Soil moisture sensor deployment method, device, electronic device, and storage medium

Abstract

The present invention relates to the field of chemical or physical analysis technology, and in particular to a soil moisture sensor deployment method, device, electronic device, and storage medium, wherein the method comprises: based on the deployment task of the soil moisture sensor, obtaining corresponding multi-source geographic data and a target soil moisture intensive observation area, screening a gateway area with stable signals within the target area, and screening a plurality of relay points that can communicate stably and are suitable for installation, and then planning a corresponding relay path, using the relay path to generate an installation path for a robot dog, so as to control the robot dog to complete the deployment task, thereby obtaining detection data transmitted back from the target soil moisture intensive observation area. Thus, the technical problems in the related art, namely, the harsh deployment conditions of soil moisture sensors in mountainous environments, the strong subjectivity of manual deployment, the difficulty in ensuring the continuity and reliability of data transmission, the difficulty in obtaining accurate and highly timely data, and the low efficiency of soil moisture monitoring, are solved.

Description

Technical Field

[0001] The present invention relates to the field of chemical or physical analysis technology, and in particular to a soil moisture sensor deployment method, device, electronic equipment and storage medium. Background Art

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

[0003] However, in related technologies, in mountainous environments, soil moisture monitoring networks use sensors that require real-time external power supply (such as C616, etc.), which often lead to problems such as power supply difficulties and inability to deploy them over large areas. This results in low soil moisture monitoring efficiency and difficulty in obtaining accurate and highly timely data. In addition, manual deployment is highly subjective, relay link reliability is low, equipment maintenance costs are high, and human resources are seriously wasted, which urgently needs to be improved. Summary of the Invention

[0004] The present invention provides a soil moisture sensor deployment method, device, electronic device, and storage medium to address the technical problems in related technologies such as harsh deployment conditions for soil moisture sensors in mountainous environments, high subjectivity in manual deployment, difficulty in ensuring the continuity and reliability of data return, difficulty in obtaining accurate and timely data, and low soil moisture monitoring efficiency.

[0005] A first aspect of the present invention provides a method for deploying soil moisture sensors, comprising the following steps: obtaining a deployment task for the soil moisture sensor, and obtaining multi-source geographic data of a target area and a target soil moisture intensive observation area based on the deployment task; screening multiple signal areas that meet preset signal stability conditions and multiple candidate sensor points that meet preset installation conditions within the target area, and generating a candidate gateway location set based on the multiple signal areas; constructing a candidate point set for the target area by combining the candidate gateway location set, the multiple candidate sensor points, and the multi-source geographic data; screening multiple relay points that meet 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 corresponding relay paths based on the multiple relay points; generating a corresponding installation path using the relay path, and controlling a robot dog to complete the deployment task using the installation path, so as to obtain soil moisture detection data transmitted back from the target soil moisture intensive observation area after the deployment task is completed.

[0006] Optionally, in one embodiment of the present invention, 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 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 using the multi-source geographic data to obtain analysis results; and constructing a candidate point set that meets preset visibility conditions in combination with the analysis results.

[0007] Optionally, in one embodiment of the present invention, the combination of the candidate point set, the multi-source geographic data and the target soil moisture intensive observation area, and screening out multiple relay points that meet preset communication conditions in the target area, includes: based on the artificial building intensive data in the multi-source geographic data, dividing the target area into multiple power supply strength areas to respectively determine the power supply strength of each candidate gateway point in the candidate point set; based on the signal coverage data in the multi-source geographic data, dividing the target area into multiple signal strength areas to respectively determine the signal strength of each candidate gateway point; based on the multi-source geographic data, dividing the target area into multiple signal strength areas to respectively determine the signal strength of each candidate gateway point; The method comprises the following steps: 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 in combination with the power supply strength, the signal strength and the road accessibility; obtaining the target gateway point based on the comprehensive score, and screening out multiple candidate sensor points within 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 end point, determining the multiple relay points from the candidate relay points in combination with the slope raster data.

[0008] Optionally, in one embodiment of the present invention, the road accessibility of each candidate gateway point is calculated based on the multi-source geographic data, including: based on the road layer data in the multi-source geographic data, road network modeling of the target area to obtain a road network model of the target area, and combining the road network model and preset road weights to construct a weighted road map of the target area; and using the weighted road map to calculate the road accessibility.

[0009] Optionally, in one embodiment of the present invention, planning the corresponding relay path based on the multiple relay points includes: calculating the sum of the elevations of the multiple relay points based on the 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; and solving the multi-objective optimization function using the slope constraint to obtain the relay path.

[0010] Optionally, in one embodiment of the present invention, the expression of the multi-objective optimization function is:

[0011] ,

[0012] R=500×exp(-0.02× ),

[0013] ,

[0014] ,

[0015] in, represents the first dynamic weight factor, represents the sum of the elevations, 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 Indicates the number of current iterations, T Indicates the total number of iterations.

[0016] Optionally, in one embodiment of the present invention, after planning the corresponding relay paths based on the multiple relay points, it also includes: dividing the target soil moisture intensive observation area into multiple grids based on a preset density; and setting a high-density area soil moisture sensor in each grid, so that the sensing signal of the high-density area soil moisture sensor is transmitted back to the target gateway through the relay path.

