Three-dimensional planting field management method and system

Abstract

The invention is suitable for the technical field of three-dimensional planting management, and particularly relates to a three-dimensional planting field management method and system, and the method comprises the steps: dividing a three-dimensional agricultural planting region, cutting the planting region into a plurality of blocks, collecting the growth data of all agricultural plants through video monitoring equipment disposed in the planting region in advance, and storing the collected growth data in a database; identifying a risk point location, selecting an infrared anchor point, starting a laser generator integrated in the video monitoring equipment in advance, and projecting infrared laser to the infrared anchor point; sending a working instruction to the inspection equipment, shooting a snapshot of the planting area, reading the projection positions of the infrared anchor points, integrating all the infrared anchor points, generating an anchor point group, and positioning the real-time position of the inspection equipment when the real-time position coincides with the projection positions. By determining the management report, defective plants in three-dimensional planting can be found in time, health management of agricultural plants is enhanced, and intelligence and refinement of agricultural production are effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of three-dimensional planting management, and in particular to a three-dimensional planting field management method and system. Background Art

[0002] Three-dimensional planting refers to a multi-level and multi-dimensional three-dimensional planting method that is carried out within the same space by rationally allocating factors such as the growth levels, cycles and habits of different plants. Three-dimensional planting is widely used in agriculture, gardening, urban greening and other fields. Compared with the traditional agricultural planar planting method, that is, planting one crop in a piece of land, three-dimensional planting breaks the limitation of the "plane" and expands the use of space to the "three-dimensional structure". Different plants can be planted at different heights, realizing "multi-layer planting and diversified operations".

[0003] However, the multi-layer planting structure mentioned above limits the management personnel's activity space and management efficiency. When conducting operations such as plant observation and pest and disease detection, managers need to rely on experience and observe each plant from multiple angles for a long time, which greatly limits the management efficiency of three-dimensional planting. At the same time, during the management process, managers need to frequently use ladders or mechanical auxiliary equipment, which also greatly increases the workload.

[0004] Therefore, "how to use drones and video monitoring equipment to digitally manage three-dimensional planting fields" is the technical problem that the present invention needs to solve. Summary of the Invention

[0005] The purpose of the present invention is to provide a three-dimensional planting field management method and system to solve the problem raised in the above background technology of "how to use drones and video monitoring equipment to digitally manage three-dimensional planting fields".

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] A three-dimensional planting field management method, the method comprising:

[0008] The planting area for vertical agriculture is divided into several blocks. The video surveillance equipment pre-deployed in the planting area is used to collect growth data of all agricultural plants, identify risk points, select infrared anchor points, and activate the laser generator pre-integrated in the video surveillance equipment to project infrared lasers at the infrared anchor points.

[0009] Sending a work instruction to the inspection equipment, taking a snapshot of the planting area, reading the projected position of the infrared anchor point, integrating all the infrared anchor points to generate an anchor point group, locating the real-time position of the inspection equipment, and when the real-time position coincides with the projected position, using a nearest neighbor algorithm to select the next anchor point from the anchor point group, generating a route guide, and sending the route guide to the inspection equipment, wherein the inspection equipment includes at least a drone and an inspection vehicle;

[0010] Collect feedback data sent back by the inspection equipment, compare the feedback data with standard plant images in a preset database, obtain defect factors, wherein the defect factors include at least diseased leaves, bad spots and weed interference, define the risk points corresponding to the defect factors as target points, integrate the target points and defect factors, generate a management report, and send the management report to a preset terminal.

[0011] Furthermore, the steps of dividing the planting area of ​​the three-dimensional agriculture into a plurality of blocks and utilizing the video surveillance equipment pre-deployed in the planting area include:

[0012] Collecting a growth change graph within the planting area via the video monitoring device, and marking the blocks into the growth change graph;

[0013] A health level for each block is configured, wherein each health level corresponds to a color, and the color is marked on the growth change graph.

[0014] Furthermore, the step of collecting growth data of all agricultural plants and identifying risk points includes:

[0015] Acquiring planting parameters of agricultural plants, wherein the planting parameters include at least: crop variety and planting time;

[0016] A standard data set is constructed, a standard growth map is created, the growth data and the standard growth map are compared to obtain defective plants, and the blocks where the defective plants are located are defined as risk points.

