Environment monitoring optimization method and system for plant growth

Abstract

The invention discloses an environment monitoring optimization method and system for plant growth, and relates to the technical field of environment monitoring, and the method comprises the steps: recognizing the canopy contour of each plant individual in a canopy distribution image, and calling a canopy coverage area and the deployment number of environment monitoring equipment; determining a first monitoring point position based on the geometric center position and the edge distribution of the canopy coverage area, performing screening adjustment according to the spatial distance relationship between the first monitoring point position and the adjacent canopy coverage area, obtaining a target monitoring point position, and converting the target monitoring point position into a physical space coordinate; and controlling the movable monitoring equipment to move or generating installation position guide information of the fixed monitoring equipment, and completing optimized deployment of the environment monitoring points of each plant individual. The deployment position of the environment monitoring equipment is automatically determined in a plant close planting scene, so that each plant individual can be effectively monitored, and meanwhile, monitoring blind areas and monitoring redundancy caused by mutual shielding of canopies or non-uniform spatial distribution in the plant growth process are avoided.

Description

Technical Field

[0001] This application relates to the field of environmental monitoring technology, and in particular to an optimized method and system for environmental monitoring of plant growth. Background Technology

[0002] Currently, environmental monitoring of plant growth mainly involves setting up different sensors such as temperature sensors, humidity sensors, and light sensors in the planting area. Temperature sensors collect temperature data, humidity sensors collect humidity data, and light sensors collect light intensity data. Then, plant growth is regulated based on the collected temperature, humidity, and light intensity data.

[0003] There are currently two methods for determining the placement of environmental monitoring equipment within a planting area. The first method is a grid-based, evenly distributed system. The grid spacing is determined by the size of the planting area, and monitoring points are then evenly placed within this grid. The second method involves manual selection based on experience. Experienced personnel observe the plant distribution within the planting area and, based on their experience, determine which locations are representative. The monitoring equipment is then placed at these selected locations. With the first method, the fixed spacing determines the location of the monitoring points. With the second method, the experience of the personnel observing the planting area and assessing the plant distribution determines the location of the monitoring points.

[0004] However, in densely planted areas, if the canopy of one plant blocks the canopy of an adjacent plant, or if the canopies of two plants are very close together, the microenvironment around one plant will differ from that around the other. Therefore, monitoring points evenly distributed in a grid, or those selected by experienced individuals based on their expertise, do not correspond to the actual spatial location of each plant, and the environmental data collected from these monitoring points cannot reflect the state of the environment surrounding each individual plant. Summary of the Invention

[0005] In view of the aforementioned problems, this application is hereby filed.

[0006] Therefore, this application provides an environmental monitoring optimization method and system for plant growth to solve the problem of how to automatically determine the deployment location of environmental monitoring equipment in densely planted scenarios, and how to update the equipment as the plant growth status changes, so that each individual plant can be effectively monitored, while avoiding monitoring blind spots and monitoring redundancy caused by mutual shading of plant canopies or uneven spatial distribution.

[0007] To solve the above-mentioned technical problems, this application provides the following technical solution: In a first aspect, this application provides an environmental monitoring optimization method for plant growth, comprising: acquiring canopy distribution images of each planting unit in a planting area; identifying the canopy outline of each individual plant in the canopy distribution image; retrieving the canopy coverage area enclosed by the canopy outline and the number of environmental monitoring devices deployed; determining a first monitoring point based on the geometric center position and edge distribution of the canopy coverage area; filtering and adjusting the first monitoring point according to the spatial distance relationship between the first monitoring point and adjacent canopy coverage areas, combined with the number of deployments, to obtain a target monitoring point; converting the target monitoring point into physical spatial coordinates of the planting area; controlling a movable monitoring device to move to the position corresponding to the physical spatial coordinates, or generating installation location guidance information for a fixed monitoring device, thereby completing the optimized deployment of environmental monitoring points for each individual plant.

[0008] Preferably, identifying the canopy contour of each plant individual in the canopy distribution image and retrieving the canopy coverage area enclosed by the canopy contour includes: performing edge detection processing on the canopy distribution image to extract the canopy contour lines in the canopy distribution image; counting the number of canopy contour lines and determining whether the canopy contour lines are closed contour lines; and retrieving the closed area enclosed by the closed contour lines as the canopy coverage area.

[0009] Preferably, determining the first monitoring point based on the geometric center position and edge distribution of the canopy coverage area includes: extracting the vertex pixel coordinates on the canopy contour line; calculating the pixel coordinates corresponding to the geometric center position of the canopy coverage area based on the vertex pixel coordinates; determining the major axis endpoint coordinates and minor axis endpoint coordinates of the canopy coverage area; calculating the major axis distance between the major axis endpoint coordinates and the minor axis distance between the minor axis endpoint coordinates; when the difference between the major axis distance and the minor axis distance is less than the minor axis distance, using the pixel coordinates corresponding to the geometric center position as the pixel coordinates of the first monitoring point; when the difference between the major axis distance and the minor axis distance is greater than or equal to the minor axis distance, adjusting the pixel coordinates corresponding to the geometric center position to obtain the pixel coordinates of the first monitoring point.

[0010] Preferably, the step of offsetting the pixel coordinates corresponding to the geometric center position to obtain the pixel coordinates of the first monitoring point includes: calculating the distance difference between the major axis distance and the minor axis distance; determining that when the distance difference is less than the major axis distance, offsetting the pixel coordinates corresponding to the geometric center position along the minor axis direction using the ratio of the distance difference to the minor axis distance as the offset ratio; determining that when the distance difference is greater than or equal to the major axis distance, offsetting the pixel coordinates corresponding to the geometric center position along the major axis direction using the ratio of the major axis distance to the minor axis distance as the offset ratio; calculating the offset distance based on the offset ratio and the minor axis distance, completing the offset processing, and obtaining the pixel coordinates of the first monitoring point.

[0011] Preferably, the step of filtering and adjusting the first monitoring points based on the spatial distance relationship between the first monitoring point and adjacent canopy-covered areas, combined with the number of deployments, to obtain target monitoring points includes: counting the first number of the first monitoring points; calculating the regional edge distance between each canopy-covered area, identifying adjacent canopy-covered area pairs whose regional edge distance is less than the minor axis distance of the corresponding canopy-covered area, as merging region pairs; for the two first monitoring points corresponding to the two canopy-covered areas in each merging region pair, selecting one of the first monitoring points as a retained monitoring point, and counting the total number of the retained monitoring point and the first monitoring points not involved in merging; when the total number is greater than the number of environmental monitoring devices deployed, filtering the retained monitoring point and the first monitoring point not involved in merging to obtain target monitoring points.

[0012] Preferably, the step of selecting one of the two first monitoring points corresponding to the two canopy coverage areas in each mergeable region pair as the retained monitoring point includes: obtaining the number of canopy outlines of each of the two canopy coverage areas in the mergeable region pair; if the number of canopy outlines of the two canopy coverage areas is the same, obtaining the area of ​​each of the two canopy coverage areas, and selecting the first monitoring point corresponding to the canopy coverage area with the larger area value as the retained monitoring point; if the number of canopy outlines of the two canopy coverage areas is different, selecting the first monitoring point corresponding to the canopy coverage area with more canopy outlines as the retained monitoring point.

