Telemetering site position display and information query system and method based on AR information labeling

Abstract

The invention discloses a telemetering site position display and information query system and method based on AR information labeling. The system comprises a multi-source data management module, an interactive query module, an AR recognition module and a mobile terminal device. The interactive query module is arranged in mobile terminal equipment, and the mobile terminal equipment is in communication connection with the AR identification module through the communication module; the AR identification module is in communication connection with the multi-source data management module through the communication module; equipment pose synchronization, spatial range screening and a three-dimensional space anchoring algorithm based on ARCore are executed through the system, and finally hierarchical information capable of being interactively displayed is generated through AR label generation and rendering; the method aims at solving the problems that in the prior art, a telemetering site information query mode is backward, the information display dimension is single, and operation steps are tedious and low in efficiency, and telemetering site visual query can be achieved through the combination of the mobile intelligent device and the space positioning and AR labeling technology.

Description

Technical Field

[0001] The present invention relates to the field of virtual reality technology, and in particular to a system and method for displaying and querying telemetry site locations based on AR information annotation. Background Art

[0002] With the improvement of the digital capabilities of hydropower stations, 3D technology, as a carrier platform for data analysis and display applications in power production management, is the foundation of smart enterprises and smart power station applications. Currently, the demand for 3D applications is constantly emerging in various business professional aspects, such as operation and maintenance simulation training, virtual power station operation, watershed maintenance support, dam area geological management, safe production, technical training, etc. In the construction of technical systems in different professional fields, there is a demand for the construction of 3D technology functions and the use of 3D models.

[0003] Currently, the company has numerous platforms, systems, and functional modules for displaying watershed scheduling information. These displays are primarily in the form of two-dimensional charts, requiring cumbersome steps to query information based on three-dimensional models. These processes are also limited to one-way information acquisition or searching for key information by inputting queries. This lacks interactivity and prevents the full potential of the established three-dimensional model library. Furthermore, due to the length of the watershed and its multiple identities, a large number of diverse telemetry stations are deployed within the basin. Querying telemetry station information in a specific area often requires complex workflows, requiring access to the corresponding unit's database and searching through a vast amount of information. This requires high levels of authority and is difficult to perform. Information display is limited in dimension, failing to intuitively reflect the physical spatial distribution of stations. Frequent application switching is required to obtain multiple types of data (such as location and real-time monitoring values). Site screening is inefficient in complex geographical environments and lacks dynamic interaction capabilities. Furthermore, professionals struggle to quickly associate station types with corresponding monitoring parameters.

[0004] Therefore, it is necessary to design a telemetry site location display and information query system and method based on AR information annotation, so as to realize convenient hydropower station scene recognition and information interaction on mobile terminals. Summary of the Invention

[0005] The purpose of the present invention is to provide a telemetry site location display and information query system and method based on AR information annotation, aiming to solve the problems of backward telemetry site information query methods in the prior art, single information display dimensions, and cumbersome and inefficient operation steps. Telemetry site visualization query can be achieved through mobile smart devices combined with spatial positioning and AR annotation technology.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is: The telemetry site location display and information query system based on AR information annotation includes a multi-source data management module, an interactive query module, an AR recognition module, and a mobile terminal device. The interactive query module is built into the mobile terminal device, and the mobile terminal device and the AR recognition module are connected to each other through a communication module. The AR recognition module and the multi-source data management module are connected to each other through a communication module. The multi-source data management module includes the telemetry site metadata database and the hydrological information database; The mobile terminal device is a mobile terminal device with a built-in positioning module, electronic compass, accelerometer and camera to achieve spatial posture perception; The AR recognition module includes a three-dimensional space anchoring module and a dynamic screening controller. The three-dimensional space anchoring module is used to generate site labels with orientation guide arrows, and the dynamic screening controller is used to filter and select the objects to be tested. The interactive query module includes a touch screen and a voice recognition module for realizing human-computer interaction; The communication module includes an LTE communication module and a Wi-Fi module.

[0007] Preferably, the telemetry site metadata database is used to store telemetry site metadata, which includes station name, station number, type, latitude and longitude, elevation, location, whether it is a control station, data source and management unit, wherein the location represents the geographical administrative area where the telemetry station is located.

