Soil moisture sensor layout method and device, electronic equipment and storage medium

Abstract

The invention relates to the technical field of chemical or physical analysis, in particular to a soil moisture sensor arrangement method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining corresponding multi-source geographic data and a target soil moisture dense observation area based on the arrangement task of a soil moisture sensor, a gateway area with stable signals is screened out in a target area, a plurality of relay points which can stably communicate and are suitable for installation are screened out, then corresponding relay paths are planned, and the installation path of the robot dog is generated by using the relay paths so as to control the robot dog to complete a layout task. And thus, detection data returned by the target soil moisture dense observation area are obtained. Therefore, the technical problems that in a mountainous area environment, the arrangement condition of the soil moisture sensor is harsh, the subjectivity of manual arrangement is high, the continuity and reliability of data return are difficult to guarantee, accurate and high-timeliness data are difficult to obtain, and the soil moisture monitoring efficiency is low in the related technology are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of chemical or physical analysis, and particularly relates to a method, device, electronic device and storage medium for arranging soil moisture sensors. Background Art

[0002] Surface soil moisture is a key variable in hydrological phenomena, climate change and energy exchange processes. Surface soil moisture in mountainous areas often plays an important role in the formation process of mountain floods. Omnidirectional and multi-level monitoring of surface soil moisture in mountainous areas is conducive to quickly obtaining the soil moisture conditions in the region, providing valuable data support for early identification and warning of mountain floods.

[0003] However, in the related art, in mountainous environments, soil moisture monitoring networks using sensors that require real-time external power supply (such as C616, etc.) often have problems such as difficult power supply, inability to be arranged over a large area, etc., resulting in low soil moisture monitoring efficiency, and it is difficult to obtain accurate and highly time-sensitive data. Moreover, manual arrangement is highly subjective, the reliability of relay links is low, the equipment maintenance cost is high, and human resources are seriously wasted, which urgently needs to be improved. Summary of the Invention

[0004] The present invention provides a method, device, electronic device and storage medium for arranging soil moisture sensors to solve the technical problems in the related art that in mountainous environments, the arrangement conditions of soil moisture sensors are harsh, and the subjectivity of manual arrangement is relatively strong, it is difficult to ensure the continuity and reliability of data transmission back, it is difficult to obtain accurate and highly time-sensitive data, and the soil moisture monitoring efficiency is low.

[0005] In a first aspect embodiment of the present invention, a method for arranging soil moisture sensors is provided, including the following steps: obtaining an arrangement task of soil moisture sensors, and obtaining multi-source geographic data of a target area and a target soil moisture intensive observation area based on the arrangement task; screening a plurality of signal areas that meet preset signal stability conditions and a plurality of candidate sensor points that meet preset installation conditions in the target area, and generating a candidate gateway location set based on the plurality of signal areas; constructing a candidate point set of the target area by combining the candidate gateway location set, the plurality of candidate sensor points and the multi-source geographic data; combining the candidate point set, the multi-source geographic data and the target soil moisture intensive observation area, screening a plurality of relay points that meet preset communication conditions in the target area, so as to plan corresponding relay paths based on the plurality of relay points; generating a corresponding installation path by using the relay path, and using the installation path to control a robotic dog to complete the arrangement task, so as to obtain soil moisture detection data transmitted back from the target soil moisture intensive observation area after the arrangement task is completed.

[0006] Optionally, in an embodiment of the present invention, constructing the candidate point set of the target area by combining the candidate gateway location set, the multiple candidate sensor points, and the multi-source geographic data includes: obtaining multiple candidate gateway points in the candidate gateway location set; performing visibility analysis on the multiple candidate gateway points and the multiple candidate sensor points by using the multi-source geographic data to obtain an analysis result; constructing a candidate point set that meets the preset visibility condition in combination with the analysis result.

[0007] Optionally, in an embodiment of the present invention, screening out multiple relay points that meet the preset communication conditions in the target area by combining the candidate point set, the multi-source geographic data, and the target soil moisture intensive observation area includes: dividing the target area into multiple power supply intensity areas based on the artificial building density data in the multi-source geographic data to respectively determine the power supply intensity of each candidate gateway point in the candidate point set; dividing the target area into multiple signal intensity areas based on the signal coverage data in the multi-source geographic data to respectively determine the signal intensity of each candidate gateway point; calculating the road accessibility of each candidate gateway point respectively based on the multi-source geographic data; calculating the slope raster data of the target area based on the multi-source geographic data; calculating the comprehensive score of each candidate gateway in combination with the power supply intensity, the signal intensity, and the road accessibility; obtaining a target gateway point based on the comprehensive score, and screening out multiple candidate sensor points in the network coverage area of the target gateway point from the candidate point set as candidate relay points; starting from the target gateway point and ending at the target soil moisture intensive observation area, determining the multiple relay points from the candidate relay points in combination with the slope raster data.

[0008] Optionally, in an embodiment of the present invention, calculating the road accessibility of each candidate gateway point respectively based on the multi-source geographic data includes: performing road network modeling on the target area based on the road layer data in the multi-source geographic data to obtain a road network model of the target area, and constructing a weighted road map of the target area in combination with the road network model and a preset road weight; calculating the road accessibility by using the weighted road map.

[0009] Optionally, in an embodiment of the present invention, planning the corresponding relay path based on the multiple relay points includes: calculating the total elevation of the multiple relay points based on the multi-source geographic data; calculating the distance and average slope between each relay point and the roads in the target area based on the multi-source geographic data; constructing a three-dimensional road-terrain coupling model of the target area based on the multi-source geographic data, and constructing a slope constraint based on the three-dimensional road-terrain coupling model and the dynamic road influence domain of the slope; constructing a multi-objective optimization function using the total elevation, the distance, and the average slope; and solving the multi-objective optimization function using the slope constraint to obtain the relay path.

[0010] Optionally, in an embodiment of the present invention, the expression of the multi-objective optimization function is: , R = 500×exp(-0.02× ), , , wherein, represents the first dynamic weight factor, represents the total elevation, represents the second dynamic weight factor, represents the distance, represents the static weight factor, represents the average slope, R represents the slope influence radius, t represents the number of the current iteration, T represents the total number of iterations.

