Data processing method and device, computer device and storage medium

Abstract

The application relates to a data processing method and device, computer equipment and a storage medium. The application can be used in the field of financial technology or other related fields. The method comprises the following steps: acquiring a route conversion image of a UAV at a current flight time; the route conversion image comprises a current route area; determining a target motion direction corresponding to the current flight time according to a historical motion direction of the UAV and the current route area; obtaining the moving position information of the UAV at the next flight time based on the target motion direction; obtaining a data acquisition result corresponding to an agricultural data acquisition task according to the data collected by the UAV moving according to the target task route; and the data acquisition result is used for data analysis of an agricultural resource evaluation task corresponding to the agricultural data acquisition task by a data processing platform. The method can efficiently complete high-precision data acquisition, has low operation and implementation cost, and improves the processing efficiency of the agricultural resource evaluation task.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a data processing method, apparatus, computer equipment, storage medium, and computer program product. Background Technology

[0002] Agricultural lending by financial institutions faces challenges in monitoring and managing agricultural loans in some remote areas due to geographical limitations and transportation constraints. Relevant technologies typically employ satellite remote sensing image recognition to monitor and manage different regions, using the estimated yield and value of crops as a basis for determining the amount of agricultural loans to be issued.

[0003] However, satellite remote sensing is difficult to operate, has high application costs, is easily affected by cloudy weather and cannot meet actual needs, and is limited by the number of tasks that can be performed. When there are too many tasks, satellite remote sensing cannot be used. Summary of the Invention

[0004] Therefore, it is necessary to provide a data processing method, apparatus, computer equipment, storage medium, and computer program product that can solve the above-mentioned technical problems.

[0005] In a first aspect, this application provides a data processing method, the method comprising:

[0006] Acquire a route transition image of the UAV at the current flight time; the route transition image includes the current route area, which is the area in the target task route corresponding to the agricultural data acquisition task currently being performed by the UAV;

[0007] Based on the historical movement direction of the UAV and the current route area, the target movement direction corresponding to the current flight time is determined; the historical movement direction is the flight movement direction of the UAV at the previous flight time.

[0008] Based on the target's direction of motion, the movement position information of the UAV at the next flight time in the current flight time is obtained; the movement position information is used to control the UAV to move in the next flight time.

[0009] Based on the data collected by the UAV moving along the target mission route, the data acquisition result corresponding to the agricultural data acquisition task is obtained; the data acquisition result is used by the data processing platform to perform data analysis on the agricultural resource assessment task corresponding to the agricultural data acquisition task.

[0010] In one embodiment, acquiring the route change image of the UAV at the current flight time includes:

[0011] Obtain ground-level annotation information for the target task route; the target task route is pre-planned for the agricultural data acquisition task.

[0012] Based on the ground annotation information, the ground images collected by the UAV at the current flight time are processed to obtain a binary image corresponding to the ground image, which is used as the route conversion image.

[0013] In one embodiment, determining the target motion direction corresponding to the current flight moment based on the historical motion direction of the UAV and the current route area includes:

[0014] Using the route transformation image, a coordinate system for the motion direction of the UAV is established;

[0015] Based on the historical movement direction of the UAV and the current route area, the target movement direction corresponding to the current flight time is determined from the movement direction coordinate system.

[0016] In one embodiment, determining the target motion direction corresponding to the current flight time from the motion direction coordinate system based on the historical motion direction of the UAV and the current route area includes:

[0017] In the route transformation image, multiple associated directions corresponding to the historical movement direction are determined; different associated directions correspond to different image edge segments, and the image edge segments are the segments of the edge portion of the route transformation image covered by the current route area;

[0018] The target edge segment is determined from each of the image edge segments, and the target motion direction corresponding to the current flight time is obtained in the motion direction coordinate system based on the target edge segment.

[0019] In one embodiment, obtaining the target motion direction corresponding to the current flight time in the motion direction coordinate system based on the target edge line segment includes:

[0020] Using the midpoint of the target edge line segment as the vector endpoint and the center point of the route transformation image as the vector starting point, the output direction vector is obtained according to the motion direction coordinate system and used as the target motion direction.

[0021] In one embodiment, obtaining the UAV's position information for the next flight moment based on the target's direction of motion includes:

[0022] Obtain preset coordinate transformation information; the preset coordinate transformation information is used to characterize the transformation relationship between the coordinate system of the UAV's motion direction and the coordinate system of the agricultural data acquisition area;

[0023] According to the preset coordinate transformation information, the target movement direction is transformed into the coordinate system of the agricultural data acquisition area to obtain the movement position coordinates of the UAV at the next flight time of the current flight time.

