The whole process management method and system of high-standard farmland construction

Abstract

The present application provides a whole-process management method and system for high-standard farmland construction, which belongs to the field of computer science and solves the problems of the design stage of high-standard farmland construction projects in the whole construction cycle, such as the inaccurate site survey; the difficulty in supervising the construction quality and the difficulty in accurately counting the progress; the lax control of the project quality in the acceptance stage; and the difficulty in discovering the non-grain use of high-standard farmland after completion in the later maintenance stage, which affects the construction effect. The method includes: obtaining construction image information and construction design stage information through the whole-process management platform of high-standard farmland construction during the construction and acceptance stages, so as to supervise the construction process through comparison and analysis; obtaining farmland image information in the maintenance stage through drones, and analyzing the type of crops planted based on the image information; in the case where the crop type is high-pole crops, controlling the drone to perform flight shooting tasks in a preset posture; extracting the inspection image information collected by the drone after separating adjacent high-pole crops in the direction of the rotor airflow.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a method and system for managing the entire process of high-standard farmland construction. Background Art

[0002] High-standard farmland construction projects refer to major agricultural infrastructure construction projects in my country's farmland system that comprehensively improve land, improve the quality of cultivated land, and improve agricultural production efficiency. During the entire construction cycle of high-standard farmland construction projects, it is difficult to discover non-grain plots of cultivated land during the design and acceptance stages; it is difficult to supervise the construction quality and accurately count the progress during the construction stage. In the process of farmland construction, some areas have insufficient policy implementation and inadequate supervision, making it difficult to ensure project quality and benefits. At the same time, there are also deficiencies in the maintenance and management of farmland after construction, which affects the continued benefits of farmland. In addition, since planting cash crops often brings higher economic benefits, some farmers or agricultural operators may arbitrarily change high-standard farmland to cash crops. Summary of the invention

[0003] The embodiments of the present application provide a whole-process management method and system for the construction of high-standard farmland, which can solve the problems of inaccurate site surveys in the design stage of high-standard farmland construction projects; difficulty in supervising construction quality and accurately counting progress in the construction stage; lax control of project quality in the acceptance stage; and difficulty in detecting the non-grain use of high-standard farmland after completion in the later maintenance stage, which affects the construction effect.

[0004] A first aspect of an embodiment of the present application provides a method for managing the entire process of high-standard farmland construction, including:

[0005] Obtain the construction and design phase information of high-standard farmland on the high-standard farmland construction full-process management platform;

[0006] Acquire construction image information with standing points and azimuths during the construction phase of high-standard farmland construction, as well as construction image information taken by drones, so as to synchronize the construction image information to the high-standard farmland construction full-process management platform;

[0007] During the construction and acceptance phases, the project management user end obtains the construction image information and the construction design phase information associated with the construction image information through the high-standard farmland construction full-process management platform, so as to supervise the construction process by comparing and analyzing the construction image information and the construction design phase information;

[0008] Acquiring farmland image information of high-standard farmland in the maintenance stage by using a drone, and analyzing the crop types of food crops planted in the high-standard farmland based on the image information, wherein the crop types include tall-stalk crops, short-stalk crops, and creeping crops;

[0009] When it is determined that the crop type is a tall crop, the UAV is controlled to perform a flight shooting task at a preset attitude and a preset flight altitude, and the rotor airflow direction associated with the preset attitude is the airflow direction for separating adjacent tall crops;

[0010] The inspection image information collected by the UAV after separating the adjacent tall crops in the direction of the rotor airflow is extracted, so as to generate a farmland management warning message associated with the high-standard farmland when economic crops exist in the inspection image information.

[0011] Optionally, it also includes:

[0012] Acquire the theoretical ridge position of the tall crop through the farmland image information;

[0013] The flight path of the flight shooting task is planned based on the theoretical ridge position.

[0014] Optionally, it also includes:

[0015] Acquire the average height of the tall crops through the farmland image information;

[0016] A preset flight altitude for the flight photography mission is determined based on the average altitude.

[0017] Optionally, it also includes:

[0018] The pitch angle, roll angle and yaw angle of the UAV when performing a flight shooting mission are determined based on the farmland image information, so that the rotor airflow has a lateral component and can separate adjacent tall crops to both sides.

[0019] Optionally, the determining, based on the farmland image information, the pitch angle, roll angle, and yaw angle of the drone when performing a flight shooting mission includes:

[0020] The Hough transform image processing algorithm is used to extract the direction vector of the crop row from the farmland image information. ;

[0021] According to the projection angle of the direction vector in the drone coordinate system, the pitch angle is set so that the camera can best look down at the crop;

[0022] Determine the roll angle based on the spacing and direction vector of the furrows , so that the rotor airflow acts vertically between the crop rows, where , Indicates the tilt of the crop row;

[0023] The yaw angle is set parallel to the heading vector so that the drone's forward direction always remains on the center line of the crop row.

[0024] Optionally, the farmland image information is 3D depth image information of the farmland acquired by a depth camera, and the determining of the pitch angle, roll angle and yaw angle of the drone when performing the flight shooting task based on the farmland image information includes:

[0025] Mapping each pixel in the 3D depth image information to an actual height and spatial position;

[0026] Segment and analyze 3D depth images using a convolutional neural network model to identify ridge edges, crop height distribution, and gaps;

[0027] Use the distance information in the 3D depth image to calculate the pitch, roll, and yaw angles required by the drone.

