Monitoring terminal delivery method, device, equipment and medium

Abstract

The embodiment of the invention provides a monitoring terminal delivery method and device, equipment and a medium. The method comprises the following steps: acquiring a first scanning result for a monitoring area; the first scanning result is obtained by scanning the monitoring area along a first scanning path by using a first aircraft carrying a first data acquisition device; obtaining a first digital earth surface model and first earth surface data according to the first scanning result; acquiring a second scanning result for the monitoring area; the second scanning result is obtained by scanning the monitoring area along a second scanning path by using a second aircraft carrying a second data acquisition device; the second scanning path is determined according to the first scanning result; obtaining a second digital earth surface model and second earth surface data according to the second scanning result; determining a target delivery area according to the first surface data and the second surface data; and putting the monitoring terminal according to the second digital earth surface model and the target putting area, thereby improving the putting efficiency of the monitoring terminal.

Description

Technical Field

[0001] The present invention relates to the field of terminal placement, and particularly to a method, device, equipment, and medium for monitoring terminal placement. Background Art

[0002] Monitoring terminals are increasingly widely used in fields such as environmental monitoring, disaster warning, and agricultural management. However, the issue of their placement efficiency has always been a key bottleneck restricting their large-scale application. In the prior art, the placement process of monitoring terminals usually relies on manual operations or simple automated equipment, resulting in low placement efficiency. Specifically, it is manifested as follows: The placement process requires multiple manual interventions and takes a long time; the selection of the placement area lacks a scientific basis, leading to repeated or ineffective placements; the adaptability of placements in complex terrains and dynamic environments is poor, further reducing the overall efficiency. These problems not only increase the placement cost but also limit the coverage and effectiveness of monitoring terminals. Therefore, there is an urgent need for an efficient and accurate method for monitoring terminal placement to solve the problem of low efficiency caused by immature placement in the prior art and meet the large-scale monitoring requirements. Summary of the Invention

[0003] In view of the above problems, embodiments of the present invention are proposed to provide a method, device, equipment, and medium for monitoring terminal placement that overcomes the above problems or at least partially solves the above problems.

[0004] To solve the above problems, embodiments of the present invention disclose a method for monitoring terminal placement, the method comprising:

[0005] Obtaining a first scan result for a monitoring area; the first scan result is obtained by scanning the monitoring area using a first aircraft equipped with a first data acquisition device along a first scan path;

[0006] Obtaining a first digital terrain model and first terrain data according to the first scan result;

[0007] Obtaining a second scan result for the monitoring area; the second scan result is obtained by scanning the monitoring area using a second aircraft equipped with a second data acquisition device along a second scan path; the second scan path is determined according to the first scan result;

[0008] Obtaining a second digital terrain model and second terrain data according to the second scan result;

[0009] Determining a target placement area according to the first terrain data and the second terrain data;

[0010] Placing a monitoring terminal according to the second digital terrain model and the target placement area.

[0011] Optionally, the first data acquisition device includes an optical camera, and the first scan result includes image data obtained by scanning the monitoring area along the first scan path by the first aircraft carrying the optical camera;

[0012] Obtaining a first digital terrain model based on the first scan result includes:

[0013] Obtaining a first digital terrain model based on the image data.

[0014] Optionally, the first data acquisition device includes an infrared sensor, and the first scan result includes infrared imaging data obtained by scanning the monitoring area along the first scan path by the first aircraft carrying the infrared sensor;

[0015] Obtaining first terrain data based on the first scan result includes:

[0016] Obtaining first terrain data based on the infrared imaging data.

[0017] Optionally, the second sensor includes a radar, and the second scan result includes radar data obtained by scanning the monitoring area along the second scan path by the second aircraft carrying the radar;

[0018] Obtaining a second digital terrain model based on the second scan result includes:

[0019] Obtaining a second digital terrain model based on the radar data.

[0020] Optionally, the second sensor includes a spectral sensor, and the scan result includes spectral data obtained by scanning the monitoring area along the second scan path by the second aircraft carrying the spectral sensor;

[0021] Obtaining second terrain data based on the second scan result includes:

[0022] Obtaining second terrain data based on the spectral data.

[0023] Optionally, obtaining the second digital terrain model based on the radar data includes:

[0024] Obtaining radar point cloud data; the radar point cloud data is obtained based on the radar data;

[0025] Determining high-altitude obstacle point cloud data based on the radar point cloud data and a preset discrimination threshold;

[0026] Obtain a second digital terrain model, where the second digital terrain model is obtained from the radar point cloud data after removing the aerial obstacle point cloud data.

[0027] Optionally, the preset discrimination threshold includes a local curvature threshold, a normal vector threshold, and a preset spatial threshold. Determining the aerial obstacle point cloud data according to the radar point cloud data and the preset discrimination threshold includes:

[0028] Obtain the geometric features and spatial features of the radar point cloud data; the geometric features include local curvature and normal vector; the spatial features include spatial distribution density and spatial distribution spacing;

[0029] Take the point cloud data with local curvature less than the local curvature threshold, normal vector greater than the normal vector threshold, and spatial features greater than the spatial threshold as the aerial obstacle point cloud data.

[0030] Optionally, determining the target placement area according to the first terrain data and the second terrain data includes:

[0031] Obtain the ground monitoring data for the monitoring area; the ground monitoring data includes the monitoring data of ground cameras, ground signal towers, hydrometeorological monitoring stations, and already placed monitoring terminals;

[0032] Generate a candidate deployable area according to the data of the ground sensors and the first terrain data;

[0033] Determine the target placement area according to the candidate deployable area and the second terrain data obtained.

[0034] Optionally, determining the target placement area according to the candidate deployable area and the second terrain data includes:

[0035] Perform a spatial overlay analysis on the candidate deployable area and the second terrain data to obtain an analysis result;

[0036] Determine the target placement area according to the analysis result.

