Land quality field sampling monitoring method based on electronic fence constraint

Abstract

The invention provides a land quality field sampling monitoring method based on electronic fence constraint, and relates to the field of geological survey. By acquiring the field image and automatically adjusting the preset sampling point position, the sampling point position can be optimized according to the actual ground feature condition, and the rationality and operability of the sampling point position are improved. The terrain is identified according to the field image and the pre-stored map, and the electronic fence is adaptively generated, so that the spatial constraint is more flexible and accurate. The shape and the range of the electronic fence can be optimized according to actual topographic features, and it is ensured that the sampling behavior is carried out within an effective and safe range. The position information of the sampling personnel and the sampling equipment is acquired in real time, and whether the sampling equipment follows the sampling personnel or not and is located in the electronic fence or not is judged, so that the sampling process is dynamically monitored in real time. Only when all conditions are met, the data are allowed to be uploaded, so that the possibility that the coordinate data are manually tampered is fundamentally eradicated, and the vulnerability of a quality control link in the prior art is effectively made up.

Description

Technical Field

[0001] This invention relates to the field of geological survey technology, and more specifically, to a method for field sampling and monitoring of land quality based on electronic fence constraints. Background Technology

[0002] In the field of land quality field sampling data collection and quality control technology, the core requirements are the verification of the authenticity of sampling locations and the precise correlation between data and spatial coordinates during field surveys. This field needs to use technical means to ensure the spatial source traceability reliability of survey data such as soil composition, geological background, and pollution status, ultimately providing a foundation of "reliable location + valid data" for applications such as land quality assessment, pollution source tracing, and resource planning.

[0003] The existing model relies solely on GPS to passively acquire location information and fill it into a fixed form. The "sampling point coordinates" field in the fixed form generally supports manual editing. In order to avoid the extra workload of resampling after the deviation exceeds the standard, some investigators may manually modify the GPS coordinate data, allowing false information that does not meet the requirements to enter the database. This not only undermines the objectivity and accuracy of the survey data, but also seriously misleads subsequent decision-making work such as land quality assessment and resource planning based on this data.

[0004] Therefore, existing technologies lack spatial constraint mechanisms, which may cause sampling to deviate from preset points, directly affecting the correlation between data and spatial coordinates. More critically, coordinate data is easily tampered with, resulting in significant vulnerabilities in the quality control process. Summary of the Invention

[0005] The problem that this invention aims to solve is that the existing technology lacks a spatial constraint mechanism, which may cause the sampling behavior to deviate from the preset point.

[0006] To address the aforementioned problems, in a first aspect, the present invention provides a method for field sampling and monitoring of land quality based on electronic fence constraints, comprising: Acquire real-world images of the sampling area; Based on the actual image and the sampling point adjustment rules, the positions of the preset sampling points are automatically adjusted. The preset sampling points are sampling points that are uniformly deployed according to the preset deployment rules. Based on real-world images and pre-stored maps, the terrain is identified, and an electronic fence is generated adaptively according to the terrain. The system acquires the location information of the sampling personnel and the location information of the sampling device bound to the sampling personnel, and determines whether the sampling device follows the sampling personnel. The sampling probe of the sampling device is equipped with a positioning module, which is used to acquire location information in real time when the device is powered on. If the sampling device follows the sampling personnel, then determine whether the sampling device's location information is within the electronic fence; If the sampling equipment is located within an electronic fence, the sampling personnel are allowed to upload the sampling labels and soil data to the information management terminal.

[0007] Optionally, the field image includes an address marker image; Before automatically adjusting the sampling point positions based on the actual image and preset sampling point layout rules, the process also includes: Based on the location information of the sampling personnel, when the distance between the sampling personnel and the sampling point is less than the first monitoring distance, the movement trajectory of the sampling personnel is monitored in real time to determine the estimated time for the sampling personnel to reach the sampling point; If the actual time taken for the sampling personnel to reach the sampling point is greater than or equal to the estimated time, it is preliminarily determined that the sampling personnel have arrived in the vicinity of the sampling point. Identify real-time markers or real-time address information in address marker images, and identify multiple target markers in high-resolution satellite imagery around sampling points. Compare real-time markers with target markers and compare real-time address information with address information of sampling points. If a real-time marker is identical to any target marker and the real-time address information is in the same area as the address information of the sampling point, then it is confirmed that the sampling personnel have arrived around the sampling point.

[0008] Optionally, the field image includes a land image of the location of the sampling point; The automatic adjustment of preset sampling point positions based on real-world images and sampling point adjustment rules includes: Identify target regions in land images that are related to the sampling targets set at the sampling points, and extract the boundaries of the target regions; Based on the location information of the sampling points and the boundary of the target area, determine the boundary distance between the sampling points and the boundary. When the boundary distance is less than or equal to the preset distance, the sampling point is moved into the target area until the boundary distance of the sampling point is greater than the preset distance.