[0028] Optionally, also include:

[0029] The image analysis results are input into the PID controller for feedback to adjust the posture so that the UAV maintains the optimal posture during the entire inspection process.

[0030] The second aspect of the embodiment of the present application provides a high-standard farmland construction whole process management system, including:

[0031] Design unit, used to obtain the construction design phase information of high-standard farmland on the high-standard farmland construction whole process management platform side;

[0032] A collection unit is used to obtain construction image information with standing points and azimuths during the construction phase of high-standard farmland construction, as well as construction image information taken by drones, so as to synchronize the construction image information to the high-standard farmland construction full-process management platform;

[0033] The supervision unit is used for the project management user to obtain the construction image information and the construction design phase information associated with the construction image information through the high-standard farmland construction full process management platform during the construction and acceptance stages, so as to supervise the construction process by comparing and analyzing the construction image information and the construction design phase information.

[0034] An acquisition unit, used to acquire farmland image information of the high-standard farmland in the maintenance stage through a drone, and analyze the crop types of food crops planted in the high-standard farmland based on the image information, wherein the crop types include tall-stalk crops, short-stalk crops and creeping crops;

[0035] an analyzing unit, for controlling the UAV to perform a flight shooting task at a preset attitude and a preset flight altitude when determining that the crop type is a tall crop, wherein the rotor airflow direction associated with the preset attitude is an airflow direction for separating adjacent tall crops;

[0036] The inspection unit is used to extract the inspection image information collected by the drone after the adjacent tall crops are separated in the direction of the rotor airflow, so as to generate a farmland management warning message associated with the high-standard farmland when economic crops exist in the inspection image information.

[0037] A third aspect of an embodiment of the present application provides an electronic device, including a memory and a processor, wherein the processor is used to implement the steps of the above-mentioned high-standard farmland construction full-process management method when executing a computer program stored in the memory.

[0038] A fourth aspect of an embodiment of the present application provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned method for managing the entire process of high-standard farmland construction are implemented.

[0039] In summary, the whole-process management method of high-standard farmland construction provided in the embodiment of the present application obtains the construction design stage information of high-standard farmland on the whole-process management platform of high-standard farmland construction; obtains the construction image information with standing points and azimuths in the construction stage of high-standard farmland construction, as well as the construction image information taken by drones, so as to synchronize the construction image information to the whole-process management platform of high-standard farmland construction; the project management user end obtains the construction image information and the construction design stage information associated with the construction image information through the whole-process management platform of high-standard farmland construction during the construction and acceptance stages, so as to supervise the construction process by comparing and analyzing the construction image information and the construction design stage information; and The drone obtains farmland image information of high-standard farmland in the maintenance stage, analyzes the crop types of food crops planted in the high-standard farmland based on the image information, and the crop types include tall crops, short crops and creeping crops; when it is determined that the crop type is a tall crop, the drone is controlled to perform a flight shooting task at a preset attitude and a preset flight altitude, and the rotor airflow direction associated with the preset attitude is the airflow direction for separating adjacent tall crops; the inspection image information collected by the drone after separating adjacent tall crops in the rotor airflow direction is extracted, so as to generate a farmland management warning message associated with the high-standard farmland when there are economic crops in the inspection image information. Thus, efficient inspection of high-standard farmland can be achieved through drones and image recognition technology. For example, in a tall corn field, the drone can identify short economic crops (such as watermelons or strawberries) hidden in the field to ensure that the high-standard farmland meets the specified food crop planting requirements. The airflow of the drone rotor separates tall crops, increasing the probability of short or creeping crops being discovered. For example, if a farmer secretly plants strawberries in a corn field, airflow separation can reveal the red fruits of the strawberry plants, making it easier to identify and collect evidence. During long-term inspections, the system can record the inspection results to form historical data for further analysis of the planting conditions and violation tendencies of high-standard farmland.

[0040] Correspondingly, the system, electronic device, and computer-readable storage medium provided by the embodiments of the present invention also have the above-mentioned technical effects. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A flow chart of a possible whole-process management method for high-standard farmland construction provided in an embodiment of the present application;

[0042] Figure 2 A schematic structural block diagram of a possible high-standard farmland construction whole-process management system provided in an embodiment of the present application;

[0043] Figure 3A schematic diagram of the hardware structure of a possible high-standard farmland construction whole-process management system provided in an embodiment of the present application;

[0044] Figure 4 A schematic structural block diagram of a possible electronic device provided in an embodiment of the present application;

[0045] Figure 5 A schematic structural block diagram of a possible computer-readable storage medium provided for an embodiment of the present application. DETAILED DESCRIPTION

[0046] The embodiments of the present application provide a whole-process management method and related equipment for the construction of high-standard farmland, which can solve the problems of inaccurate site surveys in the design stage of high-standard farmland construction projects; difficulty in supervising construction quality and accurately counting progress in the construction stage; lax control of project quality in the acceptance stage; and difficulty in detecting the non-grain use of high-standard farmland after completion in the later maintenance stage, which affects the construction effect.

[0047] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments.

[0048] See also Figure 1 , which is a flow chart of a method for managing the entire process of high-standard farmland construction provided in an embodiment of the present application, and may specifically include: S110-S160.