[0024] In one embodiment, the agricultural resource assessment task corresponds to multiple agricultural data acquisition tasks, and the method further includes:

[0025] The data acquisition results corresponding to each of the agricultural data acquisition tasks are sent to the data processing platform through the data acquisition center, so that the data processing platform can perform data analysis on the agricultural resource assessment task based on the multiple data acquisition results.

[0026] Secondly, this application also provides a data processing apparatus, the apparatus comprising:

[0027] The route transition image acquisition module is used to acquire the route transition image of the UAV at the current flight time; the route transition image includes the current route area, which is the area in the target task route corresponding to the agricultural data acquisition task currently being performed by the UAV;

[0028] The target motion direction determination module is used to determine the target motion direction corresponding to the current flight time based on the historical motion direction of the UAV and the current route area; the historical motion direction is the flight motion direction of the UAV at the previous flight time of the current flight time;

[0029] The mobile position information acquisition module is used to obtain the mobile position information of the UAV at the next flight time based on the target's direction of motion; the mobile position information is used to control the UAV to move at the next flight time.

[0030] The data acquisition result module is used to obtain the data acquisition result corresponding to the agricultural data acquisition task based on the data collected by the UAV moving along the target task route; the data acquisition result is used by the data processing platform to perform data analysis on the agricultural resource assessment task corresponding to the agricultural data acquisition task.

[0031] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the data processing method described above.

[0032] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the data processing method described above.

[0033] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of the data processing method described above.

[0034] The aforementioned data processing method, apparatus, computer equipment, storage medium, and computer program product acquire a route transition image of a UAV at the current flight moment. This route transition image includes the current route area, which is a region within the target task route corresponding to the agricultural data acquisition task currently being performed by the UAV. Then, based on the UAV's historical movement direction and the current route area, the target movement direction corresponding to the current flight moment is determined. This historical movement direction is the UAV's flight movement direction at the previous flight moment. Based on the target movement direction, the UAV's position information for the next flight moment is obtained. The positioning information is used to control the movement of the UAV in the next flight moment. Then, based on the data collected by the UAV moving along the target mission route, the data acquisition results corresponding to the agricultural data acquisition task are obtained. The data acquisition results are used by the data processing platform to perform data analysis on the agricultural resource assessment task corresponding to the agricultural data acquisition task. This realizes the optimization of data acquisition for agricultural resource assessment tasks. Based on the method of deploying UAVs in multiple locations to perform line tracking tasks, UAVs can be used to carry out automated data acquisition in parallel according to the target mission route corresponding to each agricultural data acquisition task. The operation and implementation costs are low, and high-precision data acquisition can be completed efficiently, thus improving the processing efficiency of agricultural resource assessment tasks. Attached Figure Description

[0035] Figure 1 This is a flowchart illustrating a data processing method in one embodiment;

[0036] Figure 2 This is a schematic diagram of an agricultural data acquisition task processing flow in one embodiment;

[0037] Figure 3a This is a schematic diagram of a flight motion direction acquisition process in one embodiment;

[0038] Figure 3b This is a schematic diagram of a route transition image in one embodiment;

[0039] Figure 4This is a schematic diagram of an agricultural resource assessment task processing flow in one embodiment;

[0040] Figure 5 This is a flowchart illustrating another data processing method in one embodiment;

[0041] Figure 6 This is a structural block diagram of a data processing device in one embodiment;

[0042] Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0043] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0044] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for display, data used for analysis, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties; correspondingly, this application also provides a corresponding user authorization entry point for users to choose to authorize or refuse.

[0045] In one embodiment, such as Figure 1 As shown, a data processing method is provided. This embodiment illustrates the method by applying it to a terminal, such as a drone. It is understood that this method can also be applied to a server, and further to a system including both a terminal and a server, and is implemented through interaction between the terminal and the server. In this embodiment, the method includes the following steps:

[0046] Step 101: Obtain the route transition image of the drone at the current flight moment;

[0047] The route transition image can include the current route area, which can be an area within the target task route corresponding to the agricultural data acquisition task currently being performed by the UAV.

[0048] In practical applications, ground annotation information corresponding to the target task route can be obtained based on the pre-planned target task route for agricultural data acquisition. Ground images collected by the UAV at the current flight time can also be obtained. Then, image processing can be performed on the ground images at the current flight time according to the ground annotation information to obtain the corresponding binary image, which can be used as the route conversion image.