[0011] Optionally, in an embodiment of the present invention, after planning the corresponding relay path based on the multiple relay points, it further includes: dividing the target soil moisture intensive observation area into multiple grids based on a preset density; and setting high-density area soil moisture sensors in each grid so that the sensing signals of the high-density area soil moisture sensors are transmitted back to the target gateway through the relay path.

[0012] The second aspect of the present invention provides a device for arranging soil moisture sensors, including: an acquisition module, configured to acquire the arrangement task of the soil moisture sensors, and based on the arrangement task, acquire multi-source geographic data of the target area and a target soil moisture intensive observation area; a screening module, configured to screen multiple signal areas that meet the preset signal stability condition and multiple candidate sensor points that meet the preset installation condition in the target area, and generate a candidate gateway location set based on the multiple signal areas; a construction module, configured to construct a candidate point set of the target area by combining the candidate gateway location set, the multiple candidate sensor points, and the multi-source geographic data; a planning module, configured to combine the candidate point set, the multi-source geographic data, and the target soil moisture intensive observation area, and screen multiple relay points that meet the preset communication condition in the target area, so as to plan a corresponding relay path based on the multiple relay points; an arrangement module, configured to generate a corresponding installation path by using the relay path, and use the installation path to control the robot dog to complete the arrangement task, so as to obtain the soil moisture detection data transmitted back by the target soil moisture intensive observation area after the arrangement task is completed.

[0013] Optionally, in an embodiment of the present invention, the construction module includes: an acquisition unit, configured to acquire multiple candidate gateway points in the candidate gateway location set; an analysis unit, configured to perform visibility analysis on the multiple candidate gateway points and the multiple candidate sensor points by using the multi-source geographic data to obtain an analysis result; a first construction unit, configured to construct a candidate point set that meets the preset visibility condition by combining the analysis result.

[0014] Optionally, in an embodiment of the present invention, the planning module includes: a first partitioning unit, configured to partition the target area into multiple power supply intensity areas based on the artificial building density data in the multi-source geographic data, so as to respectively determine the power supply intensity of each candidate gateway point in the candidate point set; a second partitioning unit, configured to partition the target area into multiple signal intensity areas based on the signal coverage data in the multi-source geographic data, so as to respectively determine the signal intensity of each candidate gateway point; a first calculation unit, configured to calculate the road accessibility of each candidate gateway point based on the multi-source geographic data; a second calculation unit, configured to calculate the slope raster data of the target area based on the multi-source geographic data; a third calculation unit, configured to calculate the comprehensive score of each candidate gateway in combination with the power supply intensity, the signal intensity, and the road accessibility; a screening unit, configured to obtain a target gateway point based on the comprehensive score, and screen out multiple candidate sensor points in the network coverage area of the target gateway point from the candidate point set as candidate relay points; a determination unit, configured to determine the multiple relay points from the candidate relay points with the target gateway point as the starting point and the target soil moisture intensive observation area as the ending point, in combination with the slope raster data.

[0015] Optionally, in an embodiment of the present invention, the first calculation unit includes: a construction subunit, configured to perform road network modeling on the target area based on the road layer data in the multi-source geographic data to obtain a road network model of the target area, and construct a weighted road map of the target area in combination with the road network model and a preset road weight; a calculation subunit, configured to calculate the road accessibility by using the weighted road map.

[0016] Optionally, in an embodiment of the present invention, the planning module includes: a fourth calculation unit, configured to calculate the total elevation of the multiple relay points based on the multi-source geographic data; a fifth calculation unit, configured to calculate the distance and average slope between each relay point and the road in the target area based on the multi-source geographic data; a second construction unit, configured to construct a three-dimensional road-terrain coupling model of the target area based on the multi-source geographic data, and construct a slope constraint based on the three-dimensional road-terrain coupling model and the dynamic road influence domain of the slope; a third construction unit, configured to construct a multi-objective optimization function by using the total elevation, the distance, and the average slope; a sixth calculation unit, configured to solve the multi-objective optimization function by using the slope constraint to obtain the relay path.

[0017] Optionally, in an embodiment of the present invention, the expression of the multi-objective optimization function is: , R = 500 × exp(-0.02 × ), , , wherein, represents the first dynamic weight factor, represents the total elevation, represents the second dynamic weight factor, represents the distance, represents the static weight factor, represents the average slope, R represents the slope influence radius, t represents the number of current iterations, T represents the total number of iterations.

[0018] Optionally, in an embodiment of the present invention, it further includes: a partitioning module, configured to partition the target soil moisture intensive observation area into multiple grids based on a preset density; an arrangement module, configured to set soil moisture sensors in high-density areas within each grid, so that the sensing signals of the soil moisture sensors in the high-density areas are transmitted back to the target gateway through the relay path.

[0019] An embodiment of the third aspect of the present invention provides an electronic device, including: a memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor executes the program to implement the method for arranging soil moisture sensors as described in the above embodiment.

[0020] An embodiment of the fourth aspect of the present invention provides a computer-readable storage medium, where the computer-readable storage medium stores computer instructions, and the computer instructions are used to cause the computer to execute the method for arranging soil moisture sensors as described in the above embodiment.

[0021] An embodiment of the fifth aspect of the present invention provides a computer program product, including a computer program, and when the computer program is executed, it is used to implement the method for arranging soil moisture sensors as described above.

[0022] Embodiments of the present invention can obtain multi-source geographical data of a target area and a target soil moisture intensive observation area based on the deployment task of soil moisture sensors, screen out a gateway area with stable signals in the target area, and screen out multiple relay points that can communicate stably and are suitable for installation. Then, plan the corresponding relay path, generate the installation path of the robotic dog using the relay path, control the robotic dog to complete the deployment task, so as to obtain the soil moisture detection data transmitted back from the target soil moisture intensive observation area, ensure the reliability and stability of the relay chain for the deployment of soil moisture sensors, make the transmitted data stable, accurate and highly time-sensitive, with high deployment efficiency and low cost, and be convenient for popularization and application. Thus, it solves the technical problems in the related art that in a mountainous environment, the deployment conditions of soil moisture sensors are harsh, and the subjectivity of manual deployment is strong, it is difficult to ensure the continuity and reliability of data transmission, it is difficult to obtain accurate and highly time-sensitive data, and the soil moisture monitoring efficiency is low.