[0049] S110, obtaining the construction design phase information of high-standard farmland on the high-standard farmland construction whole process management platform side;

[0050] S120, obtaining construction image information with standing points and azimuths during the construction phase of high-standard farmland construction, as well as construction image information taken by a drone, so as to synchronize the construction image information to the high-standard farmland construction whole process management platform side;

[0051] S130, the project management user end obtains the construction image information and the construction design phase information associated with the construction image information through the high-standard farmland construction full process management platform during the construction and acceptance stage, so as to supervise the construction process by comparing and analyzing the construction image information and the construction design phase information.

[0052] S140, obtaining farmland image information of the high-standard farmland in the maintenance stage by using a drone, and analyzing the crop types of food crops planted in the high-standard farmland based on the image information, wherein the crop types include tall-stem crops, short-stem crops and creeping crops.

[0053] S150, when it is determined that the crop type is a tall crop, controlling the UAV to perform a flight shooting task at a preset attitude and a preset flight altitude, wherein the rotor airflow direction associated with the preset attitude is an airflow direction for separating adjacent tall crops.

[0054] S160, extracting the inspection image information collected by the drone after separating the adjacent tall crops in the direction of the rotor airflow, so as to generate a farmland management warning message associated with the high-standard farmland when economic crops are present in the inspection image information.

[0055] It is understandable that high-standard farmland is high-quality arable land built to improve food production capacity, requiring the planting of policy-compliant tall food crops (such as corn, sorghum, etc.) to ensure stable agricultural production. However, due to the higher economic benefits of cash crops (such as vegetables or fruits), some farmers and business entities have the motivation to plant them illegally, so effective supervision is needed. Drones are equipped with high-resolution cameras that can obtain comprehensive images of farmland from the air. At the same time, by adjusting the flight altitude and attitude, the airflow generated by the rotor can be used to affect the physical form of plants in the farmland, thereby assisting in the identification of different types of crops.

[0056] For example, drones fly over high-standard farmland and collect high-resolution images that cover the entire crop landscape in the farmland. The collected image data includes the crop types and planting patterns in the farmland. With the help of image recognition technology, crops can be preliminarily classified in terms of height and morphology. Based on the image information obtained by the drone, the type of crop is identified through image processing algorithms (such as image classification networks based on deep learning), and the crops are divided into tall crops, short crops, and creeping crops. The deep learning convolutional neural network (CNN) is suitable for crop type recognition. Through pre-training models, tall food crops (such as corn and wheat) and cash crops (such as creeping crops such as tomatoes and strawberries) can be distinguished more accurately. This classification helps regulators identify whether there are illegal plantings of non-food crops. If tall crops are identified, the drone performs further shooting at a specific flight attitude and altitude, using the airflow generated by the rotor to separate the plants between the tall crops, making it easier to observe the situation under the plants. Tall crops are usually dense, and if creeping or short cash crops are planted illegally, they are often hidden between tall crops. When the drone flies at a specific height and attitude, the rotor airflow can form gaps in the crops, exposing the underlying vegetation, thereby revealing the hidden creeping crops. This airflow separation technology combined with image data makes it more difficult to hide illegal planting. The drone captures the separated inspection images and applies the image recognition algorithm again to extract image information of cash crops. In the images separated by the rotor airflow, the system can see the morphology and distribution of short poles or creeping plants more clearly, further confirm whether there are cash crops, and mark these illegal crops as abnormal. Once cash crops other than tall food crops are identified, the system automatically generates an early warning message associated with the farmland, prompting the regulatory department to conduct further inspection or processing. The early warning message system can provide timely early warnings of illegal planting during real-time drone inspections, improving the efficiency of supervision of high-standard farmland. And the information is automatically transmitted to the relevant management department to ensure that the inspection results are processed immediately.

[0057] In summary, the whole-process management method for high-standard farmland construction provided in the above-mentioned embodiment of the present application obtains the construction design stage information of high-standard farmland on the whole-process management platform of high-standard farmland construction; obtains the construction image information with standing points and azimuths in the construction stage of high-standard farmland construction, as well as the construction image information taken by drones, so as to synchronize the construction image information to the whole-process management platform of high-standard farmland construction; the project management user end obtains the construction image information and the construction design stage information associated with the construction image information through the whole-process management platform of high-standard farmland construction during the construction and acceptance stages, so as to supervise the construction process by comparing and analyzing the construction image information and the construction design stage information; The human-machine obtains the farmland image information of the high-standard farmland in the maintenance stage, analyzes the crop type of the food crops planted in the high-standard farmland based on the image information, and the crop types include tall crops, short crops and creeping crops; when it is determined that the crop type is a tall crop, the drone is controlled to perform the flight shooting task at a preset attitude and a preset flight altitude, and the rotor airflow direction associated with the preset attitude is the airflow direction for separating adjacent tall crops; the inspection image information collected by the drone after separating the adjacent tall crops in the rotor airflow direction is extracted, so as to generate a farmland management warning message associated with the high-standard farmland when there are economic crops in the inspection image information. Thus, efficient inspection of high-standard farmland can be achieved through drones and image recognition technology. For example, in a tall corn field, the drone can identify short economic crops (such as watermelons or strawberries) hidden in the field to ensure that the high-standard farmland meets the prescribed food crop planting requirements. The airflow of the drone rotor separates tall crops, increasing the probability of short or creeping crops being discovered. For example, if a farmer secretly plants strawberries in a corn field, airflow separation can reveal the red fruits of the strawberry plants, making it easier to identify and collect evidence. During long-term inspections, the system can record the inspection results to form historical data for further analysis of the planting conditions and violation tendencies of high-standard farmland.

