Warning line monitoring system and method based on edge computing and beidou positioning

Abstract

The application provides a warning line monitoring system and method based on edge computing and Beidou positioning, and relates to the technical field of intelligent monitoring.The warning line monitoring system comprises a coordinate acquisition unit, a coordinate calibration unit, a parameter calculation unit, a movement analysis unit, a time prediction unit and a warning early warning unit.The coordinate acquisition unit is used for acquiring real-time positioning coordinates.The coordinate calibration unit is used for spatially calibrating the real-time positioning coordinates to obtain actual spatial coordinates.The parameter calculation unit is used for determining a direction of travel and a speed of travel according to the actual spatial coordinates.The movement analysis unit is used for obtaining a movement speed ratio according to a theoretical speed in the direction of travel and the speed of travel.The time prediction unit is used for predicting a travel time when the Beidou positioning fails to obtain a predicted arrival time.The warning early warning unit is used for monitoring and early warning of the warning line when the predicted arrival time is less than a warning value.The system and method provided by the application can realize dynamic sensing of an early warning signal of intrusion into a warning area, and ensure the mobility and reliability of the warning line monitoring.

Description

Technical Field

[0001] This invention relates to the field of intelligent monitoring technology, and in particular to a warning line monitoring system and method based on edge computing and BeiDou positioning. Background Technology

[0002] By setting up warning lines in the restricted area and monitoring them, the behavior of moving targets crossing the warning lines can be monitored in real time, thereby improving the security of the restricted area.

[0003] In existing perimeter monitoring processes, the location of moving targets is often directly based on BeiDou positioning. However, when the terrain near the perimeter is complex or the BeiDou positioning signal is weak (such as in urban canyons, mountainous areas, or indoor obstructions), BeiDou positioning may fail. If the positioning failure occurs just before approaching the perimeter, not only will it be impossible to accurately locate the moving target, but it will also be impossible to reasonably predict any behavior that may intrude into the perimeter boundary, greatly reducing the security of the perimeter. Summary of the Invention

[0004] This invention provides a warning line monitoring system and method based on edge computing and BeiDou positioning to address the technical problem that BeiDou positioning fails when the terrain near the warning line is complex or the BeiDou positioning signal is weak. Furthermore, if the positioning failure occurs just before approaching the warning zone, it not only fails to accurately locate moving targets but also fails to reasonably predict actions that intrude into the warning line boundary, significantly reducing the security of the warning zone.

[0005] To achieve the above and other related objectives, this invention provides a warning line monitoring system based on edge computing and BeiDou positioning, comprising: a coordinate acquisition unit for acquiring the real-time positioning coordinates of a moving target monitored by BeiDou positioning around the warning line; a coordinate calibration unit for spatially calibrating the real-time positioning coordinates in a geographic model to obtain the actual spatial coordinates of the moving target; a parameter calculation unit for determining the direction and speed of the moving target based on the movement path formed by the actual spatial coordinates in the geographic model; a movement analysis unit for performing movement rhythm analysis based on the theoretical speed and movement speed of the actual spatial coordinates in the direction of movement to obtain the movement speed ratio corresponding to the corresponding time, the movement speed ratio including the translational movement speed ratio and the variable movement speed ratio; a time prediction unit for acquiring the actual spatial coordinates of the target, the target movement speed ratio, the target direction of movement, and the geographic model corresponding to the start time of the failure when BeiDou positioning fails, and predicting the movement time corresponding to the warning line to obtain the predicted arrival time; and a warning and alert unit for generating a warning signal when the predicted arrival time is less than the warning value, so as to conduct warning line monitoring and early warning.

[0006] In one embodiment of the present invention, the invention further includes: a model building unit, comprising: an image acquisition subunit for acquiring geomorphic feature images around the warning line; a model construction subunit for performing surface feature recognition on the geomorphic feature images to obtain surface feature coordinates, and performing coordinate interpolation between the surface feature coordinates to establish a geomorphic structure model around the warning line; and a calibration subunit for calibrating the coordinates of each spatial point in the geomorphic structure model using theoretical speeds in different directions of travel to obtain a regional model.

[0007] In one embodiment of the present invention, the calibration subunit includes: a first division module, used to divide the surface structure model into multiple travel routes along the circumferential direction with the center of the warning line as the center; a second division module, used to identify the linear slope corresponding to each coordinate point of each travel route and divide each travel route into travel segments corresponding to different linear slopes; a vector calculation module, used to obtain the theoretical velocity vector corresponding to each spatial point coordinate when moving towards the center of the circle based on the coordinates of each spatial point, the starting coordinates of the travel segment corresponding to the spatial point coordinates, the linear slope of the travel segment, and the calibration speed of the moving target; and a model calibration module, used to calibrate the surface structure model based on the theoretical velocity vector corresponding to each spatial point coordinate to obtain a regional model.

[0008] In one embodiment of the present invention, the vector calculation module includes: an intermediate vector calculation submodule, used to obtain an intermediate velocity vector based on the coordinates of each spatial point, the starting coordinates of the travel segment corresponding to the spatial point coordinates, the linear slope of the travel segment, and the calibration speed of the moving target; a first vector output submodule, used to use the intermediate velocity vector as the first theoretical velocity vector corresponding to the spatial point coordinates moving towards the center when the point corresponding to the spatial point coordinates is a repaired road surface; and a second vector output submodule, used to correct the intermediate velocity vector based on the velocity reduction corresponding to the non-repaired road surface when the point corresponding to the spatial point coordinates is a non-repaired road surface, to obtain the second theoretical velocity vector corresponding to the spatial point coordinates moving towards the center.