[0009] Optionally, the step of identifying the terrain based on real-world images and pre-stored maps, and adaptively generating an electronic fence based on the terrain, includes: Based on the preset dimensions, an initial electronic fence is generated with the sampling point as the center; The actual images are matched with the pre-stored map to identify the terrain where the sampling point is located and the travel path to the sampling point. The terrain includes fields, mountains, wetlands and lakes. When there is a travel path and the terrain is a plain, the initial electronic fence will be determined as the final electronic fence. When there is no travel path and the terrain is mountainous, wetland or lake, the initial electronic fence will be adjusted to a three-dimensional electronic fence. The three-dimensional electronic fence is a funnel-shaped electronic fence with a preset size as the base and a height equal to the sampling depth.

[0010] Optionally, obtaining the location information of the sampling personnel and the location information of the sampling device bound to the sampling personnel, and determining whether the sampling device follows the sampling personnel, includes: Based on the location information of the sampling personnel and the sampling equipment, determine the separation distance between the sampling personnel and the sampling equipment; If the separation distance is less than or equal to the preset separation distance, the sampling device will follow the sampling personnel. If the separation distance is greater than the preset separation distance, the sampling equipment and the sampling personnel are separated.

[0011] Optionally, the sampling probe of the sampling device is also equipped with a pressure sensor, which is used to monitor the sampling pressure of the sampling probe; If the sampling device's location information is within an electronic fence, allowing sampling personnel to upload sampling labels and soil data to the information management terminal, the following additional steps are also included: If the obtained sampling pressure is greater than the preset pressure, the sampling time will be started and the continuity of the sampling pressure will be monitored. If the sampling pressure is greater than the preset pressure for an extended period of time, and the sampling time is less than or equal to the preset maximum sampling time, then the current sampling is considered valid. If the sampling time exceeds the preset maximum sampling time or the sampling pressure exceeds the preset pressure and is interrupted within the preset duration, the current sampling is determined to be invalid.

[0012] Optionally, the method further includes: if the current sampling is valid, synchronously recording the environmental parameters at the sampling time and associating the environmental parameters with the sampled sample, wherein the environmental parameters include temperature and humidity, soil moisture content and pH value, wherein the environmental parameters are provided by a temperature and humidity meter set on the sampling device, a moisture content sensor and a pH value sensor set on the sampling probe; To encode the sample, the sample, sampling location information, sampling personnel information, sampling time and environmental parameters are associated with the sample code to generate a label, which can be printed and pasted on the surface of the sample storage container. When samples are sent for testing, the sample code is identified, environmental parameters are extracted, and the environmental parameters are compared with historical environmental data at the sampling point. If the two are consistent, the sample verification is confirmed to be valid.

[0013] Secondly, the present invention also provides a land quality field sampling and monitoring system based on electronic fence constraints, comprising: The field image acquisition module is used to acquire field images of the sampling area; The sampling point adjustment module is used to automatically adjust the position of preset sampling points according to the actual image and sampling point adjustment rules, wherein the preset sampling points are sampling points uniformly arranged according to preset layout rules; The electronic fence generation module is used to identify the terrain based on real-world images and pre-stored maps, and adaptively generate electronic fences according to the terrain. The location monitoring module is used to acquire the location information of the sampling personnel and the location information of the sampling equipment bound to the sampling personnel, and to determine whether the sampling equipment follows the sampling personnel. The sampling probe of the sampling equipment is equipped with a positioning module, which is used to acquire location information in real time when the device is powered on. The location monitoring module is also used to determine whether the location information of the sampling device is within the electronic fence if the sampling device is following the sampling personnel; if the location information of the sampling device is within the electronic fence, the sampling personnel are allowed to upload the sampling label and soil data to the information management terminal.

[0014] Thirdly, the present invention provides an electronic device, including a memory and a processor; The memory is used to store computer programs; The processor is configured to, when executing the computer program, implement the land quality field sampling and monitoring method based on electronic fence constraints as described in the first aspect.

[0015] Fourthly, the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the land quality field sampling and monitoring method based on electronic fence constraints as described in the first aspect.

[0016] This invention provides a method for field sampling and monitoring of land quality based on electronic fence constraints. Compared with existing technologies, it has the following advantages: By acquiring real-world images and automatically adjusting the locations of preset sampling points, the system can optimize sampling point locations based on actual terrain features, avoiding the problem of preset points falling in unsuitable sampling areas and improving the rationality and operability of sampling point locations. Based on real-world images and pre-stored maps, the system identifies the terrain and adaptively generates electronic fences, making spatial constraints more flexible and precise. The shape and range of the electronic fence can be optimized according to actual terrain features, such as avoiding obstacles or dangerous areas, ensuring that sampling is conducted within an effective and safe range. Furthermore, by acquiring the location information of sampling personnel and equipment in real time and determining whether the sampling equipment follows the sampling personnel and is within the electronic fence, real-time and dynamic monitoring of the sampling process is achieved. Data upload is only allowed when all conditions are met, fundamentally eliminating the possibility of coordinate data being tampered with and effectively compensating for loopholes in the quality control chain of existing technologies. This ensures that the sampling data uploaded to the information management terminal has high authenticity, accuracy, and spatial traceability reliability, providing a foundation of "reliable location + valid data" for subsequent land quality assessment, pollution source tracing, and resource planning decisions. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating a land quality field sampling and monitoring method based on electronic fence constraints, provided as an embodiment of the present invention; Figure 2 This is a schematic diagram of the uniform layout of sampling points provided in an embodiment of the present invention; Figure 3 A schematic diagram of a pre-stored map and an electronic fence provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of a land quality field sampling and monitoring system based on electronic fence constraints, provided as an embodiment of the present invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application are described clearly and completely. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0020] To better understand the above technical solutions, the following will provide a detailed explanation of the technical solutions in conjunction with the accompanying drawings and specific implementation methods.