[0017] According to a second aspect of the present invention, an embodiment provides a soil moisture sensor deployment device, comprising: an acquisition module for acquiring a deployment task for the soil moisture sensor, and acquiring multi-source geographic data of a target area and a target soil moisture intensive observation area based on the deployment task; a screening module for screening multiple signal areas that meet preset signal stability conditions and multiple candidate sensor points that meet preset installation conditions within the target area, and generating a candidate gateway location set based on the multiple signal areas; a construction module for combining the candidate gateway location set, the multiple candidate sensor points, and the multi-source geographic data to construct a candidate point set for the target area; a planning module for combining the candidate point set, the multi-source geographic data, and the target soil moisture intensive observation area to screen multiple relay points that meet preset communication conditions in the target area, and plan corresponding relay paths based on the multiple relay points; a deployment module for generating a corresponding installation path using the relay path, and controlling a robot dog to complete the deployment task using the installation path, so as to obtain soil moisture detection data transmitted back from the target soil moisture intensive observation area after the deployment task is completed.

[0018] Optionally, in one embodiment of the present invention, the construction module includes: an acquisition unit, used to obtain multiple candidate gateway points in the candidate gateway location set; an analysis unit, used to use the multi-source geographic data to perform visibility analysis on the multiple candidate gateway points and the multiple candidate sensor points to obtain analysis results; a first construction unit, used to construct a candidate point set that meets preset visibility conditions in combination with the analysis results.

[0019] Optionally, in one embodiment of the present invention, the planning module includes: a first division unit, for dividing the target area into a plurality of power supply strength areas based on artificial building density data in the multi-source geographic data, so as to respectively determine the power supply strength of each candidate gateway point in the candidate point set; a second division unit, for dividing the target area into a plurality of signal strength areas based on signal coverage data in the multi-source geographic data, so as to respectively determine the signal strength of each candidate gateway point; a first calculation unit, for respectively calculating the road accessibility of each candidate gateway point based on the multi-source geographic data; a second calculation unit, Used to calculate the slope raster data of the target area based on the multi-source geographic data; a third calculation unit, used to calculate the comprehensive score of each candidate gateway in combination with the power supply strength, the signal strength and the road accessibility; a screening unit, 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; a determination unit, used 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 end point, in combination with the slope raster data.

[0020] Optionally, in one embodiment of the present invention, the first calculation unit includes: a construction subunit, used 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 to construct a weighted road map of the target area in combination with the road network model and preset road weights; a calculation subunit, used to calculate the road accessibility using the weighted road map.

[0021] Optionally, in one embodiment of the present invention, the planning module includes: a fourth calculation unit, used to calculate the sum of the elevations of the multiple relay points based on the multi-source geographic data; a fifth calculation unit, used 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, used 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, used to construct a multi-objective optimization function using the sum of the elevations, the distance and the average slope; and a sixth calculation unit, used to solve the multi-objective optimization function using the slope constraint to obtain the relay path.

[0022] Optionally, in one embodiment of the present invention, the expression of the multi-objective optimization function is:

[0023] ,

[0024] R=500×exp(-0.02× ),

[0025] ,

[0026] ,

[0027] in, represents the first dynamic weight factor, represents the sum of the elevations, 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 Indicates the number of current iterations, T Indicates the total number of iterations.

[0028] Optionally, in one embodiment of the present invention, it also includes: a division module for dividing the target soil moisture intensive observation area into multiple grids based on a preset density; and a layout module for setting a high-density area soil moisture sensor in each grid, so that the sensing signal of the high-density area soil moisture sensor is transmitted back to the target gateway through the relay path.

[0029] A third aspect of the present invention provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the soil moisture sensor deployment method as described in the above embodiment.

[0030] A fourth aspect of the present invention provides a computer-readable storage medium storing computer instructions for causing the computer to execute the soil moisture sensor deployment method as described in the above embodiment.

[0031] A fifth aspect of the present invention provides a computer program product, including a computer program. When the computer program is executed, it is used to implement the above soil moisture sensor deployment method.

[0032] The embodiment of the present invention can obtain multi-source geographic data of the target area and the target soil moisture intensive observation area based on the deployment task of the soil moisture sensor, screen out the gateway area with stable signal in the target area, and screen out multiple relay points that can communicate stably and are suitable for installation, and then plan the corresponding relay path, use the relay path to generate the installation path of the robot dog, and control the robot 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 soil moisture sensor deployment relay chain, so that the returned data is stable, accurate and highly timely, with high deployment efficiency and low cost, which is convenient for promotion and application. Therefore, the technical problems in the related art that the deployment conditions of soil moisture sensors in mountainous environments are harsh, the manual deployment is highly subjective, it is difficult to ensure the continuity and reliability of data return, it is difficult to obtain accurate and highly timely data, and the soil moisture monitoring efficiency is low are solved.