[0049] Specifically, such as Figure 2As shown, for the current flight time, the image directly below the drone during flight can be acquired and then fed into the route image conversion module. After noise reduction processing, the output is a binary image containing only the target mission route. In other words, the route image conversion module can perform image processing on the ground image acquired by the drone at the current flight time to obtain the corresponding binary image, which serves as the route conversion image.

[0050] Step 102: Determine the target movement direction corresponding to the current flight time based on the historical movement direction of the UAV and the current route area;

[0051] As an example, the historical motion direction can be the flight motion direction of the UAV at the previous flight time of the current flight time.

[0052] In practical implementation, a route conversion image can be used to establish a motion direction coordinate system for the UAV. Then, based on the UAV's flight direction at the previous flight time and the route area it is currently in in the route conversion image, the target motion direction corresponding to the current flight time can be determined from the motion direction coordinate system.

[0053] For example, such as Figure 2 As shown, the binary image output by the route image conversion module can be passed into the flight direction calculation module. By determining the flight direction required for the current state, the target motion direction corresponding to the current flight moment can be calculated.

[0054] Step 103: Based on the target's direction of motion, obtain the UAV's position information for the next flight time at the current flight time;

[0055] Among them, the mobile location information can be used to control the drone to move in the next flight moment.

[0056] After obtaining the target's direction of motion, preset coordinate transformation information can be acquired. This preset coordinate transformation information can be used to characterize the transformation relationship between the UAV's direction of motion coordinate system and the agricultural data acquisition area coordinate system. Then, according to the preset coordinate transformation information, the target's direction of motion can be transformed into the agricultural data acquisition area coordinate system, thereby obtaining the UAV's position coordinates at the next flight time in the current flight time.

[0057] Specifically, such as Figure 2 As shown, after the flight direction calculation module determines the required flight direction for the current state, the target motion direction can be input into the result integration module. Then, the position of the UAV at the next moment can be calculated and transmitted to the controller in coordinate form (x, y, z) to control the movement of the UAV.

[0058] In one example, a drone-based line tracking method, such as for a pre-planned route marked on the ground with clearly colored lines, allows the drone to cruise along the planned route. During flight, the drone can establish a coordinate system with itself as the origin based on its initial coordinate position relative to the entire agricultural data acquisition area. Then, an algorithm can identify the marked lines in the image directly below the drone during flight, and calculate the drone's next flight position. This enables precise flight along the marked lines, reducing the operational cost of agricultural data acquisition tasks.

[0059] Step 104: Based on the data collected by the UAV moving along the target mission route, obtain the data acquisition result corresponding to the agricultural data acquisition task.

[0060] The data acquisition results can be used by the data processing platform to perform data analysis on agricultural resource assessment tasks corresponding to agricultural data acquisition tasks, such as data analysis for agricultural credit assessment.

[0061] In practical applications, by using drones to cruise along a designated route, that is, by moving and collecting data according to the target mission route, various data corresponding to agricultural data acquisition tasks can be collected efficiently, that is, data acquisition results.

[0062] In one example, agricultural credit assessment primarily focuses on crops and soil. On a macro level, drones can collect land area data and count plant numbers through patrols. Compared to manual statistical methods like comparative sampling surveys, drone-based statistics are more comprehensive and accurate, and less costly than satellite remote sensing. Furthermore, automated drone patrols can easily collect spectral information about crops, which can be used to monitor crop growth, quality, and pests and diseases. Simultaneously, it can collect spectral data from the soil to analyze soil organic matter, iron content, and other factors. This data can then be used to predict crop yield and value, enabling data analysis for agricultural resource assessment tasks.

[0063] In one alternative embodiment, using drones to perform line-tracking cruises along pre-planned routes can adapt to most small to medium-sized assessment scenarios. This approach is low-cost and simple to operate, addressing the issue of high costs associated with satellite use. Because drones can operate at low altitudes, they can compensate for the weather-related limitations (such as cloud cover) that affect satellite optical remote sensing and conventional aerial photography. Furthermore, low-altitude close-up photography can improve measurement accuracy, reaching nanometer-level precision, thus resolving the issue of low satellite resolution. By deploying drones for line tracking in multiple locations, multiple tasks can be processed simultaneously and automatically, avoiding the inefficiencies and time-consuming nature of satellite remote sensing.