[0021] like Figure 1 As shown in the embodiment of this application, a land quality field sampling and monitoring method based on electronic fence constraints is provided, comprising: S1: Obtain the actual image of the sampling area.

[0022] S2: Automatically adjust the positions of preset sampling points according to the actual image and sampling point adjustment rules, wherein the preset sampling points are sampling points uniformly arranged according to preset layout rules.

[0023] S3: Based on real-world images and pre-stored maps, identify the terrain and adaptively generate electronic fences according to the terrain.

[0024] S4: Obtain the location information of the sampling personnel and the location information of the sampling device bound to the sampling personnel, and determine whether the sampling device follows the sampling personnel. The sampling probe of the sampling device is equipped with a positioning module, which is used to obtain the location information in real time when the device is powered on.

[0025] S5: If the sampling device follows the sampling personnel, determine whether the sampling device's location information is within the electronic fence.

[0026] S6: If the sampling equipment is located within the electronic fence, the sampling personnel are allowed to upload the sampling labels and soil data to the information management terminal.

[0027] In this embodiment, by introducing on-site image-assisted sampling point adjustment, terrain-adaptive electronic fence generation, and real-time location monitoring and data upload condition restrictions, the problems of insufficient verification of sampling location authenticity and inaccurate correlation between data and spatial coordinates in the prior art are effectively solved. Compared with the existing mode that only relies on GPS to passively obtain location information and allows manual modification of coordinate data, this application constructs an active and intelligent spatial constraint mechanism.

[0028] By acquiring real-world images and automatically adjusting the locations of preset sampling points, the system can optimize sampling point locations based on actual terrain features, avoiding the problem of preset points falling in unsuitable sampling areas and improving the rationality and operability of sampling point locations. Based on real-world images and pre-stored maps, the system identifies the terrain and adaptively generates electronic fences, making spatial constraints more flexible and precise. The shape and range of the electronic fence can be optimized according to actual terrain features, such as avoiding obstacles or dangerous areas, ensuring that sampling is conducted within an effective and safe range. Furthermore, by acquiring the location information of sampling personnel and equipment in real time and determining whether the sampling equipment follows the sampling personnel and is within the electronic fence, real-time and dynamic monitoring of the sampling process is achieved. Data upload is only allowed when all conditions are met, fundamentally eliminating the possibility of coordinate data being tampered with and effectively compensating for loopholes in the quality control chain of existing technologies. This ensures that the sampling data uploaded to the information management terminal has high authenticity, accuracy, and spatial traceability reliability, providing a foundation of "reliable location + valid data" for subsequent land quality assessment, pollution source tracing, and resource planning decisions.

[0029] The following is a detailed description of each step.

[0030] S1: Acquire on-site images of the sampling area. These on-site images include address marker images and land images of the sampling point locations. The images are real-world image data of the sampling area acquired through various imaging devices (e.g., drones, satellites, handheld cameras, etc.). The on-site images contain rich information such as the features of the sampling area, topography, and vegetation cover, providing a visual basis for sampling point adjustment, terrain identification, and electronic fence generation. Address marker images refer to visual information that reflects geographical location characteristics, such as road signs, building numbers, specific landmarks, and natural landscape features. Address marker images can serve as auxiliary information to more accurately identify and confirm the actual location of sampling personnel, especially in complex areas or areas lacking clear geographical coordinate references.

[0031] Before performing step S2, the method also includes: S11: Based on the location information of the sampling personnel, when the distance between the sampling personnel and the sampling point is less than the first monitoring distance, the movement trajectory of the sampling personnel is monitored in real time to determine the estimated time for the sampling personnel to reach the sampling point.

[0032] Specifically, the first monitoring distance is a preset threshold. When a sampling personnel enters this distance range, the system activates a more intensive monitoring mode. Real-time monitoring of movement trajectories means that the system continuously records the sampling personnel's location points and, based on this location data, combined with information such as their movement speed and direction, uses path planning algorithms or machine learning models to predict the time required for them to reach the sampling point. For example, the system can dynamically calculate an estimated time based on the sampling personnel's historical movement speed data, current terrain information, and the remaining distance to the sampling point.

[0033] S12: If the actual time taken for the sampling personnel to reach the sampling point is greater than or equal to the estimated time, it is preliminarily determined that the sampling personnel have arrived in the vicinity of the sampling point.

[0034] Specifically, if the actual time taken matches or slightly exceeds the previously predicted time (considering potential obstacles or brief stops during the actual journey), it is assumed that the sampling personnel have arrived at the approximate area of ​​the sampling point along the expected path. This provides a preliminary verification based on time logic, avoiding potential errors that may arise from judging solely by distance.