[0033] Additional aspects and advantages of the present invention will be set forth in part in the description which follows and, in part, will be obvious from the description which follows, or may be learned through practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0035] Figure 1 This is a flow chart of a method for deploying soil moisture sensors according to an embodiment of the present invention;

[0036] Figure 2 A schematic diagram showing the principle of a method for deploying soil moisture sensors according to an embodiment of the present invention;

[0037] Figure 3 A schematic structural diagram of a soil moisture sensor deployment device according to an embodiment of the present invention;

[0038] Figure 4 A schematic structural diagram of an electronic device provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The following describes embodiments of the present invention in detail, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present invention, and are not to be construed as limiting the present invention.

[0040] The following describes, with reference to the accompanying drawings, a soil moisture sensor deployment method, apparatus, electronic device, and storage medium according to an embodiment of the present invention. In response to the technical issues mentioned in the background art above, such as the harsh deployment conditions for soil moisture sensors in mountainous environments and the strong subjectivity of manual deployment, which makes it difficult to ensure the continuity and reliability of data transmission, obtain accurate and timely data, and reduce soil moisture monitoring efficiency, the present invention provides a soil moisture sensor deployment method. Based on the soil moisture sensor deployment task, the method obtains multi-source geographic data of a target area and a target soil moisture intensive observation area, selects a gateway area with stable signals within the target area, and selects multiple relay points that can communicate stably and are suitable for installation. A corresponding relay path is then planned, and an installation path for a robot dog is generated using the relay path to control the robot dog to complete the deployment task, thereby obtaining soil moisture detection data transmitted back from the target soil moisture intensive observation area. This ensures the reliability and stability of the soil moisture sensor deployment relay chain, ensures stable, accurate, and timely data transmission, and increases deployment efficiency and cost, making it easy to promote and apply. This solves the technical problems in related technologies, such as the harsh deployment conditions of soil moisture sensors in mountainous environments, the strong subjectivity of manual deployment, the difficulty in ensuring the continuity and reliability of data feedback, the difficulty in obtaining accurate and highly timely data, and the low efficiency of soil moisture monitoring.

[0041] Specifically, Figure 1 A schematic flow chart of a method for deploying soil moisture sensors provided by an embodiment of the present invention.

[0042] like Figure 1 As shown, the soil moisture sensor deployment method includes the following steps:

[0043] In step S101 , a deployment task of soil moisture sensors is obtained, and based on the deployment task, multi-source geographic data of a target area and a target soil moisture intensive observation area are obtained.

[0044] During actual execution, the embodiment of the present invention may receive a soil moisture sensor deployment task, where the deployment task may include a target area where soil moisture sensors need to be deployed and a soil moisture intensive observation area in the target area.

[0045] Obtain multi-source geographic data of the target area, such as high-precision DEM (Digital Elevation Model) data, road layer data, network signal coverage data, etc.

[0046] In step S102 , multiple signal areas that meet preset signal stability conditions and multiple candidate sensor points that meet preset installation conditions are screened within the target area, and a candidate gateway position set is generated based on the multiple signal areas.

[0047] It is understandable that a key soil moisture monitoring network needs to be built in certain areas within mountainous areas. However, since these areas are often located deep in the mountains and have no network signals, it is necessary to utilize the mutual relay function of the soil moisture sensors themselves to establish relay routes and establish connections with areas where signals exist in the outside world in order to achieve the function of real-time outward signal transmission.

[0048] Based on multi-source geographic data, embodiments of the present invention can integrate point coordinate areas within the target area that have stable power supply and stable network signals as candidate gateway areas to generate a set of candidate gateway locations.

[0049] Based on multi-source geographic data, such as DEM data, embodiments of the present invention can screen out locations 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 areas with accumulated water, etc.), and use the remaining locations as candidate sensor locations (candidate relay locations). The installation conditions can be set accordingly by those skilled in the art based on actual conditions and are not specifically limited here.

[0050] In step S103 , a candidate point set of the target area is constructed by combining the candidate gateway position set, multiple candidate sensor points, and multi-source geographic data.

[0051] Furthermore, the embodiment of the present invention can preliminarily screen candidate gateway locations and candidate sensor points based on multi-source geographic data to construct a candidate point set.

[0052] Optionally, in one embodiment of the present invention, a candidate point set of a target area is constructed in combination with a candidate gateway location set, multiple candidate sensor points and multi-source geographic data, including: obtaining multiple candidate gateway points in the candidate gateway location set; performing visibility analysis on the multiple candidate gateway points and multiple candidate sensor points using multi-source geographic data to obtain analysis results; and constructing a candidate point set that meets preset visibility conditions in combination with the analysis results.

[0053] It can be understood that in the embodiment of the present invention, data is transmitted from the gateway as the starting point to the target soil moisture intensive observation area as the end point. In the transmission path, multiple soil moisture sensors for relay need to be set up to ensure the reliability and continuity of data transmission.

[0054] Since there needs to be as little obstruction as possible between the gateway and the first soil moisture sensor (the first transit soil moisture sensor), and there needs to be as little obstruction as possible between the soil moisture sensors to ensure smooth signal transmission, a visibility analysis is performed on the candidate gateway points in the gateway location set and the candidate sensor points in the target area. A set of points that can ensure mutual visibility is initially selected as a constraint condition for further optimization in the later stage.

