Air-space-ground integrated monitoring platform for mine

Abstract

The invention discloses an air-space-ground integrated monitoring platform for a mine, and the platform comprises the following modules: an air layer monitoring module which comprises a fixed 360-degree deformation monitoring radar and is used for achieving the real-time monitoring of the surface deformation of a whole mining area; the sky inspection module comprises an unmanned aerial vehicle inspection system and is used for acquiring image data of the mining area so as to carry out visual inspection and hidden danger identification on the mining area; the stratum sensing module comprises an earth surface sensor and is used for collecting mining area environment and geological parameters; and the AI early warning center is in communication connection with the empty layer monitoring module, the sky layer inspection module and the stratum sensing module so as to receive and fuse multi-source data including radar deformation data, unmanned aerial vehicle image data and surface environment data and perform data analysis and early warning generation. According to the invention, a plurality of data sources such as the radar, the unmanned aerial vehicle and the earth surface sensor are efficiently integrated, so that an omnibearing intelligent monitoring network is successfully constructed.

Description

Technical Field

[0001] This invention relates to the field of geological data monitoring technology, and in particular to an integrated air-space-ground monitoring platform for mines. Background Technology

[0002] Land subsidence caused by coal mining is a typical geological hazard. It often leads to varying degrees of ground subsidence in the mining area and a certain range, causing varying degrees of damage to buildings, roads, farmland irrigation infrastructure and other structures, and causing certain damage to the ecological environment. Therefore, continuous monitoring of land subsidence and ecological restoration caused by mining is of great significance.

[0003] In the past, surface subsidence monitoring in mining areas was mostly carried out by setting up rock movement observation stations and using traditional methods such as leveling and GNSS measurement. These methods have considerable monitoring accuracy, but the operating cost is high, the amount of monitoring data obtained is limited, and they cannot fully reflect the characteristics of surface subsidence in mining areas, making it difficult to achieve large-scale surface subsidence monitoring. Summary of the Invention

[0004] To address the aforementioned technical challenges, this invention proposes an air-space-ground AI monitoring and management platform. This platform integrates multiple advanced technologies to construct a comprehensive, three-dimensional monitoring system. Utilizing InSAR technology and active microwave remote sensing, the platform acquires large-scale, high-precision information on spatially continuous surface deformation, enabling accurate monitoring of geological changes such as ground subsidence in mining areas. Coupled with intelligent drones, it can automatically patrol and record video and photograph areas prone to hazards, promptly identifying ground fissures, new buildings, and other hazards. Sensor technology enables large-scale, high-precision, all-weather monitoring, supporting remote dynamic detection. The collaborative work of these technologies provides mining enterprises with comprehensive, real-time monitoring data, helping them promptly identify safety hazards and develop scientific mitigation plans.

[0005] To achieve the above objectives, the technical solution of the present invention provides an integrated air-space-ground monitoring platform for mines, comprising the following modules: an air layer monitoring module, including a fixed 360° deformation monitoring radar, for real-time monitoring of surface deformation throughout the mining area; an air layer inspection module, including a drone inspection system, for acquiring image data of the mining area for visual inspection and hazard identification; a ground perception module, including surface sensors, for collecting environmental and geological parameters of the mining area; and an AI early warning center, which is communicatively connected to the air layer monitoring module, the air layer inspection module, and the ground perception module to receive and fuse multi-source data including radar deformation data, drone image data, and surface environmental data, and perform data analysis and early warning generation.

[0006] Furthermore, the AI ​​early warning center generates tiered early warnings based on preset early warning thresholds and automatically generates monitoring reports.

[0007] Furthermore, the AI ​​early warning center automatically and dynamically adjusts the early warning threshold based on season and region.

[0008] Furthermore, the AI ​​early warning center automatically generates a hotspot distribution map after identifying deformation hotspots based on multi-source data. For hotspot areas, the air layer monitoring module automatically adjusts the radar scanning cycle, the sky layer inspection module automatically adjusts the drone inspection frequency, and the ground layer monitoring module adds a ground surface sensor.

[0009] Furthermore, the AI ​​early warning center reduces the false alarm rate by cross-validating radar deformation data, UAV imagery data, and surface environment data.

[0010] Furthermore, the UAV inspection system is equipped with 16x hybrid optical zoom and 4K camera equipment, and supports automated route planning and resume flight after interruption. When the airspace monitoring module triggers an early warning or detects a hotspot, it automatically adjusts the inspection plan.