[0058] For example, the overall idea of ​​the whole process management system of high-standard farmland construction is "user authority division - management of the whole process - process traceability - full traceability of archives", and through the interconnection of mobile APP, Internet and server, it realizes five functional modules, including design management, construction management, acceptance management, archive management and post-construction supervision. The system defines the operation authority according to the user roles of design, construction, supervision and management involved in the project construction, and participates in the project construction according to the authority; the whole process of project construction can be managed in an informationized manner, and the construction personnel can take on-site photos and videos (including drone aerial photography function) with standing points and azimuths of various engineering construction processes through mobile APP by combining field and indoor work; the management unit calls the image data through the Internet platform to realize the intelligent online management of project construction in an "immersive" way, which can assist the supervision unit and the management unit to dynamically supervise the construction process and project quality, progress and safety; all the image data and archival data of project management are uploaded to the server, so that the data can be left, checked and traced, and the project management efficiency can be improved.

[0059] For example, for the design management module, this module is mainly developed around the supervision of the on-site survey and visit of design personnel, the accuracy of the measurement of the dimensions of agricultural production facilities on the spot, the participation of farmers and the willingness of construction, to ensure that the planning and design of high-standard farmland projects are in line with reality and highly feasible. This module will establish the mapping standards for high-standard farmland planning, requiring the actual size to be mapped, replacing the traditional mapping mode of linear projects such as roads, irrigation and drainage ditches, forest belts, ditch slope protection, bridges, culverts, wells and other point-shaped projects in the current planning map, and mapping in the form of surface patches. The spatial combination analysis of the project's occupation of permanent basic farmland and cultivated land protection tasks will avoid audit and rectification related issues caused by the above situations. The module design requires the design unit to fill in the field survey information, upload photos and videos (the system comes with standing points, azimuths, and shooting time) according to the on-site survey, and all data will be saved in the server and cannot be modified. The module design will reflect the participation of the masses, and the relevant image materials such as the connection site, the signature of the participants' agreement to the plan, the villagers' representative meeting, the farmers' demand materials, and the agreed plan will be uploaded to the server simultaneously. National, provincial, municipal and county agricultural and rural authorities can conduct graded reviews and examinations in real time on computer web pages based on their authority. The system forms a heat map based on the density of photos, videos and movement trajectories (red indicates areas with dense survey times, blue indicates areas with sparse survey times), which can be used to determine the extent of field surveys.

[0060] For example, for the engineering construction module, by logging into the different role accounts of the construction unit, supervision unit, full-process management unit, construction unit, and competent department, you can enter different management interfaces, upload on-site photos of all types of projects and all processes of the construction process, and upload elevation surveying data and reports such as earthwork and canal engineering. The county, city, province, and national agricultural and rural departments can review and check in real time on the computer web page according to their authority, and check the daily inspection status of construction management and supervision personnel to achieve supervision and inspection of project progress, quality, safety, etc. In terms of progress management, according to the construction progress, this module takes photos of evidence from different angles at each key process point of each single project, so as to leave traces of the construction process throughout the life cycle of the project and summarize the project progress information. In terms of quality management, the construction unit realizes online inspection of key processes through this module, and the supervision unit and the full-process management unit realize quality problem inspection through this module. If the quality is unqualified, take and upload photos of the problem and description of the problem, and send them to the construction unit online and offline in the form of rectification tasks for rectification. After the rectification is completed, it will be resubmitted to the supervision unit for approval online. At the same time, the construction unit, supervision unit and full-process management unit can upload the project materials and quality inspection reports to the system for future reference. In terms of safety management, the supervision unit and the full-process management unit can conduct on-site inspections through this module. If safety hazards are found, they can take photos of the problems and upload them. They will then be sent to the construction unit online and offline in the form of rectification tasks for rectification. After the rectification is completed, it will be submitted to the supervision unit for approval again.

[0061] For example, for the project acceptance module, you can log in to the project acceptance unit role account to enter the acceptance interface. According to management requirements, take photos and upload the length, number, specifications, etc. of the project after implementation, conduct project quantity acceptance, conduct targeted quality spot checks and upload evidence photos, and complete the technical review of project quantity and quality. At the same time, upload various acceptance materials to achieve comprehensive acceptance of the project.

[0062] For example, for the archive management module, development is carried out around the completeness of material archiving. An archive management checklist is compiled in accordance with the project application and approval, bidding process requirements, survey and design results, construction supervision process records, completion acceptance archives, and acceptance results at all levels. This module standardizes and guides management personnel to upload corresponding requirements to the corresponding checklist, ensures that the archived materials are accurate and complete, and submits the electronic data archiving results with one click.

[0063] For example, for the post-construction supervision module, research and development is carried out around the operation and maintenance of various types of projects, such as the operation and maintenance of buildings and structures, damage repair, irrigation and drainage functions after the delivery of high-standard farmland projects. Managers of agricultural and rural departments at or above the county level enter the post-construction supervision interface by logging into the role account of the project maintenance unit. The project maintenance unit conducts regular inspections on the use of the project. If damage or other problems are found, take photos and upload evidence photos in time. The maintenance unit can use the system map navigation function to accurately find the corresponding location, formulate targeted maintenance plans, and upload maintenance records and photos in real time until the maintenance is completed. Achieve efficient connection of the entire chain of post-construction inspection, repair reporting, return repair, and acceptance of the project.

[0064] In some examples, this also includes:

[0065] Acquire the theoretical ridge position of the tall crop through the farmland image information;

[0066] The flight path of the flight shooting task is planned based on the theoretical ridge position.