[0055] For example, embodiments of the present invention may use a three-dimensional Bresenham algorithm to detect inter-node visibility, and define the visibility conditions as follows:

[0056] The elevation of all points on the connection path is ≤ min(z1, z2) + 5 (unit: m), where z1 and z2 are the elevations of the two points to be tested. This embodiment of the present invention can construct a communication graph and a candidate point set containing candidate gateways and candidate sensor points. The generation rules are as follows: 1. Node spacing ≤ 1000 m (a conservative estimate of the maximum straight-line relay distance between soil moisture sensors is 1000 m), 2. Line of sight is met, and 3. Road access distance ≤ 500 m.

[0057] Among them, the communication diagram can be used as an intermediate output to facilitate technical personnel to verify the relay points.

[0058] In step S104, combining 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 in the target area to plan corresponding relay paths based on the multiple relay points.

[0059] During the actual implementation process, the embodiment of the present invention can further screen the relay points based on the candidate point set and plan the relay path by using multi-source geographic data (such as signal strength distribution, power supply strength distribution, etc.) and information such as the location of the target soil moisture intensive observation area.

[0060] Optionally, in one embodiment of the present invention, a candidate point set, multi-source geographic data and a target soil moisture intensive observation area are combined to screen out multiple relay points that meet preset communication conditions in the target area, including: 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 strength areas based on the signal coverage data in the multi-source geographic data to respectively determine the signal strength 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 a comprehensive score of each candidate gateway based on the power supply intensity, signal strength and road accessibility; obtaining the target gateway point based on the comprehensive score, and screening 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 end point, determining multiple relay points from the candidate relay points in combination with the slope raster data.

[0061] For example, in an embodiment of the present invention, a Tiandi Map can be opened in ArcGIS Pro as a base map, and masks of areas with artificial buildings can be manually extracted. Based on the density of artificial buildings, the regional power supply intensity is subjectively divided into three levels: 1, 0.75, and 0.5, that is, masks of three levels are extracted.

[0062] The embodiment of the present invention can use the APP provided by multiple signal providers to query the 5G coverage status in real time, and draw the coverage status of multiple providers in the target area. Taking three providers as an example, the embodiment of the present invention can use the mask of their respective coverage status. For areas with coverage by all three providers, the signal strength is set to 1, for areas with coverage by only two providers, the signal strength is set to 0.67, for areas with coverage by one provider, the signal strength is set to 0.33, and for areas with no coverage, the signal strength is set to 0.

[0063] The embodiment of the present invention can fill the depression based on the high-precision DEM data of the target area using geographic information system tools (Arcgis, Qgis, etc.) to calculate the slope raster data of the target area;

[0064] Road accessibility is obtained by the distance between the candidate gateway to be calculated and the nearest road and the average slope obtained from the slope raster data.

[0065] Based on the above calculation method, the embodiment of the present invention can determine the power supply strength, signal strength, and road accessibility of all candidate gateway points, and then calculate the comprehensive score of each candidate gateway, and obtain the target gateway based on the comprehensive score. The calculation expression of the candidate gateway comprehensive score is:

[0066] Score(g)=0.5×power supply strength+0.4×signal strength+0.1×road accessibility.

[0067] 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.

[0068] 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.

[0069] As a possible implementation method, the embodiment of the present invention can obtain the 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 Tiandi 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).

[0070] In combination with the weighted road graph, the embodiment of the present invention can perform road accessibility calculation.

[0071] The calculation expression of road accessibility can be:

[0072] ,

[0073] 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 due to the lack of convenient parking and entry and exit).

[0074] 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 the 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 a 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; and 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:

[0075] ,

[0076] R=500×exp(-0.02× ),

[0077] ,

[0078] ,

[0079] in, represents the first dynamic weight factor, represents the sum of elevations, represents the second dynamic weight factor, Indicates distance, represents the static weight factor, represents the average slope, R represents the slope influence radius, t Indicates the number of current iterations, T Indicates the total number of iterations.

[0080] In the actual implementation process, the relay path is planned. In the embodiment of the present invention, a multi-objective optimization function with dynamic weight factors may be used: ,in, is the first dynamic weight factor, is the second dynamic weight factor, the sum of the two is 0.8, is a static weight factor, set to 0.2, z is the sum of the elevations of all relay points, and d is the distance between each point and the road. The average slope between each point and the road is solved using the simulated annealing algorithm, and it is necessary to constrain the slope of all points between each point and the road to be no more than 35 degrees to ensure that the robot dog can climb smoothly.

[0081] The embodiment of the present invention can obtain the dynamic weight factor in the following manner:

[0082] A three-dimensional road-terrain coupling model is established, and a dynamic road influence domain algorithm combining slope is proposed: influence radius R = 500×exp(-0.02× ) (unit: m) as the solution constraint, adaptive optimization mechanism, set dynamic weight factor and ,

[0083] ,

[0084] ,

[0085] in, t is the number of current iterations,T is the total number of iterations set. Following this rule, the terrain factor decreases with increasing iterations, while the road factor increases. This ensures that deployment location selection prioritizes terrain adaptation in the early stages of the iteration process and strengthens road correlation in the later stages, preventing local low-altitude traps. Finally, verification can be achieved through Monte Carlo simulations of the full network connectivity or TCI (Transport Cost Index) calculations.