[0064] Compared to traditional methods that rely on manual field surveys or satellite remote sensing for data collection, which are costly for small and medium-sized plots, the technical solution in this embodiment overcomes the limitations of satellite remote sensing, such as its unsuitability for small and medium-sized scenarios, high cost, low spectral resolution, and low efficiency, by using drones for agricultural credit assessment data collection. It is simple to implement and has low implementation costs, and can efficiently and automatically complete the task of acquiring agricultural data for agricultural resource assessment.

[0065] In the above data processing method, the route transformation image of the UAV at the current flight time is acquired. Then, based on the historical movement direction of the UAV and the current route area, the target movement direction corresponding to the current flight time is determined. Based on the target movement direction, the movement position information of the UAV at the next flight time is obtained. Then, based on the data collected by the UAV moving along the target task route, the data acquisition result corresponding to the agricultural data acquisition task is obtained. This realizes the optimization of data acquisition for agricultural resource assessment tasks. Based on the method of deploying UAVs in multiple locations to perform line tracking tasks, UAVs can be used to perform multi-task parallel automated data acquisition according to the target task routes corresponding to each agricultural data acquisition task. The operation and implementation cost is low, and high-precision data acquisition can be completed efficiently, thus improving the processing efficiency of agricultural resource assessment tasks.

[0066] In one embodiment, acquiring the route change image of the UAV at the current flight time may include the following steps:

[0067] Obtain ground annotation information for the target mission route; the target mission route is pre-planned for the agricultural data acquisition mission; according to the ground annotation information, perform image processing on the ground image collected by the UAV at the current flight time to obtain the binary image corresponding to the ground image, which is used as the route conversion image.

[0068] In practical applications, since the target mission route has been planned and marked on the ground with lines of relatively obvious colors, image processing can enable the UAV to identify the lines it needs to track, obtain the target mission route to be tracked, and obtain a binary image containing the target mission route.

[0069] In one example, for the image directly below the drone during flight, the route the drone is tracking is marked with the color that has the greatest color difference from the surrounding land (such as black), which facilitates image processing by the route image conversion module. By capturing the configured color corresponding to the target task route and performing noise reduction on the captured image, the values ​​in the resulting image matrix that are closest to the route color can be set to 1, and the other values ​​can be set to 0, resulting in a binary image containing only the target task route.

[0070] In this embodiment, ground annotation information for the target mission route is obtained, and then the ground image collected by the UAV at the current flight time is processed according to the ground annotation information to obtain a binary image corresponding to the ground image, which serves as the route conversion image and provides data support for further flight direction calculation.

[0071] In one embodiment, determining the target movement direction corresponding to the current flight time based on the historical movement direction of the UAV and the current route area may include the following steps:

[0072] Using the route transformation image, a motion direction coordinate system is established for the UAV; based on the UAV's historical motion direction and the current route area, the target motion direction corresponding to the current flight time is determined from the motion direction coordinate system.

[0073] In practical applications, such as Figure 3a As shown, a coordinate system for the drone's motion direction can be established by taking the center of the acquired binary image (i.e., the route transformation image) as the origin (i.e., taking the drone itself as the origin). The positive Y-axis can be set as the initial direction of the drone's flight, forward, and the negative Y-axis as backward. The positive X-axis is right and the negative X-axis is left. Each movement of the drone can be regarded as a tiny point-to-point displacement. The line tracking processing that the drone is performing can be achieved by connecting multiple points end to end to form a path.

[0074] In this embodiment, by using route conversion images, a motion direction coordinate system for the UAV is established. Then, based on the UAV's historical motion direction and the current route area, the target motion direction corresponding to the current flight time is determined from the motion direction coordinate system. This enables line tracking processing based on the UAV, providing data support for efficiently completing data acquisition tasks.

[0075] In one embodiment, determining the target motion direction corresponding to the current flight time from the motion direction coordinate system based on the historical motion direction of the UAV and the current route area may include the following steps:

[0076] In the route conversion image, multiple associated directions corresponding to the historical motion direction are determined; different associated directions correspond to different image edge segments, and the image edge segments are the segments of the current route area that cover the edge portion of the route conversion image; a target edge segment is determined from each of the image edge segments, and the target motion direction corresponding to the current flight time is obtained in the motion direction coordinate system based on the target edge segment.