[0017] Furthermore, the steps of sending a work instruction to the inspection device, taking a snapshot of the planting area, reading the projection position of the infrared anchor point, integrating all the infrared anchor points, and generating an anchor point group include:

[0018] In the planting area, a starting point is set, and when the inspection device reaches the starting point, the work instruction is activated;

[0019] Establish a corresponding relationship between risk points and infrared anchor points, where one risk point corresponds to at least one infrared anchor point.

[0020] Furthermore, the step of comparing the feedback data with standard plant images in a preset database to obtain defect factors includes:

[0021] Configuring a damage level for each defect factor, wherein the damage level includes at least: high, medium, and low;

[0022] The defect factors corresponding to low damage levels are defined as expected symptoms, and a comparison table consisting of expected symptoms and treatment rules is created.

[0023] Furthermore, the method further comprises:

[0024] Inserting a label generated by the damage degree into the snapshot;

[0025] Edit versioning rules based on management reports and generate version chains.

[0026] Furthermore, the method further comprises:

[0027] Reading sensor data within the planting area and establishing a mapping between the sensor data and target points;

[0028] Determine whether the sensor data is below a threshold, and if so, define abnormal data and integrate the abnormal data into a management report.

[0029] Furthermore, the system includes:

[0030] The projection module is used to divide the planting area of ​​​​three-dimensional agriculture into several blocks. Using the video surveillance equipment pre-deployed in the planting area, it collects the growth data of all agricultural plants, identifies risk points, selects infrared anchor points, and activates the laser generator pre-integrated in the video surveillance equipment to project infrared lasers at the infrared anchor points;

[0031] a sending module, configured to send work instructions to the inspection equipment, take a snapshot of the planting area, read the projected position of the infrared anchor points, integrate all the infrared anchor points to generate an anchor point group, locate the real-time position of the inspection equipment, and when the real-time position coincides with the projected position, select the next anchor point from the anchor point group using a nearest neighbor algorithm, generate route guidance, and send the route guidance to the inspection equipment, wherein the inspection equipment includes at least a drone and an inspection vehicle;

[0032] A generation module is used to collect feedback data sent back by the inspection equipment, compare the feedback data with standard plant images in a preset database, obtain defect factors, wherein the defect factors at least include: diseased leaves, bad spots and weed interference, define the risk points corresponding to the defect factors as target points, integrate the target points and defect factors, generate a management report, and send the management report to a preset terminal.

[0033] Furthermore, the projection module includes:

[0034] a marking unit, configured to collect a growth change graph within the planting area via the video monitoring device, and mark the blocks into the growth change graph;

[0035] a marking unit, configured to configure the health level of each block, wherein each health level corresponds to a color, and mark the color on the growth change graph;

[0036] An acquisition unit, configured to acquire planting parameters of agricultural plants, wherein the planting parameters include at least: crop variety and planting time;

[0037] The definition unit is used to construct a standard data set, create a standard growth map, compare the growth data and the standard growth map, obtain defective plants, and define the block where the defective plant is located as a risk point.

[0038] Furthermore, the sending module includes:

[0039] An activation unit is configured to set a starting point in the planting area, and activate the work instruction when the inspection device reaches the starting point;

[0040] The establishing unit is used to establish a corresponding relationship between risk points and infrared anchor points, where one risk point corresponds to at least one infrared anchor point.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] By dividing the planting area into several blocks, the planting area can be accurately managed, which greatly improves management efficiency. By using infrared anchor points as visual markers, the navigation stability and anti-interference ability of the inspection equipment can be greatly improved. By using inspection equipment, crops in different planting layers or at different heights can be monitored without blind spots without human intervention, thereby saving a lot of manpower while accurately collecting production data of agricultural plants, further improving management efficiency. By determining management reports, defective plants in three-dimensional planting can be discovered in time, the health management level of agricultural plants can be enhanced, and the intelligence and refinement of agricultural production can be effectively improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 A flowchart of a three-dimensional planting field management method provided by an embodiment of the present invention;

[0044] Figure 2 A block diagram of the first sub-process of the three-dimensional planting field management method provided by an embodiment of the present invention;