[0008] Preferably, the telemetry station types include reservoir stations, hydrological stations, water level stations, rainfall stations and meteorological stations.

[0009] Preferably, the hydrological information database includes measurement point information of various types of telemetry stations; reservoir station measurement point information includes reservoir water level, inflow and outflow, storage capacity and forecast flow; hydrological station measurement point information includes water level and flow; water level station measurement point information is water level; rainfall station measurement point information is rainfall; meteorological station measurement point information includes temperature, humidity, air pressure, wind speed, wind direction and rainfall.

[0010] Preferably, the three-dimensional space anchoring module executes a three-dimensional space anchoring algorithm based on ARCore.

[0011] Preferably, the dynamic screening controller performs filtering on the object to be detected including radius filtering, type filtering and alarm status filtering.

[0012] Preferably, the method of the telemetry site location display and information query system based on AR information annotation includes the following steps: S1, device posture synchronization: Collect the device's geographic coordinates and lens pointing azimuth through a mobile terminal device; S2, spatial range screening: Determine the visible area based on the view cone calculation and generate a set of candidate sites based on the user-set screening radius; S3, through the 3D space anchoring module, executes the 3D space anchoring algorithm based on ARCore to realize the anchoring of geographic coordinates to AR 3D space; S4, AR label generation and rendering: Assign differentiated icons based on site type; Dynamically calculate the spatial distance between the tag and the device, and scale the tag size based on the principle of larger near and smaller far. S5, hierarchical information display: The first-level label displays the station name and the set key indicators; The secondary details page displays site metadata, historical trend charts, and real-time video streams in columns; S6,interaction is performed through the interactive query module, including gesture and voice operations.

[0013] Preferably, in step S2, the specific method of spatial range screening is: S201, geographical radius screening, screening out the telemetry sites within the user-set radius from all telemetry sites. The specific process for candidate sites is as follows: Input parameters: The device's current location coordinates: longitude ,latitude and elevation ; User-defined filter radius ; A collection of geographic coordinates of all telemetry sites ; Perform a filter: Use the simplified plane approximation formula to calculate the horizontal distance between the site and the equipment: ; in, represents the latitude difference, Indicates the difference in longitude; represents the radius of the Earth; Elevation difference correction: If you need to consider the three-dimensional distance, further calculate the elevation difference between the site and the device: ; Generate candidate set: Retention satisfaction The site obtained preliminary screening results: ; Where S represents the geographical coordinate set of all telemetry sites; S202, cone screening, in On this basis, we further filter out sites within the current viewing cone of the device camera to avoid rendering labels outside the field of view. The specific process is as follows: Input parameters: Device attitude: including pitch angle , yaw angle and roll angle ; Camera parameters: including horizontal field of view , vertical field of view and candidate site sets ; Screening Process: Constructing the frustum model: The view frustum is defined as a quadrangular pyramid formed by the field of view of the device camera, with its vertex at the device position and its axis aligned with the camera orientation. With the camera as the origin and the direction along the positive Z axis, the four sides of the view frustum are defined by the following plane equations: Near plane: ; Far Plane: z = z far; Left and right planes: ; Upper and lower planes: ; Coordinate transformation: The ENU coordinates of the candidate site Convert to the coordinates of the camera coordinate system : Constructing a rotation matrix from device Euler angles , perform coordinate rotation: ; Determination within the viewing cone: Site The following conditions must be met simultaneously to be within the viewing cone: ; Generate the final candidate set: ; S203, executing dynamic screening optimization strategy: Spatial index acceleration: Create a quadtree index and perform frustum calculations only for sites within the current view block. Hierarchical filtering: When the user moves the device quickly, the geographic radius filtering results are used first to render rough labels, and the frustum filtering is started after the device stabilizes; Direction guidance tips: The station in the image shows an arrow at the edge of the screen, with the direction of the arrow determined by the vector cross product: ; in is the camera facing vector, is the site direction vector.

