Real-time evaluation method for operation area and operation quality of multiple agricultural machines in same farmland plot

Abstract

The invention discloses a method for evaluating the operation area and operation quality of multiple agricultural machines in the same farmland plot in real time. The method comprises the steps of information collection, drawing of an available cultivated land plot representation graph, agricultural machine track drawing, calculation of an initialized agricultural machine track area, calculation of task completion degree and agricultural machine operation quality evaluation. According to the method, the problems of operation area measurement and operation quality evaluation when multiple agricultural machines cooperatively operate on the same farmland plot are effectively solved, and scientific operation suggestions can be provided for farmers, the operation process can be optimized and the overall benefits of agricultural production can be improved by combining accurate measurement of the real-time operation area and real-time evaluation of the operation quality.

Description

Technical Field

[0001] The invention relates to a method for evaluating the operation area and operation quality of multiple agricultural machines, and in particular to a method for real-time evaluation of the operation area and operation quality of multiple agricultural machines on the same farmland plot, and belongs to the technical field of agricultural machinery. Background Art

[0002] In today's agricultural production, mechanized operation has become a key factor in improving agricultural efficiency and reducing labor intensity. However, with the increase in the number of agricultural machinery and the expansion of farmland, the coordinated operation of multiple agricultural machinery on the same farmland plot is particularly important. In this scenario, it is crucial to accurately measure the real-time operating area of ​​each agricultural machinery in order to effectively coordinate their movement paths and avoid conflicts and cross-operations. Although traditional global positioning system (GPS) technology provides spatial positioning capabilities to a certain extent, it is not ideal for real-time operating area measurement in multi-machine collaborative operations due to its accuracy and adaptability to farmland environments. On the other hand, real-time evaluation of operation quality is also crucial to ensure good growth and high yield of farmland crops. Various factors in the operation process, such as operation speed, soil conditions, fertilizer application, etc., directly affect the growth of crops. However, most of the existing operation quality evaluation methods are based on a single data source, which makes it difficult to fully consider these complex influencing factors, limiting the comprehensive grasp of operation quality.

[0003] In this technical context, the limitations of traditional technologies are overcome, and a more accurate and comprehensive multi-agricultural machinery collaborative operation management solution is provided through the comprehensive utilization of multi-feature information. By combining advanced sensor technology and data processing algorithms, real-time operation area measurement and comprehensive operation quality assessment of multiple agricultural machinery operations in the same farmland can be achieved, providing a more intelligent and efficient solution for agricultural production, which is of great significance for promoting the improvement of agricultural mechanization level and improving production efficiency. Summary of the invention

[0004] The technical problem to be solved by the present invention is to provide a method for real-time evaluation of the operation area and operation quality of multiple agricultural machines on the same farmland plot.

[0005] In order to solve the above technical problems, the technical solutions adopted by the present invention are as follows:

[0006] A method for real-time evaluation of the operation area and operation quality of multiple agricultural machines on the same farmland plot comprises the following steps:

[0007] Step 1: Information collection: Use drones to collect the boundary points of the plot along the plot boundary. The set C = {c1(x, y), ···, c i (x,y),···,c n (x, y)}, where c i(x, y), i = 1, ..., n is the boundary point of the plot with longitude coordinate x and latitude coordinate y, n is the number of boundary points of the plot, and each plot is assigned a unique ID identification information; the boundary point set D = {d1(x, y), ···, d m (x, y)}, where d i (x, y) is the boundary point of the non-agricultural cultivated land area with longitude coordinate x and latitude coordinate y, and m is the number of boundary points of the non-agricultural cultivated land area;

[0008] Step 2: Draw a plot representation of available arable land, which consists of the following specific steps:

[0009] Step 2-1: Remove unusable plot boundary points: Use a method that combines distance and angle to clean the plot boundary points. The specific method is as follows:

[0010] Distance filtering: Calculate the boundary point c of the plot i and the plot boundary point c i+1 The distance d(c i ,c i+1 ):

[0011]