[0037] Optionally, deploying the monitoring terminal according to the second digital terrain model and the target placement area includes:

[0038] Obtain the environmental information of the target placement area;

[0039] Obtain the elevation information for the monitoring area according to the second digital terrain model;

[0040] Determine the target placement height and the target placement heading angle according to the elevation information and the environmental information;

[0041] Determine a target delivery path according to the second digital surface model and the target delivery area;

[0042] Deliver the monitoring terminal according to the target delivery height, the target delivery heading angle, and the target delivery path.

[0043] On the other hand, an embodiment of the present invention also discloses a monitoring terminal delivery device, and the device includes:

[0044] A first scan result acquisition module, configured to acquire a first scan result for a monitoring area; the

[0045] The first scan result is obtained by using a first aircraft equipped with a first data acquisition device to scan the monitoring area along a first scan path;

[0046] A first data acquisition module, according to the first scan result, obtains a first digital surface model and first surface data;

[0047] A second scan result acquisition module, acquires a second scan result for the monitoring area; the second scan result is obtained by using a second aircraft equipped with a second data acquisition device to scan the monitoring area along a second scan path; the second scan path is determined according to the first scan result;

[0048] A second data acquisition module, according to the second scan result, obtains a second digital surface model and second surface data;

[0049] A target delivery area acquisition module, configured to determine a target delivery area according to the first surface data and the second surface data;

[0050] A monitoring terminal delivery module, configured to deliver the monitoring terminal according to the second digital surface model and the target delivery area.

[0051] Optionally, the first data acquisition device includes an optical camera, and the first scan result includes image data obtained by using the first aircraft equipped with the optical camera to scan the monitoring area along the first scan path;

[0052] The first data acquisition module includes:

[0053] A first model acquisition sub-module, configured to obtain a first digital surface model according to the image data.

[0054] Optionally, the first data acquisition device includes an infrared sensor, and the first scan result includes infrared imaging data obtained by using the first aircraft equipped with the infrared sensor to scan the monitoring area along the first scan path;

[0055] The first data acquisition module includes:

[0056] The first ground surface acquisition sub-module is configured to obtain first ground surface data according to the infrared imaging data.

[0057] Optionally, the second sensor includes a radar, and the second scan result includes radar data obtained by scanning the monitoring area along the second scan path by the second aircraft carrying the radar;

[0058] The second data acquisition module includes:

[0059] The second model acquisition sub-module is configured to obtain a second digital ground surface model according to the radar data.

[0060] Optionally, the second sensor includes a spectral sensor, and the scan result includes spectral data obtained by scanning the monitoring area along the second scan path by the second aircraft carrying the spectral sensor;

[0061] The second data acquisition module includes:

[0062] The second ground surface acquisition sub-module is configured to obtain second ground surface data according to the spectral data.

[0063] Optionally, the second model acquisition sub-module includes:

[0064] The radar point cloud data acquisition unit is configured to acquire radar point cloud data; the radar point cloud data is obtained according to the radar data;

[0065] The high-altitude obstacle point cloud data acquisition unit is configured to determine high-altitude obstacle point cloud data according to the radar point cloud data and a preset discrimination threshold;

[0066] The second digital model acquisition unit is configured to acquire a second digital ground surface model, and the second digital ground surface model is obtained according to the radar point cloud data after removing the high-altitude obstacle point cloud data.

[0067] Optionally, the high-altitude obstacle point cloud data acquisition unit includes:

[0068] The feature acquisition sub-unit is configured to acquire the geometric features and spatial features of the radar point cloud data; the geometric features include local curvature and normal vector; the spatial features include spatial distribution density and spatial distribution spacing;

[0069] The first obstacle acquisition sub-unit is configured to use the point cloud data with the local curvature less than the local curvature threshold, the normal vector greater than the normal vector threshold and the spatial feature greater than the spatial threshold as the high-altitude obstacle point cloud data.

[0070] Optionally, the target placement area acquisition module includes:

[0071] A ground monitoring data acquisition sub-module, configured to acquire ground monitoring data for the monitoring area; the ground monitoring data includes monitoring data of ground cameras, ground signal towers, hydrometeorological monitoring stations, and already placed monitoring terminals;

[0072] A candidate placement area acquisition sub-module, configured to generate candidate placement areas according to the data of the ground sensors and the first surface data;

[0073] A target placement area acquisition sub-module, configured to determine the target placement area according to the candidate placement areas and the second surface data.

[0074] Optionally, the target placement area acquisition sub-module includes:

[0075] A spatial overlay analysis unit, configured to perform spatial overlay analysis on the candidate placement areas and the second surface data to obtain an analysis result;

[0076] A first target placement area acquisition unit, configured to determine the target placement area according to the analysis result.

[0077] Optionally, the monitoring terminal placement module includes:

[0078] An environmental information acquisition sub-module, configured to acquire environmental information of the target placement area;

[0079] An elevation information acquisition sub-module, configured to acquire elevation information for the monitoring area according to the second digital surface model;

[0080] A first placement data acquisition sub-module, configured to determine a target placement height and a target placement heading angle according to the elevation information and the environmental information;

[0081] A second placement data acquisition sub-module, configured to determine a target placement path according to the second digital surface model and the target placement area;

[0082] A final placement sub-module, configured to place the monitoring terminal according to the target placement height, the target placement heading angle, and the target placement path.

[0083] Correspondingly, an embodiment of the present invention discloses an electronic device, including: a processor, a memory, and a computer program stored on the memory and capable of running on the processor, where when the computer program is executed by the processor, each step of the above-mentioned embodiment of the monitoring terminal placement method is implemented.