[0086] Optionally, in one embodiment of the present invention, after planning the corresponding relay path based on multiple relay points, it also includes: dividing the target soil moisture intensive observation area into multiple grids based on a preset density; setting a high-density area soil moisture sensor in each grid, so that the sensing signal of the high-density area soil moisture sensor is transmitted back to the target gateway through the relay path.

[0087] To control the density within the key observation range (target soil moisture intensive observation area), the embodiment of the present invention can divide the key observation area into multiple grids, set the grid density according to demand, and deploy soil moisture sensors at a high density within the grid according to observation requirements. These sensors transmit signals back to the gateway through sensors on the relay route.

[0088] In step S105, the relay path is used to generate a corresponding installation path, and the installation path is used 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.

[0089] According to the above optimization results, the embodiment of the present invention can use the calculated target gateway position and soil moisture sensor deployment points to construct an installation path, equip the robot dog with a certain number of soil moisture sensors, input path instructions, set the automatic return power warning threshold, and perform automated deployment starting from the gateway point. In order to reduce the risk of the robot dog having difficulty returning and losing contact in complex mountainous terrain, people can follow the robot dog along the road to provide protection. In summary, in order to achieve high-efficiency, low-cost, and wide-range deployment of new sensors in mountainous areas, as robot dog technology becomes more mature, it has played a huge role in industrial inspections, security patrols, emergency rescue and other fields. It can adapt to various complex terrains and scenarios and can effectively save labor costs.

[0090] An embodiment of the present invention proposes an intelligent deployment algorithm based on three-dimensional terrain modeling and multi-constraint optimization based on dynamic weight factors. By integrating high-precision terrain data with a communication physical model, an optimization model is constructed that prioritizes terrain obstruction, communication distance, and power supply constraints of sensors, and secondly considers the costs incurred during the automated deployment of robot dogs (the sensors are located at the lowest elevation, closest to the road, and have the gentlest slope between them and the road. The slope at each point on the optimal path must not exceed 35° to ensure that the robot dog can pass stably and smoothly). This achieves the joint optimization of gateway site selection and relay paths, significantly reducing the difficulty of monitoring network deployment and operation and maintenance costs.

[0091] Specifically, if Figure 2 As shown, the working principle of the soil moisture sensor deployment method according to an embodiment of the present invention is described in detail using an embodiment.

[0092] like Figure 2 As shown, the embodiment of the present invention may include the following steps:

[0093] 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.

[0094] 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 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 Tiandi 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 signal in the area as a preliminary set of optional gateway locations.

[0095] Step S202: Determine constraints and build communication topology model. The embodiment of the present invention can construct a wireless sensor network topology that takes terrain shielding into consideration.

[0096] Because the gateway and the first soil moisture sensor must be as unobstructed as possible, and soil moisture sensors must be as unobstructed as possible to ensure smooth signal transmission, a visibility analysis was conducted between candidate gateway points and each point in the study area. A preliminary set of points that ensured mutual line of sight was selected as a constraint for further optimization. The three-dimensional Bresenham algorithm was used to detect inter-node visibility, defining the line of sight condition as follows: the elevation of all points on the connecting path ≤ min(z1,z2)+5 (unit: m), where z1 and z2 are the elevations of the two points to be tested. A communication graph was constructed, containing candidate gateway and sensor point sets, with the following generation rules: 1. Node spacing ≤ 1000 m (a conservative estimate of the maximum straight-line relay distance between soil moisture sensors is 1000 m), 2. Line of sight was met, and 3. Road access distance ≤ 500 m.

[0097] Step S203: Determine the objective function, optimize gateway locations, and optimize relay paths. This embodiment of the present invention can employ dynamic weighting factors to achieve joint optimization of gateway location selection, relay path planning, and sensor deployment, and analyze road accessibility and transportation path slopes to assess project feasibility.

[0098] Step S202 is to ensure that all areas in the target area that can communicate with each other are obtained, which is the basis for building a soil moisture monitoring network. On the basis of step S202, other factors need to be further considered to optimize other problems faced during the deployment process. The relay path is defined as from the gateway to the soil moisture dense observation area (that is, the key monitoring area where soil moisture sensors are densely deployed. There is often no signal around these areas. They are deep in the mountains and need to be relayed to transmit data). In the middle, soil moisture sensors need to be deployed for signal relay to ensure that the monitoring data of the densely observed area can be transmitted back to the gateway through the relay route for analysis.

[0099] Optimize the gateway site selection and calculate the comprehensive score of the candidate gateway according to the following formula:

[0100] Score(g)=0.5×power supply strength+0.4×signal strength+0.1×road accessibility.

[0101] After obtaining the target gateway, the embodiment of the present invention can construct a multi-objective optimization function to determine the relay point location and plan the relay path using dynamic factors and static factors.

[0102] Step S204: Automatically deploying sensors using a robot dog. In the embodiment of the present invention, sensors can be deployed automatically using a robot dog equipped with sensors according to the calculated optimal path.

[0103] Based on the optimization results from step S203, the optimal gateway location and soil moisture sensor placement points are calculated. An installation route is constructed, and a specific number of soil moisture sensors are installed on the robot dog. Route instructions are entered, and a threshold for automatic return-to-home power warning is set. Automated deployment begins at the gateway location. To reduce the risk of the robot dog experiencing difficulty returning to home or losing contact in complex mountainous terrain, a human can accompany the robot dog along the route for added security.

