A method and system for forest inspection by a UAV based on Beidou positioning

Abstract

This invention discloses a method and system for unmanned aerial vehicle (UAV) forest patrol based on BeiDou positioning, relating to the field of forest patrol. It includes: a region limitation module for uploading location coordinates and limiting the patrol area based on the uploaded coordinates; a control module for controlling the UAV to fly within the patrol area and collect forest images; and an analysis module for receiving the forest images collected during the UAV's flight, storing the images, and analyzing the forest health trend based on the stored images. This invention, through the design and deployment of the limited patrol area and the UAV analysis logic, enables the UAV to autonomously and intelligently complete the collection of forest images. Furthermore, during the image collection process, the forest image acquisition path is autonomously and randomly generated, ensuring the diversity of forest image collection and guaranteeing that the subsequent assessment of the forest ecological environment's health by the system is more reliable and effective.

Description

Technical Field

[0001] This invention relates to the field of forest patrol technology, specifically to a method and system for unmanned aerial vehicle (UAV) forest patrol based on BeiDou positioning. Background Technology

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

[0003] Patent application number 202411531189.7 discloses an automatic forest fire prevention drone patrol system based on meteorological factors, comprising: a meteorological data acquisition device, a drone airport and edge computing device, a remote data analysis and flight management system, and a drone; the meteorological data acquisition device is used to collect meteorological factor data in real time under different meteorological conditions, special holidays, or different seasons, and the meteorological factor data includes, but is not limited to, temperature, air humidity, wind speed, rainfall, and snow thickness; the drone airport and edge computing device includes an edge computing unit and a drone airport unit, the edge computing unit being used to receive the meteorological factor data and clean and process the meteorological factor data to obtain processed data. The unmanned aerial vehicle (UAV) airport unit is used to control the UAV to patrol the inspection area. The remote data analysis and flight management system is used to receive the processed data, analyze the processed data, determine the forest fire weather risk level under different weather conditions, special holidays, or different seasons, and formulate different UAV patrol tasks according to the forest fire weather risk level, and send the UAV patrol tasks to the UAV airport unit. The UAV automatically executes the patrol task according to the control command of the UAV airport unit to complete the automatic patrol of the inspection area. This application aims to solve the problem that traditional UAV inspection systems, which rely on fixed task frequencies or manual adjustments, are difficult to meet actual needs, resulting in resource waste and reduced efficiency.

[0004] However, for monitoring forest ecological environment, staff usually use drones to collect forest images for monitoring. But the current application of this technology requires manual control during the drone flight, and the level of intelligence is relatively low.

[0005] To address this, a method and system for unmanned aerial vehicle (UAV) forest patrol based on BeiDou positioning is proposed. Summary of the Invention

[0006] In view of the above-mentioned shortcomings of the existing technology, the present invention provides a method and system for unmanned aerial vehicle (UAV) forest patrol based on Beidou positioning, which can effectively solve the problems of the existing technology.

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

[0008] This invention discloses a BeiDou-based unmanned aerial vehicle (UAV) forest patrol system, comprising:

[0009] The system comprises the following modules: a region restriction module for uploading location coordinates and defining the inspection area based on these coordinates; a control module for controlling the drone to fly within the inspection area and collect forest images; an analysis module for receiving and storing forest images collected by the drone during flight, and analyzing the forest health trend based on the stored images; an assessment module for continuously receiving the forest health trend analysis results from the analysis module and assessing the health of the forest ecosystem based on these results; an access module for providing system users with access permissions to read the forest images collected by the drone; and a notification module for obtaining the assessment results of the forest ecosystem health from the assessment module and issuing early warnings based on these results.

[0010] Furthermore, the region definition module uploads no fewer than three location coordinates, and the closed region obtained by connecting the uploaded location coordinates is recorded as the inspection region.

[0011] After the inspection area is determined, real coordinates are configured for the inspection area so that the coordinates of any position in the inspection area are consistent with the corresponding coordinates in the forest. Then, a point is selected in the inspection area, the coordinates of the point are obtained, and the coordinates of the point, together with the inspection area, are transmitted to the drone. The transmitted coordinates of the point are used as the starting point for the drone inspection, and the drone always flies within the inspection area.

[0012] Furthermore, during the flight of the drone controlled by the control module, the drone uses its onboard ranging sensor to detect the distance between itself and the obstacles below in real time. Based on the ranging results, the drone adaptively adjusts its flight altitude to keep the distance between itself and the obstacles below constant.

[0013] When the control module controls the drone to fly, the drone always flies in a straight line from a top-down perspective.