[0084] Correspondingly, an embodiment of the present invention discloses a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, each step of the above embodiment of the method for monitoring terminal placement is implemented.

[0085] The embodiments of the present invention have the following advantages: By scientifically planning the scanning rules and automating data processing, the number and time of manual intervention are reduced, the placement cycle is significantly shortened, and efficient and rapid deployment of monitoring terminals is achieved. By customizing the second scanning rule based on the first result obtained by determining the first scanning rule of the monitoring area, multi-stage scanning is realized, enabling the placement of monitoring terminals to adapt to complex terrains and dynamic environments, ensuring the stability and reliability of the placement process, and further improving the placement efficiency. By combining the first surface data and the second surface data, the placement area can be accurately selected, avoiding repeated placement and ineffective placement, reducing waste of monitoring terminals, and lowering the overall placement cost. Through an efficient and accurate placement method, large-scale monitoring requirements can be met, providing technical support for the wide application in fields such as environmental monitoring, disaster warning, and agricultural management. BRIEF DESCRIPTION OF THE DRAWINGS

[0086] Figure 1 is a flowchart of the steps of an embodiment of the method for monitoring terminal placement according to the present invention;

[0087] Figure 2 is a schematic flowchart of determining the target placement area in an embodiment of the method for monitoring terminal placement according to the present invention;

[0088] Figure 3 is a block diagram of the structure of an embodiment of the device for the method for monitoring terminal placement according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0089] To make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0090] A monitoring terminal refers to a miniaturized device that is placed in a target area by an aircraft and integrates multiple types of sensors and a Beidou positioning module, mainly responsible for tasks such as environmental data collection, position marking and warning, and data transmission back, and has characteristics such as lightweight, high integration, multi-modal communication guarantee, and environmental adaptability.

[0091] One of the core concepts of the embodiments of the present invention is that by using the secondary scanning method of rough scanning plus fine scanning, generating two surface data and a digital surface model can maximally avoid the data error problem caused by a single sensor, thereby improving the placement efficiency and achieving accurate placement.

[0092] Refer to Figure 1, showing a step flowchart of an embodiment of a method for monitoring terminal placement according to the present invention, which may specifically include the following steps:

[0093] Step 101, obtain a first scan result for the monitoring area; the first scan result is obtained by using a first aircraft equipped with a first data acquisition device to scan the monitoring area along a first scan path;

[0094] In the fields of remote sensing, surveying and mapping, and environmental monitoring, a scan result usually refers to a data set generated after collecting data on a target area through a sensor device, including image data, surface data, etc. These data are used to construct a surface model or analyze surface features.

[0095] Among them, the monitoring area can be obtained by selecting the engineering area range on a satellite map. The first aircraft is a flying tool for performing the initial scan task, which can be various flying tools such as drones, helicopters, and fixed-wing aircraft. The first data acquisition device is a sensor device for obtaining surface information of the monitoring area, which can be various devices such as optical cameras, infrared sensors, radar sensors, lidar scanners, and spectral sensors; the first scan path refers to the flight route of the first aircraft for scanning within the monitoring area; the first scan result can exist in the form of point cloud data;

[0096] A point cloud is a collection of a large number of three-dimensional points. Each point records a position in space, usually represented by (X, Y, Z) coordinates. A point cloud can also contain other information, such as color, intensity, or reflectivity, etc.

[0097] Step 102, obtain a first digital surface model and first surface data according to the first scan result;

[0098] A digital surface model (DSM) is a three-dimensional model representing the elevation of the surface and all objects on it (such as buildings, trees, etc.). It reflects the true form of the surface, including natural surfaces and man-made structures.

[0099] In one embodiment, the first data acquisition device includes an optical camera, and the first scan result includes image data obtained by using a first aircraft equipped with an optical camera to scan the monitoring area along a first scan path. Step 102 may include the following sub-steps:

[0100] Sub-step S11, obtain a first digital surface model according to the image data;

[0101] An optical camera refers to a high-resolution aerial camera, generally used for taking ground images from the air. In the process of generating the first digital surface model using image data, existing technologies such as adjustment algorithms, triangulation, and encrypted matching can be used;

[0102] One implementation process of sub-step S11 can be as follows:

[0103] The optical camera mounted on the aircraft takes pictures of the monitoring area along the first scanning path to obtain multiple overlapping two-dimensional photos. During the process, it can be required that the forward overlap rate, that is, the overlap rate of the front and back photos, reaches 60%-80%, and the side overlap rate, that is, the overlap of the left and right photos, reaches 20%-40%, to ensure the accuracy of subsequent 3D reconstruction; then, through the free network adjustment algorithm, the geometric accuracy between each image is optimized, and then the feature points of each image are obtained. Through aerial triangulation, a sparse point cloud is generated; then, a dense point cloud is generated through the dense matching algorithm, and finally, the generated dense point cloud is interpolated into a grid model to obtain the first digital surface model.

[0104] The implementation of the above process can be achieved through aerial photogrammetry software such as Pix4D or Agisoft Metashape.

[0105] In one embodiment, the first data acquisition device includes an infrared sensor, and the first scan result includes infrared imaging data obtained by scanning the monitoring area along the first scanning path by the first aircraft carrying the infrared sensor. Step 102 may include the following sub-steps:

[0106] Sub-step S21, obtaining the first surface data according to the infrared imaging data;

[0107] An infrared sensor is an electronic device that can detect and measure infrared radiation. It captures the infrared light emitted by the surface of an object, converts it into an electrical signal, and then generates thermal imaging data. By processing the infrared imaging data, surface features such as water bodies, vegetation, hard ground surfaces, animal and human frequent activity areas can be effectively extracted, and then the first surface data is generated.