[0104] 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 needs, and deploy soil moisture sensors at a high density within the grid according to observation needs. These sensors transmit signals back to the gateway through sensors on the relay route.

[0105] 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 relationships, power supply requirements, transportation path slope analysis diagram (chromatogram) and road accessibility heat map, etc. Finally, the robot dog will automatically deploy according to the data to complete the construction of the mountain soil moisture monitoring network.

[0106] According to the soil moisture sensor deployment method proposed in an embodiment of the present invention, based on the soil moisture sensor deployment task, it can obtain multi-source geographic data of the target area and the target soil moisture intensive observation area, screen out gateway areas with stable signals within the target area, and screen out multiple relay points that can communicate stably and are suitable for installation, and then plan the corresponding relay path. The relay path is used to generate the installation path of the robot dog to control the robot dog to complete the deployment task, thereby obtaining soil moisture detection data transmitted back from the target soil moisture intensive observation area, so as to ensure the reliability and stability of the soil moisture sensor deployment relay chain, make the returned data stable, accurate and highly timely, and have high deployment efficiency and low cost, which is easy to promote and apply. Therefore, it solves the technical problems in the related art that in mountainous environments, the deployment conditions of soil moisture sensors are harsh, the manual deployment is highly subjective, it is difficult to ensure the continuity and reliability of data return, it is difficult to obtain accurate and highly timely data, and the soil moisture monitoring efficiency is low.

[0107] Next, a deployment device for soil moisture sensors according to an embodiment of the present invention will be described with reference to the accompanying drawings.

[0108] Figure 3 4 is a block diagram of a soil moisture sensor deployment device according to an embodiment of the present invention.

[0109] like Figure 3 As shown, the soil moisture sensor deployment device 10 includes: an acquisition module 100 , a screening module 200 , a construction module 300 , a planning module 400 and a deployment module 500 .

[0110] Specifically, the acquisition module 100 is used to acquire the deployment task of the soil moisture sensor, and acquire multi-source geographic data of the target area and the target soil moisture intensive observation area based on the deployment task.

[0111] The screening module 200 is used to screen multiple signal areas that meet preset signal stability conditions and multiple candidate sensor points that meet preset installation conditions within the target area, and generate a candidate gateway location set based on the multiple signal areas.

[0112] The construction module 300 is used to construct a candidate point set of the target area by combining the candidate gateway location set, multiple candidate sensor points and multi-source geographic data.

[0113] The planning module 400 is used to combine the candidate point set, multi-source geographic data and the target soil moisture intensive observation area to 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.

[0114] The deployment module 500 is used to 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 from the target soil moisture intensive observation area after the deployment task is completed.

[0115] Optionally, in one embodiment of the present invention, the construction module 300 includes: an acquisition unit, an analysis unit, and a first construction unit.

[0116] The acquiring unit is used to acquire multiple candidate gateway locations in the candidate gateway location set.

[0117] The analysis unit is used to perform visibility analysis on multiple candidate gateway points and multiple candidate sensor points using multi-source geographic data to obtain analysis results.

[0118] The first construction unit is configured to construct a set of candidate points that meet a preset visibility condition based on the analysis results.

[0119] Optionally, in one embodiment of the present invention, the planning module 400 includes: a first dividing unit, a second dividing unit, a first calculating unit, a second calculating unit, a third calculating unit, a screening unit, and a determining unit.

[0120] 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, so as to respectively determine the power supply intensity of each candidate gateway point in the candidate point set.

[0121] The second division unit is used to divide the target area into multiple signal strength areas based on the signal coverage data in the multi-source geographic data, so as to respectively determine the signal strength of each candidate gateway point.

[0122] The first calculation unit is configured to calculate the road accessibility of each candidate gateway point based on multi-source geographic data.

[0123] The second calculation unit is used to calculate the slope raster data of the target area based on the multi-source geographic data.

[0124] The third calculation unit is used to calculate a comprehensive score of each candidate gateway by combining power supply strength, signal strength and road accessibility.

[0125] The screening unit is used to obtain a target gateway point based on the comprehensive score, and screen out multiple candidate sensor points within the network coverage area of ​​the target gateway point from the candidate point set as candidate relay points.

[0126] 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 end point, combined with the slope grid data.

[0127] Optionally, in one embodiment of the present invention, the first computing unit includes: a construction subunit and a computing subunit.

[0128] 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 to construct a weighted road map of the target area in combination with the road network model and preset road weights.

[0129] The calculation subunit is used to calculate road accessibility using a weighted road graph.

[0130] Optionally, in one 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.

[0131] The fourth calculation unit is used to calculate the sum of the elevations of multiple relay points based on multi-source geographic data.

[0132] The fifth calculation unit is used 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.

[0133] The second construction unit is used to construct a three-dimensional road-terrain coupling model of the target area based on multi-source geographic data, and to construct a slope constraint based on the three-dimensional road-terrain coupling model and the dynamic road influence domain of the slope.

[0134] The third construction unit is used to construct a multi-objective optimization function using the elevation sum, distance and average slope.