[0014] Preferably, in step S3, the three-dimensional space anchoring module executes the three-dimensional space anchoring algorithm based on ARCore as follows: S301, mapping geographic coordinates to AR scene coordinates: Device coordinate system establishment: Construct the Northeastern Universe (ENU) local coordinate system with the current location of the mobile device as the reference point. The reference point includes longitude and latitude. ,latitude and elevation : Among them, the X axis represents the tangent in the due east direction; the Y axis represents the tangent in the due north direction; the Z axis represents the direction perpendicular to the surface; Site coordinate conversion: Perform the conversion from the geographic coordinate system to the ENU coordinate system for the target telemetry site: ; Among them, the longitude of the target telemetry site ,latitude , elevation ; R is the radius of the Earth; AR scene alignment: Get the device's initial pose matrix through ARCore's visual inertial odometry VIO , the site coordinates in the ENU coordinate system ( x , y , z ) is converted to the three-dimensional coordinates (x′, y′, z′) in the AR scene coordinate system; S302, spatial anchoring and posture synchronization based on ARCore: Geospatial anchor generation: Use ARCore Geospatial API to generate geospatial anchor points based on the site's geographic coordinates. and preset attitude quaternion Create spatial anchor points; Azimuth calculation: calculate the relative azimuth between the device and the site : ; The azimuth Converted to Euler angles in the AR scene to adjust the tag orientation; S303, dynamic label rendering, including: Frustum Filtering: Define the camera's field of view , calculate the site direction vector and the device's heading vector Angle: ; like If the site is within the visible range, the edge direction indicator arrow will be displayed; Distance Adaptive Scaling: Label Size S Distance from device-site d Inversely proportional: ; in As the base size, is the minimum display distance threshold; Environmental perception optimization: Lighting adaptation: collect ambient light intensity through the camera L , dynamically adjust label brightness B : ; Occlusion processing: When the AR plane is detected to overlap with the label position, the label transparency is Set to 0.5 to maintain visibility.

[0015] Preferably, the dimensional space anchoring algorithm also includes precision enhancement, and the specific method is as follows: Perform multi-source data fusion: Establish a Kalman filter model and integrate GPS positioning data , visual SLAM pose data and inertial sensor data Output optimal position estimate : ; in K is the Kalman gain matrix, is the observed value; Perform feature point assisted positioning: Deploy manual markers around key sites and achieve sub-meter positioning accuracy correction through image feature matching.

[0016] The beneficial effects of the telemetry site location display and information query system and method based on AR information annotation provided by the present invention are: 1. This invention significantly improves spatial cognition efficiency and decision-making accuracy: Traditional telemetry station queries rely on two-dimensional maps overlaid with data tables, which suffers from abstract spatial location and fragmented multi-dimensional data. This patent utilizes AR spatial anchoring technology to accurately map station locations to the physical environment. Combined with dynamic label guidance (such as arrows and distance scales), differentiated icons (dam icons for reservoir stations, raindrop icons for rain gauges), and hierarchical information display (primary labels display key parameters, secondary panels display historical trend charts), this allows operators to quickly complete the cognitive loop of "location identification and analysis." For example, in flood control command scenarios, users can intuitively visualize the real-time water level correlation between upstream rain gauges and downstream hydrological stations. Combined with AR-annotated flow forecast curves, this can shorten emergency response decision-making time by over 40%. Furthermore, a visual cone filtering algorithm automatically hides out-of-view stations to avoid information overload, reducing ineffective visual clutter by 75% compared to traditional full-data display methods.

[0017] 2. The present invention improves computing efficiency by setting up a three-dimensional space anchoring algorithm and spatial range screening based on ARCore, reduces computing complexity through two-stage screening, improves user experience, ensures that only sites within the field of view are rendered to avoid interface congestion, and prompts important sites outside the field of view through azimuth arrows. It also achieves energy-saving optimization, reduces unnecessary GPU rendering load, and extends the battery life of mobile devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention will be further described below with reference to the accompanying drawings and embodiments: Figure 1 Schematic diagram of the system structure of the present invention; Figure 2 It is a schematic diagram of the process of the present invention. DETAILED DESCRIPTION