[0108] Exemplarily, after obtaining the infrared imaging data, it is necessary to remove the noise in the thermal imaging data and calibrate the temperature of the thermal imaging data. Then, surface features are extracted from the processed data. For example, low-temperature areas can be rivers and lakes; forests and grasslands are identified through temperature distribution and texture features; roads and buildings are identified through high-temperature areas; animal footprints and human activity paths are identified through local temperature changes.

[0109] This process can be combined with the data of the optical camera for cross-verification to further improve the accuracy of surface features.

[0110] Step 103: Obtain a second scan result for the monitoring area; the second scan result is obtained by using a second aircraft equipped with a second data acquisition device to scan the monitoring area along a second scan path; the second scan path is determined according to the first scan result.

[0111] After a preliminary rough scan of the monitoring area, it is necessary to further perform a refined scan of the monitoring area. Among them, the first scan result can provide a reference for the second scan path.

[0112] For example, the first digital surface model can be imported into the aircraft supporting route planning software to generate a flight route. Its flight altitude can be the same as that of the first scan. If the terrain is flat, the flight altitude can be set in the corresponding aircraft control software; in case of special terrain, the first flight path can be called to directly follow the original flight route. It should be noted that the aircraft supporting route planning software can be various route planning software in the prior art, and the embodiments of the present invention do not limit this.

[0113] Step 104: Obtain a second digital surface model and second surface data according to the second scan result.

[0114] Since the scan route of the second scan and the type of sensor carried are both obtained from the first scan result, the second scan result is more refined than the first scan result, and the reference ratio of the generated second digital surface model and second surface data is also greater.

[0115] In one embodiment, the second sensor includes a radar, and the second scan result includes radar data obtained by using the second aircraft equipped with the radar to scan the monitoring area along the second scan path.

[0116] Sub-step S31: Obtain a second digital surface model according to the radar data.

[0117] A radar is a device that uses radio waves to detect targets. By emitting electromagnetic waves and receiving reflected signals, it measures the distance, speed, and shape of the targets.

[0118] After obtaining the radar data, it is necessary to further process these radar data to generate a more accurate digital surface model.

[0119] In one embodiment, sub-step S31 may include the following sub-steps:

[0120] Sub-step S311: Obtain radar point cloud data; the radar point cloud data is obtained according to the radar data.

[0121] Radar point cloud data is three-dimensional point cloud data obtained after scanning a monitoring area with a radar, recording the spatial position information of the ground surface and objects thereon.

[0122] Sub-step S312, determine the high-altitude obstacle point cloud data according to the radar point cloud data and a preset discrimination threshold;

[0123] According to a preset discrimination threshold, filter out the high-altitude obstacle point cloud data in the radar point cloud data that may pose a threat to the flight of the UAV. This discrimination threshold can be set according to the usage scenario and combined with usage experience.

[0124] Sub-step S313, obtain a second digital surface model, where the second digital surface model is obtained from the radar point cloud data after removing the high-altitude obstacle point cloud data.

[0125] Remove the point cloud data marked as high-altitude obstacles from the radar point cloud data. And interpolate the remaining point cloud data into a regular grid model, the second digital surface model.

[0126] For example, when there is a forest area in the monitoring area, after removing the point cloud data of overly tall tree crowns according to the discrimination threshold, the remaining point cloud data can be used for the second digital surface model and further for flight path planning.

[0127] In one embodiment, sub-step S312 may further include the following sub-steps:

[0128] Sub-step S3121, obtain the geometric features and spatial features of the radar point cloud data; the geometric features include local curvature and normal vector; the spatial features include spatial distribution density and spatial distribution spacing;

[0129] Local curvature reflects the degree of curvature of a certain point in the point cloud data. For high-altitude obstacles, its local curvature usually has a large difference compared with conventional surface factors. For example, as one of the high-altitude obstacles, the local curvature of an electric wire is usually small, indicating that its surface is relatively smooth or linear. The normal vector is a vector perpendicular to the direction of the point cloud surface. For high-altitude obstacles, the direction of the normal vector is usually relatively consistent, indicating that its surface has a certain regularity. Spatial distribution density: Spatial distribution density refers to the density of the point cloud in space. The point cloud of high-altitude obstacles usually has a high distribution density because the obstacle occupies a certain volume in space. Spatial distribution spacing is the distance between points in the point cloud. The point cloud spacing of high-altitude obstacles is usually relatively uniform, indicating that its structure has a certain regularity.

[0130] According to these four indicators and a preset discrimination threshold, the point cloud data of high-altitude obstacles can be efficiently removed;

[0131] Sub-step S3122: Use the point cloud data with local curvature less than the local curvature threshold, normal vector greater than the normal vector threshold, and spatial feature greater than the spatial threshold as the high-altitude obstacle point cloud data.

[0132] Exemplarily, linear obstacles such as wires and cableways have approximately cylindrical geometric features, and their surface curvature theoretically satisfies k = 1 / r (where k is the local curvature and r is the cable radius). For example, the typical power line radius ranges from 5 to 30 mm, corresponding to a curvature of 0.03 to 0.2 mm. -1 ; Correspondingly, the curvature can be judged by calculating the minimum eigenvalue of the covariance matrix within the point cloud neighborhood; the discrimination threshold can be set to 0.3 mm. -1 Use the point cloud data with local curvature greater than this threshold as one of the candidate point cloud data for high-altitude obstacles.

[0133] For the discrimination threshold, in addition to setting it according to experience, it is also possible to obtain the labeled wire and non-wire point cloud data and use machine learning algorithms such as support vector machines and random forests to train this data to learn the optimal threshold for distinguishing between the two.

[0134] In one embodiment, the second sensor includes a spectral sensor, and the scanning result includes spectral data obtained by scanning the monitoring area along the second scanning path by the second aircraft equipped with the spectral sensor; step 104 may include the following sub-steps:

[0135] Sub-step S41: Obtain the second ground surface data according to the spectral data.