[0067] For example, through image recognition technology, the drone extracts the position of the ridge of tall crops and determines the center line between adjacent ridges as the flight path of the drone, so that it is always located between two ridges of crops during flight. Tall crops are usually planted along regular ridges, and the space between the ridges is the best patrol path, because at this position, the drone's rotor airflow can better act on the tall crops on both sides, separating them, and facilitating the observation of other vegetation or illegal crops hidden between the crops. This path design ensures that the drone patrols the farmland at the best position, improving the clarity and accuracy of identification. When patrolling, the drone strictly flies along the center line of the ridge to ensure that it is always in the "crack" of tall crops. Centerline flight allows the drone's rotor airflow to act symmetrically on the crops on both sides, separating the tall crops while reducing the actual impact on the crops. The effect of airflow at the centerline position is more significant than flying at a random position, making it easier to find short-stemmed or creeping crops (such as strawberries, pumpkins, etc.) hidden in tall crops. Compared with irregular paths, this method ensures that the separation effect produced by airflow is more accurate and lasting. During the centerline flight, the drone collects images at the set flight altitude and attitude. The airflow of the rotor effectively separates the crops on both sides, allowing the drone's camera to clearly capture any abnormal vegetation in the ridge or at the bottom. In the image after the high-stalk crops are separated by airflow, creeping or low crops can be exposed to the lens, which makes it easier for image recognition algorithms to detect hidden cash crops. For the bottom vegetation between crops, the airflow effect of the centerline flight is more obvious than during random inspections, and it can also affect the crop gaps more widely and evenly, making the inspection images more valuable for detection. Once illegal crops are detected in the ridge or between crops, the system automatically generates an early warning message and sends it to the farmland management department. The centerline flight path ensures full coverage of crop gaps and reduces the possibility of missing illegal crops. The automatically generated early warning message includes the location of the farmland, the type and location of the illegal crops, allowing the management department to quickly locate the problem area and intervene in time.

[0068] It is understandable that with the centerline flight path, the rotor airflow can more easily separate tall crops. For example, when flying along the centerline of a cornfield, the corn stalks will be temporarily separated by the airflow, exposing the strawberry plants hidden in them for easy inspection. Compared with irregular flight paths, the centerline flight path reduces occlusion in the image, allowing the drone to capture the bottom of the ridge. This is particularly effective for detecting creeping plants under tall crops such as corn and sorghum. The centerline flight path systematizes and standardizes the inspection process, greatly improving inspection efficiency. For example, a drone flying along the centerline of a ridge can cover the ridge area of ​​the entire farmland at one time, which not only improves the accuracy of identification, but also reduces rework and repeated inspections.

[0069] In some examples, this also includes:

[0070] Acquire the average height of the tall crops through the farmland image information;

[0071] A preset flight altitude for the flight photography mission is determined based on the average altitude.

[0072] For example, in the initial stage of flight, the drone extracts the average height of tall crops through farmland image information. The plant height can be measured by using three-dimensional reconstruction technology of images or directly by using ranging sensors (such as lidar). The drone obtains the height data of the plants in the field through preliminary flight or low-altitude scanning. With the help of three-dimensional reconstruction technology of multiple images, the height model of the farmland can be generated and the average height of tall crops can be calculated. For example, in a corn field, the average plant height of corn can be accurately obtained by stitching multi-angle images of the drone. After mastering the average height of tall crops, the drone can adjust the flight altitude to optimize the viewing angle and effect of shooting. According to the average height obtained, the flight altitude of the drone is set so that it can obtain crop images from the best angle. For example, if the average height of tall crops is 2 meters, the drone can be set to patrol at a height of 2.5 meters to 3 meters. Setting the flight altitude slightly higher than the average plant height can ensure that the details between the ridge and the plant are captured without blind spots, and also ensure that the image quality is clear and recognizable. Such a height setting can reduce the blind spots caused by plant occlusion in the image and improve the accuracy of the patrol. The drone flies along the planned path at a preset altitude, while collecting image information of tall crops. At this altitude, the rotor airflow can act on the crops more effectively, revealing the gaps between tall crops for easy observation. Setting a reasonable flight altitude can not only optimize the image coverage, but also allow the airflow generated by the rotor to moderately separate the tall crops, exposing potential creeping or short crops at the bottom. The airflow separation effect at a reasonable altitude is more accurate and effective than a flight altitude that is too high or too low. The image information collected by the drone at a preset altitude is further analyzed to extract the crop type and possible abnormal planting conditions, and generate an early warning. The image information obtained at a reasonable altitude has greater clarity and coverage, and combined with image recognition technology, it can more efficiently detect creeping crops or other abnormal planting phenomena in the ridges, thereby improving inspection efficiency.

[0073] It is understandable that the drone sets the flight altitude according to the average height of tall crops, which can present richer details in the image. For example, in a 2-meter-high corn field, if the drone is set at a height of 2.5 meters for shooting, it can effectively separate the upper area of ​​the corn plants while keeping the bottom of the ridge clear. The rotor airflow at the optimal height can have a moderate separation effect on tall crops, exposing hidden low crops (such as short-stemmed cash crops). For example, in a corn field, creeping watermelon or strawberry plants will appear due to airflow separation, which helps to identify hidden illegal plantings. After the drone is highly optimized, unnecessary multiple shots and height adjustments can be reduced, making farmland inspections more efficient. Reasonable flight altitude ensures the coverage and image clarity of the inspection, which helps to quickly identify abnormal conditions in the farmland.