[0045] Figure 3 A second sub-flow chart of the three-dimensional planting field management method provided by an embodiment of the present invention;

[0046] Figure 4 A block diagram of the third sub-process of the three-dimensional planting field management method provided by an embodiment of the present invention;

[0047] Figure 5 A block diagram of the composition of the three-dimensional planting field management system provided by an embodiment of the present invention;

[0048] Figure 6 A block diagram of the composition of the projection module in the three-dimensional planting field management system provided by an embodiment of the present invention;

[0049] Figure 7 A block diagram of the composition of a sending module in a three-dimensional planting field management system provided by an embodiment of the present invention;

[0050] Figure 8 This is a block diagram of the composition of the generation module in the three-dimensional planting field management system provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0052] In Example 1, Figure 1 The implementation process of the three-dimensional planting field management method provided by the embodiment of the present invention is shown and described in detail below:

[0053] S100: Divide the planting area of ​​​​three-dimensional agriculture into several blocks, use the video surveillance equipment pre-deployed in the planting area to collect the growth data of all agricultural plants, identify risk points, and select infrared anchor points. Start the laser generator pre-integrated in the video surveillance equipment and project infrared lasers to the infrared anchor points.

[0054] Determine the planting area for vertical agriculture and divide the planting area into several blocks based on crop type, planting density, soil type, crop growth stage and water requirement. In actual life, the number of agricultural plants in each block should be less than 3, otherwise it will easily lead to information overload in the snapshot and affect management accuracy.

[0055] Deploy video surveillance equipment within the planting area to ensure that every agricultural plant in every block is covered. In practice, vertical agriculture often includes multiple layers of staggered agricultural plants, and video surveillance equipment can be deployed at different heights and angles to capture plant data at different levels. Video surveillance equipment is used to collect real-time growth data on agricultural plants, including plant height, leaf condition, and color changes. To improve plant management efficiency, growth data can be approximated. If the video surveillance equipment has a high resolution, computer vision and image processing technologies can be used to directly identify problems such as pests and diseases, water shortages, and nutrient deficiencies in agricultural plants, eliminating the need to activate patrol equipment. Blocks containing potentially abnormal agricultural plants are defined as risk points, with each risk point corresponding to an infrared anchor point pre-selected by the patrol equipment manager. A laser generator pre-integrated in the video surveillance equipment is activated to precisely project infrared laser light onto the selected infrared anchor point. Laser projection helps patrol equipment accurately locate and conduct targeted photography or monitoring.

[0056] When the inspection equipment reaches the infrared anchor point, it uses the image acquisition equipment, infrared sensors, soil detectors, etc. integrated in the inspection equipment to collect precise growth data of agricultural plants at the risk point, so as to more accurately judge the yield and growth of agricultural plants.

[0057] Furthermore, multiple groups of infrared anchor points can be set at risk points and divided into different attributes; for example, infrared anchor points can be divided into positioning anchor points and shooting anchor points, etc., so as to achieve multi-angle directional shooting at a fixed position.

[0058] S200: Send a work instruction to the inspection equipment, take a snapshot of the planting area, read the projection position of the infrared anchor point, integrate all the infrared anchor points, generate an anchor point group, locate the real-time position of the inspection equipment, and when the real-time position coincides with the projection position, use the nearest neighbor algorithm to select the next anchor point from the anchor point group, generate route guidance, and send the route guidance to the inspection equipment, wherein the inspection equipment includes at least a drone and an inspection vehicle.

[0059] Send work instructions to the inspection equipment, start the image acquisition device in the inspection equipment, quickly capture high-definition images of the planting area, generate snapshots, scan all areas within the planting area, and read the projection position of the infrared anchor point.

[0060] In this application, the infrared anchor points projected by the laser generator are used as markers to ensure that the inspection equipment can accurately locate risk points in complex environments; all infrared anchor points are integrated to generate anchor point groups, which are mainly used for precise monitoring, data collection and area management.

[0061] During the inspection process, GPS or other positioning technologies are used to locate the inspection equipment in real time. When the inspection equipment reaches the infrared anchor point, the nearest neighbor algorithm is used to calculate and select the next anchor point closest to the inspection equipment in the anchor point group, and generate route guidance with the current position as the starting point and the position of the next anchor point as the end point.