[0009] In one embodiment of the present invention, the coordinate calibration unit includes: a coordinate detection subunit, used to perform coordinate detection on real-time positioning coordinates in a geographic model; a first calibration output subunit, used to use the real-time positioning coordinates as the actual spatial coordinates of the moving target when the existence of real-time positioning coordinates in the geographic model is detected; and a second calibration output subunit, used to perform altitude coordinate lookup on the geographic model based on the longitude and latitude coordinates in the real-time positioning coordinates when the absence of real-time positioning coordinates in the geographic model is detected, and to obtain the actual spatial coordinates of the moving target based on the longitude and latitude coordinates in the real-time positioning coordinates and the found altitude coordinates.

[0010] In one embodiment of the present invention, the parameter calculation unit includes: a length truncation subunit, used to truncate the movement path by a unit travel length based on the position of the actual spatial coordinates on the movement path formed in the regional model, to obtain the historical spatial coordinates of the movement path under the truncation node corresponding to the unit travel length; a direction analysis subunit, used to obtain the slope value of the current actual spatial coordinates on the unit travel length based on the unit travel length and the current actual spatial coordinates; and to perform a geographic direction conversion on the slope value to obtain the movement direction of the moving target; and a speed analysis subunit, used to obtain the time difference within the unit travel length based on the historical time corresponding to the historical spatial coordinates and the current time corresponding to the current actual spatial coordinates; and to obtain the movement speed of the moving target based on the unit travel length and the time difference.

[0011] In one embodiment of the present invention, the movement analysis unit includes: a vector lookup subunit, used to perform a corresponding theoretical speed vector lookup in the regional model based on the current actual spatial coordinates to obtain the current theoretical speed vector; a speed ratio calculation subunit, used to calculate the current theoretical speed of the current actual spatial coordinates in the current direction of travel based on the current direction of travel and the current theoretical speed vector, and to obtain the current movement speed ratio corresponding to the current moment based on the current theoretical speed and the current speed of travel corresponding to the current actual spatial coordinates; a speed ratio change analysis subunit, used to detect the change trend of the current movement speed ratio based on the historical speeds of multiple historical coordinate points before the current actual spatial coordinates and the historical speeds, and to obtain the trend change rate of the current movement speed ratio; a first speed ratio determination subunit, used to take the current movement speed ratio as the translational movement speed ratio when the trend change rate is zero; and a second speed ratio determination subunit, used to take the current movement speed ratio as the changing movement speed ratio when the trend change rate is not zero.

[0012] In one embodiment of the present invention, the speed ratio change analysis subunit includes: a history analysis module, used to extract the historical travel speeds of multiple historical coordinate points before the current actual spatial coordinates and the corresponding historical theoretical speeds of the historical travel speeds to obtain the historical travel speed ratio; a curve drawing module, used to draw a change curve between the travel speed ratio and the corresponding coordinate points based on the historical travel speed ratio and the current travel speed ratio; and a change extraction module, used to extract the linear change rate corresponding to the change curve as the trend change rate of the current travel speed ratio.

[0013] In one embodiment of the present invention, the time prediction unit includes: a path query subunit, used to perform a path query in a regional model based on the actual spatial coordinates of the target, the target's direction of travel, and a warning line, to obtain the optimal travel path from the actual spatial coordinates of the target to the warning line along the target's direction of travel; a model output subunit, used to output the theoretical speed of each predicted trajectory point corresponding to the optimal travel path through the regional model; a speed ratio processing subunit, used to process each theoretical speed through the target movement speed ratio to obtain the predicted travel speed at each predicted trajectory point, wherein the target movement speed ratio includes either a translational movement speed ratio or a variable movement speed ratio; a trajectory segment prediction subunit, used to obtain the predicted travel time at each trajectory segment distance based on the trajectory segment distance between each adjacent predicted trajectory point within the optimal travel path and the predicted travel speed; and a splicing subunit, used to splice the predicted travel times to obtain the predicted arrival time.

[0014] To achieve the above and other related objectives, this invention also provides a warning line monitoring method based on edge computing and BeiDou positioning, comprising: acquiring real-time positioning coordinates of a moving target monitored by BeiDou positioning around the warning line through a coordinate acquisition unit; spatially calibrating the real-time positioning coordinates in a regional model through a coordinate calibration unit to obtain the actual spatial coordinates of the moving target; determining the direction and speed of the moving target based on the movement path formed by the actual spatial coordinates in the regional model through a parameter calculation unit; performing movement rhythm analysis based on the theoretical speed and movement speed of the actual spatial coordinates in the direction of movement through a movement analysis unit to obtain the movement speed ratio corresponding to the corresponding time, the movement speed ratio including the translational movement speed ratio and the variable movement speed ratio; acquiring the actual spatial coordinates of the target, the target movement speed ratio, the target direction of movement, and the regional model corresponding to the start time of the failure through a time prediction unit when BeiDou positioning fails, and predicting the movement time corresponding to the warning line to obtain the predicted arrival time; and generating a warning signal through a warning unit when the predicted arrival time is less than a warning value to conduct warning line monitoring and early warning.