[0011] Furthermore, the surface sensors include groundwater monitoring wells, weather stations, and soil sensors. When the stratum sensing module detects an anomaly, it automatically triggers an anomaly warning.

[0012] Furthermore, the platform also includes an equipment status monitoring module, which is used to monitor the operating status of radar, UAV systems and surface sensors in real time, and supports remote control and fault early warning.

[0013] Furthermore, the platform also includes a data sharing module, which provides an open API interface to interface with the corresponding regulatory platform and supports setting different data sharing frequencies.

[0014] Furthermore, the platform also includes a user permission management module, which adopts a role-based access control (RBAC) model to achieve fine-grained permission management. Attached Figure Description

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic diagram of the framework of the integrated air-space-ground monitoring platform for mines according to the present invention;

[0017] Figure 2 This is a full-area subsidence thermal map generated by the platform of this invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] As mentioned in the background section, accurately monitoring surface subsidence and its development in mining areas is a crucial task for coal mining regions. In recent years, the rapidly developing Synthetic Aperture Radar Differential Interferometry (InSAR) technology can monitor minute topographic changes on the surface with high precision, effectively complementing leveling and GPS measurements. Applying it to monitoring subsidence caused by underground coal mining allows for automated, all-weather, and continuous spatial coverage monitoring of surface deformation. Therefore, the application of InSAR technology for monitoring surface deformation in mining areas will be a future trend in this field.

[0020] After obtaining ground subsidence data through this platform, the drone can automatically cruise to the coordinates of the potential hazard area and perform video recording and photography tasks. After the task is completed, it will automatically land at the designated location. It can effectively obtain information on ground fissures in mining areas and newly constructed buildings in surrounding villages. With an operating radius of up to 7 kilometers, it has an IP55 protection rating and can operate in an ambient temperature range of -35℃ to 50℃, adapting to various harsh environments.

[0021] This invention successfully constructs a comprehensive intelligent monitoring platform by efficiently integrating multiple data sources such as radar, drones, and surface sensors to achieve low-altitude inspection and geological environment monitoring. The monitoring platform includes: atmospheric layer: a fixed 360° deformation monitoring radar; celestial layer: a drone inspection system; terrestrial layer: surface sensors + AI early warning center.

[0022] 1. Overall platform operation status

[0023] In a specific embodiment, the present invention employs three fixed 360° deformation monitoring radars, deployed in key areas to the east, west, and south of the mining area, respectively, to achieve 360° monitoring without blind spots. This radar, based on an arc-shaped synthetic aperture radar system and phase differential interferometry technology, possesses sub-millimeter level accuracy.

[0024] The main operating parameters include:

[0025] Monitoring accuracy: 0.08mm (better than the ≤0.1mm equipment standard);

[0026] Scan cycle: 1 minute (balancing accuracy and data update frequency);

[0027] Monitoring range: 360°×35° for a single unit (exceeding the requirement of ≥360°×30° for equipment);

[0028] Maximum distance: Effective monitoring up to 5000m (meets the needs of the entire mining area);

[0029] Device status: Built-in 4G wireless communication function;

[0030] Environmental adaptability: It can operate stably within the operating temperature range of -45℃ to +55℃ and under IP65 protection level.

[0031] The drone inspection system adopts automated route planning technology (operating radius up to 7km), can operate stably in environments ranging from -35℃ to 50℃, and has the ability to resume flight after interruption.

[0032] Key performance indicators include:

[0033] Image quality: Equipped with 16x hybrid optical zoom and 4K video recording.

[0034] Nest status: Enables automatic landing and data transmission; IP55 protection rating; adaptable to complex environments.

[0035] Zero malfunctions: average battery life reached 5.2 hours.

[0036] The early warning software system adopts a B / S architecture, supports simultaneous access by multiple users, and is deployed on a physical server (including cloud server backup).

[0037] Main operating status:

[0038] Data processing capacity: Processes an average of 50GB of monitoring data per day, with no backlog;

[0039] Early warning function: It realizes the classification, and the sound and light alarms and SMS notifications respond quickly.

[0040] Data fusion: Enables the fusion of UAV modeling, CAD 3D modeling, laser dot matrix modeling, and radar data;

[0041] Report generation: The system supports the automatic generation of Word format reports.