[0012] If the boundary point of the plot is c i With c i+1 The distance between them is less than the minimum distance threshold d threshold_low , or the distance is greater than the maximum distance threshold d threshold_high , then we think that c i+1 is an error point and remove it;

[0013] Angle filtering: Calculate three consecutive plot boundary points c one by one i-1 , c i , c i+1 The angle θ formed i :

[0014]

[0015] If the angle θ i Less than the angle threshold θ threshold , then the boundary point c of the plot is considered i is an error point and remove it;

[0016] Step 2-2: Draw a plot representation diagram: connect the boundary points of the plots in sequence to draw a closed figure A of the agricultural cultivated land plot, and fill it with color color_A; connect the boundary points of the non-agricultural cultivated land area in sequence to draw a closed figure B of the non-agricultural cultivated land area, and fill it with color color_B;

[0017] Step 3: Drawing of agricultural machinery trajectories, which consists of the following specific steps:

[0018] Step 3-1: Obtaining the set information of agricultural machinery trajectory points: Using GPS coordinate points to collect the agricultural machinery set M = {m1,···,m k ···,m K The trajectory of each agricultural machine in S = {S1, ···, S K ,···,S K}, where the trajectory S k Consists of more than one trajectory point;

[0019] Step 3-2: Draw the trajectory path: set a path width width, draw the trajectory of each agricultural machine according to the width width into the plot representation map, and use color color_C to represent it;

[0020] Step 4: Calculate the track area of ​​each agricultural machine one by one, which consists of the following specific steps:

[0021] Step 4-1: trajectory decomposition: traverse the trajectory points of the current agricultural machinery trajectory in order, divide the agricultural machinery trajectory into more than one non-overlapping straight line segments and arc segments, and construct a trajectory segment set car_path of the current agricultural machinery trajectory, wherein the length of the straight line segment and the arc segment does not exceed the preset length length;

[0022] Step 4-2: Overlapping path processing: assign a width width to each track segment in the track segment set car_path of the current agricultural machinery track, and extract the overlapping parts of each track segment to calculate the overlapping area;

[0023] Step 4-3: After merging the trajectory segments, deduct the overlapping parts and merge them into a complete trajectory path combined_path with a path width width and no overlap;

[0024] Step 4-4: Calculate the effective operation area of ​​the current agricultural machinery: the area in the closed figure A that does not overlap with the closed figure B is taken as the cultivated land area; calculate the area of ​​the overlap area overlap_area of ​​the complete trajectory path combined_path and the cultivated land area as the effective operation area overlap_area_value of the current agricultural machinery;

[0025] Step 4-5: The area in the cultivated area that does not overlap with the complete trajectory path combined_path is filled with color color_A to form the updated closed figure A:

[0026] Step 4 - 6: Determine whether the current agricultural machine is the last one to be processed. If so, go to Step 5; otherwise, update the next agricultural machine as the current agricultural machine and go to Step 4 - 1;

[0027] Step 5: Calculate the task completion rate: Calculate the sum S of the effective operation areas of each agricultural machine ’ and use the ratio to the complete plot area S as the task completion rate

[0028] Furthermore, the method further includes a step for evaluating the operation quality of agricultural machines:

[0029] Step 6: Determine whether the task completion rate holds, where P is a set threshold, 0 < P < 1. If so, it is considered that the task of this plot is completed; otherwise, it is considered that the operation on this plot has not been completed.

[0030] The beneficial effects of the present invention are as follows:

[0031] 1. In the present invention, the system can measure the operation areas of multiple agricultural machines on the same farmland plot in real time, thus avoiding intersections and overlaps and improving the overall efficiency of the operation. Through the evaluation of the operation quality, farmers or operators can adjust the operation strategy in a timely manner, optimize resource utilization, thereby reducing production costs and increasing the benefits of agricultural production.

[0032] 2. It realizes the real - time evaluation of the operation area and operation quality, providing a scientific basis for the management of farmland crops. By accurately measuring the operation area, the system helps farmers better plan the operation area and improves the system's ability to supervise agricultural machine operations without human intervention. At the same time, the evaluation of the operation quality enables farmers to more accurately understand the operation status of agricultural machines, discover problems in a timely manner and take measures, ensuring the quality of agricultural production.