[0136] An optical sensor is a device that can capture the reflection or radiation characteristics of a target object at different wavelengths. Generally, different objects have different spectral data. According to the scanned spectral data and the preset spectral data mapping rules, different objects on the ground surface can be distinguished, and then the second ground surface data can be generated.

[0137] Step 105: Determine the target delivery area according to the first ground surface data and the second ground surface data.

[0138] In one embodiment, step 105 may include the following sub-steps:

[0139] Sub-step S51: Obtain the ground monitoring data for the monitoring area; the ground monitoring data includes the monitoring data of ground cameras, ground signal towers, hydrological and meteorological monitoring stations, and the already deployed monitoring terminals.

[0140] Before confirming the target delivery area, in addition to using the recognition algorithms in the prior art, the embodiments of the present invention also combine the data of the ground sensor network to assist in analyzing the deliverable areas. These ground sensor network data can include the monitoring data of ground cameras, ground signal towers, hydrometeorological monitoring stations, and deployed monitoring terminals, which can provide real-time conditions and environmental information about the monitoring area, such as traffic flow, weather conditions, hydrological conditions, and other various information.

[0141] Sub-step S52, generate a candidate deliverable area according to the data of the ground sensor and the first surface data;

[0142] By combining the ground sensor data and the first surface data, areas that are initially suitable for delivery can be identified, and the selection of these areas can be determined by rules formulated in advance according to business scenarios and experience.

[0143] Sub-step S53, determine the target delivery area according to the candidate deliverable area and the obtained second surface data.

[0144] Since the second surface data is determined by spectral information, it can provide more detailed compositional information different from the first surface information, such as vegetation type, soil type, water pollution degree, etc. These information helps to further refine the selection of the delivery area and ensure that the resources delivered can target specific surface characteristics or environmental problems.

[0145] In one embodiment, sub-step S53 may include the following sub-steps:

[0146] Sub-step S531, perform a spatial overlay analysis on the candidate deliverable area and the second surface data to obtain an analysis result;

[0147] Spatial overlay analysis is a commonly used technique in Geographic Information System (GIS). It involves overlaying two or more spatial data sets under the same geographic reference system to analyze their spatial relationships.

[0148] Since the candidate deliverable area and the second surface information are generated by different sensors respectively, their coordinate systems may not be consistent. Therefore, they need to be projected and registered and converted to the same coordinate system; Projection refers to the process of converting three-dimensional information on the earth's surface, such as satellite images, aerial photos, etc., into a representation on a two-dimensional plane. Different projection methods will retain or distort certain features of the earth's surface to adapt to different application requirements. Registration refers to the process of aligning two or more images or data sets from different sources, different times, or different perspectives to the same spatial coordinate system. The purpose of registration is to ensure that these images or data sets are geographically consistent for subsequent analysis and processing.

[0149] Among these surface information, there are a large number of boundaries, such as wires, buildings, etc. Obtaining these boundaries can be achieved through existing technologies such as the Candy edge detection algorithm or the Sobel algorithm edge detection algorithm. These boundary lines may not be clear enough, so methods such as curve fitting need to be used for refinement and repair to make the boundaries more accurate.

[0150] After processing the candidate drop regions and the second surface data, the candidate drop regions and the second surface data are superimposed to analyze the relationship between the two. For example, areas that are not suitable for dropping, such as water bodies or buildings, are excluded, and finally the suitable dropping areas are determined;

[0151] Such multiple operations can ensure that the generated target drop region has clear edges and greatly reduce the misjudgment risk of a single sensor.

[0152] Sub-step S532, determine the target drop region according to the analysis result.

[0153] Refer to Figure 2 , which shows a schematic flowchart of determining the target drop region in an embodiment of the monitoring terminal dropping method of the present invention.

[0154] First, during the output process of the preliminary throwable region (shp1), a high-definition camera and an infrared thermal imager are first used as the carried sensors. Among them, the high-definition camera is used to capture high-resolution images and provide detailed visual information of the surface; the infrared thermal imager is used to detect the thermal distribution of the surface and identify the thermal anomaly regions. Then, texture analysis is performed on the high-resolution images to identify different features and objects on the surface. Thermal anomaly detection is performed on the thermal distribution data to find possible heat sources or anomaly regions. After excluding the anomaly regions, the remaining regions are output as the preliminary throwable region (shp1);

[0155] During the further identification of the fine throwable region (shp2), multi-spectral sensors and hyperspectral sensors are used. The multi-spectral sensor can capture spectral information in multiple bands and provide detailed spectral characteristics of the surface. The hyperspectral sensor can capture more and finer spectral bands and provide higher-precision spectral classification information. The spectral sensor obtains the spectral characteristic data of the key bands. Classification processing is performed according to the spectral band characteristic data, so that different substances and coverage types on the surface can be identified. Then, boundary optimization is combined with the data of shp1, and finally the fine throwable region is output. That is, the target drop region.

[0156] Step 106, drop the monitoring terminal according to the second digital surface model and the target drop region.

[0157] In one embodiment, step 106 may include the following sub-steps:

[0158] Sub-step S61, obtaining environmental information of the target delivery area;

[0159] Among them, the environmental information may include meteorological conditions such as wind direction, wind force, temperature, humidity, etc. These information will affect the delivery accuracy and stability of the monitoring terminal. For example, wind direction and wind force will affect the falling trajectory of the monitoring terminal.

[0160] Sub-step S62, obtaining elevation information for the monitoring area according to the second digital surface model;

[0161] The elevation information is the altitude and undulation of the terrain.

[0162] Sub-step S63, determining the target delivery height and the target delivery course angle according to the elevation information and the environmental information;

[0163] Determine the safe delivery height according to the elevation information and the environmental information.