[0042] Data Interface: Provide free interfaces to mining companies to facilitate secondary development.

[0043] Sixteen groundwater monitoring wells, two weather stations, and 48 soil sensors were deployed on the surface, deeply integrated with "space-air" data.

[0044] Data support: Real-time rainfall and soil moisture data from meteorological stations provide strong support for radar deformation analysis and key inspections by drones. Especially during heavy rain, the AI ​​system can intelligently instruct drones to prioritize inspections of slope areas.

[0045] AI Central Integration: Surface data and aerospace data are uniformly integrated into the AI ​​early warning system, automatically generating a "Daily Monitoring Report".

[0046] Unattended operation: Sensor malfunctions (such as a sudden rise in water level) automatically trigger early warnings, reducing the workload of dedicated monitors.

[0047] 2. Surface deformation monitoring:

[0048] (1) Global deformation characteristics - cross-validation of air-space-ground data

[0049] Throughout the month, surface deformation across the entire mining area remained generally stable, with deformation rates in most areas ranging from 0 to 0.3 mm / day (within the normal range for mining subsidence). By fusing radar scans and UAV aerial photography data, the platform generated a subsidence heat map of the entire mining area, as shown below. Figure 2 As shown, the core data is as follows:

[0050] The average settlement rate for the whole month dropped to 0.15 mm / day (compared to 0.17 mm / day last month, indicating an improvement in stability).

[0051] The extreme subsidence occurred near the western mined-out area, with a maximum monthly subsidence of 8.2 mm; while the monthly subsidence in the eastern unmined area was 0.3 mm.

[0052] Temporal distribution: The settlement rate was 0.14 mm / day in the first ten days of the month, rose to 0.17 mm / day in the middle ten days due to heavy rain, and dropped to 0.14 mm / day after the weather cleared up in the last ten days of the month, indicating that the influence of meteorological factors on the settlement rate is controllable.

[0053] Analysis conclusion: The heavy rain caused the average settlement rate to rise to 0.17 mm / day in the middle of the month (an increase of 21% compared to the beginning of the month), while the "air-ground-space" data showed that the rate dropped back to 0.14 mm / day in the latter part of the month, verifying that the meteorological impact is reversible.

[0054] (2) Analysis of key areas

[0055] (a) East slope (high-risk area)

[0056] Collaborative monitoring data:

[0057] Aerial layer: Under the violent impact of the rainstorm, the horizontal displacement rate increased sharply, from the usual 0.21 mm / day to 0.5 mm / day, a value that has far exceeded the level 2 warning threshold;

[0058] Tianceng: The drone arrived at the site within 1 hour and captured images of two micro-cracks, each 10-15m long, in the lower part of the slope;

[0059] Soil strata: Sensor data at the bottom of the slope showed that the soil moisture content had reached 38%, indicating saturation. This confirmed that the large infiltration of rainwater was the direct cause of the decrease in slope strength.

[0060] Collaborative handling and results: The AI ​​central system pushed the suggestion of "interception and drainage + slope toe ballast". Within 3 days after the handling, the "air-ground-space" data showed that the deformation rate dropped to 0.18mm / day (originally manual monitoring required 3 people / day, now only 1 person is needed for verification).

[0061] Supplementary analysis: The average horizontal displacement rate of the eastern slope this month was 0.21 mm / day, and the vertical settlement rate was 0.18 mm / day (generally stable), but deformation accelerated briefly during heavy rain (maximum horizontal displacement 0.5 mm / day, vertical settlement 0.4 mm / day). Radar monitoring showed that the deformation was concentrated in the middle and lower parts of the slope (related to rainwater infiltration). The platform promptly issued a level-three warning, and the mine temporarily closed the area and drained the water. Subsequently, the deformation rate returned to normal. Long-term data indicates that the deformation in this area is seasonal (the rate is higher during the rainy season than during the dry season). In the future, it is necessary to increase the monitoring frequency during the rainy season and optimize the warning threshold.

[0062] (b) Tailings dam (sensitive area)

[0063] Collaborative monitoring data:

[0064] Void layer: Settlement rate 0.12 mm / day, horizontal displacement 0.08 mm / day;

[0065] Sky layer: Drone aerial photography shows that there are no cracks on the dam surface and the drainage channel is unobstructed;

[0066] Formation: Sensors show that the current seepage line depth is 2.8 meters, slightly below the design limit of 3.5 meters, indicating that the water level in the tailings dam is stable.

