results; an access module, configured to provide system-end users with access rights to the system and read the forest images collected by the UAV; a prompt module, configured to obtain the evaluation results of whether the forest ecological environment is healthy in the evaluation module and issue a warning prompt based on the evaluation results:

[0010] Furthermore, the number of position coordinates uploaded in the region limiting module is not less than three, and a closed region obtained by connecting the uploaded position coordinates to each other is denoted as the patrol region;

[0011] After the patrol region is determined, real coordinates are further configured for the patrol region so that any position coordinate in the patrol region is consistent with its corresponding position coordinate in the forest. Then, a point position is selected in the patrol region, the position coordinate of this point is obtained, and the position coordinate of this point together with the patrol region is transmitted to the UAV, so that the transmitted position coordinate of the point serves as the starting point of the UAV patrol, and the UAV always flies within the patrol region.

[0012] Furthermore, during the process of the control module controlling the flight of the UAV, the UAV based on the distance measuring sensor carried by itself continuously detects the distance from itself to the obstacle below, and adaptively adjusts the flight altitude based on the distance measurement result so that the distance from itself to the obstacle below always remains the same;

[0013] When the control module controls the flight of the UAV, the UAV always flies in a straight line from a top-down perspective;

[0014] A configuration unit and a sensing unit are arranged under the control module. The configuration unit is configured to configure the turning-back angle of the UAV when it reaches the boundary of the patrol region and the frequency of the UAV collecting forest images, and the sensing module is configured to sense the position information of the UAV in real time and trigger the operation of the configuration unit when it senses that the UAV reaches the boundary of the patrol region;

[0015] Among them, the frequency of the UAV collecting forest images in the configuration unit is user-defined by the system-end user.

[0016] Furthermore, the configuration unit and the sensing unit run repeatedly, and the system-end user independently decides whether to end the operation. When the configuration unit and the sensing unit end the operation, the analysis module is triggered to run.

[0017] Furthermore, when the configuration unit configures the turning angle of the drone when it reaches the boundary of the inspection area, it follows:

[0018] When the drone reaches the boundary of the inspection area, the drone first rotates horizontally by 180 degrees, and then makes a secondary horizontal rotation adjustment to the drone so that the shooting end of the camera on the drone that collects forest images faces the same direction as the direction of the sun shining on the earth's surface. Then, the drone flies again based on the control module to collect forest images;

[0019] Among them, the flight path of the drone during the process of flying to collect forest images based on the control module is synchronized with the internal record of the drone.

[0020] Furthermore, when the analysis module stores the forest images, it synchronously sets a storage interval for differentiation, so that after each operation of the configuration unit and the sensing unit ends, during the operation of the configuration unit and the sensing unit, the forest images collected by the drone are stored in the same differentiated storage interval;

[0021] The analysis logic of the forest health trend in the analysis module is as follows:

[0022]

[0023] In the formula: H is the forest health trend; is the average forest green plant coverage rate shown by all forest images; n is the total number of forest images; P i is the forest green plant coverage rate shown by the i-th forest image; S0 is the area of the inspection area; S MAX is the area of the largest sub-area in the inspection area after the inspection area is segmented based on the flight path;

[0024] Among them, the inspection area area S0 is used as a normalization parameter for the forest health trend H during calculation to prevent the value of H from being too small. The larger the forest health trend H, the better the forest health trend, and vice versa, the worse the forest health trend.

[0025] Furthermore, the evaluation module continuously receives the analysis results of the forest health trend and records the analysis results. The evaluation module always uses the latest three recorded analysis results to evaluate whether the forest ecological environment is healthy:

[0026] Among them, when the analysis results of the three records show a continuous upward trend based on the time series, it indicates that the forest ecological environment is healthy. When the analysis results of the three records show a continuous downward trend based on the time series, it indicates that the forest ecological environment is unhealthy. Otherwise, the evaluation module runs again, iterating the earliest analysis result among the three records applied last time with the latest analysis result, and performing the evaluation operation again, and so on, until the evaluation module outputs a healthy or unhealthy evaluation result and then ends.

[0027] Furthermore, the prompt module is triggered to run when the evaluation result of the evaluation module is negative or when the evaluation result cannot be output for a continuous preset number of times. The logic for the prompt module to issue a warning prompt is as follows:

[0028] Preset the content of the warning prompt message. When the prompt module is triggered to run, the prompt module sends the content of the warning prompt message to the mobile device held by the user at the system end, and the user at the system end reads the content of the warning prompt message on the mobile device.