[0164] Exemplarily, the implementation method may be to convert the point cloud data into a grid elevation map. The resolution can be based on the flight accuracy requirements, and the local maximum elevation is calculated through a sliding window to generate a safe flight height layer. And according to the wind direction and wind force, calculate the course angle compensation value of the aircraft to offset the crosswind drift and ensure the delivery accuracy. The calculation method can adopt existing technologies such as dead reckoning;

[0165] Sub-step S64, determining the target delivery path according to the second digital surface model and the target delivery area;

[0166] Exemplarily, when planning the delivery path of the aircraft, when the target delivery area is a regularly shaped area, a reciprocating flight path can be adopted; when the target delivery area is an irregularly shaped area, a spiral flight path can be adopted; and the path can be dynamically adjusted through the D*Lite algorithm during the process. The D*Lite algorithm is a dynamic path planning algorithm proposed in 2002. Its advantage is that it can use the information of the first calculated path to dynamically plan the path.

[0167] Sub-step S65, delivering the monitoring terminal according to the target delivery height, the target delivery course angle and the target delivery path.

[0168] Exemplarily, the above parameters can be integrated, and the falling trajectory of the monitoring terminal can be calculated through a ballistics model to achieve precise delivery.

[0169] By scientifically planning scanning rules and automating data processing, the number and time of manual intervention are reduced, the deployment cycle is significantly shortened, and efficient and rapid monitoring terminal deployment is achieved. By customizing the second scanning rule based on the first result obtained by determining the first scanning rule for the monitoring area, multi-stage scanning is realized, enabling the deployment of monitoring terminals to adapt to complex terrain and dynamic environments, ensuring the stability and reliability of the deployment process, and further improving the deployment efficiency. By combining the first surface data and the second surface data, the deployment area can be accurately selected, avoiding repeated and ineffective deployments, reducing waste of monitoring terminals, and lowering the overall deployment cost. Through the efficient and accurate deployment method, large-scale monitoring requirements can be met, providing technical support for wide applications in fields such as environmental monitoring, disaster warning, and agricultural management.

[0170] It should be noted that for the method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the embodiments of the present invention are not limited by the described action sequences, because according to the embodiments of the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential for the embodiments of the present invention.

[0171] Refer to Figure 3 , which shows a structural block diagram of an embodiment of a monitoring terminal deployment method device of the present invention, and specifically may include the following modules:

[0172] The first scan result acquisition module 201 is configured to acquire a first scan result for the monitoring area; the first scan result is obtained by using a first aircraft equipped with a first data acquisition device to scan the monitoring area along a first scan path;

[0173] In the fields of remote sensing, surveying and mapping, and environmental monitoring, the scan result usually refers to a data set generated after data acquisition of a target area by a sensor device, including image data, surface data, etc. These data are used to construct a surface model or analyze surface features.

[0174] Among them, the monitoring area can be obtained by selecting the engineering area range on the satellite base map. The first aircraft is a flight tool for performing the initial scan task, which can be various flight tools such as drones, helicopters, and fixed-wing aircraft. The first data acquisition device is a sensor device for acquiring surface information of the monitoring area, which can be various devices such as optical cameras, infrared sensors, radar sensors, laser scanners, and spectral sensors; the first scan path refers to the flight route of the first aircraft for scanning in the monitoring area; the first scan result can exist in the form of point cloud data;

[0175] A point cloud is a collection of a large number of three-dimensional points, where each point records a position in space, usually represented by (X, Y, Z) coordinates. A point cloud can also contain other information, such as color, intensity, or reflectivity, etc.

[0176] The first data acquisition module 202 obtains a first digital surface model and first surface data according to the first scan result.

[0177] A digital surface model (DSM) is a three-dimensional model that represents the elevation of the surface and all objects on it (such as buildings, trees, etc.). It reflects the true shape of the surface, including the natural surface and man-made structures.

[0178] The second scan result acquisition module 203 acquires a second scan result for the monitoring area; the second scan result is obtained by using a second aircraft equipped with a second data acquisition device to scan the monitoring area along a second scan path; the second scan path is determined according to the first scan result.

[0179] After a preliminary rough scan of the monitoring area, it is necessary to further perform a refined scan of the monitoring area. Among them, the first scan result can provide a reference for the second scan path.

[0180] For example, the first digital surface model can be imported into the aircraft supporting route planning software to generate a flight route. Its flight altitude can be the same as that of the first scan. If the terrain is flat, the flight altitude can be set in the corresponding aircraft control software; in case of special terrain, the first flight path can be called and the original flight route can be directly used. It should be noted that the aircraft supporting route planning software can be various route planning software in the prior art, and the embodiments of the present invention do not make any limitations thereto.

[0181] The second data acquisition module 204 obtains a second digital surface model and second surface data according to the second scan result.

[0182] Since the scan route of the second scan and the type of sensor carried are both obtained from the first scan result, the second scan result is more refined than the first scan result, and the reference ratio of the generated second digital surface model and second surface data is also greater.

[0183] The target delivery area acquisition module 205 is used to determine the target delivery area according to the first surface data and the second surface data.

[0184] The monitoring terminal delivery module 206 is used to deliver the monitoring terminal according to the second digital surface model and the target delivery area.

[0185] In one embodiment, the first data acquisition device includes an optical camera, and the first scan result includes image data obtained by scanning the monitoring area along the first scan path by the first aircraft carrying the optical camera.

[0186] The first data acquisition module includes:

[0187] A first model acquisition sub-module, configured to obtain a first digital terrain model according to the image data.

[0188] In one embodiment, the first data acquisition device includes an infrared sensor, and the first scan result includes infrared imaging data obtained by scanning the monitoring area along the first scan path by the first aircraft carrying the infrared sensor.