[0067] Collaborative conclusion: The tailings dam is generally stable and no manual drilling inspection of the dam body is required (originally once a quarter, now extended to once every six months based on the three-in-one data).

[0068] Supplementary analysis indicates that the average settling rate of the tailings dam this month was 0.12 mm / day, and the horizontal displacement was 0.08 mm / day, both remaining stable. The radar monitoring system did not detect any abnormal deformation of the dam body, and key safety indicators such as the seepage line and displacement remained within safe ranges. Drone inspections showed that the surrounding drainage system was normal (no water accumulation), and there was no trend change compared to historical data, indicating a low risk of significant deformation in the next month.

[0069] (3) Management of high-risk areas

[0070] Based on "space-air-ground" data, 10 deformation hotspots were identified. The core hotspot, P1, experienced a monthly subsidence of 8.2 mm. The coordinated control measures are as follows:

[0071] Aerial layer monitoring: The radar scanning cycle is shortened from 1 minute to 0.5 minutes, allowing for continuous tracking of subsidence dynamics at a more frequent frequency;

[0072] Skyline inspection: Drones perform special flight missions twice a week to capture high-definition images and record in detail the subtle changes in the cracks;

[0073] Ground monitoring: Two new soil moisture sensors have been installed to enable real-time monitoring and data analysis of the impact of rainwater infiltration;

[0074] AI suggests increasing the filling density of the goaf from 1 per 1000m² to 1.5 per 1000m². AI automatically generates a heat map based on air-space-ground data (which used to take 1 day to manually delineate, but now no manual survey is needed).

[0075] Top 3 Hotspot Areas Details:

[0076] Central area of ​​western goaf: monthly subsidence 8.2 mm, rate 0.55 mm / day (old goaf area, affected by surrounding mining);

[0077] The lower part of the eastern slope: monthly settlement of 6.5 mm, rate of 0.43 mm / day (heavy rain caused a decrease in the strength of the local soil and rock mass);

[0078] Southwest goaf edge area: monthly subsidence 5.8 mm, rate 0.39 mm / day (new goaf area, subsidence is still developing).

[0079] The mine implemented a series of targeted measures, including backfilling and support (for the western area), drainage reinforcement (for the eastern slope area), and adjustments to the mining plan (for the southwest), which effectively curbed the deformation trend.

[0080] (4) Early warning statistical analysis

[0081] A total of 28 warnings were triggered throughout the month (2 at Level 1, 5 at Level 2, 12 at Level 3, and 9 at Level 4), with a warning accuracy rate of 96% and only 1 false alarm (equipment vibration interference in the southern work area).

[0082] Core optimization effects:

[0083] False alarm control: Cross-validation of air, space, and ground data (radar deformation + UAV confirmation of equipment interference + surface sensor exclusion of geological changes) reduced the false alarm rate from the traditional 15% to 4%, and reduced the ineffective emergency response manpower from 3 people / time to 0.5 people / time;

[0084] Regional distribution: 12 warnings were issued for the western mining subsidence area (43%), and 9 warnings were issued for the eastern slope (32%). AI automatically adjusted the warning thresholds (e.g., the threshold for the eastern slope was reduced by 20% during heavy rain), without the need for manual calibration.

[0085] Typical early warning event (Level II early warning for the eastern slope on July 15): The platform detected a sudden increase in the deformation rate to 0.8 mm / day (exceeding the 0.5 mm / day threshold), immediately triggering an audible / visual / SMS alarm and generating an early warning report. The mine activated its emergency plan (closing off the area, conducting on-site investigation, and reinforcing drainage). Subsequent monitoring showed that the deformation rate gradually returned to normal, successfully averting the risk.

[0086] False alarm optimization measures: To address the issue of misjudging short-term deformation in the work area, the mine has set up a warning shielding area on the platform to reduce false alarms.

[0087] 3. Low-altitude patrol management

[0088] (1) Task execution – Three-in-one optimization of inspection efficiency

[0089] Throughout the month, the low-altitude inspection system covered the entire mining area, focusing on mined-out areas, slopes, tailings ponds, and transportation roads. By adopting advanced automated route planning technology, the inspection path was further optimized.