[0013] Preferably, the process of filtering the retained monitoring points and the first monitoring points not included in the merging to obtain the target monitoring points includes: dividing the planting area into multiple spatial partition grids based on the spatial range of the planting area; counting the number of retained monitoring points and the first monitoring points not included in the merging within each spatial partition grid as the number of partition points; identifying spatial partition grids with one partition point and marking the monitoring points within the corresponding spatial partition grid as mandatory monitoring points; identifying spatial partition grids with more than one partition point and marking the monitoring points within the corresponding spatial partition grid as optional monitoring points; preferentially selecting the mandatory monitoring points as target monitoring points, and selecting target monitoring points from the optional monitoring points according to the relationship between the number of environmental monitoring devices deployed and the number of mandatory monitoring points.

[0014] Preferably, selecting target monitoring points from the optional monitoring points includes: identifying the monitoring points that are reserved monitoring points among the optional monitoring points in each spatial partition grid, and counting the number of canopy coverage areas corresponding to each reserved monitoring point; identifying the monitoring points that are not included in the merging of the first monitoring points among the optional monitoring points in each spatial partition grid; for each spatial partition grid, sorting the reserved monitoring points in descending order according to the number of canopy coverage areas covered, and selecting the reserved monitoring points as target monitoring points in sequence; and selecting the first monitoring point not included in the merging as the target monitoring point based on the relationship between the number of environmental monitoring devices deployed and the number of selected target monitoring points.

[0015] Preferably, the step of converting the target monitoring point into the physical spatial coordinates of the planting area includes: acquiring the physical spatial coordinates of multiple boundary reference points of the planting area; identifying the pixel coordinates of the corresponding boundary reference points in the canopy distribution image; establishing a coordinate mapping relationship between the image coordinate system and the physical coordinate system based on the correspondence between the physical spatial coordinates of the boundary reference points and the pixel coordinates; and mapping the pixel coordinates of the target monitoring point to the physical spatial coordinates of the planting area based on the coordinate mapping relationship.

[0016] Secondly, this application also provides an environmental monitoring and optimization system for plant growth, comprising: The sensing module is used to acquire canopy distribution images of each planting unit in the planting area, identify the canopy outline of each plant individual in the canopy distribution image, and retrieve the canopy coverage area formed by the canopy outline and the number of environmental monitoring devices deployed. The planning module determines the first monitoring point based on the geometric center and edge distribution of the canopy coverage area. Based on the spatial distance relationship between the first monitoring point and the adjacent canopy coverage area, and combined with the deployment quantity, the first monitoring point is screened and adjusted to obtain the target monitoring point. The target monitoring point is then converted into the physical spatial coordinates of the planting area. The execution module is used to control the movable monitoring equipment to move to the position corresponding to the physical space coordinates, or to generate installation location guidance information for the fixed monitoring equipment, thereby completing the optimized deployment of environmental monitoring points for each plant individual.

[0017] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to perform the methods described in the first aspect of this application and various possible methods involved in the first aspect.

[0018] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the methods of the first aspect of this application and various possible aspects thereof.

[0019] Implementing this application has the following beneficial effects: This application provides an environmental monitoring optimization method and system for plant growth. The first monitoring point is determined by the geometric center and edge distribution of the canopy coverage area. Adjustments are made based on the spatial distance between adjacent canopy coverage areas. When the canopy morphology changes during plant growth, the canopy distribution image is reacquired and the target monitoring point is recalculated, ensuring that the monitoring equipment is always in the optimal position to accurately reflect the microenvironmental differences of each individual plant. Therefore, the monitoring points of this application can be updated as the plant growth status changes. Furthermore, because the determination logic of the monitoring points is based on geometric calculations rather than empirical rules, consistent results can be obtained by different operators or at different times, thereby improving the reproducibility of the monitoring scheme. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is an overall flowchart of an environmental monitoring optimization method for plant growth involved in this application; Figure 2This is a schematic diagram (a) showing the determination of the first monitoring point in the canopy coverage area of ​​an environmental monitoring optimization method for plant growth involved in this application. Figure 3 This is a schematic diagram (b) showing the determination of the first monitoring point in the canopy coverage area of ​​an environmental monitoring optimization method for plant growth involved in this application. Figure 4 This is a schematic diagram of the overall structure of an environmental monitoring and optimization system for plant growth that relates to this application; Figure 5 This is a diagram of a computer device used for environmental monitoring and optimization of plant growth, as described in this application. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0023] In one exemplary embodiment, such as Figure 1 As shown, an environmental monitoring optimization method for plant growth is provided, comprising the following steps 200 to 600. Wherein: Step 200: Obtain canopy distribution images of each planting unit in the planting area, identify the canopy outline of each individual plant in the canopy distribution image, and retrieve the canopy coverage area formed by the canopy outline and the number of environmental monitoring devices deployed.

[0024] It should be noted that in traditional plant environmental monitoring, the deployment of monitoring equipment often relies on manual on-site observation and selection, which leads to uneven coverage, omissions, low efficiency, and a high risk of errors. Therefore, this application combines canopy contour recognition to quickly determine the canopy coverage area and, based on the pre-set number of environmental monitoring equipment to be deployed, automatically determines the monitoring points.

[0025] The planting area refers to the planting rack area within a greenhouse or an open-air planting area. Each planting unit consists of potted plants placed on planting racks or individual plants planted in the soil. The canopy distribution image refers to images captured by an image acquisition device positioned above the planting area. This device can be an industrial camera, webcam, or a drone-mounted aerial camera, etc. The image acquisition device takes pictures from a top-down angle, and the canopy distribution image includes the canopy appearance of each individual plant. Environmental monitoring equipment can be temperature and humidity sensors, light intensity sensors, or mobile monitoring robots, etc. The deployment quantity of environmental monitoring equipment refers to the number preset by the user based on the actual number of available sensors or mobile devices.

[0026] In some embodiments, step 200 involves identifying the canopy outline of each individual plant in the canopy distribution image and retrieving the canopy coverage area enclosed by the canopy outline, including steps 210 to 230: Step 210: Perform edge detection processing on the canopy distribution image to extract the canopy contour lines in the canopy distribution image.

[0027] Understandably, the Canny edge detection algorithm is used to detect edge pixels in the canopy distribution image, and these edge pixels are connected to form the canopy outline. This is existing technology and will not be elaborated upon here. The canopy distribution image contains canopy images of multiple plant individuals, and edge detection processing extracts the canopy outline of each plant individual.

[0028] Step 220: Count the number of canopy contour lines and determine whether the canopy contour lines are closed contour lines.

[0029] It is not difficult to understand that the total number of canopy contour lines extracted from the canopy distribution image is counted, each canopy contour line is traversed, and it is determined whether the coordinates of the starting pixel point and the ending pixel point of the canopy contour line coincide. If they coincide, it is determined to be a closed contour line; if they do not coincide, it is determined to be a non-closed contour line.

[0030] Step 230: Select the closed area enclosed by the closed contour line as the canopy coverage area.

[0031] It's easy to understand that for canopy outlines determined to be closed, the internal region enclosed by the closed outline is extracted, and this internal region is used as the canopy coverage area of ​​the corresponding plant individual. For canopy outlines determined to be non-closed, the corresponding region is not extracted.