[0035] S13: Identify real-time markers or real-time address information in the address marker image, and identify multiple target markers in the high-resolution satellite image around the sampling point, compare the real-time markers with the target markers, and compare the real-time address information with the address information of the sampling point.

[0036] Specifically, real-time landmarks refer to identifiable objects or features with geographical indication in images captured or transmitted by sampling personnel on-site, such as specific trees, rocks, buildings, and road signs. Real-time address information refers to textual information extracted from on-site images, such as house numbers and street names. Simultaneously, the system pre-stores high-resolution satellite imagery of the area surrounding the sampling point, marking or identifying multiple target landmarks (such as specific land boundaries, water body shapes, road intersections, etc.) and the precise address information of the sampling point. The comparison process uses image recognition technology (such as feature point matching and deep learning models) to compare real-time landmarks with target landmarks to determine whether they are identical or similar. For address information, text matching or region matching is performed.

[0037] S14: If the real-time marker is the same as any target marker and the real-time address information is in the same area as the address information of the sampling point, then it is confirmed that the sampling personnel have arrived around the sampling point.

[0038] Specifically, the system only confirms that the sampling personnel have accurately arrived near the target sampling point when the real-time markers acquired on-site match at least one of the preset target markers, and the real-time address information acquired on-site and the preset address information of the sampling point are geographically located in the same area. This multi-verification mechanism significantly improves the accuracy and reliability of arrival judgment and effectively avoids misjudgments. Furthermore, the real-time markers can also be used to verify the location of the sampling personnel, preventing them from starting false sampling before reaching the vicinity of the sampling point.

[0039] S2: Automatically adjust the positions of preset sampling points according to the actual image and sampling point adjustment rules, wherein the preset sampling points are sampling points uniformly arranged according to preset layout rules.

[0040] Specifically, before conducting land quality geological sampling, the initial sampling locations are uniformly planned and determined within the sampling area according to specific layout rules (such as grid layout, random layout, etc.). Figure 2 As shown. In practice, these preset sampling points may fall in areas unsuitable for sampling, such as roads, buildings, and bodies of water. Therefore, these points need to be adjusted. For example, the system can use image recognition technology to analyze the features of land features in the field image, such as identifying areas unsuitable for sampling, such as hardened roads, water bodies, and densely vegetated areas. When the preset sampling points are located in these areas, the system will move the sampling points to the nearest suitable sampling area (such as farmland or grassland) according to preset adjustment rules, until the sampling points are located within the sampleable area. This adjustment can be based on distance-based translation or on repositioning based on the center of the area. Step S2 specifically includes the following steps.

[0041] S21: Identify target regions in the land image that are related to the sampling targets set at the sampling points, and extract the boundaries of the target regions. The target regions related to the sampling targets refer to specific land parcel types requiring land quality geological surveys, such as farmland, mountains, wetlands, forests, grasslands, and vegetated areas. Image processing techniques are used to distinguish specific regions matching the sampling targets from the land image. Boundary extraction refers to determining the precise contour of the target region. In specific implementations, image segmentation techniques, such as deep learning-based semantic segmentation models (e.g., U-Net, Mask R-CNN), can be used to train and recognize land images, thereby automatically identifying different types of sampling target regions. Alternatively, traditional image processing algorithms, such as edge detection (Canny, Sobel operators), region growing, and threshold segmentation, can be used in conjunction with preset texture, color, and shape features to identify target regions and extract their boundaries.

[0042] S22: Determine the boundary distance between the sampling point and the boundary based on the location information of the sampling point and the boundary of the target area.

[0043] S23: When the boundary distance is less than or equal to the preset distance, move the position of the sampling point into the target area until the boundary distance of the sampling point is greater than the preset distance.

[0044] Specifically, when a sampling point is too close to the boundary, it needs to be moved inside the target area to ensure the representativeness of the sampling point and ease of operation. The direction of movement is towards the center of the target area or away from the nearest boundary. A movement step size can be set, and the sampling point is moved one step away from the nearest boundary each time, and then the boundary distance is recalculated until the boundary distance meets the requirements. For example, the normal direction from the sampling point to the boundary can be calculated, and the sampling point can be moved inwards from the target area along that normal direction.

[0045] S3: Based on real-world images and pre-stored maps, identify the terrain and adaptively generate electronic fences according to the terrain.

[0046] Specifically, the pre-stored map refers to geographic information data pre-stored in the system, typically containing detailed information such as the geographic coordinates, topographic elevation, land cover classification, and road network of the sampling area. It can be high-resolution satellite imagery, topographic maps, geological maps, or digital elevation model (DEM) data, such as... Figure 3 As shown on the left. This pre-stored map data, combined with the field image, helps the system identify the actual terrain features of the sampling area. After acquiring the field image, the system matches and overlays it with the pre-stored geographic information map to identify the specific terrain type of the sampling point, such as flat farmland, rugged mountains, wetlands, or the edge of a lake. Based on the identified terrain information, the system adaptively generates a virtual electronic fence. For example, in flat farmland areas, the electronic fence can be a simple rectangular or circular area, its size and shape set according to the needs of the sampling task; while in areas with complex terrain or obstacles, the shape and extent of the electronic fence may be adjusted to avoid inaccessible or dangerous areas, ensuring the safety of sampling personnel and the effective execution of the sampling task. Step S3 specifically includes the following steps.