[0029] Furthermore, the area limitation module is wirelessly interconnected with a control module. The control module is wirelessly interconnected with the configuration unit and the sensing unit. The control module is wirelessly interconnected with an analysis module. The analysis module is wirelessly interconnected with the configuration unit and the interaction unit. The analysis module is wirelessly interconnected with the evaluation module. The evaluation module is wirelessly interconnected with an access module and a prompt module.

[0030] A method for forest inspection by an unmanned aerial vehicle based on Beidou positioning includes:

[0031] Upload the position coordinates, limit the inspection area based on the uploaded position coordinates, and select a point in the inspection area as the starting point for the unmanned aerial vehicle to fly. Control the unmanned aerial vehicle to fly in the inspection area based on the starting point, and collect forest images during the flight. Configure a return logic for the unmanned aerial vehicle so that the unmanned aerial vehicle returns when it reaches the edge of the inspection area each time it flies. Evaluate the tendency of the forest health situation based on the forest images collected during the analysis of the unmanned aerial vehicle, and evaluate whether the forest ecological environment is healthy based on the tendency of the forest health situation. When the evaluation result is negative, output the evaluation result and simultaneously provide the user end with the reading permission to read the forest images collected by the unmanned aerial vehicle.

[0032] Adopting the technical solution provided by the present invention, compared with the known prior art, it has the following beneficial effects:

[0033] 1. During the operation of the present invention, through the design and deployment of the inspection area limitation and the UAV analysis logic, the UAV can autonomously and intelligently complete the collection of forest images. Moreover, during the process of collecting forest images, the collection path of the forest images is randomly generated autonomously, ensuring the diversity of forest image collection and making the results of the subsequent evaluation of whether the forest ecological environment is healthy by the system more reliable and effective.

[0034] 2. Based on the continuous collection of forest images, the present invention implements long-term health monitoring of the forest ecological environment, stores and manages the collected forest images for more convenient viewing by forest management personnel. At the same time, with the configured specified evaluation logic, it determines the monitoring of the forest ecological environment. When it is determined to be unhealthy, it immediately prompts the forest management personnel to ensure a dynamic response in the forest maintenance work carried out by the forest management personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0036] Figure 1 It is a schematic structural diagram of a UAV forest inspection system based on Beidou positioning;

[0037] Figure 2 It is a schematic flow diagram of a UAV forest inspection method based on Beidou positioning. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0039] The following further describes the present invention with reference to the embodiments.

[0040] Embodiment 1:

[0041] A UAV forest inspection system based on Beidou positioning in this embodiment, as Figure 1 shown, includes:

[0042] An area limitation module, which is used to upload position coordinates and limit the inspection area based on the uploaded position coordinates;

[0043] The number of uploaded position coordinates in the area limiting module is not less than three. The enclosed area obtained by connecting the uploaded position coordinates to each other is denoted as the inspection area;

[0044] After the inspection area is determined, real coordinates are further configured for the inspection area so that any position coordinate in the inspection area is consistent with its corresponding position coordinate in the forest. Then, a point is selected in the inspection area, and the position coordinate of this point is obtained. The position coordinate of this point together with the inspection area is transmitted to the drone, so that the transmitted position coordinate of the point is used as the starting point of the drone inspection, and the drone always flies in the inspection area;

[0045] The control module is used to control the drone to fly in the inspection area and collect forest images;

[0046] During the process of the control module controlling the drone to fly, the drone based on the distance measuring sensor carried by itself continuously detects the distance from itself to the obstacle below. Based on the ranging result, the drone adaptively adjusts its flight altitude so that the distance from itself to the obstacle below always remains the same;

[0047] When the control module controls the drone to fly, the drone always flies in a straight line from the top-down view;

[0048] There is a configuration unit and a sensing unit under the control module. The configuration unit is used to configure the turning angle of the drone when it reaches the boundary of the inspection area and the frequency of the drone collecting forest images. The sensing module is used to sense the position information of the drone in real time. When it senses that the drone reaches the boundary of the inspection area, it triggers the configuration unit to run;

[0049] Among them, the frequency of the drone collecting forest images in the configuration unit is user-defined by the system-side user;

[0050] The configuration unit and the sensing unit run repeatedly, and the system-side user independently decides whether to end the operation. When the configuration unit and the sensing unit end the operation, it triggers the analysis module to run;

[0051] When the configuration unit configures the turning angle of the drone when it reaches the boundary of the inspection area, it follows:

[0052] When the drone reaches the boundary of the inspection area, the drone first rotates horizontally by 180 degrees, and then makes a secondary horizontal rotation adjustment to the drone so that the shooting end of the camera on the drone for collecting forest images faces the same direction as the direction of the sun shining on the earth's surface. Then, the drone flies again based on the control module to collect forest images;

[0053] Among them, the flight path of the drone during the process of flying and collecting forest images based on the control module is synchronized with the internal record of the drone;

[0054] An analysis module, configured to receive forest images collected during the flight of a drone, store the forest images, and analyze the tendency of the forest health situation based on the stored forest images;

[0055] When storing the forest images, the analysis module synchronously sets storage intervals for differentiation, such that after each operation of the configuration unit and the sensing unit ends, during the operation of the configuration unit and the sensing unit, the forest images collected by the drone are stored in the same storage interval for differentiation;

[0056] The analysis logic of the forest health situation tendency in the analysis module is as follows:

[0057]

[0058] In the formula: H is the tendency of the forest health situation; is the average forest green plant coverage rate shown in all forest images; n is the total number of forest images; P i is the forest green plant coverage rate shown in the i-th forest image; S0 is the area of the inspection area; S MAX is the area of the largest sub-area in the inspection area after the inspection area is segmented based on the flight path;

[0059] Among them, the inspection area area S0 is used as a normalization parameter when calculating the forest health situation tendency H, to prevent H from having too small a value. The larger the forest health situation tendency H, the better the forest health situation tendency; on the contrary, it indicates a worse forest health situation tendency;

[0060] Through the above logical formula, the forest health situation tendency is analyzed and represented in a digital form, providing data support for the further operation of the evaluation module in this embodiment of the system.

[0061] An evaluation module, configured to continuously receive the analysis results of the forest health situation tendency in the analysis module, and evaluate whether the forest ecological environment is healthy based on the analysis results;

[0062] The evaluation module continuously receives the analysis results of the forest health situation tendency and records the analysis results. The evaluation module always uses the latest three recorded analysis results to evaluate whether the forest ecological environment is healthy:

[0063] Among them, when the analysis results of the three records show a continuous upward trend based on time series, it indicates that the forest ecological environment is healthy; when the analysis results of the three records show a continuous downward trend based on time series, it indicates that the forest ecological environment is unhealthy; on the contrary, the operation of the evaluation module is refreshed, the earliest one of the three recorded analysis results used in the previous time is iterated with the latest analysis result, and the evaluation operation is performed again, and so on, until the evaluation module outputs a healthy or unhealthy evaluation result and then ends;

[0064] An access module, configured to provide system - end users with access rights to the system and read forest images collected by the drone;

[0065] A prompt module, configured to obtain the evaluation result of whether the forest ecological environment is healthy in the evaluation module and issue a warning prompt based on the evaluation result;

[0066] The prompt module is triggered to run when the evaluation result of the evaluation module is negative or when the evaluation result cannot be output for a consecutive preset number of times. The logic for the prompt module to issue a warning prompt is as follows:

[0067] Preset the content of the warning prompt message. When the prompt module is in the triggered running state, the prompt module sends the content of the warning prompt message to the mobile device held by the system - end user, and the system - end user reads the content of the warning prompt message on the mobile device;

[0068] The area - limiting module is connected to a control module through wireless network interaction. The control module is connected to a configuration unit and a sensing unit through wireless network interaction. The control module is connected to an analysis module through wireless network interaction. The analysis module is connected to a configuration unit and an interaction unit through wireless network interaction. The analysis module is connected to an evaluation module through wireless network interaction. The evaluation module is connected to an access module and a prompt module through wireless network interaction.

[0069] In this embodiment, the area - limiting module runs to upload the position coordinates, limits the inspection area based on the uploaded position coordinates. The control module runs later to control the drone to fly in the inspection area and collect forest images. The configuration unit synchronously configures the turning angle of the drone when it reaches the boundary of the inspection area and the frequency of the drone collecting forest images. The sensing module real - time senses the position information of the drone. When it senses that the drone reaches the boundary of the inspection area, it triggers the configuration unit to run. The analysis module further receives the forest images collected during the flight of the drone, stores the forest images, and analyzes the tendency of the forest health situation based on the stored forest images. Then, the evaluation module continuously receives the analysis results of the forest health situation tendency in the analysis module, evaluates whether the forest ecological environment is healthy based on the analysis results. Finally, the access module provides system - end users with access rights to the system to read the forest images collected by the drone, and the prompt module obtains the evaluation result of whether the forest ecological environment is healthy in the evaluation module and issues a warning prompt based on the evaluation result.