[0032] Preferably, steps 210 to 230 extract the canopy contour line through edge detection, determine the closure, and then retrieve the closed area as the canopy coverage area, thus avoiding calculation errors when determining monitoring points based on canopy geometric features due to incomplete canopy area extraction.

[0033] Preferably, step 200 acquires canopy distribution images and identifies the canopy outline and canopy coverage area of ​​each plant individual, providing basic data for determining monitoring points based on canopy geometric features. At the same time, it acquires the deployment constraints of environmental monitoring equipment, enabling the optimized deployment of points to be completed under actual equipment resource constraints.

[0034] Step 400: Determine the first monitoring point based on the geometric center and edge distribution of the canopy coverage area. Based on the spatial distance relationship between the first monitoring point and the adjacent canopy coverage area, and in combination with the deployment quantity, screen and adjust the first monitoring point to obtain the target monitoring point. Convert the target monitoring point into the physical spatial coordinates of the planting area.

[0035] In some embodiments, step 400 specifically includes steps 410 to 430: Step 410: Determine the first monitoring point (corresponding to the canopy coverage area) based on the geometric center location and edge distribution of the canopy coverage area.

[0036] Specifically, step 410 includes steps 411 and 412: Step 411: Extract the vertex pixel coordinates on the canopy contour line, and calculate the pixel coordinates corresponding to the geometric center of the canopy coverage area based on the vertex pixel coordinates.

[0037] It should be noted that the process involves traversing the canopy outline to obtain the coordinates of all pixels constituting the canopy outline. The average x-coordinate is calculated by averaging the x-coordinates of all pixels, and similarly, the average y-coordinate is calculated by averaging the y-coordinates of all pixels. Combining the average x-coordinates and average y-coordinates yields the pixel coordinates corresponding to the geometric center of the canopy-covered area.

[0038] Step 412: Determine the coordinates of the major axis endpoints and minor axis endpoints of the canopy coverage area, and calculate the major axis distance between the major axis endpoints and the minor axis distance between the minor axis endpoints.

[0039] It should be noted that, by traversing all pixels on the canopy contour line, calculating the distance between any two pixels, identifying the two pixels with the largest distance, and using these two pixels as the endpoints of the major axis of the canopy coverage area, the coordinates of the major axis endpoints are recorded. The major axis distance between the coordinates of the major axis endpoints is then calculated.

[0040] The direction of the line connecting the endpoints of the major axis is defined as the major axis direction. The direction perpendicular to the major axis direction is defined as the minor axis direction. The pixel coordinates of the two boundary vertices of the canopy contour line are defined along the minor axis direction and defined as the endpoint coordinates of the minor axis. The distance between the endpoint coordinates of the minor axis is calculated as the minor axis distance. The major axis distance reflects the spatial span of the canopy coverage area along its longest direction.

[0041] After determining the major axis direction, identify the two farthest pixels on the canopy contour line along a direction perpendicular to the major axis. These two farthest pixels are then taken as the minor axis endpoints of the canopy coverage area, and their coordinates are recorded. The minor axis distance between these endpoints is calculated. This minor axis distance reflects the spatial span of the canopy coverage area in the direction perpendicular to the major axis.

[0042] It should be noted that in traditional plant environmental monitoring, monitoring points are often directly set at the geometric center of the canopy coverage area, without considering the impact of canopy shape characteristics on the rationality of the monitoring point location. For canopy coverage areas with a near-circular shape, the geometric center of the canopy coverage area can well represent the environmental conditions of the entire canopy. However, for canopy coverage areas with a narrow and elongated shape, the geometric center of the canopy coverage area is often deviated from the main part of the canopy, resulting in insufficient representativeness of the monitoring data. Therefore, this application determines the shape characteristics of the canopy coverage area by calculating the major axis distance and minor axis distance, thereby determining whether it is necessary to offset and adjust the geometric center position of the canopy coverage area.

[0043] like Figure 2 The diagram (a) illustrates the determination of the first monitoring point location within the canopy-covered area, showcasing a typical scenario based on canopy shape features. The canopy contour line 101 is nearly circular. By identifying the major axis endpoint 102 and minor axis endpoint 103 on the canopy contour line 101, the major axis distance and minor axis distance are calculated. When the difference between the major axis distance and the minor axis distance is less than the minor axis distance, the canopy-covered area is determined to be nearly circular. In this case, the geometric center position 104 coincides with the first monitoring point location, requiring no offset adjustment. It should be noted that the canopy contour line 101 in the diagram is a simplified schematic representation. In actual applications, the canopy contour line extracted through edge detection is an irregular closed contour line. The major axis endpoint 102 and minor axis endpoint 103 are the farthest pixels measured on the irregular canopy contour line. The major axis distance and minor axis distance are used to quantitatively describe the shape features of the canopy-covered area, rather than treating the canopy-covered area as a regular geometric shape.

[0044] like Figure 3 As shown in Figure (b), this diagram illustrates the determination of the first monitoring point in a canopy-covered area, demonstrating a second typical scenario based on canopy shape characteristics. The canopy outline 101 is elongated. When the difference between the major axis distance and the minor axis distance is greater than or equal to the minor axis distance, the canopy-covered area is determined to be elongated. In this case, the geometric center position 105 needs to be offset. The offset distance is moved along the offset direction (referring to the direction from the geometric center position 105 to the first monitoring point 106, indicating an upward offset along the minor axis) to obtain the adjusted first monitoring point 106. The first monitoring point 106 is closer to the main body of the canopy-covered area than the geometric center position 105, and can more accurately represent the environmental conditions of the canopy-covered area, thereby improving the accuracy and effectiveness of environmental monitoring. Similarly, Figure 3 The canopy outline 101 in the diagram is represented by an ellipse. In actual applications, the canopy outline is irregular in shape. By comparing the major axis distance and the minor axis distance, it is determined whether the canopy coverage area exhibits a narrow and elongated feature, thereby determining whether offset adjustment is necessary.

[0045] Specifically, when the difference between the major axis distance and the minor axis distance is less than the minor axis distance, it indicates that the shape of the canopy coverage area is close to a circle and the canopy is evenly distributed. The pixel coordinates corresponding to the geometric center of the canopy coverage area are directly used as the pixel coordinates of the first monitoring point corresponding to the canopy coverage area.

[0046] When the difference between the major axis distance and the minor axis distance is greater than or equal to the minor axis distance, it indicates that the canopy coverage area is elongated and the canopy distribution is uneven. The pixel coordinates corresponding to the geometric center of the canopy coverage area are offset and adjusted to obtain the pixel coordinates of the first monitoring point.

[0047] It is worth mentioning that step 412, by analyzing the relationship between the difference between the major and minor axis distances and the minor axis distance, allows this application to determine the shape characteristics of the canopy coverage area. When the difference between the major and minor axis distances is less than the minor axis distance, it indicates that the length difference between the major and minor axes is small, the canopy coverage area is close to circular or elliptical, and the geometric center of the canopy coverage area can well represent the spatial position of the entire canopy. When the difference between the major and minor axis distances is greater than or equal to the minor axis distance, it indicates that the major axis is significantly longer than the minor axis, the canopy coverage area has a long and narrow shape, and the geometric center of the canopy coverage area often deviates from the main part of the canopy, requiring offset adjustments to obtain a more reasonable monitoring point.