[0062] The nearest neighbor algorithm evaluates the distance between each infrared anchor point and the inspection device, selects the nearest infrared anchor point as the next anchor point, generates route guidance, and sends the route guidance to the inspection device. The inspection device performs movement operations according to the guidance and performs tasks such as image capture and data collection at all infrared anchor points.

[0063] In this application, the inspection equipment may be a drone or an inspection vehicle, or an inspection robot, etc.

[0064] S300: Collect feedback data sent back by the inspection equipment, compare the feedback data with standard plant images in a preset database, obtain defect factors, wherein the defect factors include at least diseased leaves, bad spots and weed interference, define the risk points corresponding to the defect factors as target points, integrate the target points and defect factors, generate a management report, and send the management report to a preset terminal.

[0065] The data collected by the inspection equipment is defined as feedback data. The standard plant images and feedback data stored in the preset database are compared. By analyzing the morphology, color, leaf status and other growth characteristics of the agricultural plants, the difference between the feedback data and the standard plant images is identified, and this difference is defined as a defect factor. By determining the defect factor, it is possible to accurately detect whether the agricultural plants have problems such as pests and diseases, malnutrition, water shortage, yellowing leaves or other growth abnormalities.

[0066] When a defect factor is detected, the risk point where the defect factor is located is defined as the target point, and the target point and defect factor are integrated to generate a management report. Furthermore, in addition to including the specific situation of the target point, potential problems found, the health status of the crop and the changing trend of environmental parameters, the management report should also mark the location, severity and recommended repair measures of each defect point. The generated management report will be sent to the preset terminal in real time via a wireless network or other communication methods, where the preset terminal is the management personnel terminal of the inspection equipment.

[0067] In Example 2, Figure 2 The implementation process of the three-dimensional planting field management method provided by an embodiment of the present invention is shown. The following details the steps of dividing the planting area of ​​three-dimensional agriculture and dividing it into several blocks, and using the video monitoring equipment pre-deployed in the planting area, as follows:

[0068] S101: Collecting a growth change graph within a planting area via the video monitoring device, and marking the blocks into the growth change graph.

[0069] Using video surveillance equipment, we collect growth change images of agricultural plants in the planting area. The growth change images include changes in agricultural plants at different growth stages, such as plant height, leaf color, signs of pests and diseases, and soil moisture. The agricultural plants corresponding to each block are labeled.

[0070] S102: configuring a health level for each block, wherein each health level corresponds to a color, and marking the color on a growth change graph.

[0071] According to the growth change graph, the health level of each block is determined, where each health level corresponds to a color. The corresponding color is marked on the growth change graph to intuitively display the health status of each block.

[0072] In Example 3, Figure 2 The implementation process of the three-dimensional planting field management method provided by an embodiment of the present invention is shown. The steps of collecting growth data of all agricultural plants and identifying risk points are described in detail below:

[0073] S103: Acquire planting parameters of agricultural plants, wherein the planting parameters at least include: crop variety and planting time.

[0074] Obtain the planting parameters of agricultural plants, where the planting parameters include crop variety and planting time. Crop variety refers to the specific type of crop, and planting time refers to the time from sowing to the current growth stage of the agricultural plant.

[0075] S104: constructing a standard data set, creating a standard growth map, comparing the growth data with the standard growth map, obtaining defective plants, and defining the blocks where the defective plants are located as risk points.

[0076] A large amount of existing agricultural planting data is collected, including multi-dimensional data of different crops at different growth stages (such as growth height, leaf color, root development and fruit maturity, etc.), a standard data set containing multiple crops is constructed, and a standard growth atlas is generated. The standard growth atlas is mainly used to describe the normal development characteristics of agricultural plants at different growth stages; by comparing the growth data with the standard growth atlas, defective plants are obtained. Defective plants usually show signs of slow growth, abnormal color and signs of diseases and pests, etc. The blocks where the defective plants are located are defined as risk points.