[0014] The control module is equipped with a configuration unit and a sensing unit. 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 drone's location information in real time. When the drone is sensed to have reached the boundary of the inspection area, the configuration unit is triggered to run.

[0015] The frequency at which the drone collects forest images in the configuration unit is customized by the system user.

[0016] Furthermore, the configuration unit and the sensing unit run repeatedly, and the system user decides whether to stop running. When the configuration unit and the sensing unit stop running, the analysis module is triggered to run.

[0017] Furthermore, when configuring the turnaround angle of the UAV when it reaches the boundary of the inspection area, the configuration unit follows the following rules:

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

[0019] In this process, the flight path of the UAV during the flight to collect forest images is synchronized with the internal recording of the UAV.

[0020] Furthermore, when storing forest images, the analysis module simultaneously sets up distinct storage intervals so that the forest images collected by the UAV during the operation of the configuration unit and the sensing unit are stored in the same distinct storage interval after each operation of the configuration unit and the sensing unit.

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

[0022]

[0023] In the formula: H represents the forest health trend; P represents the average forest vegetation cover across all forest images; n is the total number of forest images; P i Si represents the forest vegetation coverage shown in the i-th forest image; S0 represents the area of ​​the inspection area; Si represents the forest vegetation coverage shown in the i-th forest image. MAX The area of ​​the largest sub-region in the inspection area after the inspection area is divided based on the flight path;

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

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

[0026] Specifically, if the analysis results of the three records show a continuous upward trend over time, it indicates that the forest ecological environment is healthy; if the analysis results of the three records show a continuous downward trend over time, it indicates that the forest ecological environment is unhealthy. Conversely, if the analysis results show a downward trend over time, the evaluation module is refreshed, and the earliest analysis result from the three records in the previous application is used as the latest analysis result. The evaluation operation is then performed again, and so on, until the evaluation module outputs a healthy or unhealthy evaluation result.

[0027] Furthermore, the prompting module is triggered when the evaluation module's evaluation result is negative or when no evaluation result can be output for a preset number of consecutive times. The logic for the prompting module to issue a warning is as follows:

[0028] The system pre-sets warning message content. When the warning module is in operation, it sends the warning message content to the mobile device held by the user on the system side, and the user reads the warning message content on the mobile device.

[0029] Furthermore, the area restriction module is interactively connected to a control module via a wireless network. The control module is interactively connected to a configuration unit and a sensing unit via a wireless network. The control module is interactively connected to an analysis module via a wireless network. The analysis module is interactively connected to the configuration unit and the interaction unit via a wireless network. The analysis module is interactively connected to an evaluation module via a wireless network. The evaluation module is interactively connected to an access module and a prompting module via a wireless network.

[0030] A method for unmanned aerial vehicle (UAV) forest patrol based on BeiDou positioning includes:

[0031] Upload location coordinates, define the inspection area based on the uploaded coordinates, and select a point within the inspection area as the drone's flight start point; control the drone to fly within the inspection area based on the flight start point, collecting forest images during flight; configure turnaround logic for the drone, causing it to turn back each time it reaches the edge of the inspection area; assess the forest health trend based on the forest images collected during the drone's analysis, and evaluate whether the forest ecological environment is healthy based on the forest health trend; if the assessment result is negative, output the assessment result and simultaneously provide the user with access to read the forest images collected by the drone.

[0032] Compared with known prior art, the technical solution provided by this invention has the following beneficial effects:

[0033] 1. During operation, this invention enables drones to autonomously and intelligently collect forest images by designing and deploying limited inspection areas and drone analysis logic. Furthermore, during the forest image collection process, the forest image collection path is automatically and randomly generated, ensuring the diversity of forest image collection and making the subsequent assessment of the health of the forest ecological environment more reliable and effective.

[0034] 2. This invention is based on continuous forest image acquisition to implement long-term health monitoring of the forest ecological environment and stores and manages the acquired forest images so that forest managers can view them more quickly. At the same time, it is configured with specified evaluation logic to judge the monitoring of the forest ecological environment. When it is judged to be unhealthy, it will immediately notify the forest managers to ensure that the forest management personnel can carry out dynamic response to the forest maintenance work. Attached Figure Description

[0035] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without any creative effort.

[0036] Figure 1 This is a schematic diagram of a UAV forest patrol system based on BeiDou positioning.

[0037] Figure 2 This is a flowchart illustrating a method for unmanned aerial vehicle (UAV) forest patrol based on BeiDou positioning. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0039] The present invention will be further described below with reference to embodiments.