[0048] Furthermore, the pixel coordinates corresponding to the geometric center position are offset and adjusted to obtain the pixel coordinates of the first monitoring point, including steps A1 and A2: Step A1: Calculate the distance difference between the major axis distance and the minor axis distance.

[0049] Specifically, when the distance difference is less than the major axis distance, it indicates that the canopy coverage area is of a moderately long and narrow shape. Along the minor axis direction, the pixel coordinates corresponding to the geometric center position of the canopy coverage area are offset by using the ratio of the distance difference to the minor axis distance as the offset ratio.

[0050] When the distance difference is greater than or equal to the major axis distance, it indicates that the canopy coverage area is extremely long and narrow. Along the major axis, the ratio of the major axis distance to the minor axis distance is used as the offset ratio to offset the pixel coordinates corresponding to the geometric center position.

[0051] It should be noted that for moderately elongated canopy areas, while there is a slight difference between the long and short axes, the difference is not particularly significant. This is because the main body of the canopy in moderately elongated canopy areas tends to be more concentrated along the short axis. Shifting the monitoring points along the short axis moves them closer to the main body of the canopy, thus improving the representativeness of the monitoring data. Conversely, for extremely elongated canopy areas, the long axis is significantly longer than the short axis. The main body of the canopy in extremely elongated canopy areas extends along the long axis. Shifting the monitoring points along the long axis brings them closer to the main growth area of ​​the canopy, preventing them from deviating too far from the main body of the canopy.

[0052] Step A2: Calculate the offset distance based on the offset ratio and minor axis distance, complete the offset processing, and obtain the pixel coordinates of the first monitoring point.

[0053] The offset adjustment parameter controls the magnitude of the offset processing, preventing excessive offset distance from causing the first monitoring point to exceed the canopy coverage area. In this embodiment, the offset adjustment parameter can be set to a value between 0.2 and 0.4.

[0054] When determining the offset along the minor axis, obtain the direction vector from the pixel coordinates corresponding to the geometric center of the canopy coverage area to the coordinates of the minor axis endpoint. Move the pixel coordinates corresponding to the geometric center of the canopy coverage area by the offset distance along the minor axis direction vector to complete the offset process and obtain the offset pixel coordinates. Use the offset pixel coordinates as the pixel coordinates of the first monitoring point corresponding to the canopy coverage area.

[0055] When determining the offset along the major axis, obtain the direction vector from the pixel coordinates corresponding to the geometric center of the canopy coverage area to the coordinates of the endpoint of the major axis. Move the pixel coordinates corresponding to the geometric center of the canopy coverage area by an offset distance along the major axis direction vector to complete the offset process and obtain the offset pixel coordinates. Use the offset pixel coordinates as the pixel coordinates of the first monitoring point corresponding to the canopy coverage area.

[0056] It is worth mentioning that by adjusting the offset parameters to control the offset distance, the first monitoring point after offset can still be located inside the canopy coverage area, thus avoiding the first monitoring point from falling outside the canopy coverage area and losing its monitoring significance due to excessive offset distance.

[0057] Preferably, steps A1 and A2 calculate the distance difference between the major axis and the minor axis. Based on the relationship between the distance difference and the major axis, they select to offset along the minor axis or the major axis, and calculate the offset distance according to different offset ratios to achieve precise adjustment of the geometric center position of the canopy coverage area. For elongated canopy coverage areas, this avoids the first monitoring point falling at the edge of the canopy coverage area, ensuring that the first monitoring point is located in a more representative position within the canopy coverage area. This allows the environmental data collected by the environmental monitoring equipment at the first monitoring point to more accurately reflect the microenvironmental characteristics of the entire canopy coverage area.

[0058] Preferably, step 410 solves the problem that the traditional method of uniformly using the geometric center as the monitoring point leads to unreasonable monitoring points for narrow and elongated canopies. This makes the determined first monitoring point more scientifically represent the environmental conditions of the corresponding canopy-covered area, providing reliable initial point data for the optimized deployment of monitoring points, thereby improving the scientificity and practicality of the overall environmental monitoring scheme.

[0059] Step 420: Based on the spatial distance relationship between the first monitoring point and the adjacent canopy-covered area, and in combination with the number of deployments, the first monitoring point is screened and adjusted to obtain the target monitoring point.

[0060] Specifically, step 420 includes steps 421 to 424: Step 421: Count the first number of the first monitoring point.

[0061] Traverse all canopy-covered areas in the planting area, count the total number of first monitoring points corresponding to each canopy-covered area, and obtain the first number of first monitoring points.

[0062] Step 422: Calculate the edge distance between each canopy coverage area, identify adjacent canopy coverage area pairs whose edge distance is less than the minor axis distance of the corresponding canopy coverage area, and identify them as mergeable area pairs.

[0063] Traverse all canopy-covered areas within the planting area. For any two canopy-covered areas, calculate the edge distance between their edges. This edge distance is the minimum distance between the canopy outlines of the two canopy-covered areas. The edge distance reflects the spatial separation between adjacent canopy-covered areas; a smaller edge distance indicates that the two canopy-covered areas are spatially closer.

[0064] Determine if the distance between the edges of two regions is less than the minor axis distance of the corresponding canopy coverage area. If the distance between the edges of two regions is less than the minor axis distance of the corresponding canopy coverage area, it indicates that the two canopy coverage areas are spatially close and are considered as adjacent canopy coverage area pairs. Identify all adjacent canopy coverage area pairs to obtain mergeable region pairs.

[0065] It should be noted that in traditional plant environmental monitoring, the deployment of environmental monitoring equipment often involves setting up separate monitoring points for each individual plant, without considering the spatial relationships and microenvironmental similarities between adjacent plant individuals. For spatially adjacent plant individuals, the environmental conditions across canopy coverage areas often exhibit high consistency, including microenvironmental parameters such as light intensity, temperature distribution, and humidity levels. Given a limited number of environmental monitoring devices, setting up independent monitoring points for each closely adjacent plant individual wastes monitoring resources and reduces the coverage density of monitoring equipment in other areas. Therefore, this application identifies mergeable region pairs, providing a basis for sharing monitoring points among spatially adjacent canopy coverage areas, thereby optimizing the deployment efficiency of monitoring equipment while ensuring monitoring effectiveness.

[0066] Step 423: For the two first monitoring points corresponding to the two canopy-covered areas in each mergeable area pair, select one of the first monitoring points as the retained monitoring point, and count the total number of retained monitoring points and the first monitoring points that did not participate in the merging.

[0067] Iterate through each pair of mergeable regions to obtain the two first monitoring points corresponding to the two canopy-covered areas in the pair. For each of the two first monitoring points, select one as the reserved monitoring point. The reserved monitoring point is used to represent the environmental monitoring points of the two canopy-covered areas in the pair of mergeable regions.

[0068] Identify all first monitoring points in the planting area that were not included in the merging process. These first monitoring points are those whose corresponding canopy coverage area does not belong to any merging pair. Count the total number of all retained monitoring points and all first monitoring points that were not included in the merging process.