[0047] S31: Based on the preset dimensions, generate an initial electronic fence centered on the sampling point, such as... Figure 3 As shown on the right.

[0048] S32: Match the field image with the pre-stored map to identify the terrain where the sampling point is located and the travel path to the sampling point. The terrain refers to the natural landform features of the area where the sampling point is located, specifically including fields, mountains, wetlands and lakes.

[0049] Specifically, the travel path is the route taken by the sampling personnel from their current location to the sampling point. The travel path can be identified using a path planning algorithm, combined with road information, obstacle information, and terrain navigability data from a pre-stored map. S33: When there is a travel path and the terrain is a plain, it indicates that the terrain of the area is relatively simple, and the two-dimensional initial electronic fence is sufficient to meet the constraint requirements. The initial electronic fence is determined as the final electronic fence.

[0050] S34: When there is no travel path and the terrain is mountainous, wetland, or lake, sampling is difficult and sampling points are inaccessible. To reduce the difficulty of sampling and ensure the safety of sampling personnel, the initial electronic fence can be adjusted to a three-dimensional electronic fence. The three-dimensional electronic fence is a funnel-shaped electronic fence with a preset size as the base and a height equal to the sampling depth. This expands the size of the ground electronic fence, allowing the sampling probe to enter the electronic fence as quickly as possible, removing data upload restrictions, expanding the sampling range, and even collecting samples near the sampling point is considered a successful sampling. Moreover, the funnel-shaped electronic fence also allows sampling personnel to sample from the side at an angle, allowing them to sample by extending the sampling equipment. Even if the sampling personnel are not inside the electronic fence, the sampling work can still be completed.

[0051] Based on the specific terrain and feasibility of the travel path at the sampling point, different forms of electronic fences are intelligently and adaptively generated. In plains areas with simple terrain and well-defined travel paths, simple and efficient two-dimensional electronic fences can be used for constraint; while in mountainous, wetland, or lake areas with complex terrain and limited travel paths, three-dimensional electronic fences with vertical constraint capabilities can be generated, especially funnel-shaped electronic fences. These, combined with sampling depth, ensure sample representativeness while also guaranteeing the safety of sampling personnel and expanding their working space. This improves the adaptability of electronic fences to the sampling area, effectively avoiding excessive requirements due to complex terrain or sampling depth requirements, thereby enhancing the feasibility and reliability of geological sampling and providing a more solid foundation for subsequent data analysis and decision-making.

[0052] S4: Obtain the location information of the sampling personnel and the location information of the sampling device bound to the sampling personnel, and determine whether the sampling device follows the sampling personnel. The sampling probe of the sampling device is equipped with a positioning module, which is used to obtain the location information in real time when the device is powered on.

[0053] Specifically, the positioning module can employ a Global Positioning System (GPS) module, a BeiDou navigation module, etc. This module can acquire the precise coordinates of the sampling device's location in real time when powered on, providing fundamental data for location monitoring and electronic fence determination. By calculating the distance between the sampling personnel and the sampling device, it is determined whether the sampling device remains within the effective control range of the sampling personnel, i.e., whether it follows the sampling personnel. For example, if the distance between the two remains within a preset small range, it is determined to be following. Step S4 specifically includes the following steps.

[0054] S41: Determine the separation distance between the sampling personnel and the sampling equipment based on the location information of the sampling personnel and the sampling equipment.

[0055] S42: If the separation distance is less than or equal to the preset separation distance, determine that the sampling device follows the sampling personnel.

[0056] S43: If the separation distance is greater than the preset separation distance, determine that the sampling equipment and the sampling personnel are separated.

[0057] By monitoring and comparing the separation distance between sampling personnel and sampling equipment in real time, situations where equipment is out of personnel supervision can be detected promptly. This effectively prevents misuse, theft, or sampling in unauthorized areas, greatly improving the authenticity, reliability, and traceability of sampling data and ensuring standardized management of the sampling process. Furthermore, this separation assessment can be performed within minutes of sampling personnel arriving near the sampling point and the sampling equipment being turned on; once assessed, it need not be repeated.

[0058] S5: If the sampling device follows the sampling personnel, determine whether the sampling device's location information is within the electronic fence.

[0059] S6: If the sampling equipment is located within the electronic fence, the sampling personnel are allowed to upload the sampling labels and soil data to the information management terminal.

[0060] Specifically, the system only lifts the data upload restriction when the sampling device is identified as following the sampling personnel and its location is confirmed to be within a valid electronic fence. At this point, the sampling personnel can securely and accurately upload recorded sampling label information (such as sample number, sampling time, sampling point coordinates, etc.) and collected soil data (such as pH value, organic matter content, etc.) to a remote information management terminal for storage and management via the sampling device or a linked terminal. This mechanism ensures that only sampling data meeting strict spatial constraints is received by the system, thereby guaranteeing the authenticity and reliability of the data.