[0077] In Example 4, Figure 3The implementation process of the three-dimensional planting field management method provided by an embodiment of the present invention is shown. The following details the steps of sending a work instruction to the inspection equipment, taking a snapshot of the planting area, reading the projection position of the infrared anchor point, integrating all the infrared anchor points, and generating an anchor point group.

[0078] S201: In the planting area, a starting point is set, and when the inspection device reaches the starting point, the work instruction is activated.

[0079] In the planting area, a starting point is set, where the starting point is determined by the manager of the inspection equipment. When the inspection equipment reaches the starting point, the work instruction is activated.

[0080] S202: Establishing a correspondence between risk points and infrared anchor points, where one risk point corresponds to at least one infrared anchor point.

[0081] At the risk points, multiple infrared anchor points are selected; in actual use, the infrared anchor points can be divided into positioning anchor points and shooting anchor points, so that when the inspection equipment reaches the preset position, it can perform various tasks such as shooting and measurement.

[0082] In Example 5, Figure 4 The implementation process of the three-dimensional planting field management method provided by an embodiment of the present invention is shown. The steps of comparing the feedback data with the standard plant images in the preset database to obtain the defect factors are described in detail as follows:

[0083] S301: Configuring a damage level for each defect factor, wherein the damage level includes at least: high, medium, and low.

[0084] The corresponding degree of damage is configured based on the scope, severity and actual impact of the defect factor on crop growth. For example, the degree of damage is divided into three levels: high, medium and low, where "high" means that the defect factor poses a serious threat to the growth and yield of agricultural plants, and may cause crop death or a significant reduction in yield.

[0085] S302: Defect factors corresponding to low damage levels are defined as expected symptoms, and a comparison table consisting of expected symptoms and processing rules is created.

[0086] Find out the agricultural plants with low damage levels, define the defect factors corresponding to the agricultural plants as expected signs, query the comparison table, determine the corresponding treatment rules, and thus handle the agricultural plants in a timely manner.

[0087] For example, a small number of aphids or powdery mildew appear on agricultural plants, but the distribution area of ​​these pests and diseases is small and does not have a serious impact on the overall health of the agricultural plants; in this case, the treatment rules can be: regular spraying of low doses of organic pesticides or the use of biological control methods.

[0088] In Example 6, different from Example 1, in this embodiment of the present invention, the method further includes:

[0089] Inserting a label generated by the damage degree into the snapshot;

[0090] Edit versioning rules based on management reports and generate version chains.

[0091] In the snapshot, the damage level of each block is determined, and a tag generated by the damage level is inserted into the block; the management report is versioned according to the version recording rules, where the version recording rules can be: after each inspection, a version corresponding to the management report is generated; and the newly generated version is associated with the previous version to generate a version chain; where the version chain refers to the storage of the management report in a chain-like manner.

[0092] In Example 7, different from Example 1, in this embodiment of the present invention, the method further includes:

[0093] Reading sensor data within the planting area and establishing a mapping between the sensor data and target points;

[0094] Determine whether the sensor data is below a threshold, and if so, define abnormal data and integrate the abnormal data into a management report.

[0095] Utilize various sensing devices pre-deployed in the planting area (such as temperature and humidity sensors, soil moisture sensors, light sensors, and meteorological sensors, etc.) to collect sensor data corresponding to each target point. If the sensor data is lower than the threshold, it means that there is an abnormality in the growth environment of the agricultural plants at the target point. The abnormal data is the cause of the defects in the agricultural plants, and the abnormal data is integrated into the management report.

[0096] Figure 5 The following is a structural block diagram of a three-dimensional planting field management system provided by an embodiment of the present invention. The three-dimensional planting field management system 1 includes:

[0097] The projection module 11 is used to divide the planting area of ​​​​three-dimensional agriculture into several blocks, use the video monitoring equipment pre-deployed in the planting area to collect the growth data of all agricultural plants, identify risk points, select infrared anchor points, and start the laser generator pre-integrated in the video monitoring equipment to project infrared lasers at the infrared anchor points;

[0098] The sending module 12 is used to send work instructions to the inspection equipment, take a snapshot of the planting area, read the projected position of the infrared anchor point, integrate all the infrared anchor points to generate an anchor point group, locate the real-time position of the inspection equipment, and when the real-time position coincides with the projected position, use the nearest neighbor algorithm to select the next anchor point from the anchor point group, generate route guidance, and send the route guidance to the inspection equipment, wherein the inspection equipment at least includes a drone and an inspection vehicle;

[0099] The generation module 13 is used to collect the feedback data sent back by the inspection equipment, compare the feedback data with the standard plant images in the preset database, obtain defect factors, wherein the defect factors at least include: diseased leaves, bad spots and weed interference, define the risk points corresponding to the defect factors as target points, integrate the target points and defect factors, generate a management report, and send the management report to the preset terminal.