[0069] Furthermore, in step 423, for each pair of mergeable regions, one of the two first monitoring points corresponding to the two canopy-covered areas is selected as the retained monitoring point, including steps B1 and B2: Step B1: Obtain the number of canopy outlines for each of the two canopy-covered regions in the mergeable region pair.

[0070] For the first canopy coverage area in the mergeable region pair, count the number of canopy outlines contained in the first canopy coverage area to obtain the number of canopy outlines in the first canopy coverage area. For the second canopy coverage area in the mergeable region pair, count the number of canopy outlines contained in the second canopy coverage area to obtain the number of canopy outlines in the second canopy coverage area.

[0071] The number of canopy outlines reflects the complexity of the canopy of the plant in the canopy-covered area. The more canopy outlines there are, the more complex the canopy structure of the plant is, and it may contain multiple independent canopy branches or canopy layers.

[0072] Step B2: Determine whether the number of canopy outlines in the two canopy-covered areas is the same.

[0073] When the number of canopy outlines in two canopy-covered areas is the same, the area of ​​each canopy-covered area is obtained, and the first monitoring point corresponding to the canopy-covered area with the larger area value is selected as the reserved monitoring point.

[0074] It should be noted that when the number of canopy outlines is the same in two canopy-covered regions, it indicates that the canopy complexity of the corresponding plant individuals in the two canopy-covered regions is comparable. Obtain the areas of the first and second canopy-covered regions in the mergeable region pair. Compare the area values ​​of the two canopy-covered regions and identify the canopy-covered region with the larger area value. The first monitoring point corresponding to the canopy-covered region with the larger area value is selected as the retained monitoring point.

[0075] Understandably, when two canopy cover areas are of comparable canopy complexity, the larger canopy cover area often represents larger plant individuals or a denser canopy distribution, and thus has a wider impact on the microenvironment. Using the first monitoring point corresponding to the larger canopy cover area as the retained monitoring point allows it to better represent the overall environmental characteristics of the mergeable area pair.

[0076] When two canopy coverage areas have a different number of canopy outlines, it indicates a difference in the canopy complexity of the corresponding plant individuals. By comparing the number of canopy outlines in the two canopy coverage areas, the canopy coverage area with a higher number of outlines is identified. The first monitoring point corresponding to the canopy coverage area with a higher number of outlines is designated as the retained monitoring point.

[0077] It should be noted that plants with more complex canopy structures tend to be more sensitive to environmental changes. Canopy coverage areas with a greater number of canopy outlines correspond to plants with more canopy layers or branches, and the microenvironmental gradient within the canopy is more significant. Using the first monitoring point corresponding to the canopy coverage area with the more complex canopy structure as the retained monitoring point can capture richer information on environmental changes, making the environmental data collected at the retained monitoring point more representative of the mergeable area pair.

[0078] Preferably, steps B1 and B2 involve obtaining the number and area of ​​canopy outlines for each of the two canopy-covered regions in the mergeable region pair, and determining the retained monitoring points based on the number and area of ​​canopy outlines. This allows the application to select more representative monitoring points within the mergeable region pair. For canopy-covered regions with varying canopy complexity, the application prioritizes selecting the first monitoring point corresponding to the canopy-covered region with the more complex canopy structure. For canopy-covered regions with similar canopy complexity, the application prioritizes selecting the first monitoring point corresponding to the canopy-covered region with the larger area. This ensures that the retained monitoring points more accurately reflect the overall environmental characteristics of the mergeable region pair, thereby avoiding the problem of insufficient representativeness of monitoring data caused by randomly selecting monitoring points.

[0079] Step 424: When the total number is greater than the number of environmental monitoring devices deployed, the retained monitoring points and the first monitoring points not included in the merging are screened to obtain the target monitoring points.

[0080] If the total number is less than or equal to the number of environmental monitoring devices deployed, it means that after merging the mergeable area pairs, the total number of retained monitoring points and the first monitoring points not involved in the merging meets the deployment quantity constraint for environmental monitoring devices. All retained monitoring points and all first monitoring points not involved in the merging are then designated as target monitoring points.

[0081] If the total number is greater than the number of environmental monitoring devices deployed, it means that the total number of retained monitoring points and the first monitoring points not included in the merger still exceeds the number of environmental monitoring devices deployed, and further screening of the retained monitoring points and the first monitoring points not included in the merger is required.

[0082] Specifically, step 424 involves filtering the retained monitoring points and the first monitoring points that were not included in the merging process to obtain the target monitoring points, including steps C1 to C5: Step C1: Based on the spatial extent of the planting area, divide the planting area into multiple spatial partition grids.

[0083] The spatial partition grid consists of rectangular areas of equal size within the planting area, with multiple spatial partition grids covering the entire planting area. The size of the spatial partition grid is determined based on the spatial extent of the planting area and the preset partition density, which is the number of spatial partition grids per unit area.

[0084] It is worth mentioning that by dividing the planting area into multiple spatial grids, the spatial distribution of monitoring points can be managed in a grid-like manner, ensuring the uniformity of spatial coverage of monitoring points within the planting area. The spatial grid provides a spatial reference framework for the selection of monitoring points, avoiding the problem of monitoring points being too dense in some areas and sparse in others.

[0085] Step C2: Count the number of retained monitoring points and the number of first monitoring points that did not participate in the merging within each spatial partition grid, and use this as the number of partition points.

[0086] Traverse each spatial partition grid. For each spatial partition grid, identify all retained monitoring points and all first monitoring points that were not merged within the spatial partition grid. Count the total number of retained monitoring points and first monitoring points that were not merged within the spatial partition grid, and use this total number as the number of partition points for the spatial partition grid.

[0087] The number of monitoring points in a spatial partition grid reflects the density of monitoring points within the grid. The larger the number of monitoring points in a spatial partition grid, the denser the monitoring points within the grid.

[0088] Step C3: Identify a spatial partition grid with one number of monitoring points and mark the monitoring points within the corresponding spatial partition grid as mandatory monitoring points.

[0089] Traverse each spatial partition grid and determine if the number of partition points in each spatial partition grid is one. Identify spatial partition grids with one partition point. For spatial partition grids with one partition point, obtain the monitoring points within the spatial partition grid and mark the monitoring points within the spatial partition grid as mandatory monitoring points.

[0090] It should be noted that a spatial grid with only one monitoring point contains only one monitoring point, and the planting area corresponding to the spatial grid relies solely on this single monitoring point for environmental monitoring. If the mandatory monitoring point is deleted, the planting area corresponding to the spatial grid with only one monitoring point will lose environmental monitoring coverage, resulting in monitoring blind spots. Therefore, the mandatory monitoring point must be retained to ensure the integrity of environmental monitoring coverage for each spatial grid within the planting area.

[0091] Step C4: Identify spatial partition grids with more than one partition point and mark the monitoring points within the corresponding spatial partition grids as optional monitoring points.

[0092] Traverse each spatial partition grid and determine if the number of partition points in each spatial partition grid is greater than one. Identify spatial partition grids with more than one partition point. For spatial partition grids with more than one partition point, obtain all monitoring points within the spatial partition grid and mark all monitoring points within the spatial partition grid as optional monitoring points.