[0090] AI Collaborative Advantages: Referring to the advanced "air-ground collaboration" model, drones automatically respond to "air-ground-space" data commands (such as radar detecting hotspots → drones prioritizing inspection). The application of drone technology has shortened the inspection cycle from 2 days to 1 day and achieved full automation without the need for manual scheduling, thereby greatly improving inspection efficiency.

[0091] (2) Inspection image data acquisition and processing

[0092] Data collection: The drone was equipped with 16x hybrid optical zoom and 4K camera equipment, and collected data throughout the month.

[0093] Data processing: In terms of 3D modeling, 16 3D models with sub-meter accuracy were generated, covering the main production and monitoring areas. By converting 2D images into 3D models, the accuracy of the analysis was significantly improved.

[0094] Data Management: The platform's image library supports searching by time, region, and task type, and the comparative analysis function can display terrain changes and project progress.

[0095] (3) Closed-loop handling of hidden dangers

[0096] Throughout the month, 38 potential hazards were identified through inspection image analysis (3 major, 12 relatively major, and 23 minor), including ground fissures, slope instability, poor drainage, and equipment malfunctions.

[0097] (4) Unmanned operation and maintenance

[0098] The drone nest achieves "automatic take-off and landing + charging + data transmission," and works in conjunction with the "air-ground-space" system. Its core achievements are as follows:

[0099] Automatic supplementary inspection: Radar detects an anomaly → AI instructs the machine nest to initiate supplementary inspection (originally manual dispatch took 1 hour, now responds in 5 minutes);

[0100] Status monitoring: AI monitors the battery level and temperature of the cell in real time, automatically alarms for faults, and reduces the frequency of manual inspections from once a day to once a week;

[0101] Cost savings: Reduces labor costs and increases inspection efficiency by 50%.

[0102] Remote intelligent monitoring: The platform monitors the drone's battery status, flight trajectory, and nest status in real time around the clock. It successfully handled 8 low battery warnings and 3 weak signal warnings, all of which were quickly resolved through remote operation without affecting the mission.

[0103] 4. Geological Environment Monitoring

[0104] (1) High-precision monitoring of the goaf areas (mainly in the west and south) of the entire mining area was carried out using a fixed 360° deformation monitoring radar, and the subsidence of the goaf areas was analyzed.

[0105] (2) Collect and analyze meteorological data in real time and efficiently, and conduct meteorological monitoring.

[0106] (3) Groundwater levels are monitored through 16 groundwater monitoring wells (covering mining / sensitive areas).

[0107] (4) Monitor the water from old kilns and surface water that pose major water hazards, and build a prevention and control system through multi-source data.

[0108] 5. Data Center

[0109] (1) Multi-source data fusion

[0110] The data center integrates various types of data and utilizes advanced algorithms to achieve spatiotemporal registration and deep correlation analysis, effectively overcoming the limitations of a single data source.

[0111] Radar data + ground sensors: improving the accuracy of surface deformation monitoring;

[0112] Drone imagery + 3D modeling: Enhancing the intuitiveness of engineering design;

[0113] Multi-source data collaboration: provides support for macro (whole mine area management) and micro (local hidden dangers) decision-making, and improves the scientific nature of management.

[0114] (2) Automated report generation

[0115] The data center relies on a pre-set template system to automatically generate various types of reports, which greatly reduces human intervention and effectively lowers the error rate.

[0116] (3) Data sharing management

[0117] Shared data types: surface deformation, early warning information, meteorological data, and groundwater data;

[0118] The sharing frequency is set as follows: early warning information is shared instantly, monitoring data is summarized and shared daily, and reports are shared weekly.

[0119] Sharing method: Open API interface to connect to the corresponding data platform for automatic data transmission and synchronization;

[0120] Sharing rate: 92% for the whole month (exceeding the requirement of ≥80%);

[0121] Security management measures include: using data encryption technology to ensure data security, implementing strict access control to prevent information leakage, and recording shared logs for traceability.

[0122] 6. System Management

[0123] (1) User permission management: The platform adopts a role-based access control (RBAC) model to achieve fine-grained permission management and ensure operational security and compliance. The system supports dynamic adaptation of permissions, and administrators can flexibly adjust role permissions according to actual conditions.

[0124] (2) Equipment monitoring: The platform monitors the status of all hardware devices (drones, radar, sensors, servers, etc.) in real time to achieve remote management and fault early warning. The monitoring content includes equipment operating status, communication status, power status, etc.