[0061] The sampling probe of the sampling device is also equipped with a pressure sensor, which is used to monitor the sampling pressure of the sampling probe.

[0062] After step S6, the method further includes the following steps.

[0063] S71: If the obtained sampling pressure is greater than the preset pressure, start timing the sampling time and monitor the continuity of the sampling pressure.

[0064] S72: If the sampling pressure is greater than the preset pressure for a continuous period of time and the sampling time is less than or equal to the preset maximum sampling time, then the current sampling is determined to be valid.

[0065] S73: If the sampling time is greater than the preset maximum sampling time or the sampling pressure is greater than the preset pressure and the sampling is interrupted within the preset duration, the current sampling is determined to be invalid.

[0066] Specifically, by installing a pressure sensor within the sampling probe of the sampling device, the system can acquire real-time physical feedback on the contact between the sampling probe and the soil. When the sampling personnel insert the probe into the soil and apply sufficient force, the pressure sensor detects the corresponding sampling pressure. The system intelligently compares this real-time pressure with a preset pressure. Once the preset pressure is reached or exceeded, a precise timing mechanism is activated, continuously monitoring the stability of the sampling pressure. This continuous monitoring ensures that the sampling probe maintains a stable insertion state in the soil, rather than a brief contact. Only when the sampling pressure continuously meets the preset conditions, the duration reaches the preset duration, and the entire sampling process does not exceed the preset maximum sampling time, will the system confirm the validity of the sampling operation. If any condition is not met, such as pressure interruption or excessive sampling time, the sampling is deemed invalid. This mechanism, combined with the previous location- and device-bound judgment, forms a more rigorous and comprehensive sampling validity verification process, greatly improving the reliability of the sampling data from the source.

[0067] S74: If the current sampling is valid, record the environmental parameters at the sampling time synchronously and associate the environmental parameters with the sample. The environmental parameters include temperature and humidity, soil moisture content and pH value. The environmental parameters are provided by the temperature and humidity meter set on the sampling device, and the moisture content sensor and pH value sensor set on the sampling probe.

[0068] Specifically, upon receiving a "sampling valid" signal, the control unit inside the sampling device can immediately trigger the environmental parameter sensors to read data and store the read data along with a unique identifier for the current sampling event. Alternatively, the sampling device can send the "sampling valid" signal to an information management terminal or cloud platform via a wireless communication module. The information management terminal or cloud platform can then obtain environmental parameters from nearby fixed environmental monitoring stations or satellite remote sensing data based on the sampling device's location information and correlate them with the sample data.

[0069] S75: This is a sample code. It associates the sample, sampling location information, sampling personnel information, sampling time, and environmental parameters with the sample code to generate a label, which can be printed and pasted on the surface of the sample storage container.

[0070] Specifically, for sample coding, the sample, sampling location information, sampling personnel information, sampling time, and environmental parameters are associated with the sample code to generate a label. This label can then be printed and affixed to the surface of the sample storage container. The aim is to establish a complete sample identification and traceability system, ensuring that each physical sample uniquely corresponds to all its related metadata, facilitating subsequent management, testing, and data retrieval. The sampling device can have a built-in small printer. After valid sampling, it generates a QR code or barcode label containing the sample code, location information, personnel information, time, and environmental parameters based on a preset template, and automatically prints it out for sampling personnel to affix. Alternatively, the sampling device can upload all associated information to the database of an information management terminal via a wireless network. The information management terminal generates a unique sample code and label information, and sends the label to a portable printer on-site via a remote printing service.

[0071] S76: When submitting samples for testing, identify the sample code, extract environmental parameters, and compare these parameters with historical environmental data at the sampling point. If the two match, the sample verification is confirmed to be valid. By comparing the environmental parameters at the time of sampling with historical data, it can be determined whether the sample was collected under expected or acceptable environmental conditions, thereby improving the reliability of the test results.

[0072] After confirming that the sampling equipment is effectively sampling within the electronic fence, environmental parameters, including temperature, humidity, soil moisture content, and pH value, are acquired in real time and synchronously using a temperature and humidity meter integrated into the sampling equipment, as well as a moisture content sensor and pH sensor installed on the sampling probe. These environmental parameters are linked together with the sample, sampling location information, sampling personnel information, and sampling time to generate a unique sample code. This code and its associated information are used to generate a printable label for affixing to the surface of the physical sample storage container, thereby achieving a tight binding and traceability between the sample and environmental data. When the sample is sent for testing, the environmental parameters at the time of sampling can be easily extracted by identifying the sample code and compared with historical environmental data at that sampling point. This comparison mechanism effectively verifies whether the sample was collected under the expected environmental conditions, thereby ensuring the authenticity and reliability of the sampling data and solving the problem of insufficient reliability of sampling results due to missing or difficult-to-verify environmental data in traditional sampling processes. By correlating environmental parameters with the depth of the sample and introducing a verification mechanism, the proposed scheme significantly improves the scientific rigor and accuracy of land quality geological sampling monitoring, thereby enhancing the overall credibility of land quality geological sampling monitoring.