[0093] It is understandable that a spatial grid with more than one monitoring point contains multiple monitoring points, and the planting area corresponding to the spatial grid has a certain degree of monitoring redundancy. During the selection process, optional monitoring points can be chosen based on the deployment constraints of environmental monitoring equipment. By selectively retaining some optional monitoring points, environmental monitoring coverage of the spatial grid can be maintained while meeting the deployment constraints.

[0094] Step C5: Prioritize the selection of mandatory monitoring points as target monitoring points. Based on the relationship between the number of environmental monitoring devices deployed and the number of mandatory monitoring points, select target monitoring points from the available monitoring points.

[0095] Count the number of all mandatory monitoring points to obtain the total number of mandatory monitoring points. Use all mandatory monitoring points as target monitoring points. Calculate the difference between the number of environmental monitoring devices deployed and the number of mandatory monitoring points to obtain the remaining deployment quantity. The remaining deployment quantity is the number of environmental monitoring devices deployed minus the number of mandatory monitoring points.

[0096] Based on the remaining deployment quantity, target monitoring points are selected from the optional monitoring points. When the remaining deployment quantity is greater than zero, it means that after retaining all mandatory monitoring points, there are still environmental monitoring devices available for deploying optional monitoring points. When the remaining deployment quantity is equal to zero, it means that the number of environmental monitoring devices deployed is exactly equal to the number of mandatory monitoring points, and no target monitoring point is selected from the optional monitoring points.

[0097] Preferably, steps C1 to C5 involve dividing the planting area into multiple spatial grids, counting the number of monitoring points within each grid, identifying mandatory and optional monitoring points, prioritizing the retention of mandatory points, and selecting optional points based on the remaining deployment capacity. This achieves the technical effect of optimizing the spatial distribution of monitoring points when the number of environmental monitoring devices is limited. Spatial grid management ensures uniform coverage of monitoring points within the planting area, preventing blind spots caused by some grids losing environmental monitoring coverage. Furthermore, the classification and selection of mandatory and optional monitoring points enables hierarchical optimization of monitoring points, improving the rationality of the monitoring point selection strategy and the utilization efficiency of monitoring resources.

[0098] It should be noted that step C5, which involves selecting the target monitoring point from the available monitoring points, includes steps C51 to C54: Step C51: Identify the monitoring points that are reserved monitoring points among the optional monitoring points in each spatial partition grid, and count the number of canopy coverage areas corresponding to each reserved monitoring point.

[0099] Traverse each spatial partition grid, and for each spatial partition grid, identify all possible monitoring points within the grid. Determine whether each possible monitoring point is a reserved monitoring point. Identify the possible monitoring points that are reserved monitoring points.

[0100] For each optional monitoring point that is a retained monitoring point, obtain the pairs of mergeable areas corresponding to the optional monitoring points, count the number of canopy-covered areas contained in the pairs of mergeable areas, and use the number of canopy-covered areas as the number of canopy-covered areas corresponding to the retained monitoring points.

[0101] The number of canopy-covered areas covered by the retained monitoring points reflects the monitoring coverage of the retained monitoring points. The more canopy-covered areas covered by the retained monitoring points, the more canopy-covered areas the retained monitoring points can represent for environmental monitoring.

[0102] Step C52: Identify the monitoring points that belong to the first monitoring point that has not been merged among the optional monitoring points in each spatial partition grid.

[0103] Traverse each spatial partition grid, and for each spatial partition grid, identify all possible monitoring points within the grid. Determine whether each possible monitoring point belongs to the first monitoring point that has not been merged. Identify the possible monitoring points that belong to the first monitoring point that has not been merged.

[0104] Step C53: For each spatial grid, sort the reserved monitoring points in descending order according to the number of canopy coverage areas, and select the reserved monitoring points as target monitoring points in sequence.

[0105] Traverse each spatial partition grid, and for each spatial partition grid, obtain all optional monitoring points that belong to the reserved monitoring points. Sort the reserved monitoring points in descending order according to the number of canopy coverage areas corresponding to each reserved monitoring point, and obtain the reserved monitoring point sorting sequence.

[0106] Based on the remaining number of deployments, select target monitoring points sequentially from the reserved monitoring point ranking sequence. When the remaining number of deployments is greater than zero, start from the first reserved monitoring point in the reserved monitoring point ranking sequence and select target monitoring points sequentially until the remaining number of deployments is reduced to zero or all reserved monitoring points in the reserved monitoring point ranking sequence have been selected.

[0107] It is worth mentioning that prioritizing the selection of monitoring sites covering a large number of canopy-covered areas maximizes the coverage efficiency of these sites within the constraint of a limited number of environmental monitoring devices. These retained monitoring sites can simultaneously represent multiple closely adjacent canopy-covered areas for environmental monitoring, reducing the total number of monitoring sites required and improving the utilization efficiency of monitoring resources.

[0108] Step C54: Based on the relationship between the number of environmental monitoring devices deployed and the number of selected target monitoring points, select the first monitoring point that was not included in the merging as the target monitoring point.

[0109] The number of selected target monitoring points is counted, including all mandatory monitoring points and the reserved monitoring points selected in step C53. The difference between the number of environmental monitoring devices deployed and the number of selected target monitoring points is calculated to obtain the remaining number of selections.

[0110] Determine if the remaining selection quantity is greater than zero. If the remaining selection quantity is greater than zero, it means that after selecting all mandatory monitoring points and some reserved monitoring points, there are still environmental monitoring devices available for deployment at the first monitoring points that were not included in the merging process.

[0111] Traverse each spatial partition grid. For each spatial partition grid, obtain all available monitoring points belonging to the first monitoring points that were not merged within the spatial partition grid. Based on the remaining selection quantity, sequentially select the first monitoring points that were not merged from the available monitoring points belonging to the first monitoring points that were not merged as target monitoring points, until the remaining selection quantity is reduced to zero or all available monitoring points belonging to the first monitoring points that were not merged have been selected.

[0112] Preferably, steps C51 to C54 identify the reserved monitoring points and the first monitoring points not included in the merging process among the optional monitoring points. Prioritizing the selection of reserved monitoring points with a larger number of canopy-covered areas, and then selecting the first monitoring points not included in the merging process based on the remaining deployment quantity, achieves the technical effect of stratified screening among the optional monitoring points. By prioritizing the selection of reserved monitoring points with a larger number of canopy-covered areas, the coverage efficiency of the monitoring points is maximized. This ensures that, given a limited number of environmental monitoring devices, the monitoring points can cover as much canopy-covered area as possible, improving the utilization rate of monitoring resources and the overall effectiveness of the monitoring scheme.

[0113] Preferably, step 420 identifies mergeable region pairs and selects retained monitoring points based on the spatial distance relationship between the first monitoring point and adjacent canopy-covered areas. Combining this with the number of environmental monitoring devices deployed, and through spatial zoning and grid management, as well as hierarchical screening of mandatory and optional monitoring points, the first monitoring point is optimized and adjusted. This solves the technical problems of unreasonable monitoring point distribution, uneven spatial coverage, and low monitoring resource utilization efficiency in traditional methods when the number of environmental monitoring devices is limited. It ensures the uniform distribution of target monitoring points within the planting area and sufficient coverage of the canopy-covered area, avoiding monitoring blind spots. Furthermore, by merging monitoring points in closely adjacent canopy-covered areas, it improves the deployment efficiency of monitoring devices, providing a complete optimization scheme for the scientific deployment of environmental monitoring points.