[0040] Example 1:

[0041] This embodiment presents a BeiDou-based unmanned aerial vehicle (UAV) forest patrol system, such as... Figure 1 As shown, it includes:

[0042] The area restriction module is used to upload location coordinates and restrict the inspection area based on the uploaded location coordinates;

[0043] The region restriction module shall upload no fewer than three location coordinates. The closed region obtained by connecting the uploaded location coordinates shall be recorded as the inspection region.

[0044] After the inspection area is determined, real coordinates are configured for the inspection area so that the coordinates of any position in the inspection area are consistent with the corresponding coordinates in the forest. Then, a point is selected in the inspection area, the coordinates of the point are obtained, and the coordinates of the point, together with the inspection area, are transmitted to the drone. The transmitted coordinates of the point are used as the starting point for the drone inspection, and the drone always flies within 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 flight of the drone controlled by the control module, the drone uses its onboard ranging sensor to detect the distance between itself and the obstacles below in real time. Based on the ranging results, the drone adaptively adjusts its flight altitude to keep the distance between itself and the obstacles below constant.

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

[0048] The control module has a configuration unit and a sensing unit at the lower level. 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 drone's location information in real time. When the drone is sensed to have reached the boundary of the inspection area, the configuration unit is triggered to run.

[0049] In the configuration unit, the frequency of forest image acquisition by the drone is customized by the system user;

[0050] The configuration unit and the perception unit run repeatedly, and the system user decides whether to stop running. When the configuration unit and the perception unit stop running, the analysis module is triggered to run.

[0051] When configuring the turnaround angle of the UAV when it reaches the boundary of the inspection area, the configuration unit follows the following rules:

[0052] When the drone reaches the boundary of the inspection area, the drone first rotates horizontally 180 degrees, and then performs a second horizontal rotation adjustment so that the camera end of the drone that collects forest images is facing the same direction as the sun shining on the earth's surface. Then, the drone flies again to collect forest images based on the control module.

[0053] Among them, the flight path of the UAV during the process of collecting forest images based on the control module is synchronously recorded inside the UAV.

[0054] The analysis module is used to receive forest images collected during the flight of the UAV, store the forest images, and analyze the forest health trend based on the stored forest images.

[0055] When storing forest images, the analysis module synchronously sets up differentiated storage intervals so that the forest images collected by the UAV during the operation of the configuration unit and the sensing unit are stored in the same differentiated storage interval after each operation of the configuration unit and the sensing unit.

[0056] The analysis logic for forest health trend in the analysis module is as follows:

[0057]

[0058] In the formula: H represents the forest health trend; P represents the average forest vegetation cover across all forest images; n is the total number of forest images; P i Si represents the forest vegetation coverage shown in the i-th forest image; S0 represents the area of ​​the inspection area; Si represents the forest vegetation coverage shown in the i-th forest image. MAX The area of ​​the largest sub-region in the inspection area after the inspection area is divided based on the flight path;

[0059] Among them, the area S0 of the inspection area is used as a normalization parameter in the calculation of the forest health trend H to prevent H from being too small. The larger the forest health trend H is, the better the forest health trend is, and vice versa.

[0060] The above logical formulas are used to analyze and represent the forest health trend in a digital form, providing data support for the further operation of the system's evaluation module in this embodiment.

[0061] The assessment module is used to continuously receive the forest health trend analysis results from the analysis module, and assess whether the forest ecological environment is healthy based on the analysis results.

[0062] The assessment module continuously receives and records the results of forest health trend analysis. The module consistently uses the results of the three most recent records to assess the health of the forest ecological environment.

[0063] When the analysis results of the three records show a continuous upward trend over time, it indicates that the forest ecological environment is healthy. When the analysis results of the three records show a continuous downward trend over time, it indicates that the forest ecological environment is unhealthy. Conversely, the evaluation module is refreshed and the latest analysis result is used to iterate over the earliest analysis result of the three records from the previous application. The evaluation operation is then performed again, and so on, until the evaluation module outputs a healthy or unhealthy evaluation result.

[0064] The access module is used to grant system users access permissions to read forest images collected by drones;

[0065] The alert module is used to obtain the assessment results of whether the forest ecological environment is healthy from the assessment module, and issue early warning alerts based on the assessment results;

[0066] The prompt module is triggered when the evaluation module returns a negative result or fails to output an evaluation result for a preset number of consecutive times. The logic for the prompt module to issue a warning is as follows:

[0067] The system has a preset warning message content. When the warning module is triggered and running, the warning message content is sent to the mobile device held by the user on the system side. The user on the system side reads the warning message content on the mobile device.