[0100] Figure 6 The following is a structural block diagram of a three-dimensional planting field management system provided by an embodiment of the present invention. The projection module 11 includes:

[0101] The marking unit 111 is used to collect a growth change graph in the planting area via the video monitoring device and mark the blocks in the growth change graph;

[0102] A labeling unit 112 is configured to configure a health level for each block, wherein each health level corresponds to a color, and the color is labeled in the growth change graph;

[0103] An acquisition unit 113 is configured to acquire planting parameters of agricultural plants, wherein the planting parameters include at least: crop variety and planting duration;

[0104] The definition unit 114 is used to construct a standard data set, create a standard growth map, compare the growth data with the standard growth map, obtain defective plants, and define the blocks where the defective plants are located as risk points.

[0105] Figure 7 The structure block diagram of the three-dimensional planting field management system provided by an embodiment of the present invention is shown. The sending module 12 includes:

[0106] An activation unit 121 is configured to set a starting point in the planting area and activate the work instruction when the inspection device reaches the starting point;

[0107] The establishing unit 122 is configured to establish a correspondence between risk points and infrared anchor points, wherein one risk point corresponds to at least one infrared anchor point.

[0108] Figure 8 The structure block diagram of the three-dimensional planting field management system provided by the embodiment of the present invention is shown. The generation module 13 includes:

[0109] A configuration unit 131 is configured to configure a damage level of each defect factor, wherein the damage level includes at least: high, medium, and low;

[0110] The creation unit 132 is configured to define defect factors corresponding to low damage levels as expected symptoms, and to create a comparison table consisting of expected symptoms and processing rules.

[0111] The projection module 11 is mainly used to complete step S100, the sending module 12 is mainly used to complete step S200, and the generation module 13 is mainly used to complete step S300;

[0112] The marking unit 111 is mainly used to complete step S101, the annotation unit 112 is mainly used to complete step S102, the acquisition unit 113 is mainly used to complete step S103, and the definition unit 114 is mainly used to complete step S104;

[0113] The activation unit 121 is mainly used to complete step S201, and the establishment unit 122 is mainly used to complete step S202;

[0114] The configuration unit 131 is mainly used to complete step S301, and the creation unit 132 is mainly used to complete step S302.

[0115] The technical features of the above-mentioned embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above-mentioned embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0116] The above-described embodiments merely illustrate several implementations of the present invention, and while their descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art would be able to make numerous variations and improvements without departing from the spirit of the present invention, all of which fall within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the appended claims.

[0117] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A three-dimensional planting field management method, characterized in that: The method comprises: The planting area for vertical agriculture is divided into several blocks. The video surveillance equipment pre-deployed in the planting area is used to collect growth data of all agricultural plants, identify risk points, select infrared anchor points, and activate the laser generator pre-integrated in the video surveillance equipment to project infrared lasers at the infrared anchor points. Sending a work instruction to the inspection equipment, taking a snapshot of the planting area, reading the projected position of the infrared anchor point, integrating all the infrared anchor points to generate an anchor point group, locating the real-time position of the inspection equipment, and when the real-time position coincides with the projected position, using a nearest neighbor algorithm to select the next anchor point from the anchor point group, generating a route guide, and sending the route guide to the inspection equipment, wherein the inspection equipment includes at least a drone and an inspection vehicle; Collect feedback data sent back by the inspection equipment, compare the feedback data with standard plant images in a preset database, obtain defect factors, wherein the defect factors include at least diseased leaves, bad spots and weed interference, define the risk points corresponding to the defect factors as target points, integrate the target points and defect factors, generate a management report, and send the management report to a preset terminal.