[0033] 3. The real - time measurement and evaluation method adopted helps to improve the efficiency of agricultural data processing. By monitoring the operation status of multiple agricultural machines in real time, compared with the traditional method of manually adjusting parameters, it significantly improves the efficiency of agricultural data processing, enabling farmers to obtain personalized agricultural management solutions more quickly. Description of the Drawings

[0034] Figure 1 is a flowchart of the present invention. Detailed Embodiments

[0035] The following embodiments are used to illustrate the present invention.

[0036] Example 1

[0037] A method for real - time evaluation of the operation areas and operation quality of multiple agricultural machines on the same farmland plot includes the following steps:

[0038] Step 1: Information collection: Use drones to collect the boundary points of the plot along the plot boundary. The set C = {c1(x, y), ···, c i (x,y),···,c n (x, y)}, where c i (x, y), i = 1, ..., n is the boundary point of the plot with longitude coordinate x and latitude coordinate y, n is the number of boundary points of the plot, and each plot is assigned a unique ID identification information; the boundary point set D = {d1(x, y), ···, d m (x, y)}, where d i (x, y) is the boundary point of the non-agricultural cultivated land area with longitude coordinate x and latitude coordinate y, and m is the number of boundary points of the non-agricultural cultivated land area;

[0039] Step 2: Draw a plot representation of available arable land, which consists of the following specific steps:

[0040] Step 2-1: Remove unusable plot boundary points: Use a method that combines distance and angle to clean the plot boundary points. The specific method is as follows:

[0041] Distance filtering: Calculate the boundary point c of the plot i and the plot boundary point c i+1 The distance d(c i ,c i+1 ):

[0042]

[0043] If the boundary point of the plot is c i With c i+1 The distance between them is less than the minimum distance threshold d threshold_log , or the distance is greater than the maximum distance threshold d threshold_high , then we think that c i+1 is an error point and remove it;

[0044] Angle filtering: Calculate three consecutive plot boundary points c one by one i-1 , c i , c i+1 The angle θ formed i :

[0045]

[0046] If the angle θ i Less than the angle threshold θ thershold , then the land boundary point c is considered i is an error point and remove it;

[0047] Step 2-2: Draw a plot representation diagram: connect the boundary points of the plots in sequence to draw a closed figure A of the agricultural cultivated land plot, and fill it with color color_A; connect the boundary points of the non-agricultural cultivated land area in sequence to draw a closed figure B of the non-agricultural cultivated land area, and fill it with color color_B;

[0048] Step 3: Drawing of agricultural machinery trajectories, which consists of the following specific steps:

[0049] Step 3-1: Obtaining the set information of agricultural machinery trajectory points: Using GPS coordinate points to collect the agricultural machinery set M = {m1,···,m k ···,m K The trajectory of each agricultural machine in S = {S1, ···, S k ,···,S K}, where the trajectory S k Consists of more than one trajectory point;

[0050] Step 3-2: Draw the trajectory path: set a path width width, draw the trajectory of each agricultural machine according to the width width into the plot representation map, and use color color_C to represent it;

[0051] Step 4: Calculate the track area of ​​each agricultural machine one by one, which consists of the following specific steps:

[0052] Step 4-1: trajectory decomposition: traverse the trajectory points of the current agricultural machinery trajectory in order, divide the agricultural machinery trajectory into more than one non-overlapping straight line segments and arc segments, and construct a trajectory segment set car_path of the current agricultural machinery trajectory, wherein the length of the straight line segment and the arc segment does not exceed the preset length length;

[0053] Step 4-2: Overlapping path processing: assign a width width to each track segment in the track segment set car_path of the current agricultural machinery track, and extract the overlapping parts of each track segment to calculate the overlapping area;

[0054] Step 4-3: After merging the trajectory segments, deduct the overlapping parts and merge them into a complete trajectory path combined_path with a path width width and no overlap;

[0055] Step 4-4: Calculate the effective operation area of ​​the current agricultural machinery: Calculate the closed figure A minus the overlapping area with the closed figure B as the cultivated land area; obtain the overlapping area overlap_area of ​​the complete trajectory path combined_path and the cultivated land area, and calculate the area of ​​the overlapping area overlap_area as the effective operation area overlap_area_value of the current agricultural machinery;

[0056] Step 4-5: After deducting the overlapping area from the cultivated area, fill it with color color_A to form the updated closed figure A:

[0057] Step 4-6: Determine whether the current agricultural machine is the last one to be processed. If so, go to Step 5; otherwise, update the next agricultural machine to the current agricultural machine and go to Step 4-1.