[0015] The beneficial effects of this invention are as follows: This invention proposes a warning line monitoring system and method based on edge computing and BeiDou positioning. By acquiring the real-time positioning coordinates of a mobile device detecting a moving target near the warning line using BeiDou positioning, and to ensure coordinate accuracy, the real-time positioning coordinates are calibrated based on a constructed geographic model to determine if they accurately fall within the model. If not, the real-time positioning coordinates are readjusted to determine the actual spatial coordinates of the moving target. Then, using the calibrated actual spatial coordinates, a corresponding movement path is constructed within the geographic model, and the moving target's direction and speed are analyzed and determined based on this path. After determining the direction and speed, the theoretical speed corresponding to the geographic model in the direction of movement is extracted, and combined with the corresponding speed, the moving target's speed ratio at different times is calculated as a backup in case of BeiDou positioning failure, thus achieving further edge computing. Specifically, when BeiDou positioning fails (including detecting weak positioning signals or inability to locate), the target's actual spatial coordinates, speed ratio, and direction of travel at the start of the failure can be obtained. This information, combined with a constructed regional model (e.g., theoretical speed, surface structure), can be used to predict the time it takes for the target to reach the warning line from its actual spatial coordinates, thus accurately assessing the predicted arrival time. Finally, the predicted arrival time can be compared with the warning value. When the predicted arrival time is less than the warning value, a warning signal is generated for monitoring and issuing warnings for the warning line. This ensures dynamic perception of warning signals based on regional model parameters such as geological shape and theoretical speed during the movement of the warning line for the moving target, guaranteeing the mobility and reliability of the warning line monitoring. Attached Figure Description

[0016] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort.

[0017] In the attached diagram: Figure 1 This is a structural block diagram of a warning line monitoring system based on edge computing and BeiDou positioning provided in an embodiment of the present invention; Figure 2 The diagram shown illustrates the velocity vector calibration process according to an embodiment of the present invention.

[0018] Figure 3 The diagram shown illustrates the coordinate calibration process using a regional model, as provided in an embodiment of the present invention.

[0019] Figure 4 The diagram shows a process for extracting the unit travel length of a movement path according to an embodiment of the present invention.

[0020] Figure 5 The diagram shown is a flowchart illustrating a warning line monitoring method based on edge computing and BeiDou positioning provided in an embodiment of the present invention.

[0021] The attached figures are labeled as follows: Coordinate acquisition unit 111; coordinate calibration unit 112; parameter calculation unit 113; movement analysis unit 114; time prediction unit 115; warning and alert unit 116. Detailed Implementation

[0022] The following specific examples illustrate the implementation of the present invention. Those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0023] It should be noted that the illustrations provided in the following embodiments are only schematic representations of the basic concept of the present invention. The drawings only show the components related to the present invention and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0024] In the following description, numerous details are explored to provide a more thorough explanation of embodiments of the invention. However, it will be apparent to those skilled in the art that embodiments of the invention may be practiced without these specific details. In other embodiments, well-known structures and devices are shown in block diagram form rather than in detail to avoid obscuring embodiments of the invention.

[0025] Please see Figure 1This invention provides a warning line monitoring system based on edge computing and BeiDou positioning, comprising: a coordinate acquisition unit 111 for acquiring the real-time positioning coordinates of a moving target monitored by BeiDou positioning around the warning line; a coordinate calibration unit 112 for spatially calibrating the real-time positioning coordinates in a geographic model to obtain the actual spatial coordinates of the moving target; a parameter calculation unit 113 for determining the direction and speed of the moving target based on the movement path formed by the actual spatial coordinates in the geographic model; a movement analysis unit 114 for performing movement rhythm analysis based on the theoretical speed and movement speed of the actual spatial coordinates in the direction of movement to obtain the movement speed ratio corresponding to the corresponding time, the movement speed ratio including the translational movement speed ratio and the variable movement speed ratio; a time prediction unit 115 for acquiring the actual spatial coordinates of the target, the target movement speed ratio, the target direction of movement, and the geographic model corresponding to the start time of the failure when BeiDou positioning fails, and predicting the movement time corresponding to the warning line to obtain the predicted arrival time; and a warning and alert unit 116 for generating a warning signal when the predicted arrival time is less than the warning value, so as to conduct warning line monitoring and alerting.

[0026] As can be seen from the above, when using a warning line to monitor and warn of moving targets carrying mobile devices, the coordinate acquisition unit 111 can obtain the real-time positioning coordinates of the mobile device detected by BeiDou positioning when it is located around the warning line. These real-time positioning coordinates can specifically be three-dimensional coordinates. After obtaining the real-time positioning coordinates, to ensure accuracy, the coordinate calibration unit 112 can use these coordinates to perform spatial position calibration based on the constructed regional model. This determines whether the real-time positioning coordinates accurately fall within the regional model. If not, the real-time positioning coordinates can be readjusted to determine the actual spatial coordinates of the moving target based on the real-time positioning coordinates. Then, the parameter calculation unit 113 can use the calibrated actual spatial coordinates to further construct a corresponding movement path in the regional model, and based on this movement path, analyze and determine the moving target's movement parameters, including the direction and speed of movement. After determining the direction and speed of travel, the motion analysis unit 114 further extracts the theoretical speed of the actual spatial coordinates corresponding to the geographical model in the direction of travel. Combined with the corresponding speed, the movement speed ratio of the moving target at different times is calculated as a backup in case of BeiDou positioning failure, enabling further edge computing. Specifically, when BeiDou positioning fails (including detecting weak positioning signals or inability to locate), the time prediction unit 115 obtains the target's actual spatial coordinates, movement speed ratio, and direction of travel at the start of the failure. Using these coordinates, combined with the constructed geographical model (e.g., theoretical speed, surface structure), the travel time from the target's actual spatial coordinates to the warning line can be predicted, accurately assessing the predicted arrival time. Finally, the warning unit 116 can compare the predicted arrival time and the warning value, and generate a warning signal when the predicted arrival time is less than the warning value, so as to monitor and warn the warning line. This ensures the dynamic perception of the warning signal based on regional model parameters such as geological shape and theoretical speed during the movement of the warning line of the moving target, and ensures the mobility and reliability of the warning line monitoring.