[0189] The first data acquisition module includes:

[0190] A first terrain acquisition sub-module, configured to obtain first terrain data according to the infrared imaging data.

[0191] In one embodiment, the second sensor includes a radar, and the second scan result includes radar data obtained by scanning the monitoring area along the second scan path by the second aircraft carrying the radar.

[0192] The second data acquisition module includes:

[0193] A second model acquisition sub-module, configured to obtain a second digital terrain model according to the radar data.

[0194] In one embodiment, the second sensor includes a spectral sensor, and the scan result includes spectral data obtained by scanning the monitoring area along the second scan path by the second aircraft carrying the spectral sensor.

[0195] The second data acquisition module includes:

[0196] A second terrain acquisition sub-module, configured to obtain second terrain data according to the spectral data.

[0197] In one embodiment, the second model acquisition sub-module includes:

[0198] A radar point cloud data acquisition unit, configured to acquire radar point cloud data; the radar point cloud data is obtained according to the radar data;

[0199] An obstacle point cloud data acquisition unit, configured to determine high-altitude obstacle point cloud data according to the radar point cloud data and a preset discrimination threshold.

[0200] A second digital model acquisition unit, configured to acquire a second digital surface model, where the second digital surface model is obtained from the radar point cloud data after removing the aerial obstacle point cloud data.

[0201] In one embodiment, the obstacle point cloud data acquisition unit includes:

[0202] A feature acquisition subunit, configured to acquire the geometric features and spatial features of the radar point cloud data; the geometric features include local curvature and normal vector; the spatial features include spatial distribution density and spatial distribution spacing;

[0203] A first obstacle acquisition subunit, configured to use the point cloud data with local curvature less than the local curvature threshold, normal vector greater than the normal vector threshold, and spatial features greater than the spatial threshold as the aerial obstacle point cloud data.

[0204] In one embodiment, the target delivery area acquisition module includes:

[0205] A ground monitoring data acquisition sub-module, configured to acquire the ground monitoring data for the monitoring area; the ground monitoring data includes the monitoring data of ground cameras, ground signal towers, hydrometeorological monitoring stations, and already deployed monitoring terminals;

[0206] A candidate deployable area acquisition sub-module, configured to generate a candidate deployable area according to the data of the ground sensors and the first surface data;

[0207] A target delivery area acquisition sub-module, configured to determine the target delivery area according to the candidate deployable area and the second surface data.

[0208] In one embodiment, the target delivery area acquisition sub-module includes:

[0209] A spatial overlay analysis unit, configured to perform a spatial overlay analysis on the candidate deployable area and the second surface data to obtain an analysis result;

[0210] A first target delivery area acquisition unit, configured to determine the target delivery area according to the analysis result.

[0211] In one embodiment, the monitoring terminal deployment module includes:

[0212] An environment information acquisition sub-module, configured to obtain the environment information of the target delivery area;

[0213] An elevation information acquisition sub-module, configured to obtain the elevation information for the monitoring area according to the second digital surface model;

[0214] The first delivery data acquisition sub-module is used to determine the target delivery height and the target delivery course angle according to the elevation information and the environmental information;

[0215] The second delivery data acquisition sub-module is used to determine the target delivery path according to the second digital surface model and the target delivery area;

[0216] The final delivery sub-module is used to deliver the monitoring terminal according to the target delivery height, the target delivery course angle and the target delivery path.

[0217] Through scientific planning of the scanning rules and automated data processing, the number and time of manual intervention are reduced, the delivery cycle is significantly shortened, and efficient and rapid deployment of the monitoring terminal is achieved. By customizing the second scanning rule based on the first result obtained by determining the first scanning rule of the monitoring area, multi-stage scanning is realized, enabling the delivery of the monitoring terminal to adapt to complex surfaces and dynamic environments, ensuring the stability and reliability of the delivery process, and further improving the delivery efficiency. By combining the first surface data and the second surface data, the delivery area can be accurately selected, avoiding repeated delivery and ineffective delivery, reducing the waste of monitoring terminals, and lowering the overall delivery cost. Through the efficient and accurate delivery method, large-scale monitoring requirements can be met, providing technical support for the wide application in fields such as environmental monitoring, disaster warning, and agricultural management.

[0218] For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and for the relevant parts, refer to the partial description of the method embodiment.

[0219] The embodiment of the present invention also provides an electronic device, including:

[0220] It includes a processor, a memory, and a computer program stored on the memory and capable of running on the processor. When the computer program is executed by the processor, it realizes each process of the above-mentioned method embodiment for delivering a monitoring terminal, and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0221] The embodiment of the present invention also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by the processor, it realizes each process of the above-mentioned method embodiment for delivering a monitoring terminal, and can achieve the same technical effect. To avoid repetition, it will not be elaborated here.

[0222] Each embodiment in this specification is described in a progressive manner. The key point of each embodiment is to illustrate the differences from other embodiments. The same or similar parts among the embodiments can be referred to each other.

[0223] Those skilled in the art should understand that the embodiments of the present invention can be provided as methods, devices, or computer program products. Therefore, the embodiments of the present invention can take the form of all-hardware embodiments, all-software embodiments, or embodiments combining software and hardware aspects. Moreover, the embodiments of the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0224] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal devices generate a device for realizing the functions specified in Figure 1 one or more flows and / or Figure 1 blocks.

[0225] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal devices to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device realizes the functions specified in Figure 1 one or more flows and / or Figure 1 blocks.

[0226] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal devices, so that a series of operation steps are executed on the computer or other programmable terminal devices to generate a computer-implemented process. Therefore, the instructions executed on the computer or other programmable terminal devices provide steps for realizing the functions specified in Figure 1 one or more flows and / or Figure 1 blocks.