[0058] Step 5: Calculate the task completion rate: Calculate the total sum S of the effective operation areas of each agricultural machine ’ The ratio to the area S of the complete plot is used as the task completion rate

[0059] Step 6: Evaluate the operation quality of the agricultural machine: Determine whether the task completion rate holds, where P is a set threshold, 0 < P < 1. If so, it is considered that the task of this plot is completed; otherwise, it is considered that the operation on this plot has not been completed.

[0060] In this embodiment, a drone and a GPS coordinate acquisition device are used to collect the coordinate point information of the boundary positions of agricultural land plots. The non-cultivable areas such as ponds and woods within the plot are non-agricultural cultivated areas, and the set of coordinate points of their boundary positions is D = {d1(x, y), ···, d m (x, y)}, where d i (x, y) is the coordinate point on the boundary of the non-agricultural cultivated area;

[0061] For the error points in the set of coordinate points, we can adopt a method combining distance and angle to clean these points. This method is applicable to path drawing because it considers the relative positions between points and the formed angles.

[0062] The plot representation diagram is an SVG diagram. Create an SVG file, connect the obtained plot coordinate points in sequence to obtain the closed figure A representing the agricultural cultivated land plot, fill it with color_A, and draw the coordinate points of the non-cultivable plot as the closed figure B representing the non-agricultural cultivated area in the figure and fill it with color_B; when drawing the agricultural machine trajectory path, set a path width width, draw the trajectory of the agricultural machine into the SVG diagram according to the width width and fill it with color_C.

[0063] A farm machinery track is an irregular route, and it needs to be divided into several paths with no overlapping straight line segments and arc segments to facilitate the calculation of the track area, thereby reducing the calculation error. By traversing the points on the farm machinery track in order, it is determined whether the continuous points form a straight line or an arc with a length not exceeding length, and the entire farm machinery track is divided into several segmented track sets car_path. Each small track path in the track car_path set is assigned a width width to obtain a sub-path set path_with_widths carrying width information, which is used to process path overlap and calculate the area.

[0064] Path overlap processing uses the unary_union method in the Python library Shapely to process all subpaths in the subpath set path_with_widths, calculates the area of ​​the overlapping parts only once, and merges all paths into a complete path combined_path.

[0065] Since a single plot of land can be operated by multiple agricultural machinery in batches, the operation status of each sub-operation needs to be calculated and recorded separately, and it is necessary to ensure that the routes of the two sub-tasks do not overlap and affect the area calculation. Therefore, the method of cutting the plot area and calculating it separately in batches is adopted. The specific method is as follows: the effective operating area of ​​the path of the first agricultural machinery is calculated by overlapping with the complete plot information boundaries. After this calculation, we will remove the area where the agricultural machinery is operating from the complete plot, and record the new plot information sub_boundaries after cutting the plot in the system. In the subsequent area calculation process, we only consider the overlapping part of the agricultural machinery's operating area with the new plot information, and will not continue to consider the area that has been operated. This can effectively avoid repeated operations.

[0066] At present, the technical solution of the present invention has been piloted, and a user survey has been conducted in a small range. The survey results show that user satisfaction is high, and preparations for the transformation and promotion of the results have begun. At the same time, a survey on intellectual property risk warning has been carried out.