[0125] (3) System settings: Administrators can flexibly adjust system parameters according to the actual needs of the mine to improve performance and accuracy.

[0126] The monitoring platform of this invention features a wide monitoring range, covering large mining areas; high monitoring accuracy, reaching millimeter level, precisely capturing minute topographical changes; and all-weather, 24 / 7 operation capability, unaffected by adverse weather conditions. Simultaneously, the platform achieves fully automated monitoring, reducing manual intervention and improving monitoring efficiency and data reliability. Furthermore, it can integrate and analyze various monitoring data, providing mining enterprises with more comprehensive and accurate decision-making support.

[0127] Compared to traditional monitoring methods, the platform of this invention offers significant advantages. Traditional rock movement observation stations, combining leveling and GNSS measurements, suffer from high operating costs, limited data volume, difficulty in achieving large-scale monitoring, and significant susceptibility to weather and terrain factors. In contrast, the platform of this invention utilizes InSAR technology, greatly improving monitoring efficiency, accurately covering large areas, and providing early warnings of potential surface deformation trends. Unmanned aerial vehicle (UAV) automated inspection further enhances efficiency, ensures personnel safety, and facilitates convenient information collection. Currently, few similar platforms on the market can integrate multiple advanced technologies so comprehensively, providing a one-stop monitoring service. The platform of this invention, with its advanced technology, complete functionality, and high cost-effectiveness, possesses strong market competitiveness.

[0128] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An integrated air-space-ground monitoring platform for mines, characterized in that, Includes the following modules: The void layer monitoring module includes a fixed 360° deformation monitoring radar, which is used to realize real-time monitoring of surface deformation throughout the mining area; The top-level inspection module includes a drone inspection system, which is used to acquire image data of the mining area for visual inspection and hazard identification. The stratum sensing module includes surface sensors for collecting environmental and geological parameters of the mining area; The AI ​​early warning center is communicatively connected to the air layer monitoring module, the sky layer inspection module, and the ground layer perception module to receive and fuse multi-source data, including radar deformation data, UAV image data, and surface environment data, and to perform data analysis and generate early warnings.

2. The integrated air-space-ground monitoring platform for mines according to claim 1, characterized in that, The AI ​​early warning center generates tiered early warnings based on preset early warning thresholds and automatically generates monitoring reports.

3. The integrated air-space-ground monitoring platform for mines according to claim 2, characterized in that, The AI ​​early warning center automatically adjusts the early warning threshold dynamically based on season and region.

4. The integrated air-space-ground monitoring platform for mines according to claim 3, characterized in that, The AI ​​early warning center automatically generates a hotspot distribution map after identifying deformation hotspots based on multi-source data. For hotspot areas, the air layer monitoring module automatically adjusts the radar scanning cycle, the sky layer inspection module automatically adjusts the drone inspection frequency, and the ground layer monitoring module adds a ground surface sensor.

5. The integrated air-space-ground monitoring platform for mines according to claim 4, characterized in that, The AI ​​early warning center reduces the false alarm rate by cross-validating radar deformation data, UAV imagery data, and surface environment data.

6. The integrated air-space-ground monitoring platform for mines according to claim 5, characterized in that, The UAV inspection system is equipped with 16x hybrid optical zoom and 4K camera equipment, and supports automated route planning and resume flight after interruption. When the airspace monitoring module triggers an early warning or detects a hotspot, it automatically adjusts the inspection plan.

7. The integrated air-space-ground monitoring platform for mines according to claim 6, characterized in that, The surface sensors include groundwater monitoring wells, weather stations, and soil sensors. When the stratum sensing module detects an anomaly, it automatically triggers an anomaly warning.

8. The integrated air-space-ground monitoring platform for mines according to claims 1-7, characterized in that, The platform also includes an equipment status monitoring module, which is used to monitor the operating status of radar, UAV systems and surface sensors in real time, and supports remote control and fault early warning.

9. The integrated air-space-ground monitoring platform for mines according to any one of claims 1-7, characterized in that, The platform also includes a data sharing module, which provides an open API interface to connect with the corresponding regulatory platform and supports setting different data sharing frequencies.

10. The integrated air-space-ground monitoring platform for mines according to any one of claims 1-7, characterized in that, The platform also includes a user permission management module, which adopts a role-based access control (RBAC) model to achieve fine-grained permission management.

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