[0023] Additional aspects and advantages of the present invention will be given in part in the following description, become apparent in part from the following description, or be understood through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] The above and / or additional aspects and advantages of the present invention will become apparent and easy to understand from the following description of the embodiments in conjunction with the drawings, where: Figure 1 FIG. is a flowchart of a method for deploying soil moisture sensors according to an embodiment of the present invention; Figure 2 FIG. is a schematic diagram of the principle of a method for deploying soil moisture sensors according to an embodiment of the present invention; Figure 3 FIG. is a schematic structural diagram of a device for deploying soil moisture sensors according to an embodiment of the present invention; Figure 4 FIG. is a schematic structural diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0025] The embodiments of the present invention will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements with the same or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and are intended to explain the present invention, and should not be construed as limiting the present invention.

[0026] The following describes a method, device, electronic device, and storage medium for deploying a soil moisture sensor according to an embodiment of the present invention. In view of the technical problems in the related art mentioned in the above background art, in a mountainous environment, the deployment conditions of soil moisture sensors are harsh, and the subjectivity of manual deployment is relatively strong, making it difficult to ensure the continuity and reliability of data transmission back, difficult to obtain accurate and highly time-sensitive data, and the soil moisture monitoring efficiency is relatively low. The present invention provides a method for deploying a soil moisture sensor. In this method, based on the deployment task of the soil moisture sensor, multi-source geographical data of the target area and a target soil moisture intensive observation area can be obtained. Signal-stable gateway areas are screened out within the target area, and multiple relay points that can communicate stably and are suitable for installation are screened out. Then, the corresponding relay paths are planned, and the installation paths of the robotic dog are generated using the relay paths to control the robotic dog to complete the deployment task, thereby obtaining the soil moisture detection data transmitted back from the target soil moisture intensive observation area, so as to ensure the reliability and stability of the relay chain for deploying the soil moisture sensor, making the transmitted data stable, accurate, and highly time-sensitive, with high deployment efficiency and low cost, and being convenient for popularization and application. Thus, the technical problems in the related art, in a mountainous environment, where the deployment conditions of soil moisture sensors are harsh, the subjectivity of manual deployment is relatively strong, it is difficult to ensure the continuity and reliability of data transmission back, it is difficult to obtain accurate and highly time-sensitive data, and the soil moisture monitoring efficiency is relatively low are solved.

[0027] Specifically, Figure 1 It is a flowchart of a method for deploying a soil moisture sensor provided by an embodiment of the present invention.

[0028] As Figure 1 shown, the method for deploying the soil moisture sensor includes the following steps: In step S101, obtain the deployment task of the soil moisture sensor, and based on the deployment task, obtain the multi-source geographical data of the target area and the target soil moisture intensive observation area.

[0029] In the actual execution process, an embodiment of the present invention can receive the deployment task of the soil moisture sensor. The deployment task may include the target area where the soil moisture sensor needs to be deployed and the target soil moisture intensive observation area of the target area, etc.

[0030] Obtain the multi-source geographical data of the target area, such as high-precision DEM (Digital Elevation Model) data, road layer data, network signal coverage data, etc.

[0031] In step S102, screen out multiple signal areas that meet the preset signal stability conditions and multiple candidate sensor points that meet the preset installation conditions within the target area, and generate a candidate gateway location set based on the multiple signal areas.

[0032] It is understandable that in some areas within the mountainous region, a key soil moisture monitoring network needs to be built. However, since these areas are often located deep in the mountains and there is no network signal, it is necessary to utilize the mutual relay function of the soil moisture sensors themselves to establish a relay route and establish contact with areas where there is a signal outside, so as to achieve the function of transmitting signals out in real time.

[0033] According to multi-source geographical data, embodiments of the present invention can integrate the coordinate areas within the target area that can be stably powered and have a stable network signal as candidate areas for gateways, and generate a set of candidate gateway positions.

[0034] According to multi-source geographical data, such as DEM data, embodiments of the present invention can screen out the points where soil moisture sensors cannot be installed (such as areas affected by natural disasters, areas with frequent human activities, areas with strong electromagnetic interference, low-lying waterlogged areas, etc.), and use the remaining points as candidate sensor points (candidate relay points). Among them, the installation conditions can be set by those skilled in the art according to the actual situation, and no specific limitation is made here.

[0035] In step S103, a set of candidate points for the target area is constructed by combining the set of candidate gateway positions, multiple candidate sensor points, and multi-source geographical data.

[0036] Furthermore, embodiments of the present invention can preliminarily screen the candidate gateway positions and candidate sensor points according to multi-source geographical data to construct a set of candidate points.

[0037] Optionally, in an embodiment of the present invention, constructing a set of candidate points for the target area by combining the set of candidate gateway positions, multiple candidate sensor points, and multi-source geographical data includes: obtaining multiple candidate gateway points in the set of candidate gateway positions; performing visibility analysis on the multiple candidate gateway points and multiple candidate sensor points using multi-source geographical data to obtain an analysis result; and constructing a set of candidate points that meet the preset visibility conditions in combination with the analysis result.

[0038] It is understandable that in embodiments of the present invention, the data is transmitted starting from the gateway and ending at the target intensive soil moisture observation area. In the transmission path, multiple soil moisture sensors for relay need to be set to ensure the reliability and continuity of data transmission.

[0039] Since there should be as little obstruction as possible between the gateway and the first soil moisture sensor (the first relayed soil moisture sensor), and there should also be as little obstruction as possible between soil moisture sensors to ensure smooth signal transmission. Therefore, visibility analysis is performed on the gateway candidate points in the gateway location set and each candidate sensor point in the target area, and a point set that can ensure mutual visibility is initially selected as a constraint condition for further optimization in the later stage.