[0068] The area restriction module is interconnected with the control module via a wireless network. The control module is interconnected with the configuration unit and the sensing unit via a wireless network. The control module is interconnected with the analysis module via a wireless network. The analysis module is interconnected with the configuration unit and the interaction unit via a wireless network. The analysis module is interconnected with the evaluation module via a wireless network. The evaluation module is interconnected with the access module and the prompting module via a wireless network.

[0069] In this embodiment, the area limitation module uploads location coordinates and limits the inspection area based on the uploaded coordinates. The control module then controls the drone to fly within the inspection area and collect forest images. The configuration unit synchronously configures the drone's turnaround angle when it reaches the boundary of the inspection area and the frequency of forest image collection. The perception module senses the drone's location information in real time. When the drone reaches the boundary of the inspection area, it triggers the configuration unit to run. The analysis module further receives and stores the forest images collected during the drone's flight and analyzes the forest health trend based on the stored images. The evaluation module continuously receives the forest health trend analysis results from the analysis module and evaluates the health of the forest ecological environment based on the analysis results. Finally, the access module provides system users with access to the system to read the forest images collected by the drone. The prompting module obtains the evaluation results of the forest ecological environment health from the evaluation module and issues an early warning based on the evaluation results.

[0070] The system operation described in the above embodiments provides a fully intelligent drone forest patrol technology, ensuring that the drone patrol process requires less human control, thereby achieving a higher frequency and more stable forest patrol service.

[0071] Example 2:

[0072] At the implementation level, based on Example 1, this example refers to... Figure 2 A further detailed description of the UAV forest patrol system based on BeiDou positioning in Example 1 is provided below:

[0073] A method for unmanned aerial vehicle (UAV) forest patrol based on BeiDou positioning includes the following steps:

[0074] Step 1: Upload location coordinates. Based on the uploaded location coordinates, limit the inspection area and select a point in the inspection area as the starting point for the drone's flight.

[0075] Step 2: Control the drone to fly within the inspection area based on the flight start point, and collect forest images during the flight;

[0076] Step 3: Configure the drone with turnaround logic so that the drone turns around every time it reaches the edge of the inspection area;

[0077] Step 4: Assess the forest health trend based on the forest images collected during the UAV analysis, and assess the health of the forest ecological environment based on the forest health trend.

[0078] Step 5: If the evaluation result is negative, output the evaluation result and simultaneously grant the user access to read the forest images collected by the drone.

[0079] In summary, the system and method in the above embodiments, through the design and deployment of limited inspection areas and UAV analysis logic, enable UAVs to autonomously and intelligently complete the acquisition of forest images. During the acquisition process, the forest image acquisition path is autonomously and randomly generated, ensuring the diversity of forest image acquisition and making the subsequent assessment of the health of the forest ecological environment more reliable and effective. At the same time, based on continuous forest image acquisition, long-term health monitoring of the forest ecological environment is implemented, and the acquired forest images are stored and managed for easier viewing by forest management personnel. Furthermore, the system is configured with specified assessment logic to determine the monitoring of the forest ecological environment. When the forest ecological environment is determined to be unhealthy, forest management personnel are immediately notified, ensuring that forest management personnel can carry out dynamic responses in their forest maintenance work.

[0080] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions will 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.