[0227] Although the preferred embodiments of the embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they know the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments and all changes and modifications falling within the scope of the embodiments of the present invention.

[0228] Finally, it should also be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or terminal device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or terminal device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or terminal device comprising said element.

[0229] The above has introduced in detail a monitoring terminal placement method, device, equipment and medium provided by the present invention. Specific examples are used in this text to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present invention.

Claims

1. A method for monitoring terminal placement, characterized in that The method includes: Obtaining a first scan result for a monitoring area; the first scan result is obtained by scanning the monitoring area along a first scan path using a first aircraft equipped with a first data collection device; Obtaining a first digital surface model and first surface data according to the first scan result; Obtaining a second scan result for the monitoring area; the second scan result is obtained by scanning the monitoring area along a second scan path using a second aircraft equipped with a second data collection device; the second scan path is determined according to the first scan result; Obtaining a second digital surface model and second surface data according to the second scan result; Determining a target delivery area according to the first surface data and the second surface data; Delivering a monitoring terminal according to the second digital surface model and the target delivery area.

2. The monitoring terminal placement method according to claim 1, wherein The first data collection device includes an optical camera, and the first scan result includes image data obtained by scanning the monitoring area along the first scan path using the first aircraft equipped with the optical camera; The obtaining of the first digital surface model according to the first scan result includes: Obtaining a first digital surface model according to the image data.

3. The method for monitoring terminal delivery according to claim 2, wherein The first data collection device includes an infrared sensor, and the first scan result includes infrared imaging data obtained by scanning the monitoring area along the first scan path using the first aircraft equipped with the infrared sensor; The obtaining of the first surface data according to the first scan result includes: Obtaining first surface data according to the infrared imaging data.

4. A method for monitoring terminal delivery according to claim 1, characterized in that, The second data collection device includes a radar, and the second scan result includes radar data obtained by scanning the monitoring area along the second scan path using the second aircraft equipped with the radar; The obtaining of the second digital surface model according to the second scan result includes: Obtaining a second digital surface model according to the radar data.

5. The monitoring terminal delivery method according to claim 4, characterized in that, The second data collection device includes a spectral sensor, and the scan result includes spectral data obtained by scanning the monitoring area along the second scan path using the second aircraft equipped with the spectral sensor; The obtaining of the second surface data according to the second scan result includes: Obtaining second surface data according to the spectral data.

6. The monitoring terminal placement method according to claim 4, wherein The obtaining of the second digital surface model according to the radar data includes: Obtaining radar point cloud data; the radar point cloud data is obtained according to the radar data; Determining high-altitude obstacle point cloud data according to the radar point cloud data and a preset discrimination threshold; Obtaining a second digital surface model, where the second digital surface model is obtained according to the radar point cloud data after removing the high-altitude obstacle point cloud data.

7. A method for monitoring terminal delivery according to claim 6, characterized in that, The preset discrimination threshold includes a local curvature threshold, a normal vector threshold, and a preset space threshold. The determining of the high-altitude obstacle point cloud data according to the radar point cloud data and the preset discrimination threshold includes: Obtain the geometric features and spatial features of the radar point cloud data; the geometric features include local curvature and normal vector; the spatial features include spatial distribution density and spatial distribution spacing; Take the point cloud data with local curvature less than the local curvature threshold, normal vector greater than the normal vector threshold and spatial features greater than the spatial threshold as the high-altitude obstacle point cloud data.

8. A method for monitoring terminal placement according to claim 3, characterized in that The determining the target placement area according to the first surface data and the second surface data includes: Obtain the ground monitoring data for the monitoring area; the ground monitoring data includes the monitoring data of ground cameras, ground signal towers, hydrometeorological monitoring stations and the already placed monitoring terminals; Generate a candidate deployable area according to the data of the ground sensor and the first surface data; Determine the target placement area according to the candidate deployable area and the second surface data.

9. The monitoring terminal placement method according to claim 8, wherein, The determining the target placement area according to the candidate deployable area and the second surface data includes: Perform a spatial overlay analysis on the candidate deployable area and the second surface data to obtain an analysis result; Determine the target placement area according to the analysis result.

10. The monitoring terminal delivery method according to claim 1, wherein The deploying the monitoring terminal according to the second digital surface model and the target placement area includes: Obtain the environmental information of the target placement area; Obtain the elevation information for the monitoring area according to the second digital surface model; Determine the target placement height and target placement heading angle according to the elevation information and the environmental information; Determine the target placement path according to the second digital surface model and the target placement area; Deploy the monitoring terminal according to the target placement height, target placement heading angle and target placement path.

11. A monitoring terminal delivery device, characterized in that, The device includes: A first scan result acquisition module, configured to obtain a first scan result for the monitoring area; the first scan result is obtained by scanning the monitoring area along a first scan path using a first aircraft equipped with a first data acquisition device; A first data acquisition module, which obtains a first digital surface model and first surface data according to the first scan result; A second scan result acquisition module, which obtains a second scan result for the monitoring area; the second scan result is obtained by scanning the monitoring area along a second scan path using a second aircraft equipped with a second data acquisition device; the second scan path is determined according to the first scan result; A second data acquisition module, which obtains a second digital surface model and second surface data according to the second scan result; A target placement area acquisition module, configured to determine the target placement area according to the first surface data and the second surface data; A monitoring terminal deployment module, configured to deploy the monitoring terminal according to the second digital surface model and the target placement area.

12. An electronic device, characterized in that, Includes: A processor, a memory, and a computer program stored on the memory and capable of running on the processor. When the computer program is executed by the processor, it implements the steps of a method for deploying a monitoring terminal according to any one of claims 1-10.

13. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of a method for monitoring terminal delivery as described in any one of claims 1-10 are implemented.

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