[0114] Step 430: Convert the target monitoring points into physical spatial coordinates of the planting area.

[0115] Specifically, step 430 includes steps 431 to 434: Step 431: Obtain the physical space coordinates of multiple boundary reference points of the planting area.

[0116] Obtain multiple boundary reference points for the planting area. These boundary reference points are feature points on the boundary of the planting area, including the four corner points or marker points on the boundary. Obtain the physical space coordinates of each boundary reference point within the planting area. These physical space coordinates are the coordinate positions of the boundary reference points in actual 3D space.

[0117] Step 432: Identify the pixel coordinates of the corresponding boundary reference points in the canopy distribution image.

[0118] Identify image feature points corresponding to the planting area boundary reference points in the canopy distribution image, and obtain the pixel coordinates of each boundary reference point in the canopy distribution image.

[0119] Step 433: Based on the correspondence between the physical space coordinates of the boundary reference points and the pixel coordinates, establish the coordinate mapping relationship between the image coordinate system and the physical coordinate system.

[0120] Based on the correspondence between the physical space coordinates of multiple boundary reference points and the pixel coordinates, a coordinate mapping relationship is established between the image coordinate system and the physical coordinate system. The coordinate mapping relationship is the transformation relationship between the pixel coordinates in the image coordinate system and the physical space coordinates in the physical coordinate system.

[0121] Step 434: Based on the coordinate mapping relationship, map the pixel coordinates of the target monitoring point to the physical spatial coordinates of the planting area.

[0122] Obtain the pixel coordinates of each target monitoring point in the canopy distribution image. Based on the coordinate mapping relationship, convert the pixel coordinates of each target monitoring point into the physical spatial coordinates of the planting area to obtain the actual deployment location of the target monitoring point in the planting area.

[0123] Preferably, steps 431 to 434 establish a coordinate mapping relationship between the image coordinate system and the physical coordinate system by obtaining the physical space coordinates and pixel coordinates of the boundary reference point, and convert the pixel coordinates of the target monitoring point into physical space coordinates, thereby realizing the coordinate transformation from image space to actual physical space and providing accurate location information for the actual deployment of environmental monitoring equipment in the planting area.

[0124] Preferably, step 400 determines the first monitoring point based on the geometric center and edge distribution of the canopy coverage area. It then identifies mergeable region pairs and selects retained monitoring points based on the spatial distance relationship between the first monitoring point and adjacent canopy coverage areas. Finally, it obtains target monitoring points through spatial partitioning and grid management, and hierarchical filtering, taking into account the number of environmental monitoring devices deployed. These target monitoring points are then converted into physical spatial coordinates of the planting area. This completes the technical solution from canopy shape feature analysis to monitoring point optimization and selection, and finally to the determination of actual deployment locations. It solves the technical problems of traditional methods, such as reliance on manual experience, unreasonable spatial distribution, and low efficiency in monitoring resource utilization. By considering canopy shape features, spatial proximity, and equipment quantity constraints, it ensures the scientific validity and rationality of monitoring points, avoids monitoring blind spots, and improves the deployment efficiency of environmental monitoring equipment and the representativeness of monitoring data.

[0125] Step 600: Control the mobile monitoring equipment to move to the position corresponding to the physical space coordinates, or generate installation location guidance information for the fixed monitoring equipment, and complete the optimized deployment of environmental monitoring points for each plant individual.

[0126] It should be noted that the type of environmental monitoring equipment needs to be determined. When the environmental monitoring equipment is determined to be a mobile monitoring device, a movement path for the mobile monitoring device is generated based on the physical spatial coordinates of the target monitoring point. The mobile monitoring device is then controlled to move to the position corresponding to the physical spatial coordinates, thus completing the deployment of the environmental monitoring point.

[0127] When the environmental monitoring equipment is determined to be a fixed monitoring device, the installation location guidance information of the fixed monitoring device is generated based on the physical spatial coordinates of the target monitoring point. The installation location guidance information includes the location identifier of the target monitoring point in the planting area and installation instructions. The installation location guidance information is sent to the management terminal to complete the deployment guidance of the environmental monitoring point.

[0128] In summary, this application achieves automated and optimized deployment of plant growth environment monitoring points, solving the technical problems of traditional methods such as reliance on manual on-site surveys for determining monitoring points, uneven point coverage, and low efficiency in monitoring resource utilization. Through canopy shape feature analysis, spatial proximity identification, and stratified screening under equipment quantity constraints, it ensures the scientific distribution of monitoring points within the planting area and sufficient coverage of the canopy coverage area, avoids the occurrence of monitoring blind spots, and improves the deployment efficiency of environmental monitoring equipment and the accuracy of monitoring data.

[0129] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0130] Based on the same inventive concept, this application also provides an environmental monitoring and optimization system for plant growth. The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the environmental monitoring and optimization system for plant growth provided below can be found in the limitations of the environmental monitoring and optimization method for plant growth described above, and will not be repeated here.

[0131] In one exemplary embodiment, such as Figure 4 As shown, an environmental monitoring and optimization system for plant growth is provided, comprising: The sensing module is used to acquire canopy distribution images of each planting unit in the planting area, identify the canopy outline of each plant individual in the canopy distribution image, and retrieve the canopy coverage area formed by the canopy outline and the number of environmental monitoring devices deployed. The planning module determines the first monitoring point based on the geometric center and edge distribution of the canopy coverage area. Based on the spatial distance relationship between the first monitoring point and the adjacent canopy coverage area, and combined with the deployment quantity, the first monitoring point is screened and adjusted to obtain the target monitoring point. The target monitoring point is then converted into the physical spatial coordinates of the planting area. The execution module is used to control the movement of mobile monitoring devices to the location corresponding to the physical space coordinates, or to generate installation location guidance information for fixed monitoring devices, thereby completing the optimized deployment of environmental monitoring points for each individual plant.

[0132] The modules in the aforementioned environmental monitoring and optimization system for plant growth can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0133] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 5As shown, the computer device includes a processor, memory, input / output interface, communication interface, display unit, and input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interface is used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When executed by the processor, the computer program implements an environmental monitoring and optimization method for plant growth. The display unit is used to form a visually visible image and can be a display screen, projection device, or virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0134] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0135] In one embodiment, a computer device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above method embodiments.

[0136] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements the steps in the above method embodiments.

[0137] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above method embodiments.

[0138] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0139] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0140] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0141] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for environmental monitoring and optimization of plant growth, characterized in that, include: Acquire canopy distribution images of each planting unit in the planting area, identify the canopy outline of each individual plant in the canopy distribution image, and retrieve the canopy coverage area formed by the canopy outline and the number of environmental monitoring devices deployed. The first monitoring point is determined based on the geometric center and edge distribution of the canopy coverage area. The first monitoring point is then screened and adjusted according to the spatial distance relationship between the first monitoring point and the adjacent canopy coverage area, combined with the number of deployments, to obtain the target monitoring point. The target monitoring point is then converted into the physical spatial coordinates of the planting area. The system controls the movement of mobile monitoring devices to the positions corresponding to the physical space coordinates, or generates installation location guidance information for fixed monitoring devices, thereby optimizing the deployment of environmental monitoring points for each plant individual.