[0077] In one example, by recording the drone's movement direction at the previous moment in the route transition image, the coverage length of the edge portion and the path in different directions can be analyzed. Furthermore, by comparing the coverage lengths in the front, left, and right directions of the movement direction at the previous moment, the longest line segment (i.e., the target edge line segment) can be selected. For example, as shown... Figure 3b As shown, the direction of motion at the previous moment is forward (i.e., the historical direction of motion). In its corresponding forward, left, and right directions (i.e., multiple related directions), the edge of the left direction is not covered by black, meaning that the edge of this direction is not covered by the path. The length of the black covered line segment (i.e., the image edge line segment) in the forward direction is less than the length of the black covered line segment in the right direction. Therefore, the right direction can be taken as the target motion direction corresponding to the current flight moment.

[0078] In this embodiment, by determining multiple associated directions corresponding to the historical motion direction in the route conversion image, and then determining the target edge segment from each image edge segment, the target motion direction corresponding to the current flight time is obtained in the motion direction coordinate system based on the target edge segment, and the next flight direction can be calculated accurately and effectively.

[0079] In one embodiment, obtaining the target motion direction corresponding to the current flight time in the motion direction coordinate system based on the target edge line segment may include the following steps:

[0080] Using the midpoint of the target edge line segment as the vector endpoint and the center point of the route transformation image as the vector starting point, the output direction vector is obtained according to the motion direction coordinate system and used as the target motion direction.

[0081] In the specific implementation, the midpoint of the target edge line segment can be obtained as the vector endpoint, the center point of the route transformation image can be used as the vector starting point, and the vector can be used as the movement direction to output a (x, y, z) direction vector as the movement direction of the UAV (i.e. the target movement direction). This movement direction can be recorded and input into the next movement direction calculation.

[0082] In this embodiment, by taking the midpoint of the target edge line segment as the vector endpoint and the center point of the route transformation image as the vector starting point, the output direction vector is obtained according to the motion direction coordinate system and used as the target motion direction, thus accurately and effectively calculating the UAV flight direction.

[0083] In one embodiment, obtaining the UAV's position information for the next flight moment based on the target's direction of motion may include the following steps:

[0084] Obtain preset coordinate transformation information; the preset coordinate transformation information is used to characterize the transformation relationship between the UAV's motion direction coordinate system and the agricultural data acquisition area coordinate system; according to the preset coordinate transformation information, the target motion direction is transformed to the agricultural data acquisition area coordinate system to obtain the UAV's movement position coordinates at the next flight time at the current flight time.

[0085] In practical applications, such as Figure 2 As shown, for the obtained motion direction vector (i.e., the target motion direction), since the coordinate system of the agricultural data acquisition area and the UAV's motion direction coordinate system are two independent coordinate systems, it can be processed by x′=xcos(θ)+ysin(θ) and y′=ycos(θ)+xsin(θ) to keep its height unchanged. Then, the motion direction vector can be uniformly converted into the agricultural data acquisition area coordinate system. Then, the coordinate position after movement (i.e., the movement position coordinate) can be calculated by finalX=x+x′·0.000001 and can be input into the UAV controller to control the UAV to complete the flight cruise.

[0086] In this embodiment, by acquiring preset coordinate transformation information and then converting the target movement direction to the coordinate system of the agricultural data acquisition area according to the preset coordinate transformation information, the movement position coordinates of the UAV at the next flight moment at the current flight moment are obtained. This enables the UAV to perform line tracking cruise work according to the target mission route, which helps to efficiently complete high-precision data acquisition and improves the processing efficiency of agricultural resource assessment tasks.

[0087] In one embodiment, the agricultural resource assessment task corresponds to multiple agricultural data acquisition tasks, and may further include the following steps:

[0088] The data acquisition results corresponding to each of the agricultural data acquisition tasks are sent to the data processing platform through the data acquisition center, so that the data processing platform can perform data analysis on the agricultural resource assessment task based on the multiple data acquisition results.

[0089] In one example, such as Figure 4 As shown, the deployment of drones in multiple locations enables automated data collection for multi-regional and multi-task evaluation processes. The drone data can be transmitted to the sub-control center (i.e., the data acquisition center corresponding to each agricultural data acquisition task) for data collection. The collected data (i.e., the data acquisition results) can then be sent to the central control center (i.e., the data processing platform) for unified data processing and analysis.

[0090] In another example, addressing the issue that satellite remote sensing is susceptible to weather conditions and its low resolution cannot meet the needs of certain scenarios, a drone can control its flight altitude by controlling the z-value of the input controller. This allows the drone to operate at ultra-low altitudes below 100 meters, avoiding weather interference with the camera mission and accuracy. Furthermore, high-precision equipment can be used to improve the resolution of the images acquired by the drone, thereby enhancing the effectiveness of agricultural data acquisition.