[0073] like Figure 4 As shown in the figure, an embodiment of this application provides a land quality field sampling and monitoring system based on electronic fence constraints, comprising: The field image acquisition module 10 is used to acquire field images of the sampling area.

[0074] The sampling point adjustment module 20 is used to automatically adjust the position of preset sampling points according to the actual image and sampling point adjustment rules, wherein the preset sampling points are sampling points uniformly arranged according to preset layout rules.

[0075] The electronic fence generation module 30 is used to identify the terrain based on real-world images and pre-stored maps, and to adaptively generate an electronic fence based on the terrain.

[0076] The location monitoring module 40 is used to acquire the location information of the sampling personnel and the location information of the sampling equipment bound to the sampling personnel, and to determine whether the sampling equipment follows the sampling personnel. The sampling probe of the sampling equipment is equipped with a positioning module, which is used to acquire location information in real time when the device is powered on.

[0077] The location monitoring module 40 is also used to determine whether the location information of the sampling device is within the electronic fence if the sampling device is following the sampling personnel; if the location information of the sampling device is within the electronic fence, the sampling personnel are allowed to upload the sampling label and soil data to the information management terminal.

[0078] In this embodiment, the field image acquisition module 10 acquires field images that provide the system with real environmental information about the sampling area; the sampling point adjustment module 20 automatically adjusts the preset sampling point positions based on this information to ensure the operability of the sampling points in the actual terrain; the electronic fence generation module 30 adaptively generates an electronic fence based on the identified terrain, defining precise geographical boundaries for the sampling activity; the location monitoring module 40 allows data upload only through a dual verification mechanism (i.e., the sampling device follows the sampling personnel and is located within the electronic fence), effectively preventing sampling location deviation and coordinate data tampering. Through the above technical solutions, dynamic constraints on the authenticity of the sampling location and conditional control of data upload are achieved, significantly improving the spatial traceability reliability of land quality field sampling data, and providing a solid data foundation for subsequent applications such as land quality assessment, pollution source tracing, and resource planning.

[0079] An electronic device provided in this application includes a memory and a processor; the memory is used to store a computer program; the processor is used to implement the land quality field sampling and monitoring method based on electronic fence constraints as described above when the computer program is executed.

[0080] This application provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the land quality field sampling and monitoring method based on electronic fence constraints as described above.

[0081] In this embodiment, the beneficial effects of the electronic device and the computer-readable storage medium are similar to those of the above-described land quality field sampling and monitoring method based on electronic fence constraints, and will not be repeated here.

[0082] The present invention will now describe electronic devices that can serve as servers or information management terminals for this application. These electronic devices are intended to represent various forms of digital electronic computer devices, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic devices may also represent various forms of mobile devices, such as personal digital assistant devices, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present application described and / or claimed herein.

[0083] Electronic devices include a computing unit that can perform various appropriate actions and processes based on a computer program stored in read-only memory (ROM) or loaded from a storage unit into random access memory (RAM). The RAM can also store various programs and data required for device operation. The computing unit, ROM, and RAM are interconnected via a bus. Input / output (I / O) interfaces are also connected to the bus.

[0084] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc., and can be installed in an information management terminal or other terminal. In this application, the separately described modules may or may not be physically separate. Some or all of the modules can be selected to achieve the purpose of the embodiments of this application according to actual needs. Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0085] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0086] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for field sampling and monitoring of land quality based on electronic fence constraints, characterized in that, include: Acquire real-world images of the sampling area; Based on the actual image and the sampling point adjustment rules, the positions of the preset sampling points are automatically adjusted. The preset sampling points are sampling points that are uniformly deployed according to the preset deployment rules. Based on real-world images and pre-stored maps, the terrain is identified, and an electronic fence is generated adaptively according to the terrain. The system acquires the location information of the sampling personnel and the location information of the sampling device bound to the sampling personnel, and determines whether the sampling device follows the sampling personnel. The sampling probe of the sampling device is equipped with a positioning module, which is used to acquire location information in real time when the device is powered on. If the sampling device follows the sampling personnel, then determine whether the sampling device's location information is within the electronic fence; If the sampling equipment is located within an electronic fence, the sampling personnel are allowed to upload the sampling labels and soil data to the information management terminal.

2. The land quality field sampling and monitoring method based on electronic fence constraints as described in claim 1, characterized in that, The field images include address marker images; Before automatically adjusting the sampling point positions based on the actual image and preset sampling point layout rules, the process also includes: Based on the location information of the sampling personnel, when the distance between the sampling personnel and the sampling point is less than the first monitoring distance, the movement trajectory of the sampling personnel is monitored in real time to determine the estimated time for the sampling personnel to reach the sampling point; If the actual time taken for the sampling personnel to reach the sampling point is greater than or equal to the estimated time, it is preliminarily determined that the sampling personnel have arrived in the vicinity of the sampling point. Identify real-time markers or real-time address information in address marker images, and identify multiple target markers in high-resolution satellite imagery around sampling points. Compare real-time markers with target markers and compare real-time address information with address information of sampling points. If a real-time marker is identical to any target marker and the real-time address information is in the same area as the address information of the sampling point, then it is confirmed that the sampling personnel have arrived around the sampling point.