[0027] The edge computing and BeiDou positioning-based warning line monitoring system of the present invention may further include: a model building unit, which includes: an image acquisition subunit for acquiring geomorphic feature images around the warning line; a model construction subunit for identifying surface features in the geomorphic feature images to obtain surface feature coordinates, and performing coordinate interpolation between the surface feature coordinates to establish a geomorphic structure model around the warning line; and a calibration subunit for calibrating the coordinates of each spatial point in the geomorphic structure model using theoretical velocities in different directions to obtain a regional model.

[0028] When using the warning line monitoring system of this invention, it is also necessary to model and calibrate the regional model in advance through the model building unit to ensure the accuracy of the predicted arrival time. Specifically, the image acquisition subunit can first acquire images of the terrain features around the warning line. For example, images of the terrain features around the warning line can be acquired through drone photography and then uploaded to the model image acquisition subunit. Then, the model building subunit first identifies the surface features in the terrain image features and, based on the drone's shooting altitude, determines the coordinates of the surface features at each directly identifiable location. The surface feature coordinates are used to construct the basic framework of the surface structure model, and interpolation is performed between the surface feature coordinates to construct the surface structure model that reflects the surface shape features around the warning line. Of course, areas where the surface feature coordinates cannot be identified can also be calibrated manually to ensure the accuracy of the surface shape features around the warning line. After determining the surface structure model, the theoretical velocities of each spatial point in the surface structure model can be further calibrated in different directions of travel by calibration sub-units, thereby deriving a regional model. This model can not only show the position coordinates of each location point around the warning line, but also reflect the theoretical velocity of each location point. This facilitates the prediction of the moving target's speed ratio and the prediction of the travel time to the warning line when BeiDou positioning fails, so as to make advance warning and prevention measures.

[0029] In the model building unit, the calibration subunit may further include: a first division module, used to divide the surface structure model into multiple travel routes along the circumferential direction with the center of the warning line as the center; a second division module, used to identify the linear slope corresponding to each coordinate point of each travel route and divide each travel route into travel segments corresponding to different linear slopes; a vector calculation module, used to obtain the theoretical velocity vector corresponding to each spatial point coordinate when moving towards the center, based on the coordinates of each spatial point, the starting coordinates of the travel segment corresponding to the spatial point coordinate, the linear slope of the travel segment, and the calibration velocity of the moving target; and a model calibration module, used to calibrate the surface structure model based on the theoretical velocity vector corresponding to each spatial point coordinate to obtain a regional model.

[0030] Please see Figure 2When calibrating the theoretical velocity ratio of the surface structure model, the calibration subunit can first use the first partitioning module to divide the surface structure model into multiple travel routes towards the center of the warning line, using the center of the warning line as the center, to calibrate the theoretical four-dimensional vector of the moving target. Specifically, the second partitioning module can identify and calculate the linear slope corresponding to each coordinate point on the travel route, thereby dividing the travel route into multiple different travel segments based on the different linear slopes. The vector calculation module calculates the theoretical velocity vector corresponding to each spatial point coordinate as it travels towards the center, based on the coordinates of each spatial point, the starting coordinates of the corresponding travel segment, the linear slope of the travel segment, and the calibration velocity of the moving target. After calculating the theoretical velocity vector, the model calibration module can calibrate the theoretical velocity vector of each spatial point coordinate in the surface structure model. After calibration, the regional model is updated to not only show the position coordinates of each location point around the warning line, but also reflect the theoretical velocity of each location point.

[0031] The vector calculation module may further include: an intermediate vector calculation submodule, used to obtain an intermediate velocity vector based on the coordinates of each spatial point, the starting coordinates of the travel segment corresponding to the spatial point coordinates, the linear slope of the travel segment, and the calibration speed of the moving target; a first vector output submodule, used to use the intermediate velocity vector as the first theoretical velocity vector corresponding to the spatial point coordinates moving towards the center when the point corresponding to the spatial point coordinates is a repaired road surface; and a second vector output submodule, used to correct the intermediate velocity vector based on the velocity reduction corresponding to the non-repaired road surface when the point corresponding to the spatial point coordinates is a non-repaired road surface, to obtain the second theoretical velocity vector corresponding to the spatial point coordinates moving towards the center.

[0032] During the theoretical velocity vector calculation process, the vector calculation module can obtain an intermediate velocity vector through the intermediate vector calculation submodule, based on the coordinates of each spatial point, the starting coordinates of the corresponding travel segment, the linear slope of the travel segment, and the calibrated velocity of the moving target. After obtaining the intermediate velocity vector, the position corresponding to the spatial point coordinates can be further detected. When the position corresponding to the spatial point coordinates is a repaired road surface, the first vector output submodule uses the intermediate velocity vector as the first theoretical velocity vector corresponding to the spatial point coordinates moving towards the center of the circle. When the position corresponding to the spatial point coordinates is not a repaired road surface, the second vector output submodule corrects the intermediate velocity vector based on the velocity reduction corresponding to the non-repaired road surface, obtaining the second theoretical velocity vector corresponding to the spatial point coordinates moving towards the center of the circle.