[0091] In this embodiment, the data acquisition results corresponding to each agricultural data acquisition task are sent to the data processing platform through the data acquisition center corresponding to each agricultural data acquisition task. The data processing platform can then perform data analysis on the agricultural resource assessment task based on multiple data acquisition results. This allows for automated data acquisition using drones in parallel with multiple tasks, thereby improving the processing efficiency of agricultural resource assessment tasks.

[0092] In one embodiment, such as Figure 5 The diagram illustrates another data processing method. In this embodiment, the method includes the following steps:

[0093] In step 501, ground annotation information for the target mission route is obtained; the target mission route is pre-planned for the agricultural data acquisition task. In step 502, according to the ground annotation information, image processing is performed on the ground image collected by the UAV at the current flight time to obtain a binary image corresponding to the ground image, which serves as the route conversion image. In step 503, the route conversion image is used to establish a motion direction coordinate system for the UAV. In step 504, based on the UAV's historical motion direction and the current route area, the target motion direction corresponding to the current flight time is determined from the motion direction coordinate system. In step 505, preset coordinate transformation information is obtained; the preset coordinate transformation information is used to characterize the transformation relationship between the UAV's motion direction coordinate system and the agricultural data acquisition area coordinate system. In step 506, according to the preset coordinate transformation information, the target motion direction is transformed to the agricultural data acquisition area coordinate system to obtain the UAV's movement position coordinates at the next flight time. In step 507, based on the data collected by the UAV moving along the target mission route, the data acquisition result corresponding to the agricultural data acquisition task is obtained. In step 508, the data acquisition results corresponding to each agricultural data acquisition task are sent to the data processing platform through the data acquisition center corresponding to each agricultural data acquisition task. This allows the data processing platform to perform data analysis on the agricultural resource assessment task based on multiple data acquisition results. It should be noted that the specific limitations of the above steps can be found in the specific limitations of a data processing method described above, and will not be repeated here.

[0094] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0095] Based on the same inventive concept, this application also provides a data processing apparatus for implementing the data processing method described above. The solution provided by this apparatus is similar to the implementation scheme described in the above method; therefore, the specific limitations in one or more data processing apparatus embodiments provided below can be found in the limitations of the data processing method described above, and will not be repeated here.

[0096] In one embodiment, such as Figure 6 As shown, a data processing apparatus is provided, comprising:

[0097] The route conversion image acquisition module 601 is used to acquire the route conversion image of the UAV at the current flight time; the route conversion image includes the current route area, which is the area in the target task route corresponding to the agricultural data acquisition task currently being performed by the UAV;

[0098] The target motion direction determination module 602 is used to determine the target motion direction corresponding to the current flight time based on the historical motion direction of the UAV and the current route area; the historical motion direction is the flight motion direction of the UAV at the previous flight time of the current flight time;

[0099] The mobile position information acquisition module 603 is used to obtain the mobile position information of the UAV at the next flight time based on the target's direction of motion; the mobile position information is used to control the UAV to move at the next flight time.

[0100] The data acquisition result obtaining module 604 is used to obtain the data acquisition result corresponding to the agricultural data acquisition task based on the data collected by the UAV moving along the target task route; the data acquisition result is used by the data processing platform to perform data analysis on the agricultural resource assessment task corresponding to the agricultural data acquisition task.

[0101] In one embodiment, the route conversion image acquisition module 601 includes:

[0102] The ground annotation information acquisition submodule is used to acquire ground annotation information for the target task route; the target task route is pre-planned for the agricultural data acquisition task.

[0103] The image processing submodule is used to process the ground image collected by the UAV at the current flight time according to the ground annotation information to obtain the binary image corresponding to the ground image, which is used as the route conversion image.

[0104] In one embodiment, the target motion direction determination module 602 includes:

[0105] The motion direction coordinate system establishment submodule is used to establish a motion direction coordinate system for the UAV using the route-transformed image.

[0106] The target motion direction acquisition submodule is used to determine the target motion direction corresponding to the current flight time from the motion direction coordinate system based on the historical motion direction of the UAV and the current route area.

[0107] In one embodiment, the target motion direction obtaining submodule includes:

[0108] The associated direction determination unit is used to determine multiple associated directions corresponding to the historical motion direction in the route transformation image; different associated directions correspond to different image edge segments, and the image edge segments are the segments of the edge portion of the route area currently in the route that covers the route transformation image;

[0109] The target edge segment determination unit is used to determine the target edge segment from each of the image edge segments, and to obtain the target motion direction corresponding to the current flight time in the motion direction coordinate system based on the target edge segment.