[0074] In some examples, this also includes:

[0075] The pitch angle, roll angle and yaw angle of the UAV when performing a flight shooting mission are determined based on the farmland image information, so that the rotor airflow has a lateral component and can separate adjacent tall crops to both sides.

[0076] In some examples, determining the pitch angle, roll angle, and yaw angle of the drone when performing a flight shooting mission based on the farmland image information includes:

[0077] The Hough transform image processing algorithm is used to extract the direction vector of the crop row from the farmland image information. ;

[0078] According to the projection angle of the direction vector in the drone coordinate system, the pitch angle is set so that the camera can best look down at the crop;

[0079] Determine the roll angle based on the spacing and direction vector of the furrows , so that the rotor airflow acts vertically between the crop rows, where , Indicates the degree of inclination of the crop row;

[0080] The yaw angle is set parallel to the heading vector so that the drone's forward direction always remains on the center line of the crop row.

[0081] For example, vector projection and trigonometric functions are used to calculate the attitude angle to ensure that the rotor airflow is aligned with the gap between crop rows. The direction vector is updated in real time, and the attitude angle is adjusted according to the new direction. Since the rotor airflow is always perpendicular to the crop row, it can better separate tall crops and reduce omissions. Flying along the direction vector, the attitude of the drone remains stable, effectively avoiding frequent adjustments due to changes in the direction of the crop row.

[0082] In some examples, the farmland image information is 3D depth image information of the farmland acquired by a depth camera, and the pitch angle, roll angle, and yaw angle of the drone when performing the flight shooting task based on the farmland image information include:

[0083] Mapping each pixel in the 3D depth image information to an actual height and spatial position;

[0084] Segment and analyze 3D depth images using a convolutional neural network model to identify ridge edges, crop height distribution, and gaps;

[0085] Use the distance information in the 3D depth image to calculate the pitch, roll, and yaw angles required by the drone.

[0086] For example, the model analyzes the crop gaps in each frame of the depth map to ensure that the camera maintains the optimal pitch angle within the coverage area. Based on the spacing between adjacent furrows and crops, the depth information model adjusts the roll angle to ensure the best direction of the rotor airflow. The model extracts the direction of the crop row and dynamically adjusts the yaw angle to move the drone along the direction of the crop row. As a result, through deep image analysis, the drone's attitude adjustment is more accurate, especially in plots with large changes in crop height or uneven terrain.

[0087] In some examples, this also includes:

[0088] The image analysis results are fed into the PID controller for feedback to adjust the posture, so that the drone maintains the optimal posture during the entire inspection process. As a result, the feedback mechanism can adapt to the farmland terrain and crop distribution and automatically optimize the drone's posture.

[0089] The above describes the whole process management method of high-standard farmland construction in the embodiment of the present application. The following describes the whole process management system of high-standard farmland construction in the embodiment of the present application.

[0090] See also Figure 2 In the embodiments of the present application, an embodiment of a management system for the whole process of high-standard farmland construction is described, which may include:

[0091] Design unit 201, used to obtain the construction design phase information of high-standard farmland on the high-standard farmland construction whole process management platform side;

[0092] The collection unit 202 is used to obtain the construction image information with the standing point and azimuth during the construction phase of the high-standard farmland construction, as well as the construction image information taken by the drone, so as to synchronize the construction image information to the high-standard farmland construction whole process management platform side;

[0093] The supervision unit 203 is used for the project management user end to obtain the construction image information and the construction design phase information associated with the construction image information through the high-standard farmland construction full process management platform during the construction and acceptance stage, so as to supervise the construction process by comparing and analyzing the construction image information and the construction design phase information;

[0094] The acquisition unit 204 is used to acquire farmland image information of the high-standard farmland in the maintenance stage through the drone, and analyze the crop types of food crops planted in the high-standard farmland based on the image information, wherein the crop types include tall crops, short crops and creeping crops;

[0095] The analyzing unit 205 is used to control the UAV to perform the flight shooting task at a preset attitude and a preset flight altitude when determining that the crop type is a tall crop, and the rotor airflow direction associated with the preset attitude is the airflow direction for separating adjacent tall crops;

[0096] The inspection unit 206 is used to extract the inspection image information collected by the drone after the adjacent tall crops are separated in the direction of the rotor airflow, so as to generate a farmland management warning message associated with the high-standard farmland when economic crops exist in the inspection image information.

[0097] In summary, the high-standard farmland construction full-process management system provided by the above-mentioned embodiment obtains the construction design stage information of the high-standard farmland on the high-standard farmland construction full-process management platform side; obtains the construction image information with standing points and azimuths in the construction stage of the high-standard farmland construction, as well as the construction image information taken by drones, so as to synchronize the construction image information to the high-standard farmland construction full-process management platform side; the project management user end obtains the construction image information and the construction design stage information associated with the construction image information through the high-standard farmland construction full-process management platform side during the construction and acceptance stages, so as to supervise the construction process by comparing and analyzing the construction image information and the construction design stage information; through drones The farmland image information of the high-standard farmland in the maintenance stage is obtained, and the crop types of the food crops planted in the high-standard farmland are analyzed based on the image information, and the crop types include tall crops, short crops and creeping crops; when it is determined that the crop type is a tall crop, the UAV is controlled to perform a flight shooting task with a preset attitude and a preset flight altitude, and the rotor airflow direction associated with the preset attitude is the airflow direction for separating adjacent tall crops; the inspection image information collected by the UAV after separating the adjacent tall crops in the rotor airflow direction is extracted, so as to generate a farmland management warning message associated with the high-standard farmland when there are economic crops in the inspection image information. Thus, efficient inspection of high-standard farmland can be achieved through UAVs and image recognition technology. For example, in a tall corn field, the UAV can identify short economic crops (such as watermelons or strawberries) hidden in the field to ensure that the high-standard farmland meets the prescribed food crop planting requirements. The airflow of the UAV rotor separates tall crops, increasing the probability of short or creeping crops being discovered. For example, if a farmer secretly plants strawberries in a corn field, airflow separation can reveal the red fruits of the strawberry plants, making it easier to identify and collect evidence. During long-term inspections, the system can record the inspection results to form historical data for further analysis of the planting conditions and violation tendencies of high-standard farmland.