[0033] In the specific calculation process, the linear slope of the traveling line segment can be used to find the corresponding velocity attenuation factor through the linear slope-velocity attenuation factor correspondence table. Then, combined with the velocity attenuation caused by the unit length, the intermediate velocity vector corresponding to each spatial point coordinate when moving towards the center of the circle can be calculated.

[0034] The formula for calculating the intermediate velocity vector can be expressed as: ; Indicates the intermediate velocity vector. Indicates the calibrated speed. Indicates the velocity decay factor. This indicates the number of units of length formed by the traveling line segment. It is an integer. This represents the rate of velocity decay, and its value increases with the amount of velocity per unit length. Increases with the increase, Indicates the length of the travel segment. This indicates the unit length and can be set manually.

[0035] Finally, when the point corresponding to the spatial coordinates is the road surface being repaired, the intermediate velocity vector can be directly used. The first theoretical velocity vector is used as the reference point. When the spatial coordinates correspond to an unrepaired road surface, the second theoretical velocity vector can be expressed by the formula: , Represents the second theoretical velocity vector. This indicates a decrease in speed, and this decrease can be set to a fixed value through human experience.

[0036] Of course, when calibrating the theoretical velocity vector of the surface structure model, the theoretical velocity vector of the road section can also be calibrated directly through human experience, or by other means.

[0037] In the warning line monitoring system of the present invention, the coordinate calibration unit 112 may further include: a coordinate detection subunit, used to perform coordinate detection on real-time positioning coordinates in the regional model; a first calibration output subunit, used to use the real-time positioning coordinates as the actual spatial coordinates of the moving target when the real-time positioning coordinates are detected in the regional model; and a second calibration output subunit, used to perform altitude coordinate search on the regional model based on the longitude and latitude coordinates in the real-time positioning coordinates when the real-time positioning coordinates are not detected in the regional model, and obtain the actual spatial coordinates of the moving target based on the longitude and latitude coordinates in the real-time positioning coordinates and the found altitude coordinates.

[0038] During spatial coordinate calibration, the coordinate detection subunit can use the geographic model to detect whether the real-time positioning coordinates correspond. If real-time positioning coordinates are detected in the geographic model, the first calibration output subunit can directly use the real-time positioning coordinates as the actual spatial coordinates of the moving target. However, if real-time positioning coordinates are not detected in the geographic model, such as... Figure 3 In the given example, the second calibration output subunit can use the longitude and latitude coordinates from the real-time positioning coordinates to look up the corresponding elevation coordinates of the land surface in the regional model. Then, by combining these with the longitude and latitude coordinates from the real-time positioning coordinates, the actual spatial coordinates of the calibrated moving target can be updated.

[0039] In the warning line monitoring system of the present invention, the parameter calculation unit 113 may further include: a length interception subunit, used to intercept the movement path by a unit travel length according to the position of the actual spatial coordinates on the movement path formed in the regional model, and obtain the historical spatial coordinates of the movement path under the interception node corresponding to the unit travel length; a direction analysis subunit, used to obtain the slope value of the current actual spatial coordinates on the unit travel length according to the unit travel length and the current actual spatial coordinates; and to perform geographical direction conversion on the slope value to obtain the movement direction of the moving target; and a speed analysis subunit, used to obtain the time difference within the unit travel length according to the historical time corresponding to the historical spatial coordinates and the current time corresponding to the current actual spatial coordinates; and to obtain the movement speed of the moving target according to the unit travel length and the time difference.

[0040] When determining the direction and speed of a moving target, parameter calculation unit 113 can first extract the position of the actual spatial coordinates of the sub-unit on the movement path formed in the regional model by length-truncation sub-units. It then performs unit-length truncation on the path already traversed by each actual spatial coordinate, thereby finding the interception node after the unit-length truncation on the movement path before the actual spatial coordinates and outputting the historical spatial coordinates corresponding to that interception node. For details, please refer to [reference needed]. Figure 4 The example given is as follows. Then, the direction analysis sub-unit uses the unit travel length and the current actual spatial coordinates to determine the tangent line on the line segment corresponding to the current actual spatial coordinates on the unit travel length. The inclination of this tangent line in the coordinate system is used as the slope value of the current actual spatial coordinates on the unit travel length. This slope value is then transformed to correspond to the actual geographical orientation, thereby determining the direction of travel of the moving target.

[0041] In the warning line monitoring system of the present invention, the movement analysis unit 114 includes: a vector lookup subunit, used to perform a corresponding theoretical speed vector lookup in the regional model based on the current actual spatial coordinates to obtain the current theoretical speed vector; a speed ratio calculation subunit, used to calculate the current theoretical speed of the current actual spatial coordinates in the current direction of travel based on the current direction of travel and the current theoretical speed vector, and to obtain the current movement speed ratio corresponding to the current moment based on the current theoretical speed and the current speed of travel corresponding to the current actual spatial coordinates; a speed ratio change analysis subunit, used to detect the change trend of the current movement speed ratio based on the historical speeds of multiple historical coordinate points before the current actual spatial coordinates and the historical speeds, and to obtain the trend change rate of the current movement speed ratio; a first speed ratio determination subunit, used to take the current movement speed ratio as the translational movement speed ratio when the trend change rate is zero; and a second speed ratio determination subunit, used to take the current movement speed ratio as the changing movement speed ratio when the trend change rate is not zero.