[0110] In one embodiment, the target edge segment determination unit includes:

[0111] The output direction vector obtaining unit is used to obtain the output direction vector based on the motion direction coordinate system, with the midpoint of the target edge line segment as the vector endpoint and the center point of the route transformation image as the vector starting point, and to serve as the target motion direction.

[0112] In one embodiment, the mobile location information obtaining module 603 includes:

[0113] The coordinate transformation information acquisition submodule is used to acquire preset coordinate transformation information; the preset coordinate transformation information is used to characterize the transformation relationship between the UAV's motion direction coordinate system and the agricultural data acquisition area coordinate system;

[0114] The coordinate transformation submodule is used to transform the target movement direction to the coordinate system of the agricultural data acquisition area according to the preset coordinate transformation information, so as to obtain the movement position coordinates of the UAV at the next flight time of the current flight time.

[0115] In one embodiment, the agricultural resource assessment task corresponds to multiple agricultural data acquisition tasks, and the apparatus further includes:

[0116] The agricultural resource assessment module is used to send the data acquisition results corresponding to each of the agricultural data acquisition tasks to the data processing platform through the data acquisition center corresponding to each agricultural data acquisition task, so that the data processing platform can perform data analysis on the agricultural resource assessment task based on multiple data acquisition results.

[0117] Each module in the aforementioned data processing device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0118] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 7 As shown, the computer device includes a processor, memory, communication interface, display screen, and input device connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a data processing method.

[0119] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0120] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the following steps:

[0121] Acquire a route transition image of the UAV at the current flight time; the route transition image includes the current route area, which is the area in the target task route corresponding to the agricultural data acquisition task currently being performed by the UAV;

[0122] Based on the historical movement direction of the UAV and the current route area, the target movement direction corresponding to the current flight time is determined; the historical movement direction is the flight movement direction of the UAV at the previous flight time.

[0123] Based on the target's direction of motion, the movement position information of the UAV at the next flight time in the current flight time is obtained; the movement position information is used to control the UAV to move in the next flight time.

[0124] Based on the data collected by the UAV moving along the target mission route, the data acquisition result corresponding to the agricultural data acquisition task is obtained; the data acquisition result is used by the data processing platform to perform data analysis on the agricultural resource assessment task corresponding to the agricultural data acquisition task.

[0125] In one embodiment, the processor, when executing a computer program, also implements the steps of the data processing method described in the other embodiments above.

[0126] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, the computer program performing the following steps when executed by a processor:

[0127] Acquire a route transition image of the UAV at the current flight time; the route transition image includes the current route area, which is the area in the target task route corresponding to the agricultural data acquisition task currently being performed by the UAV;

[0128] Based on the historical movement direction of the UAV and the current route area, the target movement direction corresponding to the current flight time is determined; the historical movement direction is the flight movement direction of the UAV at the previous flight time.

[0129] Based on the target's direction of motion, the movement position information of the UAV at the next flight time in the current flight time is obtained; the movement position information is used to control the UAV to move in the next flight time.

[0130] Based on the data collected by the UAV moving along the target mission route, the data acquisition result corresponding to the agricultural data acquisition task is obtained; the data acquisition result is used by the data processing platform to perform data analysis on the agricultural resource assessment task corresponding to the agricultural data acquisition task.

[0131] In one embodiment, when the computer program is executed by a processor, it also implements the steps of the data processing method described in the other embodiments above.

[0132] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, performs the following steps:

[0133] Acquire a route transition image of the UAV at the current flight time; the route transition image includes the current route area, which is the area in the target task route corresponding to the agricultural data acquisition task currently being performed by the UAV;

[0134] Based on the historical movement direction of the UAV and the current route area, the target movement direction corresponding to the current flight time is determined; the historical movement direction is the flight movement direction of the UAV at the previous flight time.

[0135] Based on the target's direction of motion, the movement position information of the UAV at the next flight time in the current flight time is obtained; the movement position information is used to control the UAV to move in the next flight time.

[0136] Based on the data collected by the UAV moving along the target mission route, the data acquisition result corresponding to the agricultural data acquisition task is obtained; the data acquisition result is used by the data processing platform to perform data analysis on the agricultural resource assessment task corresponding to the agricultural data acquisition task.

[0137] In one embodiment, when the computer program is executed by a processor, it also implements the steps of the data processing method described in the other embodiments above.