[0040] For example, the embodiment of the present invention can use the three-dimensional Bresenham algorithm to detect the visibility between nodes, and define the visibility condition as follows: The elevation of all points on the connection path ≤ min(z1, z2) + 5 (unit: m), where z1 and z2 are the elevations of the two points to be tested; the embodiment of the present invention can construct a communication graph and a candidate point set including candidate gateways and candidate sensor points, and the generation rules are as follows: 1. The node spacing ≤ 1000m (conservatively estimated that the maximum straight-line relay distance between soil moisture sensors is 1000m), 2. Meet the visibility condition, 3. The accessible distance of the road ≤ 500m.

[0041] Among them, the communication graph can be used as an intermediate output to facilitate technicians to verify the relay points.

[0042] In step S104, in combination with the candidate point set, multi-source geographic data, and the target soil moisture intensive observation area, multiple relay points that meet the preset communication conditions are screened out in the target area, so as to plan the corresponding relay path based on the multiple relay points.

[0043] In the actual execution process, the embodiment of the present invention can, on the basis of the candidate point set, use multi-source geographic data (such as signal strength distribution, power supply strength distribution, etc.) and the location information of the target soil moisture intensive observation area to further screen the relay points, and then plan the relay path.

[0044] Optionally, in an embodiment of the present invention, by combining a set of candidate points, multi-source geographic data, and a target soil moisture intensive observation area, a plurality of relay points that meet the preset communication conditions are screened out in the target area, including: dividing the target area into a plurality of power supply intensity areas based on the artificial building density data in the multi-source geographic data to respectively determine the power supply intensity of each candidate gateway point in the set of candidate points; dividing the target area into a plurality of signal intensity areas based on the signal coverage data in the multi-source geographic data to respectively determine the signal intensity of each candidate gateway point; calculating the road accessibility of each candidate gateway point based on the multi-source geographic data; calculating the slope raster data of the target area based on the multi-source geographic data; calculating the comprehensive score of each candidate gateway by combining the power supply intensity, signal intensity, and road accessibility; obtaining the target gateway point based on the comprehensive score, and screening out a plurality of candidate sensor points in the network coverage area of the target gateway point from the set of candidate points as candidate relay points; taking the target gateway point as the starting point and the target soil moisture intensive observation area as the ending point, and determining a plurality of relay points from the candidate relay points in combination with the slope raster data.

[0045] For example, in an embodiment of the present invention, the Tianditu can be opened as a base map in Arcgis pro, and the mask of the area with artificial buildings inside the area can be manually extracted. According to the density of artificial buildings, the power supply intensity of the area is subjectively divided into three levels: 1, 0.75, and 0.5, that is, masks of the three levels are extracted; In an embodiment of the present invention, the APP for real-time querying of 5G coverage provided by multiple signal providers can be used to respectively draw the respective coverage situations of multiple providers in the target area. Taking three providers as an example, in an embodiment of the present invention, masks of their respective coverage states can be made. For the areas covered by all three providers, the signal intensity is set to 1, for the areas covered by only two providers, it is set to 0.67, for the areas covered by only one provider, it is set to 0.33, and for the areas without coverage, it is set to 0; In an embodiment of the present invention, the high-precision DEM data of the target area can be used, and geographical information system tools (such as Arcgis, Qgis, etc.) can be used for filling depressions to calculate the slope raster data of the target area; The road accessibility is obtained from the distance between the candidate gateway to be calculated and the nearest road and the average slope obtained from the slope raster data.

[0046] Based on the above calculation method, in an embodiment of the present invention, the power supply intensity, signal intensity, and road accessibility of all candidate gateway points can be determined, and then the comprehensive score of each candidate gateway can be calculated, and the target gateway can be obtained according to the comprehensive score. Among them, the calculation expression of the comprehensive score of the candidate gateway is: Score(g)=0.5 × power supply intensity + 0.4 × signal intensity + 0.1 × road accessibility.

[0047] Based on the target gateway, the embodiment of the present invention can determine the relay point and plan the relay path based on the network coverage of the target gateway in combination with the slope grid data and the target soil moisture intensive observation area.

[0048] Optionally, in one embodiment of the present invention, the road accessibility of each candidate gateway point is calculated based on multi-source geographic data, including: based on the road layer data in the multi-source geographic data, road network modeling of the target area is performed to obtain a road network model of the target area, and a weighted road map of the target area is constructed in combination with the road network model and preset road weights; and road accessibility is calculated using the weighted road map.

[0049] As a possible implementation method, the embodiment of the present invention can obtain road layer data (shp type) of the target area based on multi-source geographic data (if there is no shp data for small trails such as mountain trails, it can be manually masked and extracted from the world map image that comes with ArcGIS), model the road network, and construct a weighted road map. The weights are set as follows: road grade (highway 0.2, county road 0.5, mountain trail 1.0).

[0050] In combination with the weighted road graph, the embodiment of the present invention can perform road accessibility calculation.

[0051] Among them, the calculation expression of road accessibility can be: , Where d is the three-dimensional straight-line distance between the candidate gateway and the nearest road, is the average slope of the connection point between the candidate gateway and the nearest road, is the road weight level, with county roads / rural roads taking 1, mountain dirt roads / trails taking 0.7, and expressways / national highways taking 0.3. Expressways have the lowest weight because they cannot facilitate parking and entry and exit).

[0052] Optionally, in one embodiment of the present invention, planning corresponding relay paths based on multiple relay points includes: calculating the sum of the elevations of multiple relay points based on multi-source geographic data; calculating the distance and average slope between each relay point and the road in the target area based on the multi-source geographic data; constructing a three-dimensional road-terrain coupling model of the target area based on the multi-source geographic data, and constructing a slope constraint based on the three-dimensional road-terrain coupling model and the dynamic road influence domain of the slope; constructing a multi-objective optimization function using the sum of the elevations, the distance and the average slope; solving the multi-objective optimization function using the slope constraint to obtain the relay path, wherein the expression of the multi-objective optimization function is: , R = 500 × exp (-0.02 × ), , , Among them, represents the first dynamic weight factor, represents the total elevation, represents the second dynamic weight factor, represents the distance, represents the static weight factor, represents the average slope, R represents the slope influence radius, t represents the number of current iterations, T represents the total number of iterations.