[0098] above Figure 2 The high-standard farmland construction whole process management system in the embodiment of the present application is described from the perspective of modular functional entities. The high-standard farmland construction whole process management system in the embodiment of the present application is described in detail from the perspective of hardware processing. Please refer to Figure 3 , an embodiment of the high-standard farmland construction whole process management system 300 in the embodiment of the present application includes:

[0099] An input device 301, an output device 302, a processor 303 and a memory 304, wherein the number of the processor 303 can be one or more. Figure 3In some embodiments of the present application, the input device 301, the output device 302, the processor 303 and the memory 304 may be connected via a bus or other means, wherein: Figure 3 The example of connecting through bus is taken in the following.

[0100] Wherein, by calling the operation instruction stored in the memory 304, the processor 303 is used to perform the following steps:

[0101] Acquiring farmland image information of high-standard farmland in the maintenance stage by using a drone, and analyzing the crop types of food crops planted in the high-standard farmland based on the image information, wherein the crop types include tall-stalk crops, short-stalk crops, and creeping crops;

[0102] When it is determined that the crop type is a tall crop, the UAV is controlled to perform a flight shooting task at a preset attitude and a preset flight altitude, and the rotor airflow direction associated with the preset attitude is the airflow direction for separating adjacent tall crops;

[0103] The inspection image information collected by the UAV after separating the adjacent tall crops in the direction of the rotor airflow is extracted, so as to generate a farmland management warning message associated with the high-standard farmland when economic crops exist in the inspection image information.

[0104] By calling the operation instructions stored in the memory 304, the processor 303 is also used to execute Figure 1 Any method in the corresponding embodiment.

[0105] See also Figure 4 , Figure 4 A schematic diagram of an embodiment of an electronic device provided in an embodiment of the present application.

[0106] like Figure 4 As shown, an embodiment of the present application provides an electronic device 400, including an electronic device memory 410, an electronic device processor 420, and a computer program 411 stored in the electronic device memory 410 and executable on the electronic device processor 420. When the electronic device processor 420 executes the computer program 411, the following steps are implemented:

[0107] Acquiring farmland image information of high-standard farmland in the maintenance stage by using a drone, and analyzing the crop types of food crops planted in the high-standard farmland based on the image information, wherein the crop types include tall-stalk crops, short-stalk crops, and creeping crops;

[0108] When it is determined that the crop type is a tall crop, the UAV is controlled to perform a flight shooting task at a preset attitude and a preset flight altitude, and the rotor airflow direction associated with the preset attitude is the airflow direction for separating adjacent tall crops;

[0109] The inspection image information collected by the UAV after separating the adjacent tall crops in the direction of the rotor airflow is extracted, so as to generate a farmland management warning message associated with the high-standard farmland when economic crops exist in the inspection image information.

[0110] In the specific implementation process, when the electronic device processor 420 executes the computer program 411, it can achieve Figure 1 Any implementation manner in the corresponding embodiments.

[0111] Since the electronic device introduced in this embodiment is a device used to implement a full-process management system for high-standard farmland construction in the embodiment of the present application, based on the method introduced in the embodiment of the present application, technical personnel in this field can understand the specific implementation mode of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of the present application is not introduced in detail here. As long as the equipment used by technical personnel in this field to implement the method in the embodiment of the present application is within the scope of protection of this application.

[0112] See also Figure 5 , Figure 5 A schematic diagram of an embodiment of a computer-readable storage medium provided in an embodiment of the present application.

[0113] like Figure 5 As shown, this embodiment provides a computer-readable storage medium 500, on which a target computer program 511 is stored. When the target computer program 511 is executed by a processor, the following steps are implemented:

[0114] Obtain the construction and design phase information of high-standard farmland on the high-standard farmland construction full-process management platform;

[0115] Acquire construction image information with standing points and azimuths during the construction phase of high-standard farmland construction, as well as construction image information taken by drones, so as to synchronize the construction image information to the high-standard farmland construction full-process management platform;

[0116] During the construction and acceptance phases, the project management user end obtains the construction image information and the construction design phase information associated with the construction image information through the high-standard farmland construction full-process management platform, so as to supervise the construction process by comparing and analyzing the construction image information and the construction design phase information;

[0117] Acquiring farmland image information of high-standard farmland in the maintenance stage by using a drone, and analyzing the crop types of food crops planted in the high-standard farmland based on the image information, wherein the crop types include tall-stalk crops, short-stalk crops, and creeping crops;

[0118] When it is determined that the crop type is a tall crop, the UAV is controlled to perform a flight shooting task at a preset attitude and a preset flight altitude, and the rotor airflow direction associated with the preset attitude is the airflow direction for separating adjacent tall crops;

[0119] The inspection image information collected by the UAV after separating the adjacent tall crops in the direction of the rotor airflow is extracted, so as to generate a farmland management warning message associated with the high-standard farmland when economic crops exist in the inspection image information.