[0135] The sixth computing unit is configured to solve a multi-objective optimization function using a slope constraint to obtain a relay path.

[0136] Optionally, in one embodiment of the present invention, the expression of the multi-objective optimization function is:

[0137] ,

[0138] R=500×exp(-0.02× ),

[0139] ,

[0140] ,

[0141] in, represents the first dynamic weight factor, represents the sum of elevations, represents the second dynamic weight factor, Indicates distance, represents the static weight factor, represents the average slope, R represents the slope influence radius, t Indicates the number of current iterations, T Indicates the total number of iterations.

[0142] Optionally, in one embodiment of the present invention, the soil moisture sensor deployment device 10 further includes: a division module and a layout module.

[0143] Among them, the division module is used to divide the target soil moisture intensive observation area into multiple grids based on a preset density.

[0144] The arrangement module is used to set a high-density area soil moisture sensor in each grid, so that the sensing signal of the high-density area soil moisture sensor is transmitted back to the target gateway through the relay path.

[0145] It should be noted that the above explanation of the embodiment of the method for deploying soil moisture sensors is also applicable to the device for deploying soil moisture sensors in this embodiment, and will not be repeated here.

[0146] The soil moisture sensor deployment device proposed in an embodiment of the present invention can obtain multi-source geographic data of the target area and the target soil moisture intensive observation area based on the soil moisture sensor deployment task, screen out gateway areas with stable signals in the target area, and screen out multiple relay points that can communicate stably and are suitable for installation, and then plan the corresponding relay path. The relay path is used to generate the installation path of the robot dog to control the robot 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 soil moisture sensor deployment relay chain, make the returned data stable, accurate and highly timely, and have high deployment efficiency and low cost, which is easy to promote and apply. Therefore, the technical problems in the related art that the deployment conditions of soil moisture sensors in mountainous environments are harsh, the manual deployment is highly subjective, it is difficult to ensure the continuity and reliability of data return, it is difficult to obtain accurate and highly timely data, and the soil moisture monitoring efficiency is low are solved.

[0147] Figure 4 This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device may include:

[0148] Memory 401 , processor 402 , and computer programs stored in the memory 401 and executable on the processor 402 .

[0149] When the processor 402 executes the program, the method for deploying the soil moisture sensor provided in the above embodiment is implemented.

[0150] Furthermore, the electronic device further includes:

[0151] The communication interface 403 is used for communication between the memory 401 and the processor 402 .

[0152] The memory 401 is used to store computer programs that can be run on the processor 402 .

[0153] The memory 401 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0154] If the memory 401, processor 402, and communication interface 403 are implemented independently, the communication interface 403, memory 401, and processor 402 can be connected to each other via a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus. Buses can be divided into address buses, data buses, control buses, etc. For ease of representation, Figure 4 Only one thick line is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0155] Optionally, in a specific implementation, if the memory 401 , the processor 402 and the communication interface 403 are integrated on a chip, the memory 401 , the processor 402 and the communication interface 403 can communicate with each other through an internal interface.

[0156] The processor 402 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present invention.

[0157] This embodiment further provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the above-mentioned soil moisture sensor deployment method is implemented.

[0158] An embodiment of the present invention further provides a computer program product, including a computer program. When the computer program is executed by a processor, the method for deploying soil moisture sensors provided in an embodiment of the present invention is implemented.

[0159] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art can combine and combine different embodiments or examples described in this specification and the features of different embodiments or examples without contradiction.

[0160] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be understood to indicate or imply relative importance or implicitly specify the number of technical features indicated. Thus, a feature specified as "first" or "second" may explicitly or implicitly include at least one such feature. In the description of the present invention, "N" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0161] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or N executable instructions for implementing a custom logical function or step of a process, and the scope of the preferred embodiments of the present invention includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present invention pertain.

[0162] The logic and / or steps represented in a flowchart or otherwise described herein, for example, can be considered a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" is any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (not exhaustive) of computer-readable media include: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program can be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing it in other suitable ways as necessary, and then storing it in a computer memory.

[0163] It should be understood that various components of the present invention can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiment, the N steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any of the following technologies known in the art or a combination thereof can be used: a discrete logic circuit having logic gate circuits for implementing logical functions on data signals, an application-specific integrated circuit having suitable combinational logic gate circuits, a programmable gate array (PGA), a field-programmable gate array (FPGA), etc.

[0164] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, 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 embodiment.

[0165] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing module, or each unit may exist physically separately, or two or more units may be integrated into a single module. The aforementioned integrated modules may be implemented in the form of hardware or in the form of software functional modules. If the integrated modules are implemented in the form of software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium.