[0053] In the actual execution process, when planning the relay path, the embodiment of the present invention can adopt a multi-objective optimization function with dynamic weight factors: , where is the first dynamic weight factor, is the second dynamic weight factor, and the sum of the two is 0.8, is the static weight factor, set to 0.2, z is the total elevation of each relay point, and d is the distance between each point and the road is the average slope between each point and the road. The simulated annealing algorithm is used for solution, and it is necessary to constrain that the slope of all points between each point and the road is not greater than 35 degrees to ensure that the robot dog can climb smoothly.

[0054] Among them, the embodiment of the present invention can obtain the dynamic weight factor in the following way: Establish a three-dimensional road-terrain coupling model, and propose a dynamic road influence domain algorithm combined with slope: the influence radius R = 500×exp(-0.02× )(unit: m) is used as the solution constraint condition, an adaptive optimization mechanism, and the dynamic weight factors and are set, , , Among them, t is the number of current iterations, T is the set total number of iterations. According to this rule, the terrain factor decays as the number of iterations increases, while the road factor increases as the number of iterations increases, so as to ensure that the layout position focuses on terrain adaptation in the early stage and strengthens the association with the road in the later stage during the iterative process, and prevent falling into the local low-altitude trap. Finally, it can be verified through Monte Carlo simulation of the network connectivity rate or calculation of TCI (Transport Cost Index), etc.

[0055] Optionally, in an embodiment of the present invention, after planning the corresponding relay paths based on multiple relay points, it further includes: dividing the target soil moisture intensive observation area into multiple grids based on a preset density; setting high-density area soil moisture sensors in each grid, so that the sensing signals of the high-density area soil moisture sensors are transmitted back to the target gateway through the relay paths.

[0056] By controlling the density within the key observation range (target soil moisture intensive observation area), the embodiments of the present invention can divide the key observation area into multiple grids, set the grid density according to requirements, densely arrange soil moisture sensors within the grids according to the observation requirements, and the signals of these sensors are transmitted back to the gateway through the sensors on the relay route.

[0057] In step S105, generate the corresponding installation path by using the relay path, and use the installation path to control the robot dog to complete the deployment task, so as to obtain the soil moisture detection data transmitted back from the target soil moisture intensive observation area after the deployment task is completed.

[0058] According to the above optimization results, the embodiments of the present invention can use the calculated target gateway location and the layout points of the soil moisture sensors to construct an installation path, equip the robot dog with a certain number of soil moisture sensors, input the path command, set the automatic return power warning threshold, and start the automatic deployment from the gateway point. To reduce the risk of the robot dog being difficult to return and losing contact in the complex terrain of the mountainous area, people can follow the robot dog along the road to provide guarantee. In summary, to achieve high-efficiency, low-cost, and wide-range deployment of new sensors in mountainous areas, with the increasing maturity of robot dog technology, it has played a huge value in the fields of industrial inspection, security patrol, emergency rescue, etc., can adapt to various complex terrains and scenarios, and can effectively save labor costs.

[0059] The embodiments of the present invention propose an intelligent deployment algorithm for three-dimensional terrain modeling and multi-constraint optimization based on dynamic weight factors. By integrating high-precision terrain data and communication physical models, an optimization model is constructed that first considers the terrain occlusion, communication distance, and power supply constraints of the sensors, and then considers the costs generated during the automatic deployment process of the robot dog (the elevation of the sensor is the lowest, the distance from the road is the closest, the slope between the sensor and the road is the gentlest, and the slope of each point on the optimal path shall not be greater than 35° to ensure that the robot dog can pass stably and gently), so as to realize the joint optimization of gateway location selection and relay path, and significantly reduce the deployment difficulty and operation and maintenance costs of the monitoring network.

[0060] Specifically, as Figure 2 shown, an embodiment is used to elaborate in detail the working principle of the method for deploying soil moisture sensors in the embodiments of the present invention.

[0061] As Figure 2As shown, the embodiment of the present invention may include the following steps: Step S201: Acquire multi-source geographic data of the target area and perform data preprocessing. The embodiment of the present invention can integrate geographic data such as high-precision DEM, road network, signal strength, village distribution, etc., and preprocess the data.

[0062] The embodiment of the present invention can obtain high-precision DEM data of the target area as raw data, use geographic information system tools (Arcgis, Qgis, etc.) to fill depressions, and calculate the slope raster data of the target area; obtain the road layer data (shp type) of the target area (if there is no shp data for small trails such as mountain trails, it can be manually masked and extracted from the world map image provided by ArcGIS), model the road network, and construct a weighted road map. The weights are set as follows: road grade (highway 0.2, county road 0.5, mountain trail 1.0); integrate the point coordinate areas with stable power supply and stable network signals in the area as a preliminary set of gateway locations for selection.

[0063] Step S202: determine constraint conditions and build communication topology model. The embodiment of the present invention can construct a wireless sensor network topology that takes terrain shielding into consideration.

[0064] Since there should be no obstruction between the gateway and the first soil moisture sensor as much as possible, and between the soil moisture sensors as much as possible to ensure smooth signal transmission, the visibility analysis of the candidate points of the gateway set and each point in the study area is carried out, and the point set that can ensure mutual visibility is initially selected as the constraint condition for further optimization in the later stage. The three-dimensional Bresenham algorithm is used to detect the visibility between nodes, and the visibility condition is defined as follows: the elevation of all points on the connection path ≤min(z1,z2)+5 (unit: m), where z1 and z2 are the elevations of the two points to be tested; the communication graph and the set of candidate gateways and sensor points are constructed, and the generation rules are as follows: 1. The node spacing is ≤1000m (the maximum straight-line relay distance between soil moisture sensors is conservatively estimated to be 1000m), 2. The visibility condition is met, and 3. The road reachable distance is ≤500m.