2. The environmental monitoring and optimization method for plant growth as described in claim 1, characterized in that: The step of identifying the canopy outline of each individual plant in the canopy distribution image and retrieving the canopy coverage area enclosed by the canopy outline includes: Edge detection processing is performed on the canopy distribution image to extract the canopy contour lines in the canopy distribution image; Count the number of canopy contour lines and determine whether the canopy contour lines are closed contour lines; The closed area enclosed by the closed contour line is selected as the canopy coverage area.

3. The environmental monitoring and optimization method for plant growth as described in claim 1, characterized in that: The determination of the first monitoring point based on the geometric center and edge distribution of the canopy coverage area includes: Extract the vertex pixel coordinates on the canopy contour line, and calculate the pixel coordinates corresponding to the geometric center position of the canopy coverage area based on the vertex pixel coordinates; Determine the coordinates of the major axis endpoints and the minor axis endpoints of the canopy coverage area, and calculate the major axis distance between the major axis endpoints and the minor axis distance between the minor axis endpoints; When the difference between the major axis distance and the minor axis distance is less than the minor axis distance, the pixel coordinates corresponding to the geometric center position are taken as the pixel coordinates of the first monitoring point. When the difference between the major axis distance and the minor axis distance is greater than or equal to the minor axis distance, the pixel coordinates corresponding to the geometric center position are offset and adjusted to obtain the pixel coordinates of the first monitoring point.

4. The environmental monitoring and optimization method for plant growth as described in claim 3, characterized in that: The step of offsetting and adjusting the pixel coordinates corresponding to the geometric center position to obtain the pixel coordinates of the first monitoring point includes: Calculate the distance difference between the major axis distance and the minor axis distance; When the distance difference is determined to be less than the major axis distance, the pixel coordinates corresponding to the geometric center position are offset along the minor axis direction, using the ratio of the distance difference to the minor axis distance as the offset ratio. When the distance difference is greater than or equal to the major axis distance, the pixel coordinates corresponding to the geometric center position are offset along the major axis direction, using the ratio of the major axis distance to the minor axis distance as the offset ratio. Based on the offset ratio and the minor axis distance, the offset distance is calculated, the offset processing is completed, and the pixel coordinates of the first monitoring point are obtained.

5. The environmental monitoring and optimization method for plant growth as described in claim 1, characterized in that: The step of filtering and adjusting the first monitoring point based on the spatial distance relationship between the first monitoring point and the adjacent canopy-covered area, combined with the number of deployments, to obtain the target monitoring point includes: Count the first number of the first monitoring points; Calculate the region edge distance between each canopy coverage area, and identify adjacent canopy coverage area pairs whose region edge distance is less than the minor axis distance of the corresponding canopy coverage area as mergeable region pairs; For each pair of mergeable regions, one of the two first monitoring points corresponding to the two canopy-covered areas is selected as a retained monitoring point, and the total number of the retained monitoring point and the first monitoring points that did not participate in the merging is counted. When the total number is determined to be greater than the number of environmental monitoring devices deployed, the retained monitoring points and the first monitoring points not included in the merging are screened to obtain the target monitoring points.

6. The environmental monitoring and optimization method for plant growth as described in claim 5, characterized in that: The step of selecting one of the two first monitoring points corresponding to the two canopy-covered areas in each mergeable region pair as the retained monitoring point includes: Obtain the number of canopy outlines for each of the two canopy-covered regions in the mergeable region pair; When the number of canopy outlines in two canopy-covered areas is the same, obtain the area of ​​each of the two canopy-covered areas, and select the first monitoring point corresponding to the canopy-covered area with the larger area value as the retained monitoring point; When the number of canopy outlines differs between two canopy-covered areas, the first monitoring point corresponding to the canopy-covered area with the larger number of canopy outlines is selected as the retained monitoring point.

7. The environmental monitoring and optimization method for plant growth as described in claim 5, characterized in that: The process of filtering the retained monitoring points and the first monitoring points not included in the merging process to obtain the target monitoring points includes: Based on the spatial extent of the planting area, the planting area is divided into multiple spatial partition grids; The number of retained monitoring points and the number of first monitoring points that were not merged within each spatial partition grid is counted as the number of points in each partition. Identify a spatial partition grid with one number of partition points, and mark the monitoring points within the corresponding spatial partition grid as mandatory monitoring points; Identify spatial partition grids with more than one partition point, and mark the monitoring points within the corresponding spatial partition grids as optional monitoring points; Prioritize the selection of mandatory monitoring points as target monitoring points, and select target monitoring points from the optional monitoring points based on the relationship between the number of environmental monitoring devices deployed and the number of mandatory monitoring points.

8. The environmental monitoring and optimization method for plant growth as described in claim 7, characterized in that: Selecting a target monitoring point from the available monitoring points includes: Identify the monitoring points that are reserved monitoring points among the optional monitoring points in each spatial partition grid, and count the number of canopy coverage areas corresponding to each reserved monitoring point; Identify the monitoring points that belong to the first monitoring point that has not been merged among the optional monitoring points in each spatial partition grid; For each spatial grid, the reserved monitoring points are sorted in descending order according to the number of canopy-covered areas they cover, and the reserved monitoring points are selected as target monitoring points in sequence. Based on the relationship between the number of environmental monitoring devices deployed and the number of selected target monitoring points, the first monitoring point that was not included in the merging was selected as the target monitoring point.

9. The environmental monitoring and optimization method for plant growth as described in claim 1, characterized in that: The step of converting the target monitoring point into the physical spatial coordinates of the planting area includes: Obtain the physical space coordinates of multiple boundary reference points of the planting area; Identify the pixel coordinates of the corresponding boundary reference points in the canopy distribution image; Based on the correspondence between the physical space coordinates of the boundary reference points and the pixel coordinates, a coordinate mapping relationship between the image coordinate system and the physical coordinate system is established. Based on the coordinate mapping relationship, the pixel coordinates of the target monitoring point are mapped to the physical spatial coordinates of the planting area.

10. An environmental monitoring and optimization system for plant growth, employing the environmental monitoring and optimization method for plant growth as described in any one of claims 1 to 9, characterized in that, include: The sensing module is used to acquire canopy distribution images of each planting unit in the planting area, identify the canopy outline of each plant individual in the canopy distribution image, and retrieve the canopy coverage area formed by the canopy outline and the number of environmental monitoring devices deployed. The planning module determines the first monitoring point based on the geometric center and edge distribution of the canopy coverage area. Based on the spatial distance relationship between the first monitoring point and the adjacent canopy coverage area, and combined with the deployment quantity, the first monitoring point is screened and adjusted to obtain the target monitoring point. The target monitoring point is then converted into the physical spatial coordinates of the planting area. The execution module is used to control the movable monitoring equipment to move to the position corresponding to the physical space coordinates, or to generate installation location guidance information for the fixed monitoring equipment, thereby completing the optimized deployment of environmental monitoring points for each plant individual.

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