[0019] Example 1: like Figure 1 As shown, the telemetry site location display and information query system based on AR information annotation includes a multi-source data management module, an interactive query module, an AR recognition module and a mobile terminal device; the interactive query module is built into the mobile terminal device, and the mobile terminal device and the AR recognition module are connected to each other through the communication module; the AR recognition module and the multi-source data management module are connected to each other through the communication module; The multi-source data management module includes the telemetry site metadata database and the hydrological information database; The mobile terminal device is a mobile terminal device with a built-in positioning module, electronic compass, accelerometer and camera to achieve spatial posture perception; The AR recognition module includes a three-dimensional space anchoring module and a dynamic screening controller. The three-dimensional space anchoring module is used to generate site labels with orientation guide arrows, and the dynamic screening controller is used to filter and select the objects to be tested. The interactive query module includes a touch screen and a voice recognition module for realizing human-computer interaction; The communication module includes an LTE communication module and a Wi-Fi module.

[0020] Preferably, the telemetry site metadata database is used to store telemetry site metadata, which includes station name, station number, type, latitude and longitude, elevation, location, whether it is a control station, data source and management unit, wherein the location represents the geographical administrative area where the telemetry station is located.

[0021] Preferably, the telemetry station types include reservoir stations, hydrological stations, water level stations, rainfall stations and meteorological stations.

[0022] Preferably, the hydrological information database includes measurement point information of various types of telemetry stations; reservoir station measurement point information includes reservoir water level, inflow and outflow, storage capacity and forecast flow; hydrological station measurement point information includes water level and flow; water level station measurement point information is water level; rainfall station measurement point information is rainfall; meteorological station measurement point information includes temperature, humidity, air pressure, wind speed, wind direction and rainfall.

[0023] Preferably, the three-dimensional space anchoring module executes a three-dimensional space anchoring algorithm based on ARCore.

[0024] Preferably, the dynamic screening controller performs filtering on the object to be detected including radius filtering, type filtering and alarm status filtering.

[0025] like Figure 2 As shown, the method of the telemetry site location display and information query system based on AR information annotation includes the following steps: S1, device posture synchronization: Collect the device's geographic coordinates and lens pointing azimuth through a mobile terminal device; S2, spatial range screening: Determine the visible area based on the view cone calculation and generate a set of candidate sites based on the user-set screening radius; S3, through the 3D space anchoring module, executes the 3D space anchoring algorithm based on ARCore to realize the anchoring of geographic coordinates to AR 3D space; S4, AR label generation and rendering: Assign differentiated icons based on site type; Dynamically calculate the spatial distance between the tag and the device, and scale the tag size based on the principle of larger near and smaller far. S5, hierarchical information display: The first-level label displays the station name and the set key indicators; The secondary details page displays site metadata, historical trend charts, and real-time video streams in columns; S6,interaction is performed through the interactive query module, including gesture and voice operations.

[0026] Preferably, in step S2, the specific method of spatial range screening is: S201, geographical radius screening, screening out the telemetry sites within the user-set radius from all telemetry sites. The specific process for candidate sites is as follows: Input parameters: The device's current location coordinates: longitude ,latitude and elevation ; User-defined filter radius ; A collection of geographic coordinates of all telemetry sites ; Perform a filter: Use the simplified plane approximation formula to calculate the horizontal distance between the site and the equipment: ; in, represents the latitude difference, Indicates the difference in longitude; represents the radius of the Earth; Elevation difference correction: If you need to consider the three-dimensional distance, further calculate the elevation difference between the site and the device: ; Generate candidate set: Retention satisfaction The site obtained preliminary screening results: ; Where S represents the geographical coordinate set of all telemetry sites; S202, cone screening, in On this basis, we further filter out sites within the current viewing cone of the device camera to avoid rendering labels outside the field of view. The specific process is as follows: Input parameters: Device attitude: including pitch angle , yaw angle and roll angle ; Camera parameters: including horizontal field of view , vertical field of view and candidate site sets ; Screening Process: Constructing the frustum model: The view frustum is defined as a quadrangular pyramid formed by the field of view of the device camera, with its vertex at the device position and its axis aligned with the camera orientation. With the camera as the origin and the direction along the positive Z axis, the four sides of the view frustum are defined by the following plane equations: Near plane: ; Far Plane: z = z far; Left and right planes: ; Upper and lower planes: ; Coordinate transformation: The ENU coordinates of the candidate site Convert to the coordinates of the camera coordinate system : Constructing a rotation matrix from device Euler angles , perform coordinate rotation: ; Determination within the viewing cone: Site The following conditions must be met simultaneously to be within the viewing cone: ; Generate the final candidate set: ; S203, executing dynamic screening optimization strategy: Spatial index acceleration: Create a quadtree index and perform frustum calculations only for sites within the current view block. Hierarchical filtering: When the user moves the device quickly, the geographic radius filtering results are used first to render rough labels, and the frustum filtering is started after the device stabilizes; Direction guidance tips: The station in the image shows an arrow at the edge of the screen, with the direction of the arrow determined by the vector cross product: ; in is the camera facing vector, is the site direction vector.