[0120] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, a computer, a server, or a data center to another website site, a computer, a server, or a data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can store or a data storage device such as a server or a data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid state disk (SSD)), etc.

[0121] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0122] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0123] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0124] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0125] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0126] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for managing the entire process of high-standard farmland construction, characterized in that: include: Obtain information on the construction and design phase of high-standard farmland on the high-standard farmland construction full-process management platform; Acquire construction image information with standing points and azimuths during the construction phase of high-standard farmland construction, as well as construction image information taken by drones, and synchronize the construction image information to the high-standard farmland construction full-process management platform; During the construction and acceptance phases, the project management user end obtains construction image information and construction design phase information associated with the construction image information through the high-standard farmland construction full-process management platform, so as to supervise the construction process by comparing and analyzing the construction image information and the construction design phase information; acquiring farmland image information of high-standard farmland in a maintenance phase by means of a drone, and analyzing the crop types of food crops planted in the high-standard farmland based on the image information, wherein the crop types include tall crops, short crops, and creeping crops; When it is determined that the crop type is tall crops, controlling the UAV to perform a flight photography mission at a preset attitude and a preset flight altitude, wherein the rotor airflow direction associated with the preset attitude is an airflow direction for separating adjacent tall crops; The inspection image information collected by the UAV after separating the adjacent tall crops in the direction of the rotor airflow is extracted, so as to generate a project management user-side warning message associated with the high-standard farmland when low economic crops exist in the inspection image information.

2. The method according to claim 1, characterized in that Also includes: Acquiring the theoretical ridge position of the tall crop through the farmland image information; A flight path for the flight shooting mission is planned based on the theoretical ridge position.

3. The method according to claim 1, characterized in that Also includes: Obtaining the average height of the tall crops through the farmland image information; A preset flight altitude for the flight photography mission is determined based on the average altitude.

4. The method according to claim 1, wherein Also includes: The pitch angle, roll angle and yaw angle of the UAV are determined based on the farmland image information when performing a flight shooting mission, so that the rotor airflow has a lateral component to separate adjacent tall crops to both sides.

5. The method according to claim 4, characterized in that The determining, based on the farmland image information, the pitch angle, roll angle, and yaw angle of the UAV when performing the flight shooting mission includes: Using the Hough transform image processing algorithm, the direction vector of the crop row is extracted from the farmland image information. ; According to the projection angle of the direction vector in the drone coordinate system, the pitch angle is set so that the camera can best look down at the crops; Determine the roll angle based on the furrow spacing and direction vector So that the rotor airflow acts vertically between the crop rows, , Indicates the degree of inclination of the crop row; Set the yaw angle parallel to the heading vector so that the drone's forward direction always remains in the center line of the crop row.

6. The method according to claim 4, characterized in that The farmland image information is 3D depth image information of the farmland acquired by a depth camera, and the determining of the pitch angle, roll angle, and yaw angle of the drone when performing the flight shooting mission based on the farmland image information includes: Mapping each pixel in the 3D depth image information to an actual height and spatial position; Segment and analyze 3D depth images using a convolutional neural network model to identify ridge edges, crop height distribution, and gaps. The distance information in the 3D depth image is used to calculate the pitch, roll, and yaw angles required by the drone.

7. The method according to claim 5 or 6, characterized in that Also includes: The image analysis results are input into the PID controller for feedback to adjust the posture so that the UAV maintains the optimal posture during the entire inspection process.

8. A high-standard farmland construction whole process management system, characterized by: The system comprises: The design unit is used to obtain the construction design phase information of high-standard farmland on the high-standard farmland construction full-process management platform; The acquisition unit is used to obtain construction image information with standing points and azimuths during the construction phase of high-standard farmland construction, as well as construction image information taken by drones, so as to synchronize the construction image information to the high-standard farmland construction full-process management platform; A supervision unit is used for the project management user end to obtain construction image information and construction design phase information associated with the construction image information through the high-standard farmland construction full-process management platform during the construction and acceptance stages, so as to supervise the construction process by comparing and analyzing the construction image information and the construction design phase information; an acquisition unit, configured to acquire farmland image information of the high-standard farmland during the maintenance phase by using a drone, and analyze the crop types of food crops planted in the high-standard farmland based on the image information, wherein the crop types include tall crops, short crops, and creeping crops; an analyzing unit configured to, upon determining that the crop type is a tall crop, control the UAV to perform a flight photography mission at a preset attitude and a preset flight altitude, wherein the rotor airflow direction associated with the preset attitude is an airflow direction for separating adjacent tall crops; The inspection unit is used to extract the inspection image information collected by the drone after the adjacent tall crops are separated in the direction of the rotor airflow, so as to generate a farmland management warning message associated with the high-standard farmland when low economic crops exist in the inspection image information.

9. An electronic device, characterized in that: The electronic device includes at least one processor and at least one memory connected to the processor, wherein the processor is used to call program instructions in the memory to execute the full-process management method for high-standard farmland construction as described in any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium includes a stored program, wherein, when the program is running, the device where the storage medium is located is controlled to execute the high-standard farmland construction full-process management method according to any one of claims 1 to 7.

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