[0042] In determining the movement speed ratio of a moving target, the movement analysis unit 114 can first use a vector lookup subunit to quickly and easily find the theoretical velocity vector corresponding to the current actual spatial coordinates in the geographic model. Then, the speed ratio calculation subunit uses the current direction of travel and the current theoretical velocity vector to determine the angle between them, and calculates the current theoretical velocity at the current actual spatial coordinates in the current direction of travel, following a vector calculation method. Finally, based on the current theoretical velocity and the current travel velocity corresponding to the current actual spatial coordinates, the speed ratio between the current travel velocity and the current theoretical velocity is determined, serving as the current movement speed ratio at the current moment. Furthermore, to determine the changes in the movement speed ratio at points after the current actual spatial coordinates, the speed ratio change analysis subunit can use the historical travel velocities of multiple historical coordinate points before the current actual spatial coordinates to detect the trend of change in the current movement speed ratio, thus determining the rate of change of the current movement speed ratio. When the trend change rate is zero, the current moving speed ratio can be used as the horizontal moving speed ratio by determining the sub-unit through the first speed ratio. When the trend change rate is not zero, the current moving speed ratio can be used as the variable moving speed ratio by determining the sub-unit through the second speed ratio.

[0043] In the movement analysis unit 114, the speed ratio change analysis subunit may further include: a history analysis module, used to extract the historical travel speed and the corresponding historical theoretical speed of multiple historical coordinate points before the current actual spatial coordinates, to obtain the historical movement speed ratio; a curve drawing module, used to draw the change curve between the movement speed ratio and the corresponding coordinate point based on the historical movement speed ratio and the current movement speed ratio; and a change extraction module, used to extract the linear change rate corresponding to the change curve as the trend change rate of the current movement speed ratio.

[0044] When analyzing and calculating the trend change rate, the speed ratio change analysis subunit can extract the historical travel speed and its corresponding theoretical speed from multiple historical coordinate points before the current actual spatial coordinates through the historical analysis module. Then, referring to the aforementioned current movement speed ratio calculation method, the historical movement speed ratio can be calculated. The curve plotting module then uses the historical and current movement speed ratios to plot the change curve between the movement speed ratio (including historical and current movement speed ratios) and the corresponding coordinate points. Finally, the change extraction module extracts the linear change rate corresponding to the change curve as the trend change rate of the current movement speed ratio. For example, the least squares method can be used to determine the linear slope of the change curve based on the distribution of historical and current movement speed ratios, which can then be used as the trend change rate. This allows for the determination of whether the movement speed ratio will change after the current movement speed ratio. If it does change, the current movement speed ratio can be increased or decreased accordingly based on the changing trend change rate, thus ensuring the accuracy of the prediction time.

[0045] In the warning line monitoring system of the present invention, the time prediction unit 115 includes: a path query subunit, used to perform a path query in the regional model based on the actual spatial coordinates of the target, the target's direction of travel, and the warning line, to obtain the optimal travel path from the actual spatial coordinates of the target to the warning line along the target's direction of travel; a model output subunit, used to output the theoretical speed of each predicted trajectory point corresponding to the optimal travel path through the regional model; a speed ratio processing subunit, used to process each theoretical speed through the target movement speed ratio to obtain the predicted travel speed under each predicted trajectory point, wherein the target movement speed ratio includes one of the translational movement speed ratio and the variable movement speed ratio; a trajectory segment prediction subunit, used to obtain the predicted travel time under each trajectory segment distance based on the trajectory segment distance between each adjacent predicted trajectory point within the optimal travel path and the predicted travel speed; and a splicing subunit, used to splice the predicted travel times to obtain the predicted arrival time.

[0046] In the process of predicting arrival time, the time prediction unit 115 can use the path query subunit to determine the optimal travel path from the target's actual spatial coordinates to the warning line along the target's travel direction in the regional model, using the target's actual spatial coordinates, travel direction, and warning line. This optimal travel path can be the shortest distance obtained using the proximity principle. Then, the model output subunit directly outputs the theoretical speed of each predicted trajectory point corresponding to the optimal travel path using the regional model. Subsequently, the speed ratio processing subunit processes each theoretical speed using the target's movement speed ratio to obtain the predicted travel speed at each predicted trajectory point. Furthermore, the trajectory segment prediction subunit uses the trajectory segment distance between adjacent predicted trajectory points within the optimal travel path and the predicted travel speed to predict the predicted travel time for each trajectory segment distance. Finally, the splicing subunit splices the predicted travel times and superimposes them to obtain the predicted arrival time. This predicted arrival time can then be used for early warning monitoring, improving the safety and reliability of the warning line monitoring process.

[0047] Preferably, the formula for calculating the predicted arrival time can be expressed as: ; in, Indicates the predicted arrival time. This represents the distance between adjacent predicted trajectory points. Indicates the first Predict the theoretical velocity corresponding to the trajectory point. Indicates the target movement speed ratio. This represents the rate of change of the trend corresponding to the target moving speed ratio. Indicates when Predicted travel time Indicates when The predicted travel time.