[0065] Step S203: Determine the objective function, gateway point selection and relay path optimization. The embodiment of the present invention can use dynamic weight factors to achieve joint optimization of gateway site selection, relay path planning and sensor deployment, and analyze road accessibility and transportation path slope to evaluate engineering feasibility.

[0066] Step S202 is to ensure that all areas within the target area that can communicate with each other are obtained, which is the basis for constructing a soil moisture monitoring network. On the basis of step S202, other factors need to be further considered to optimize other problems faced in the layout process. The relay path is defined as follows: from the gateway to the soil moisture intensive observation area (that is, the key monitoring area where soil moisture sensors are densely arranged. There is often no signal around these areas, and they are deep in the mountains. Data needs to be relayed through soil moisture sensors to ensure that the monitoring data in the intensive observation area can be transmitted back to the gateway through the relay route and then analyzed).

[0067] Optimize the gateway location selection, and calculate the comprehensive score of the candidate gateway according to the following formula: Score(g)=0.5×Power supply intensity + 0.4×Signal intensity + 0.1×Road accessibility.

[0068] After obtaining the target gateway, the embodiment of the present invention can construct a multi-objective optimization function to determine the relay points and plan the relay path by using dynamic factors and static factors.

[0069] Step S204: Automatically deploy sensors by using a robotic dog. The embodiment of the present invention can use a robotic dog to carry sensors and perform automatic deployment according to the calculated optimal path.

[0070] According to various optimization results in step S203, calculate the best gateway position and the optimal soil moisture sensor deployment points, construct the installation path, equip the robotic dog with a certain number of soil moisture sensors, input the path command, set the warning threshold for the automatic return power, and start automatic deployment from the gateway position. To reduce the risk of the robotic dog being difficult to return and losing contact in the complex terrain of the mountains, people can follow the robotic dog along the road to provide guarantee.

[0071] In addition, the embodiment of the present invention can control the density within the key observation range, divide the key observation area into multiple grids, set the grid density according to requirements, and densely deploy soil moisture sensors within the grids according to the observation requirements. These sensors transmit signals back to the gateway through the sensors on the relay route.

[0072] After the deployment is completed, the embodiment of the present invention can output a device deployment parameter table, including multiple parameters such as coordinates, elevation, relay relationship, power supply requirements, etc., a transportation path slope analysis chart (chromatogram), and a road accessibility heat map, etc. Finally, the robotic dog performs automatic deployment according to the data, and the mountain soil moisture monitoring network is constructed.

[0073] The method for deploying a soil moisture sensor according to an embodiment of the present invention can obtain multi-source geographical data of a target area and a target soil moisture intensive observation area based on the deployment task of the soil moisture sensor, screen out a gateway area with stable signals in the target area, and screen out a plurality of relay points that can communicate stably and are suitable for installation, and then plan a corresponding relay path, use the relay path to generate an installation path for the robot dog to control the robot dog to complete the deployment task, so as to obtain the soil moisture detection data transmitted back from the target soil moisture intensive observation area, so as to ensure the reliability and stability of the relay chain for the deployment of the soil moisture sensor, make the transmitted data stable, accurate and highly time-sensitive, with high deployment efficiency and low cost, and is convenient for popularization and application. Thus, the technical problems in the related art are solved, that is, in a mountainous environment, the deployment conditions of the soil moisture sensor are harsh, and the subjectivity of manual deployment is strong, it is difficult to ensure the continuity and reliability of data transmission, it is difficult to obtain accurate and highly time-sensitive data, and the soil moisture monitoring efficiency is low.

[0074] Next, the deployment device of the soil moisture sensor according to an embodiment of the present invention will be described with reference to the accompanying drawings.

[0075] Figure 3 It is a block diagram of the deployment device of the soil moisture sensor according to an embodiment of the present invention.

[0076] As Figure 3 shown, the deployment device 10 of the soil moisture sensor includes: an acquisition module 100, a screening module 200, a construction module 300, a planning module 400, and a deployment module 500.

[0077] Specifically, the acquisition module 100 is configured to obtain the deployment task of the soil moisture sensor and obtain multi-source geographical data of the target area and the target soil moisture intensive observation area based on the deployment task.

[0078] The screening module 200 is configured to screen out a plurality of signal areas that meet the preset signal stability condition and a plurality of candidate sensor points that meet the preset installation condition in the target area, and generate a candidate gateway location set based on the plurality of signal areas.

[0079] The construction module 300 is configured to construct a candidate point set of the target area by combining the candidate gateway location set, the plurality of candidate sensor points, and the multi-source geographical data.

[0080] The planning module 400 is configured to screen out a plurality of relay points that meet the preset communication condition in the target area by combining the candidate point set, the multi-source geographical data, and the target soil moisture intensive observation area, and plan a corresponding relay path based on the plurality of relay points.

[0081] The deployment module 500 is used to generate corresponding installation paths using relay paths and control the robotic dog to complete the deployment task using the installation paths, so as to obtain the soil moisture detection data transmitted back by the target soil moisture intensive observation area after the deployment task is completed.

[0082] Optionally, in an embodiment of the present invention, the construction module 300 includes: an acquisition unit, an analysis unit, and a first construction unit.

[0083] Among them, the acquisition unit is used to acquire multiple candidate gateway points in the candidate gateway location set.

[0084] The analysis unit is used to perform visibility analysis on the multiple candidate gateway points and multiple candidate sensor points using multi-source geographic data to obtain an analysis result.

[0085] The first construction unit is used to construct a set of candidate points that meet the preset visibility conditions in combination with the analysis result.

[0086] Optionally, in an embodiment of the present invention, the planning module 400 includes: a first division unit, a second division unit, a first calculation unit, a second calculation unit, a third calculation unit, a screening unit, and a determination unit.

[0087] Among them, the first division unit is used to divide the target area into multiple power supply intensity areas based on the artificial building density data in the multi-source geographic data to respectively determine the power supply intensity of each candidate gateway point in the candidate point set.

[0088] The second division unit is used to divide the target area into multiple signal intensity areas based on the signal coverage data in the multi-source geographic data to respectively determine the signal intensity of each candidate gateway point.