Claims

1. A BeiDou-based unmanned aerial vehicle (UAV) forest patrol system, characterized in that, include: The area restriction module is used to upload location coordinates and restrict the inspection area based on the uploaded location coordinates; The control module is used to control the drone to fly in the inspection area and collect forest images; The analysis module is used to receive forest images collected during the flight of the UAV, store the forest images, and analyze the forest health trend based on the stored forest images. The assessment module is used to continuously receive the forest health trend analysis results from the analysis module, and assess whether the forest ecological environment is healthy based on the analysis results. The access module is used to grant system users access permissions to read forest images collected by drones; The alert module is used to obtain the assessment results of whether the forest ecological environment is healthy from the assessment module, and issue early warning alerts based on the assessment results; The control module has a configuration unit at its lower level. When configuring the turnaround angle of the UAV when it reaches the boundary of the inspection area, the configuration unit follows the following procedure: when the UAV reaches the boundary of the inspection area, the UAV first rotates horizontally by 180 degrees, and then performs a second horizontal rotation adjustment so that the camera end of the UAV that collects forest images is facing the same direction as the sun shining on the earth's surface. After that, the UAV flies again to collect forest images based on the control module. The flight path of the UAV during the process of collecting forest images based on the control module is recorded synchronously inside the UAV. When storing forest images, the analysis module synchronously sets distinct storage intervals, ensuring that forest images collected by the UAV during the operation of the configuration unit and sensing unit are stored in the same distinct storage interval after each operation. The analysis logic for forest health trend in the analysis module is as follows: ； In the formula: To assess the health status of the forest; The average forest vegetation cover shown for all forest images; The total number of forest images; Let i represent the forest vegetation coverage rate shown in the i-th forest image; The area to be inspected; The inspection area is the area of ​​the largest sub-region within the inspection area after it is segmented based on the flight path; where the inspection area is... As a trend in forest health Normalization parameters during calculation, to prevent If the value is too small, the forest health status tends to be... The larger the value, the better the forest's health status; conversely, the smaller the value, the worse the forest's health status. The assessment module continuously receives and records the forest health trend analysis results. The assessment module always uses the analysis results of the three most recent records to assess whether the forest ecological environment is healthy: when the analysis results of the three records show a continuous upward trend over time, it indicates that the forest ecological environment is healthy; when the analysis results of the three records show a continuous downward trend over time, it indicates that the forest ecological environment is unhealthy. Conversely, the assessment module is refreshed, and the earliest analysis result among the three records used in the previous application is iterated with the latest analysis result, and the assessment operation is performed again. This process continues until the assessment module outputs a healthy or unhealthy assessment result and then ends.

2. The UAV forest patrol system based on BeiDou positioning according to claim 1, characterized in that, The region limitation module uploads no fewer than three location coordinates. The closed region obtained by connecting the uploaded location coordinates is recorded as the inspection region. After the inspection area is determined, real coordinates are configured for the inspection area so that the coordinates of any position in the inspection area are consistent with the corresponding coordinates in the forest. Then, a point is selected in the inspection area, the coordinates of the point are obtained, and the coordinates of the point, together with the inspection area, are transmitted to the drone. The transmitted coordinates of the point are used as the starting point for the drone inspection, and the drone always flies within the inspection area.

3. The UAV forest patrol system based on BeiDou positioning according to claim 1, characterized in that, During the flight of the drone controlled by the control module, the drone uses its onboard ranging sensor to detect the distance between itself and the obstacles below in real time. Based on the ranging results, the drone adaptively adjusts its flight altitude to keep the distance between itself and the obstacles below constant. When the control module controls the drone to fly, the drone always flies in a straight line from a top-down perspective. The control module is equipped with a sensing unit at its lower level. The sensing module is used to sense the location information of the UAV in real time. When it senses that the UAV has reached the boundary of the inspection area, it triggers the configuration unit to run. The frequency at which the drone collects forest images in the configuration unit is customized by the system user.

4. A UAV 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 user decides whether to stop running. When the configuration unit and the sensing unit stop running, the analysis module is triggered to run.

5. A UAV forest patrol system based on BeiDou positioning according to claim 1, characterized in that, The prompting module is triggered when the evaluation module's evaluation result is negative or when no evaluation result can be output for a preset number of consecutive times. The logic for the prompting module to issue a warning is as follows: The system pre-sets warning message content. When the warning module is in operation, it sends the warning message content to the mobile device held by the user on the system side, and the user reads the warning message content on the mobile device.

6. The UAV forest patrol system based on BeiDou positioning according to claim 1, characterized in that, The area restriction module is interactively connected to a control module via a wireless network. The control module is interactively connected to a configuration unit and a sensing unit via a wireless network. The control module is interactively connected to an analysis module via a wireless network. The analysis module is interactively connected to the configuration unit and the interaction unit via a wireless network. The analysis module is interactively connected to an evaluation module via a wireless network. The evaluation module is interactively connected to an access module and a prompting module via a wireless network.

7. A method for unmanned aerial vehicle (UAV) forest patrol based on BeiDou positioning, wherein the method is an implementation method of the UAV forest patrol system based on BeiDou positioning as described in any one of claims 1-6, characterized in that, Includes the following steps: Step 1: Upload location coordinates. Based on the uploaded location coordinates, limit the inspection area and select a point in the inspection area as the starting point for the drone's flight. Step 2: Control the drone to fly within the inspection area based on the flight start point, and collect forest images during the flight; Step 3: Configure the drone with turnaround logic so that the drone turns around every time it reaches the edge of the inspection area; Step 4: Assess the forest health trend based on the forest images collected during the UAV analysis, and assess the health of the forest ecological environment based on the forest health trend. Step 5: If the evaluation result is negative, output the evaluation result and simultaneously grant the user access to read the forest images collected by the drone.

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