[0048] Please see Figure 5 The present invention also provides a warning line monitoring method based on edge computing and BeiDou positioning, comprising: Step 10: Obtain the real-time positioning coordinates of the moving target around the warning line through the coordinate acquisition unit 111; Step 20: The real-time positioning coordinates are spatially calibrated in the regional model using the coordinate calibration unit 112 to obtain the actual spatial coordinates of the moving target; Step 30: The parameter calculation unit 113 determines the direction and speed of movement of the moving target based on the movement path formed by the actual spatial coordinates in the regional model. Step 40: The movement analysis unit 114 performs movement rhythm analysis based on the theoretical speed and movement speed of the actual spatial coordinates in the direction of travel to obtain the movement speed ratio corresponding to the corresponding moment. The movement speed ratio includes the translational movement speed ratio and the variable movement speed ratio. Step 50: When BeiDou positioning fails, the time prediction unit 115 obtains the target's actual spatial coordinates, target movement speed ratio, target direction of travel, and regional model corresponding to the start time of failure, and performs a travel time prediction corresponding to the warning line to obtain the predicted arrival time. Step 60: When the predicted arrival time is less than the warning value, the warning unit 116 generates a warning signal to monitor and warn of the warning line.

[0049] In summary, this invention discloses a warning line monitoring system and method based on edge computing and BeiDou positioning. By acquiring the real-time positioning coordinates of a mobile device detecting a moving target near a warning line using BeiDou positioning, and to ensure coordinate accuracy, the real-time positioning coordinates are calibrated using a constructed geographic model. This determines whether the real-time positioning coordinates accurately fall within the geographic model. If not, the real-time positioning coordinates are readjusted to determine the actual spatial coordinates of the moving target. Then, using the calibrated actual spatial coordinates, a corresponding movement path is constructed within the geographic model, and the moving target's direction and speed are analyzed and determined based on this path. After determining the direction and speed, the theoretical speed corresponding to the geographic model under the actual spatial coordinates in the direction of movement is extracted. Combined with the corresponding speed, the moving target's speed ratio at different times is calculated as a backup in case of BeiDou positioning failure, thus achieving further edge computing. Specifically, when BeiDou positioning fails (including detecting weak positioning signals or inability to locate), the actual spatial coordinates, speed ratio, and direction of travel of the target at the start of the failure can be obtained. These parameters, combined with a constructed regional model (e.g., theoretical speed, surface structure), can then be used to predict the travel time from the target's actual spatial coordinates to the warning line, thus accurately assessing the predicted arrival time. Finally, the predicted arrival time can be compared with the warning value, and a warning signal is generated when the predicted arrival time is less than the warning value. This allows for monitoring and issuing warnings for the warning line, ensuring dynamic perception of warning signals based on regional model parameters such as geological shape and theoretical speed during the movement of the moving target along the warning line, guaranteeing the mobility and reliability of the warning line monitoring. Therefore, this invention effectively overcomes the various shortcomings of existing technologies and has high industrial application value.

[0050] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

Claims

1. A warning line monitoring system based on edge computing and BeiDou positioning, characterized in that, include: The coordinate acquisition unit is used to acquire the real-time positioning coordinates of the moving target monitored by Beidou positioning around the warning line; The model building unit is used to acquire geomorphic feature images around the warning line to establish a surface structure model, and divide the travel route with the center of the warning line as the center. The travel line segments are divided according to the linear slope. Based on the starting coordinates of the travel line segments corresponding to the spatial point coordinates, the linear slope of the travel line segments, the calibration speed of the moving target, and the road conditions where the spatial point coordinates are located, the theoretical velocity vector of each spatial point coordinate moving towards the center is obtained, and the regional model is calibrated. The road conditions include repaired road surfaces and unrepaired road surfaces, and the theoretical velocity vector includes a first theoretical velocity vector corresponding to the repaired road surface and a second theoretical velocity vector corresponding to the unrepaired road surface. The coordinate calibration unit is used to perform spatial calibration of the real-time positioning coordinates in the regional model. When the real-time positioning coordinates are not in the regional model, the unit performs height coordinate search and replacement on the regional model based on the longitude and latitude coordinates of the real-time positioning coordinates to obtain the actual spatial coordinates of the moving target. The parameter calculation unit is used to determine the direction and speed of the moving target based on the movement path formed by the actual spatial coordinates in the regional model. The movement analysis unit is used to perform movement rhythm analysis based on the theoretical speed in the regional model under the direction of movement and the actual spatial coordinates, to obtain the movement speed ratio at the corresponding moment, and to extract the trend change rate of the movement speed ratio, wherein the movement speed ratio includes the horizontal movement speed ratio and the variable movement speed ratio. The time prediction unit is used to, when BeiDou positioning fails, acquire the target's actual spatial coordinates, target movement speed ratio, target direction of travel, and regional model corresponding to the start time of the failure; query the optimal travel path along the regional model; and, based on the theoretical speed of each predicted trajectory point in the optimal travel path, the corresponding movement speed ratio, and the trend change rate, predict the travel time corresponding to the warning line to obtain the predicted arrival time; and The warning and alert unit is used to generate an alert signal when the predicted arrival time is less than the warning value, so as to monitor and warn of the warning line.

2. The warning line monitoring system based on edge computing and BeiDou positioning according to claim 1, characterized in that, Also includes: Model building unit, the model building unit includes: The image acquisition subunit is used to acquire images of the terrain features around the warning line; The model construction subunit is used to perform surface feature recognition on the terrain feature image, obtain surface feature coordinates, and perform coordinate interpolation between the surface feature coordinates to establish a surface structure model around the warning line; and The calibration subunit is used to calibrate the theoretical velocity of each spatial point coordinate in the surface structure model in different directions of travel to obtain the regional model.