[0138] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0139] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0140] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A data processing method, characterized in that, The method includes: Acquire a route transition image of the UAV at the current flight time; the route transition image includes the current route area, which is the area in the target task route corresponding to the agricultural data acquisition task currently being performed by the UAV; Using the route transformation image, a coordinate system for the motion direction of the UAV is established; In the route conversion image, multiple associated directions corresponding to the historical movement direction of the UAV are determined; different associated directions correspond to different image edge segments, and the image edge segments are the segments that cover the edge portion of the route conversion image where the current route area is located; The target edge segment is determined from each of the image edge segments. The midpoint of the target edge segment is taken as the vector endpoint, and the center point of the route conversion image is taken as the vector start point. The output direction vector is obtained according to the motion direction coordinate system and is used as the target motion direction. The historical motion direction is the flight motion direction of the UAV at the previous flight time of the current flight time; Based on the target's direction of motion, the movement position information of the UAV at the next flight time in the current flight time is obtained; the movement position information is used to control the UAV to move in the next flight time. Based on the data collected by the UAV moving along the target mission route, the data acquisition result corresponding to the agricultural data acquisition task is obtained; the data acquisition result is used by the data processing platform to perform data analysis on the agricultural resource assessment task corresponding to the agricultural data acquisition task.

2. The method according to claim 1, characterized in that, The acquisition of the route change image of the UAV at the current flight time includes: Obtain ground-level annotation information for the target task route; the target task route is pre-planned for the agricultural data acquisition task. Based on the ground annotation information, the ground images collected by the UAV at the current flight time are processed to obtain a binary image corresponding to the ground image, which is used as the route conversion image.

3. The method according to claim 1, characterized in that, The step of obtaining the UAV's position information for the next flight moment based on the target's direction of motion includes: Obtain preset coordinate transformation information; the preset coordinate transformation information is used to characterize the transformation relationship between the coordinate system of the UAV's motion direction and the coordinate system of the agricultural data acquisition area; According to the preset coordinate transformation information, the target movement direction is transformed into the coordinate system of the agricultural data acquisition area to obtain the movement position coordinates of the UAV at the next flight time of the current flight time.

4. The method according to any one of claims 1 to 3, characterized in that, The agricultural resource assessment task corresponds to multiple agricultural data acquisition tasks, and the method further includes: The data acquisition results corresponding to each of the agricultural data acquisition tasks are sent to the data processing platform through the data acquisition center, so that the data processing platform can perform data analysis on the agricultural resource assessment task based on the multiple data acquisition results.

5. A data processing apparatus, characterized in that, The device includes: The route transition image acquisition module is used to acquire the route transition image of the UAV at the current flight time; the route transition image includes the current route area, which is the area in the target task route corresponding to the agricultural data acquisition task currently being performed by the UAV; The target motion direction determination module is used to determine the target motion direction corresponding to the current flight time based on the historical motion direction of the UAV and the current route area; the historical motion direction is the flight motion direction of the UAV at the previous flight time of the current flight time; The mobile position information acquisition module is used to obtain the mobile position information of the UAV at the next flight time based on the target's direction of motion; the mobile position information is used to control the UAV to move at the next flight time. The data acquisition result module is used to obtain the data acquisition result corresponding to the agricultural data acquisition task based on the data collected by the UAV moving along the target task route; the data acquisition result is used by the data processing platform to perform data analysis on the agricultural resource assessment task corresponding to the agricultural data acquisition task. The target motion direction determination module includes: The motion direction coordinate system establishment submodule is used to establish a motion direction coordinate system for the UAV using the route-transformed image. The target motion direction acquisition submodule is used to determine the target motion direction corresponding to the current flight time from the motion direction coordinate system based on the historical motion direction of the UAV and the current route area. The target motion direction is obtained by the sub-module including: The associated direction determination unit is used to determine multiple associated directions corresponding to the historical motion direction in the route transformation image; different associated directions correspond to different image edge segments, and the image edge segments are the segments of the edge portion of the route area currently in the route that covers the route transformation image; The target edge segment determination unit is used to determine the target edge segment from each of the image edge segments, and to obtain the target motion direction corresponding to the current flight time in the motion direction coordinate system based on the target edge segment; The target edge segment determination unit includes: The output direction vector obtaining unit is used to obtain the output direction vector based on the motion direction coordinate system, with the midpoint of the target edge line segment as the vector endpoint and the center point of the route transformation image as the vector starting point, and to serve as the target motion direction.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 4.

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