Claims

1. A method for real-time evaluation of the operation area and operation quality of multiple agricultural machinery in the same farmland plot, characterized in that: The following steps are involved: Step 1: Information collection: Use drones to collect the boundary points of the plot along the plot boundary. The set C = {c1(x, y), ···, c i (x,y),···,c n (x, y)}, where c i (x, y), i = 1, ..., n is the boundary point of the plot with longitude coordinate x and latitude coordinate y, n is the number of boundary points of the plot, and each plot is assigned a unique ID identification information; the boundary point set D = {d1(x, y), ···, d m (x, y)}, where d i (x, y) is the boundary point of the non-agricultural cultivated land area with longitude coordinate x and latitude coordinate y, and m is the number of boundary points of the non-agricultural cultivated land area; Step 2: Draw a plot representation of available arable land, which consists of the following specific steps: Step 2-1: Remove unusable plot boundary points: Use a method that combines distance and angle to clean the plot boundary points. The specific method is as follows: Distance filtering: Calculate the boundary point c of the plot i and the plot boundary point c i+1 The distance d(c i ,c i+1 ): If the boundary point of the plot is c i With c i+1 The distance between them is less than the minimum distance threshold d threshold_low , or the distance is greater than the maximum distance threshold d threshold_high , then we think that c i+1 is an error point and remove it; Angle filtering: Calculate three consecutive plot boundary points c one by one i-1 , c i , c i+1 The angle θ formed i : If the angle θ i Less than the angle threshold θ threshold , then the land boundary point c is considered i is an error point and remove it; Step 2-2: Draw a plot representation diagram: connect the boundary points of the plots in sequence to draw a closed figure A of the agricultural cultivated land plot, and fill it with color color_A; connect the boundary points of the non-agricultural cultivated land area in sequence to draw a closed figure B of the non-agricultural cultivated land area, and fill it with color color_B; Step 3: Drawing of agricultural machinery trajectories, which consists of the following specific steps: Step 3-1: Obtaining the set information of agricultural machinery trajectory points: Using GPS coordinate points to collect the agricultural machinery set M = {m1,···,m k ···,m K The trajectory of each agricultural machine in S = {S1, ···, S k ,···,S K }, where the trajectory S k Consists of more than one trajectory point; Step 3-2: Draw the trajectory path: set a path width width, draw the trajectory of each agricultural machine according to the width width into the plot representation map, and use color color_C to represent it; Step 4: Calculate the track area of ​​each agricultural machine one by one, which consists of the following specific steps: Step 4-1: trajectory decomposition: traverse the trajectory points of the current agricultural machinery trajectory in order, divide the agricultural machinery trajectory into more than one non-overlapping straight line segments and arc segments, and construct a trajectory segment set car_path of the current agricultural machinery trajectory, wherein the length of the straight line segment and the arc segment does not exceed the preset length length; Step 4-2: Overlapping path processing: assign a width width to each track segment in the track segment set car_path of the current agricultural machinery track, and extract the overlapping parts of each track segment to calculate the overlapping area; Step 4-3: After merging the trajectory segments, deduct the overlapping parts and merge them into a complete trajectory path combined_path with a path width width and no overlap; Step 4-4: Calculate the effective operation area of ​​the current agricultural machinery: the area in the closed figure A that does not overlap with the closed figure B is taken as the cultivated land area; calculate the area of ​​the overlap area overlap_area of ​​the complete trajectory path combined_path and the cultivated land area as the effective operation area overlap_area_value of the current agricultural machinery; Step 4-5: The area in the cultivated area that does not overlap with the complete trajectory path combined_path is filled with color color_A to form the updated closed figure A: Step 4-6: Determine whether the current agricultural machine is the last agricultural machine to be processed. If so, go to step 5. Otherwise, update the next agricultural machine to the current agricultural machine and go to step 4-1. Step 5: Calculate the task completion: Calculate the effective operation area and S of each agricultural machine ’ The ratio of the area of ​​the complete plot S is taken as the task completion degree 2. The method for real-time evaluation of the operation area and operation quality of multiple agricultural machines on the same farmland plot according to claim 1 is characterized by: It also includes the agricultural machinery operation quality evaluation step 6: judging whether the task completion degree is established, where P is a set threshold, 0 < P < 1. If so, it is considered that the task of this plot is completed; otherwise, it is considered that the operation on this plot has not been completed.

Images