[0070] Through the operation of the system in the above - mentioned embodiment, a fully intelligent drone forest inspection technology is provided, ensuring that the drone inspection process has a lower demand for manual control, thereby realizing a higher - frequency and more stable forest inspection service.

[0071] Embodiment 2:

[0072] At the specific implementation level, on the basis of Embodiment 1, this embodiment refers toFigure 2 A further specific description is made for an unmanned aerial vehicle (UAV) forest inspection system based on Beidou positioning in Embodiment 1:

[0073] An unmanned aerial vehicle forest inspection method based on Beidou positioning includes the following steps:

[0074] Step 1: Upload the position coordinates, define the inspection area based on the uploaded position coordinates, and select a point in the inspection area as the UAV flight starting point;

[0075] Step 2: Control the UAV to fly in the inspection area based on the flight starting point, and collect forest images during the flight;

[0076] Step 3: Configure a return logic for the UAV so that the UAV returns when it reaches the edge of the inspection area each time it flies;

[0077] Step 4: Evaluate the tendency of the forest health situation based on the forest images collected during the UAV analysis process, and evaluate whether the forest ecological environment is healthy based on the tendency of the forest health situation;

[0078] Step 5: When the evaluation result is negative, output the evaluation result, and simultaneously provide the user terminal with the reading permission to read the forest images collected by the UAV.

[0079] In summary, in the above embodiments, the system and method enable the UAV to autonomously and intelligently complete the collection of forest images through the design and deployment of the defined inspection area and the UAV analysis logic. During the process of collecting forest images, the forest image collection path is randomly generated autonomously, ensuring the diversity of forest image collection, guaranteeing that the results of the subsequent evaluation of whether the forest ecological environment is healthy by the system are more reliable and effective. At the same time, based on the continuous collection of forest images, the long-term health of the forest ecological environment is implemented, and the collected forest images are stored and managed for forest managers to view more quickly. At the same time, with the configured specified evaluation logic, the monitoring of the forest ecological environment is determined. When it is determined to be unhealthy, forest managers are immediately prompted to ensure the dynamic response of the forest managers' forest maintenance work.

[0080] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements will not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An unmanned aerial vehicle forest inspection system based on Beidou positioning, characterized in that, Including: A region limiting module, which is used to upload position coordinates and limit the inspection region based on the uploaded position coordinates; A control module, which is used to control the drone to fly in the inspection region and collect forest images; An analysis module, which is used to receive the forest images collected during the flight of the drone, store the forest images, and analyze the tendency of the forest health situation based on the stored forest images; An evaluation module, which is used to continuously receive the analysis results of the forest health situation tendency in the analysis module and evaluate whether the forest ecological environment is healthy based on the analysis results; An access module, which is used to provide system-end users with access rights to the system and read the forest images collected by the drone; A prompt module, which is used to obtain the evaluation results of whether the forest ecological environment is healthy in the evaluation module and issue a warning prompt based on the evaluation results.

2. The drone forest inspection system based on Beidou positioning according to claim 1, wherein, The number of position coordinates uploaded in the region limiting module is not less than three. The closed region obtained by connecting the uploaded position coordinates is recorded as the inspection region; After the inspection region is determined, real coordinates are further configured for the inspection region so that any position coordinate in the inspection region is consistent with its corresponding position coordinate in the forest. Then, a point is selected in the inspection region, and the position coordinate of this point is obtained. The position coordinate of this point and the inspection region are transmitted to the drone, and the transmitted position coordinate of the point is used as the starting point of the drone inspection, and the drone always flies in the inspection region.

3. The drone forest patrol system based on Beidou positioning according to claim 1, characterized in that, During the process of the control module controlling the drone to fly, the drone uses the ranging sensor carried by itself to detect the distance from itself to the obstacle below in real time. Based on the ranging result, the drone adaptively adjusts its flight altitude so that the distance from itself to the obstacle below always remains the same; When the control module controls the drone to fly, the drone always flies in a straight line from a top-down perspective; A configuration unit and a sensing unit are set under the control module. The configuration unit is used to configure the turning angle of the drone when it reaches the boundary of the inspection region and the frequency of the drone collecting forest images. The sensing module is used to sense the position information of the drone in real time. When it senses that the drone reaches the boundary of the inspection region, it triggers the configuration unit to run; Among them, the frequency of the drone collecting forest images in the configuration unit is user-defined by the system-end user.