[0027] Preferably, in step S3, the three-dimensional space anchoring module executes the three-dimensional space anchoring algorithm based on ARCore as follows: S301, mapping geographic coordinates to AR scene coordinates: Device coordinate system establishment: Construct the Northeastern Universe (ENU) local coordinate system with the current location of the mobile device as the reference point. The reference point includes longitude and latitude. ,latitude and elevation : Among them, the X axis represents the tangent in the due east direction; the Y axis represents the tangent in the due north direction; the Z axis represents the direction perpendicular to the surface; Site coordinate conversion: Perform the conversion from the geographic coordinate system to the ENU coordinate system for the target telemetry site: ; Among them, the longitude of the target telemetry site ,latitude , elevation ; R is the radius of the Earth; AR scene alignment: Get the device's initial pose matrix through ARCore's visual inertial odometry VIO , the site coordinates in the ENU coordinate system ( x , y , z ) is converted to the three-dimensional coordinates (x′, y′, z′) in the AR scene coordinate system; S302, spatial anchoring and posture synchronization based on ARCore: Geospatial anchor generation: Use ARCore Geospatial API to generate geospatial anchor points based on the site's geographic coordinates. and preset attitude quaternion Create spatial anchor points; Azimuth calculation: calculate the relative azimuth between the device and the site : ; The azimuth Converted to Euler angles in the AR scene to adjust the tag orientation; S303, dynamic label rendering, including: Frustum Filtering: Define the camera's field of view , calculate the site direction vector and the device's heading vector Angle: ; like If the site is within the visible range, the edge direction indicator arrow will be displayed; Distance Adaptive Scaling: Label Size S Distance from device-site d Inversely proportional: ; in As the base size, is the minimum display distance threshold; Environmental perception optimization: Lighting adaptation: collect ambient light intensity through the camera L , dynamically adjust label brightness B : ; Occlusion processing: When the AR plane is detected to overlap with the label position, the label transparency is Set to 0.5 to maintain visibility.

[0028] Preferably, the dimensional space anchoring algorithm also includes precision enhancement, and the specific method is as follows: Perform multi-source data fusion: Establish a Kalman filter model and integrate GPS positioning data , visual SLAM pose data and inertial sensor data Output optimal position estimate : ; in K is the Kalman gain matrix, is the observed value; Perform feature point assisted positioning: Deploy manual markers around key sites and achieve sub-meter positioning accuracy correction through image feature matching.

[0029] Example 2: This embodiment provides a specific implementation process of the 3D space anchoring algorithm based on ARCore: The user is located at 30.5°N, 114.3°E, and 50 meters above sea level. He needs to check the rain gauge 500 meters away at 30.4998°N, 114.2995°E, and 48 meters above sea level. The execution process is as follows: 1. Coordinate conversion, calculate the relative position in the ENU coordinate system: ; 2. Anchoring and rendering: Create an AR spatial anchor, bind the rain gauge label, and render it at the 3D coordinates (−36.7, −222.4, −2): Based on real-time distance m, proportionally reducing the label size to 44.3% of the preset value.

[0030] Example 3: This embodiment provides a specific implementation process of spatial range screening: User-defined filter radius , horizontal field of view of the device .