[0166] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and are not to be construed as limiting the present invention. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for deploying soil moisture sensors, characterized in that: The following steps are involved: Obtaining a deployment task for soil moisture sensors, and obtaining multi-source geographic data of a target area and a target soil moisture intensive observation area based on the deployment task; Screening a plurality of signal areas that meet a preset signal stability condition and a plurality of candidate sensor points that meet a preset installation condition within the target area, and generating a set of candidate gateway locations based on the plurality of signal areas; Constructing a candidate point set for the target area by combining the candidate gateway position set, the plurality of candidate sensor points, and the multi-source geographic data; Based on the candidate point set, the multi-source geographic data, and the target soil moisture intensive observation area, a plurality of relay points that meet preset communication conditions are screened in the target area, so as to plan corresponding relay paths based on the plurality of 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 soil moisture detection data transmitted back from the target soil moisture intensive observation area after the deployment task is completed; The step of combining the candidate gateway location set, the plurality of candidate sensor locations, and the multi-source geographic data to construct the candidate location set of the target area includes: obtaining a plurality of candidate gateway locations from the candidate gateway location set; performing a visibility analysis on the plurality of candidate gateway locations and the plurality of candidate sensor locations using the multi-source geographic data to obtain an analysis result; and constructing a candidate location set that meets a preset visibility condition based on the analysis result. Wherein, the combination of the candidate point set, the multi-source geographic data and the target soil moisture intensive observation area, and screening out multiple relay points that meet the preset communication conditions in the target area, includes: based on the artificial building intensive data in the multi-source geographic data, dividing the target area into multiple power supply strength areas to respectively determine the power supply strength of each candidate gateway point in the candidate point set; based on the signal coverage data in the multi-source geographic data, dividing the target area into multiple signal strength areas to respectively determine the signal strength of each candidate gateway point; based on the multi-source geographic data, respectively calculating The road accessibility of each candidate gateway point; 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 strength, the signal strength and the road accessibility; obtaining the target gateway point based on the comprehensive score, and screening out multiple candidate sensor points within 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 end point, determining the multiple relay points from the candidate relay points in combination with the slope raster data.

2. The method for deploying soil moisture sensors according to claim 1, characterized in that: The calculating the road accessibility of each candidate gateway point based on the multi-source geographic data includes: Based on the road layer data in the multi-source geographic data, a road network model is performed on the target area to obtain a road network model of the target area, and a weighted road map of the target area is constructed by combining the road network model and preset road weights; The road accessibility is calculated using the weighted road graph.

3. The method for deploying soil moisture sensors according to claim 1, wherein: The planning of corresponding relay paths based on the multiple relay points includes: Calculate the sum of the elevations of the plurality of relay points based on the multi-source geographic data; Calculate 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 a dynamic road influence domain of slope; constructing a multi-objective optimization function using the elevation sum, the distance, and the average slope; The multi-objective optimization function is solved using the slope constraint to obtain the relay path.

4. The method for deploying soil moisture sensors according to claim 3, wherein: The expression of the multi-objective optimization function is: ， R=500×exp(-0.02× ), ， ， in, represents the first dynamic weight factor, represents the sum of the elevations, 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 Indicates the number of current iterations, T Indicates the total number of iterations.

5. The method for deploying soil moisture sensors according to claim 1, wherein: After planning corresponding relay paths based on the multiple relay points, the method further includes: Dividing the target soil moisture dense observation area into multiple grids based on a preset density; A high-density area soil moisture sensor is set in each grid, so that the sensing signal of the high-density area soil moisture sensor is transmitted back to the target gateway through the relay path.

6. A soil moisture sensor deployment device, characterized in that: include: An acquisition module is used to acquire a deployment task of soil moisture sensors and acquire multi-source geographic data of a target area and a target soil moisture intensive observation area based on the deployment task; a screening module, configured to screen a plurality of signal areas that meet a preset signal stability condition and a plurality of candidate sensor points that meet a preset installation condition within the target area, and generate a set of candidate gateway locations based on the plurality of signal areas; A construction module, configured to construct a candidate point set for the target area by combining the candidate gateway position set, the plurality of 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, screen a plurality of relay points in the target area that meet preset communication conditions, and plan corresponding relay paths based on the plurality of relay points; a deployment module, configured to generate a corresponding installation path using the relay path, and control the robot dog to complete the deployment task using the installation path, so as to obtain soil moisture detection data transmitted back from the target soil moisture intensive observation area after the deployment task is completed; The construction module includes: an acquisition unit for acquiring a plurality of candidate gateway points from the candidate gateway location set; an analysis unit for performing visibility analysis on the plurality of candidate gateway points and the plurality of candidate sensor points using the multi-source geographic data to obtain analysis results; and a first construction unit for constructing a set of candidate points that meet a preset visibility condition based on the analysis results. The planning module includes: a first division unit for dividing the target area into a plurality of power supply strength areas based on the artificial building density data in the multi-source geographic data, so as to respectively determine the power supply strength of each candidate gateway point in the candidate point set; a second division unit for dividing the target area into a plurality of signal strength areas based on the signal coverage data in the multi-source geographic data, so as to respectively determine the signal strength of each candidate gateway point; a first calculation unit for respectively calculating the road accessibility of each candidate gateway point based on the multi-source geographic data; a second calculation unit for respectively calculating the road accessibility of each candidate gateway point based on the multi-source geographic data; The source geographic data is used to calculate the slope raster data of the target area; a third calculation unit is used to calculate the comprehensive score of each candidate gateway in combination with the power supply strength, the signal strength and the road accessibility; a 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; a determination unit is used 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 end point, in combination with the slope raster data.

7. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the program to implement the soil moisture sensor deployment method according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method for deploying the soil moisture sensor according to any one of claims 1 to 5.

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