4. The drone forest patrol system based on Beidou positioning according to claim 3, characterized in that, The configuration unit and the sensing unit run repeatedly, and the system-end user independently decides whether to end the operation. When the configuration unit and the sensing unit end the operation, it triggers the analysis module to run.

5. The drone forest patrol system based on Beidou positioning according to claim 1 is characterized in that, When the configuration unit configures the turning angle of the drone when it reaches the boundary of the inspection region, it follows: When the drone reaches the boundary of the inspection region, the drone first rotates 180 degrees horizontally, and then makes a secondary horizontal rotation adjustment to the drone so that the shooting end of the camera for collecting forest images on the drone faces the same direction as the direction of the sun shining on the earth's surface. Then, the drone flies again based on the control module to collect forest images; Among them, the flight path of the drone during the process of flying and collecting forest images based on the control module is synchronized with the internal record of the drone.

6. The drone forest patrol system based on Beidou positioning according to claim 1 is characterized in that, When storing forest images, the analysis module synchronously sets storage intervals for differentiation, so that after each operation of the configuration unit and the sensing unit is completed, during the operation of the configuration unit and the sensing unit, the forest images collected by the drone are stored in the same storage interval for differentiation; The analysis logic of the forest health trend in the analysis module is as follows: Where: H is the forest health trend; is the average forest green plant coverage rate shown in all forest images; n is the total number of forest images; P i is the forest green plant coverage rate shown in the i-th forest image; S0 is the area of the inspection area; S MAX is the area of the largest sub-region in the inspection area after the inspection area is segmented based on the flight path; Among them, the inspection area area S0 is used as the normalization parameter for calculating the forest health trend H to prevent H from taking too small a value. The larger the forest health trend H, the better the forest health trend. Conversely, it means that the forest health trend is worse.

7. The drone forest inspection system based on Beidou positioning according to claim 1, characterized in that, The evaluation module continuously receives the analysis results of the forest health trend and records the analysis results. The evaluation module always uses the latest three recorded analysis results to evaluate whether the forest ecological environment is healthy: Among them, when the analysis results of the three records show a continuous upward trend based on time series, it means that the forest ecological environment is healthy. When the analysis results of the three records show a continuous downward trend based on time series, it means that the forest ecological environment is unhealthy. Otherwise, the operation of the evaluation module is refreshed, and the earliest one of the three recorded analysis results applied last time is iterated with the latest analysis result, and the evaluation operation is performed again, and so on, until the evaluation module outputs a healthy or unhealthy evaluation result and then ends.

8. The drone forest patrol system based on Beidou positioning according to claim 1, wherein, The prompt module is triggered to run when the evaluation result of the evaluation module is negative or the evaluation result cannot be output for a continuous preset number of times. The logic for the prompt module to issue a warning prompt is as follows: Preset the content of the warning prompt message. When the prompt module is triggered to run, the prompt module sends the content of the warning prompt message to the mobile device held by the user at the system end, and the user at the system end reads the content of the warning prompt message on the mobile device.

9. The drone forest patrol system based on Beidou positioning according to claim 1, characterized in that, The area limiting module is connected to a control module through wireless network interaction. The control module is connected to the configuration unit and the sensing unit through wireless network interaction. The control module is connected to an analysis module through wireless network interaction. The analysis module is connected to the configuration unit and the interaction unit through wireless network interaction. The analysis module is connected to an evaluation module through wireless network interaction. The evaluation module is connected to an access module and a prompt module through wireless network interaction.

10. A method for forest inspection by an unmanned aerial vehicle based on Beidou positioning, which is an implementation method of an unmanned aerial vehicle forest inspection system based on Beidou positioning as described in any one of claims 1-9, characterized in that, It includes the following steps: Step 1: Upload the position coordinates, limit the inspection area based on the uploaded position coordinates, and select a point in the inspection area as the drone flight starting point; Step 2: Control the drone to fly in the inspection area based on the flight starting point and collect forest images during the flight; Step 3: Configure a return logic for the drone so that the drone returns when it reaches the edge of the inspection area each time it flies; Step 4: Evaluate the forest health trend based on the forest images collected during the drone analysis process, and evaluate whether the forest ecological environment is healthy based on the forest health trend; Step 5: When the evaluation result is negative, output the evaluation result and simultaneously provide the user end with the reading permission to read the forest images collected by the drone.

Images