2. The three-dimensional planting field management method according to claim 1, characterized in that: The steps of dividing the planting area of ​​the three-dimensional agriculture into a plurality of blocks and using the video surveillance equipment pre-deployed in the planting area include: Collecting a growth change graph within the planting area via the video monitoring device, and marking the blocks into the growth change graph; A health level for each block is configured, wherein each health level corresponds to a color, and the color is marked on the growth change graph.

3. The three-dimensional planting field management method according to claim 2, characterized in that: The steps of collecting growth data of all agricultural plants and identifying risk points include: Acquiring planting parameters of agricultural plants, wherein the planting parameters include at least: crop variety and planting time; A standard data set is constructed, a standard growth map is created, the growth data and the standard growth map are compared to obtain defective plants, and the blocks where the defective plants are located are defined as risk points.

4. The three-dimensional planting field management method according to claim 3, characterized in that: The steps of sending a work instruction to the inspection device, taking a snapshot of the planting area, reading the projection position of the infrared anchor point, integrating all the infrared anchor points, and generating an anchor point group include: In the planting area, a starting point is set, and when the inspection device reaches the starting point, the work instruction is activated; Establish a corresponding relationship between risk points and infrared anchor points, where one risk point corresponds to at least one infrared anchor point.

5. The three-dimensional planting field management method according to claim 1, characterized in that: The step of comparing the feedback data with standard plant images in a preset database to obtain defect factors includes: Configuring a damage level for each defect factor, wherein the damage level includes at least: high, medium, and low; The defect factors corresponding to low damage levels are defined as expected symptoms, and a comparison table consisting of expected symptoms and treatment rules is created.

6. The three-dimensional planting field management method according to claim 4, characterized in that: The method further comprises: Inserting a label generated by the damage degree into the snapshot; Edit versioning rules based on management reports and generate version chains.

7. The three-dimensional planting field management method according to claim 4, characterized in that: The method further comprises: Reading sensor data within the planting area and establishing a mapping between the sensor data and target points; Determine whether the sensor data is below a threshold, and if so, define abnormal data and integrate the abnormal data into a management report.

8. A three-dimensional planting field management system, characterized in that: The system comprises: The projection module is used to divide the planting area of ​​​​three-dimensional agriculture into several blocks. Using the video surveillance equipment pre-deployed in the planting area, it collects the growth data of all agricultural plants, identifies risk points, selects infrared anchor points, and activates the laser generator pre-integrated in the video surveillance equipment to project infrared lasers at the infrared anchor points; a sending module, configured to send work instructions to the inspection equipment, take a snapshot of the planting area, read the projected position of the infrared anchor points, integrate all the infrared anchor points to generate an anchor point group, locate the real-time position of the inspection equipment, and when the real-time position coincides with the projected position, select the next anchor point from the anchor point group using a nearest neighbor algorithm, generate route guidance, and send the route guidance to the inspection equipment, wherein the inspection equipment includes at least a drone and an inspection vehicle; A generation module is used to collect feedback data sent back by the inspection equipment, compare the feedback data with standard plant images in a preset database, obtain defect factors, wherein the defect factors at least include: diseased leaves, bad spots and weed interference, define the risk points corresponding to the defect factors as target points, integrate the target points and defect factors, generate a management report, and send the management report to a preset terminal.

9. The three-dimensional planting field management system according to claim 8, characterized in that: The projection module includes: a marking unit, configured to collect a growth change graph within the planting area via the video monitoring device, and mark the blocks into the growth change graph; a marking unit, configured to configure the health level of each block, wherein each health level corresponds to a color, and mark the color on the growth change graph; an acquisition unit, configured to acquire planting parameters of agricultural plants, wherein the planting parameters include at least: crop variety and planting time; The definition unit is used to construct a standard data set, create a standard growth map, compare the growth data and the standard growth map, obtain defective plants, and define the block where the defective plant is located as a risk point.

10. The three-dimensional planting field management system according to claim 9, characterized in that: The sending module includes: An activation unit is used to set a starting point in the planting area, and activate the work instruction when the inspection device reaches the starting point; The establishing unit is used to establish a corresponding relationship between risk points and infrared anchor points, where one risk point corresponds to at least one infrared anchor point.

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