[0031] The screening process is as follows: Calculate the horizontal distance between all sites and equipment, and filter out di 20 sites with horz≤5000m ; Set the frustum parameters in the device coordinate system to: ; The 20 sites were judged within the visual cone, and finally 8 sites met the conditions. ; The remaining 12 sites display direction arrows at the edge of the screen, prompting users to rotate the device to view them.

Claims

1. A telemetry site location display and information query system based on AR information annotation, characterized by: It includes a multi-source data management module, an interactive query module, an AR recognition module and a mobile terminal device; the interactive query module is built into the mobile terminal device, and the mobile terminal device and the AR recognition module are connected to each other through the communication module; the AR recognition module and the multi-source data management module are connected to each other through the communication module; The multi-source data management module includes the telemetry site metadata database and the hydrological information database; The mobile terminal device is a mobile terminal device with a built-in positioning module, electronic compass, accelerometer and camera to achieve spatial posture perception; The AR recognition module includes a three-dimensional space anchoring module and a dynamic screening controller. The three-dimensional space anchoring module is used to generate site labels with orientation guide arrows, and the dynamic screening controller is used to filter and select the objects to be tested. The interactive query module includes a touch screen and a voice recognition module for realizing human-computer interaction; The communication module includes an LTE communication module and a Wi-Fi module.

2. The telemetry site location display and information query system based on AR information annotation according to claim 1 is characterized by: The telemetry site metadata database is used to store telemetry site metadata, which includes station name, station number, type, latitude and longitude, elevation, location, whether it is a control station, data source and management unit, where the location represents the geographical administrative area where the telemetry station is located.

3. The system and method for displaying and querying telemetry site locations based on AR information annotation according to claim 2, characterized in that: The telemetry station types include reservoir stations, hydrological stations, water level stations, rainfall stations and meteorological stations.

4. The AR information annotation-based telemetry site location display and information query system according to claim 3, characterized in that: The hydrological information database includes measurement point information of various types of telemetry stations; reservoir station measurement point information includes reservoir water level, inflow and outflow, storage capacity and forecast flow; hydrological station measurement point information includes water level and flow; water level station measurement point information is water level; rainfall station measurement point information is rainfall; meteorological station measurement point information includes temperature, humidity, air pressure, wind speed, wind direction and rainfall.

5. The telemetry site location display and information query system based on AR information annotation according to claim 1 is characterized in that: The three-dimensional space anchoring module executes a three-dimensional space anchoring algorithm based on ARCore.

6. The telemetry site location display and information query system based on AR information annotation according to claim 1 is characterized by: The dynamic screening controller filters the objects to be tested, including radius filtering, type filtering and alarm status filtering.

7. The method of the telemetry site location display and information query system based on AR information annotation according to any one of claims 1 to 6, characterized in that: The following steps are involved: S1, device posture synchronization: Collect the device's geographic coordinates and lens pointing azimuth through a mobile terminal device; S2, spatial range screening: Determine the visible area based on the view cone calculation and generate a set of candidate sites based on the user-set screening radius; S3, through the 3D space anchoring module, executes the 3D space anchoring algorithm based on ARCore to realize the anchoring of geographic coordinates to AR 3D space; S4, AR label generation and rendering: Assign differentiated icons based on site type; Dynamically calculate the spatial distance between the tag and the device, and scale the tag size based on the principle of larger near and smaller far. S5, hierarchical information display: The first-level label displays the station name and the set key indicators; The secondary details page displays site metadata, historical trend charts, and real-time video streams in columns; S6,interaction is performed through the interactive query module, including gesture and voice operations.