[0089] The first calculation unit is used to calculate the road accessibility of each candidate gateway point based on the multi-source geographic data.

[0090] The second calculation unit is used to calculate the slope raster data of the target area based on the multi-source geographic data.

[0091] The third calculation unit is used to calculate the comprehensive score of each candidate gateway by combining the power supply intensity, signal intensity, and road accessibility.

[0092] The screening unit is used to obtain the target gateway point based on the comprehensive score and screen out multiple candidate sensor points under the network coverage area of the target gateway point from the candidate point set as candidate relay points.

[0093] The determination unit is used to determine multiple relay points from the candidate relay points with the target gateway point as the starting point and the target soil moisture intensive observation area as the ending point in combination with the slope raster data.

[0094] Optionally, in an embodiment of the present invention, the first calculation unit includes: a construction subunit and a calculation subunit.

[0095] Among them, the construction subunit is used to model the road network of the target area based on the road layer data in the multi-source geographic data to obtain the road network model of the target area, and construct a weighted road map of the target area by combining the road network model and the preset road weights.

[0096] The calculation subunit is used to calculate the road accessibility using the weighted road map.

[0097] Optionally, in an embodiment of the present invention, the planning module 400 includes: a fourth calculation unit, a fifth calculation unit, a second construction unit, a third construction unit, and a sixth calculation unit.

[0098] Among them, the fourth calculation unit is used to calculate the total elevation of multiple relay points based on the multi-source geographic data.

[0099] The fifth calculation unit is used to calculate the distance and average slope between each relay point and the roads in the target area based on the multi-source geographic data.

[0100] The second construction unit is used to construct a three-dimensional road-terrain coupling model of the target area based on the multi-source geographic data, and construct slope constraints based on the three-dimensional road-terrain coupling model and the dynamic road influence domain of the slope.

[0101] The third construction unit is used to construct a multi-objective optimization function using the total elevation, distance, and average slope.

[0102] The sixth calculation unit is used to solve the multi-objective optimization function using the slope constraints to obtain the relay path.

[0103] Optionally, in an embodiment of the present invention, the expression of the multi-objective optimization function is: , R = 500×exp(-0.02× ), , , Among them, represents the first dynamic weight factor, represents the total elevation, represents the second dynamic weight factor, represents the distance, represents the static weight factor, represents the average slope, R represents the slope influence radius, t represents the number of the current iteration,T Indicates the total number of iterations.

[0104] Optionally, in an embodiment of the present invention, the soil moisture sensor deployment device 10 further includes: a division module and an arrangement module.

[0105] Wherein, the division module is configured to divide the target soil moisture intensive observation area into multiple grids based on a preset density.

[0106] The arrangement module is configured to set soil moisture sensors in high-density areas within each grid, so that the sensing signals of the soil moisture sensors in the high-density areas are transmitted back to the target gateway through a relay path.

[0107] It should be noted that the foregoing explanation of the embodiments of the method for deploying soil moisture sensors also applies to the device for deploying soil moisture sensors in this embodiment, and will not be repeated here.

[0108] According to the device for deploying soil moisture sensors proposed in the embodiments of the present invention, based on the deployment task of soil moisture sensors, multi-source geographical data of the target area and the target soil moisture intensive observation area can be obtained, a gateway area with stable signals can be screened out within the target area, and multiple relay points that can communicate stably and are suitable for installation can be screened out. Furthermore, a corresponding relay path can be planned, and the installation path of the robot dog can be generated using the relay path to control the robot dog to complete the deployment task, so as to obtain the soil moisture detection data transmitted back from the target soil moisture intensive observation area, to ensure the reliability and stability of the relay chain for deploying soil moisture sensors, so that the transmitted data is stable, accurate and has high timeliness, the deployment efficiency is high, and the cost is low, which is convenient for popularization and application. Thus, the technical problems in the related art are solved, that is, in a mountainous environment, the deployment conditions of soil moisture sensors are harsh, and the subjectivity of manual deployment is strong, it is difficult to ensure the continuity and reliability of data transmission, it is difficult to obtain accurate and highly time-sensitive data, and the soil moisture monitoring efficiency is low.

[0109] Figure 4 It is a schematic structural diagram of an electronic device provided by an embodiment of the present invention. The electronic device may include: A memory 401, a processor 402, and a computer program stored on the memory 401 and executable on the processor 402.

[0110] When the processor 402 executes the program, it implements the method for deploying soil moisture sensors provided in the above embodiments.

[0111] Furthermore, the electronic device further includes: A communication interface 403 for communication between the memory 401 and the processor 402.

[0112] A memory 401 for storing a computer program that can run on a processor 402.

[0113] The memory 401 may include high-speed RAM memory and may also include non-volatile memory, such as at least one disk memory.

[0114] If the memory 401, the processor 402, and the communication interface 403 are implemented independently, the communication interface 403, the memory 401, and the processor 402 can be interconnected through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 only a thick line is shown in the figure, but it does not mean that there is only one bus or one type of bus.

[0115] Optionally, in a specific implementation, if the memory 401, the processor 402, and the communication interface 403 are integrated on a single chip, the memory 401, the processor 402, and the communication interface 403 can communicate with each other through an internal interface.

[0116] The processor 402 may be a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention.

[0117] This embodiment also provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the layout method of the soil moisture sensor as described above is implemented.

[0118] This embodiment of the present invention also provides a computer program product, including a computer program, and when the computer program is executed by a processor, the layout method of the soil moisture sensor provided by the embodiments of the present invention is implemented.

[0119] In the description of this specification, the descriptions with reference to terms such as "one embodiment", "some embodiments", "examples", "specific examples", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0120] In addition, the terms "first" and "second" are used only for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, the meaning of "N" is at least two, such as two, three, etc., unless otherwise specifically defined.

[0121] Any process or method description shown in the flowchart or described in other ways herein may be understood to represent a module, segment, or portion of code including one or N executable instructions for implementing a customized logic function or process, and the scope of the preferred embodiments of the present invention includes additional implementations, where the functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0122] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definable sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or used in combination with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in combination with an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection portion (electronic device) having one or N wirings, a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing as appropriate, and then stored in a computer memory.