3. The land quality field sampling and monitoring method based on electronic fence constraints as described in claim 1, characterized in that, The field images include land images of the locations where the sampling points are located; The automatic adjustment of preset sampling point positions based on real-world images and sampling point adjustment rules includes: Identify target regions in land images that are related to the sampling targets set at the sampling points, and extract the boundaries of the target regions; Based on the location information of the sampling points and the boundary of the target area, determine the boundary distance between the sampling points and the boundary. When the boundary distance is less than or equal to the preset distance, the sampling point is moved into the target area until the boundary distance of the sampling point is greater than the preset distance.

4. The land quality field sampling and monitoring method based on electronic fence constraints as described in claim 1, characterized in that, The step of identifying the terrain based on real-world images and pre-stored maps, and adaptively generating an electronic fence based on the terrain, includes: Based on the preset dimensions, an initial electronic fence is generated with the sampling point as the center; The actual images are matched with the pre-stored map to identify the terrain where the sampling point is located and the travel path to the sampling point. The terrain includes fields, mountains, wetlands and lakes. When there is a travel path and the terrain is a plain, the initial electronic fence will be determined as the final electronic fence. When there is no travel path and the terrain is mountainous, wetland or lake, the initial electronic fence will be adjusted to a three-dimensional electronic fence. The three-dimensional electronic fence is a funnel-shaped electronic fence with a preset size as the base and a height equal to the sampling depth.

5. The land quality field sampling and monitoring method based on electronic fence constraints as described in claim 1, characterized in that, The step of obtaining the location information of the sampling personnel and the location information of the sampling device bound to the sampling personnel, and determining whether the sampling device follows the sampling personnel, includes: Based on the location information of the sampling personnel and the sampling equipment, determine the separation distance between the sampling personnel and the sampling equipment; If the separation distance is less than or equal to the preset separation distance, the sampling device will follow the sampling personnel. If the separation distance is greater than the preset separation distance, the sampling equipment and the sampling personnel are separated.

6. The land quality field sampling and monitoring method based on electronic fence constraints as described in claim 1, characterized in that, The sampling probe of the sampling device is also equipped with a pressure sensor, which is used to monitor the sampling pressure of the sampling probe. If the sampling device's location information is within an electronic fence, allowing sampling personnel to upload sampling labels and soil data to the information management terminal, the following additional steps are also included: If the obtained sampling pressure is greater than the preset pressure, the sampling time will be started and the continuity of the sampling pressure will be monitored. If the sampling pressure is greater than the preset pressure for an extended period of time, and the sampling time is less than or equal to the preset maximum sampling time, then the current sampling is considered valid. If the sampling time exceeds the preset maximum sampling time or the sampling pressure exceeds the preset pressure and is interrupted within the preset duration, the current sampling is determined to be invalid.

7. The land quality field sampling and monitoring method based on electronic fence constraints as described in claim 6, characterized in that, Also includes: If the current sampling is valid, the environmental parameters at the sampling time are recorded synchronously and associated with the sample. The environmental parameters include temperature and humidity, soil moisture content and pH value. The environmental parameters are provided by the temperature and humidity meter set on the sampling equipment, and the moisture content sensor and pH value sensor set on the sampling probe. To encode the sample, the sample, sampling location information, sampling personnel information, sampling time and environmental parameters are associated with the sample code to generate a label, which can be printed and pasted on the surface of the sample storage container. When samples are sent for testing, the sample code is identified, environmental parameters are extracted, and the environmental parameters are compared with historical environmental data at the sampling point. If the two are consistent, the sample verification is confirmed to be valid.

8. A land quality field sampling and monitoring system based on electronic fence constraints, characterized in that, include: The field image acquisition module is used to acquire field images of the sampling area; The sampling point adjustment module is used to automatically adjust the position of preset sampling points according to the actual image and sampling point adjustment rules, wherein the preset sampling points are sampling points uniformly arranged according to preset layout rules; The electronic fence generation module is used to identify the terrain based on real-world images and pre-stored maps, and adaptively generate electronic fences according to the terrain. The location monitoring module is used to acquire the location information of the sampling personnel and the location information of the sampling equipment bound to the sampling personnel, and to determine whether the sampling equipment follows the sampling personnel. The sampling probe of the sampling equipment is equipped with a positioning module, which is used to acquire location information in real time when the device is powered on. The location monitoring module is also used to determine whether the location information of the sampling device is within the electronic fence if the sampling device is following the sampling personnel; if the location information of the sampling device is within the electronic fence, the sampling personnel are allowed to upload the sampling label and soil data to the information management terminal.

9. An electronic device, characterized in that, Including memory and processor; The memory is used to store computer programs; The processor is configured to, when executing the computer program, implement the land quality field sampling and monitoring method based on electronic fence constraints as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the land quality field sampling and monitoring method based on electronic fence constraints as described in any one of claims 1 to 7.

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