8. The method of the telemetry site location display and information query system based on AR information annotation according to claim 7, characterized in that: In step S2, the specific method of spatial range screening is: S201, geographical radius screening, screening out the telemetry sites within the user-set radius from all telemetry sites. The specific process for candidate sites is as follows: Input parameters: The device's current location coordinates: longitude ,latitude and elevation ; User-defined filter radius ; A collection of geographic coordinates of all telemetry sites ; Perform a filter: Use the simplified plane approximation formula to calculate the horizontal distance between the site and the equipment: ； in, represents the latitude difference, Indicates the difference in longitude; represents the radius of the Earth; Elevation difference correction: If you need to consider the three-dimensional distance, further calculate the elevation difference between the site and the device: ； Generate candidate set: Retention satisfaction The site obtained preliminary screening results: ； Where S represents the geographical coordinate set of all telemetry sites; S202, cone screening, in On this basis, we further filter out sites within the current viewing cone of the device camera to avoid rendering labels outside the field of view. The specific process is as follows: Input parameters: Device attitude: including pitch angle , yaw angle and roll angle ; Camera parameters: including horizontal field of view , vertical field of view and candidate site sets ; Screening Process: Constructing the frustum model: The view frustum is defined as a quadrangular pyramid formed by the field of view of the device camera, with its vertex at the device position and its axis aligned with the camera orientation. With the camera as the origin and the direction along the positive Z axis, the four sides of the view frustum are defined by the following plane equations: Near plane: ; Far Plane: z = z far; Left and right planes: ; Upper and lower planes: ; Coordinate transformation: The ENU coordinates of the candidate site Convert to the coordinates of the camera coordinate system : Constructing a rotation matrix from device Euler angles , perform coordinate rotation: ； Determination within the viewing cone: Site The following conditions must be met simultaneously to be within the viewing cone: ； Generate the final candidate set: ; S203, executing dynamic screening optimization strategy: Spatial index acceleration: Create a quadtree index and perform frustum calculations only for sites within the current view block. Hierarchical filtering: When the user moves the device quickly, the geographic radius filtering results are used first to render rough labels, and the frustum filtering is started after the device stabilizes; Direction guidance tips: The station in the image shows an arrow at the edge of the screen, with the direction of the arrow determined by the vector cross product: ； in is the camera facing vector, is the site direction vector.

9. The method of the telemetry site location display and information query system based on AR information annotation according to claim 8, characterized in that: In step S3, the 3D space anchoring module executes the ARCore-based 3D space anchoring algorithm as follows: S301, mapping geographic coordinates to AR scene coordinates: Device coordinate system establishment: Construct the Northeastern Universe (ENU) local coordinate system with the current location of the mobile device as the reference point. The reference point includes longitude and latitude. ,latitude and elevation : Among them, the X axis represents the tangent in the due east direction; the Y axis represents the tangent in the due north direction; the Z axis represents the direction perpendicular to the surface; Site coordinate conversion: Perform the conversion from the geographic coordinate system to the ENU coordinate system for the target telemetry site: ； Among them, the longitude of the target telemetry site ,latitude , elevation ; R is the radius of the Earth; AR scene alignment: Get the device's initial pose matrix through ARCore's visual inertial odometry VIO , the site coordinates in the ENU coordinate system ( x , y , z ) is converted to the three-dimensional coordinates (x′, y′, z′) in the AR scene coordinate system; S302, spatial anchoring and posture synchronization based on ARCore: Geospatial anchor generation: Use ARCore Geospatial API to generate geospatial anchor points based on the site's geographic coordinates. and preset attitude quaternion Create spatial anchor points; Azimuth calculation: calculate the relative azimuth between the device and the site : ； The azimuth Converted to Euler angles in the AR scene to adjust the tag orientation; S303, dynamic label rendering, including: Frustum Filtering: Define the camera's field of view , calculate the site direction vector and the device's heading vector Angle: ； like If the site is within the visible range, the edge direction indicator arrow will be displayed; Distance Adaptive Scaling: Label Size S Distance from device-site d Inversely proportional: ； in As the base size, is the minimum display distance threshold; Environmental perception optimization: Lighting adaptation: collect ambient light intensity through the camera L , dynamically adjust label brightness B : ； Occlusion processing: When the AR plane is detected to overlap with the label position, the label transparency is Set to 0.5 to maintain visibility.

10. The method of the telemetry site location display and information query system based on AR information annotation according to claim 9, characterized in that: The 3D space anchoring algorithm also includes precision enhancement, the specific method is as follows: Perform multi-source data fusion: Establish a Kalman filter model and integrate GPS positioning data , visual SLAM pose data and inertial sensor data Output optimal position estimate : ； in K is the Kalman gain matrix, is the observed value; Perform feature point assisted positioning: Deploy manual markers around key sites and achieve sub-meter positioning accuracy correction through image feature matching.

Images