[0123] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having suitable combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), and the like.

[0124] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the methods of the above embodiments can be completed by a program instructing relevant hardware, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0125] In addition, each functional unit in various embodiments of the present invention may be integrated into a processing module, may exist physically alone for each unit, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0126] The above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for arranging soil moisture sensors, characterized in that, Including the following steps: Obtain the deployment task of the soil moisture sensor, and based on the deployment task, obtain multi-source geographical data of the target area and the target soil moisture intensive observation area; Screen multiple signal areas that meet the preset signal stability conditions and multiple candidate sensor points that meet the preset installation conditions within the target area, and generate a candidate gateway location set based on the multiple signal areas; Construct a candidate point set of the target area by combining the candidate gateway location set, the multiple candidate sensor points, and the multi-source geographical data; Combine the candidate point set, the multi-source geographical data, and the target soil moisture intensive observation area, and screen out multiple relay points that meet the preset communication conditions in the target area, so as to plan corresponding relay paths based on the multiple relay points; Generate a corresponding installation path using the relay path, and use the installation path to control the robot dog to complete the deployment task, so as to obtain the soil moisture detection data transmitted back by the target soil moisture intensive observation area after the deployment task is completed.

2. The method for arranging soil moisture sensors according to claim 1, characterized in that, The constructing the candidate point set of the target area by combining the candidate gateway location set, the multiple candidate sensor points, and the multi-source geographical data includes: Obtain multiple candidate gateway points in the candidate gateway location set; Perform visibility analysis on the multiple candidate gateway points and the multiple candidate sensor points using the multi-source geographical data to obtain an analysis result; Construct a candidate point set that meets the preset visibility conditions by combining the analysis result.

3. The method for arranging soil moisture sensors according to claim 1, characterized in that, The screening out multiple relay points that meet the preset communication conditions in the target area by combining the candidate point set, the multi-source geographical data, and the target soil moisture intensive observation area includes: Based on the artificial building density data in the multi-source geographical data, divide the target area into multiple power supply intensity areas to respectively determine the power supply intensity of each candidate gateway point in the candidate point set; Based on the signal coverage data in the multi-source geographical data, divide the target area into multiple signal intensity areas to respectively determine the signal intensity of each candidate gateway point; Calculate the road accessibility of each candidate gateway point respectively based on the multi-source geographical data; Calculate the slope raster data of the target area based on the multi-source geographical data; Calculate the comprehensive score of each candidate gateway by combining the power supply intensity, the signal intensity, and the road accessibility; Obtain the target gateway point based on the comprehensive score, and screen out multiple candidate sensor points under the network coverage area of the target gateway point from the candidate point set as candidate relay points; Taking the target gateway point as the starting point and the target soil moisture intensive observation area as the ending point, determine the multiple relay points from the candidate relay points by combining the slope raster data.

4. The method for arranging soil moisture sensors according to claim 3, characterized in that, The calculating the road accessibility of each candidate gateway point respectively based on the multi-source geographical data includes: Based on the road layer data in the multi-source geographic data, perform road network modeling on the target area to obtain the road network model of the target area, and construct the weighted road map of the target area by combining the road network model and the preset road weights; Calculate the road accessibility using the weighted road map.

5. The method for arranging soil moisture sensors according to claim 3, characterized in that, The planning of the corresponding relay paths based on the multiple relay points includes: Calculate the total elevation of the multiple relay points based on the multi-source geographic data; Calculate the distance and average slope between each relay point and the roads in the target area based on the multi-source geographic data; Construct a three-dimensional road-terrain coupling model of the target area based on the multi-source geographic data, and construct slope constraints based on the three-dimensional road-terrain coupling model and the dynamic road influence domain of the slope; Construct a multi-objective optimization function using the total elevation, the distance, and the average slope; Solve the multi-objective optimization function using the slope constraints to obtain the relay path.

6. The method for arranging soil moisture sensors according to claim 5, characterized in that, The expression of the multi-objective optimization function is: ， R = 500×exp(-0.02× ), ， ， Among them, represents the first dynamic weight factor, represents the total elevation, represents the second dynamic weight factor, represents the distance, represents the static weight factor, represents the average slope, and R represents the slope influence radius, t represents the number of current iterations, T represents the total number of iterations.

7. The layout method of the soil moisture sensor according to claim 3, wherein, After planning the corresponding relay paths based on the multiple relay points, it further includes: Divide the target soil moisture intensive observation area into multiple grids based on a preset density; Set soil moisture sensors in the high-density area in each grid so that the sensing signals of the soil moisture sensors in the high-density area are transmitted back to the target gateway through the relay path.

8. A layout device for a soil moisture sensor, wherein, It includes: An acquisition module, configured to acquire the layout task of the soil moisture sensors, and acquire the multi-source geographic data of the target area and the target soil moisture intensive observation area based on the layout task; A screening module, configured to screen multiple signal areas that meet the preset signal stability conditions and multiple candidate sensor points that meet the preset installation conditions in the target area, and generate a candidate gateway location set based on the multiple signal areas; A construction module, configured to construct a candidate point set of the target area by combining the candidate gateway location set, the multiple candidate sensor points, and the multi-source geographic data; A planning module, configured to screen out multiple relay points that meet the preset communication conditions in the target area by combining the candidate point set, the multi-source geographic data, and the target soil moisture intensive observation area, so as to plan the corresponding relay paths based on the multiple relay points; A layout module, configured to generate a corresponding installation path using the relay path, and control the robot dog to complete the layout task using the installation path, so as to obtain the soil moisture detection data transmitted back from the target soil moisture intensive observation area after the layout task is completed.

9. An electronic device, wherein, It includes: A memory, a processor, and a computer program stored on the memory and executable on the processor, and the processor executes the program to implement the method for laying out soil moisture sensors according to any one of claims 1-7.

10. A computer-readable storage medium, on which a computer program is stored, wherein, The program is executed by the processor to be used to implement the method for laying out soil moisture sensors according to any one of claims 1-7.

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