3. The warning line monitoring system based on edge computing and BeiDou positioning according to claim 2, characterized in that, The calibration subunit includes: The first division module is used to divide the surface structure model into multiple travel routes along the circumferential direction, with the center of the warning line as the center. The second division module is used to identify the linear slope corresponding to each coordinate point of each of the travel routes and divide each of the travel routes into travel segments corresponding to different linear slopes. The vector calculation module is used to obtain the theoretical velocity vector corresponding to each spatial point as it moves towards the center of the circle, based on the coordinates of each spatial point, the starting coordinates of the corresponding travel segment, the linear slope of the travel segment, and the calibrated velocity of the moving target; and The model calibration module is used to calibrate the surface structure model based on the theoretical velocity vector corresponding to the coordinates of each spatial point, so as to obtain the regional model.

4. The warning line monitoring system based on edge computing and BeiDou positioning according to claim 3, characterized in that, The vector calculation module includes: The intermediate vector calculation submodule is used to obtain the intermediate velocity vector based on the coordinates of each spatial point, the starting coordinates of the travel segment corresponding to the spatial point coordinates, the linear slope of the travel segment, and the calibration velocity of the moving target. The first vector output submodule is used to, when the point corresponding to the spatial point coordinates is a road surface under repair, use the intermediate velocity vector as the first theoretical velocity vector corresponding to the spatial point coordinates moving towards the center of the circle; and The second vector output submodule is used to correct the intermediate velocity vector based on the velocity reduction corresponding to the unrepaired road surface when the point corresponding to the spatial point coordinates is an unrepaired road surface, so as to obtain the second theoretical velocity vector corresponding to the spatial point coordinates moving towards the center of the circle.

5. The warning line monitoring system based on edge computing and BeiDou positioning according to claim 1, characterized in that, The coordinate calibration unit includes: A coordinate detection subunit is used to perform coordinate detection on the real-time positioning coordinates in the geographic model; The first calibration output subunit is used to use the real-time positioning coordinates as the actual spatial coordinates of the moving target when the real-time positioning coordinates are detected in the geographic model; and The second calibration output subunit is used to perform an altitude coordinate search on the regional model based on the longitude and latitude coordinates in the real-time positioning coordinates when the real-time positioning coordinates are not detected in the regional model. Based on the longitude and latitude coordinates in the real-time positioning coordinates and the found altitude coordinates, the actual spatial coordinates of the moving target are obtained.

6. The warning line monitoring system based on edge computing and BeiDou positioning according to claim 1, characterized in that, The parameter calculation unit includes: The length truncation subunit is used to truncate the action path by a unit travel length based on the position of the actual spatial coordinates on the action path formed in the regional model, so as to obtain the historical spatial coordinates of the action path under the truncation node corresponding to the unit travel length. The direction analysis subunit is used to obtain the slope value of the current actual spatial coordinates along the unit travel length based on the unit travel length and the current actual spatial coordinates; to perform a geographic direction transformation on the slope value to obtain the travel direction of the moving target; and The speed analysis subunit is used to obtain the time difference within the unit travel length based on the historical time corresponding to the historical spatial coordinates and the current time corresponding to the current actual spatial coordinates; and to obtain the travel speed of the moving target based on the unit travel length and the time difference.

7. The warning line monitoring system based on edge computing and BeiDou positioning according to claim 1, characterized in that, The mobility analysis unit includes: The vector lookup subunit is used to perform a corresponding theoretical velocity vector lookup in the regional model based on the current actual spatial coordinates to obtain the current theoretical velocity vector. The speed ratio calculation subunit is used to calculate the current theoretical speed of the current actual spatial coordinates in the current direction of travel based on the current direction of travel corresponding to the current actual spatial coordinates and the current theoretical speed vector, and to obtain the current movement speed ratio corresponding to the current moment based on the current theoretical speed and the current speed of travel corresponding to the current actual spatial coordinates. The speed ratio change analysis subunit is used to detect the change trend of the current movement speed ratio based on the historical travel speed and historical travel speed of multiple historical coordinate points before the current actual spatial coordinates, and to obtain the trend change rate of the current movement speed ratio. The first speed ratio determination subunit is used to take the current moving speed ratio as the translational moving speed ratio when the trend change rate is zero; and The second speed ratio determination subunit is used to take the current moving speed ratio as the changing moving speed ratio when the trend change rate is not zero.

8. The warning line monitoring system based on edge computing and BeiDou positioning according to claim 7, characterized in that, The speed ratio change analysis subunit includes: The historical analysis module is used to extract the historical travel speed and the corresponding historical theoretical speed of multiple historical coordinate points before the current actual spatial coordinates, and to obtain the historical movement speed ratio. The curve drawing module is used to draw a curve showing the change between the movement speed ratio and the corresponding coordinate points based on the historical movement speed ratio and the current movement speed ratio; and The change extraction module is used to extract the linear rate of change corresponding to the change curve as the trend rate of change of the current moving speed ratio.

9. The warning line monitoring system based on edge computing and BeiDou positioning according to claim 1, characterized in that, The time prediction unit includes: The path query subunit is used to perform a path query in the regional model based on the actual spatial coordinates of the target, the direction of travel of the target, and the warning line, to obtain the optimal travel path from the actual spatial coordinates of the target to the warning line along the direction of travel of the target. The model output sub-unit is used to output the theoretical speed of each predicted trajectory point corresponding to the optimal travel path through the regional model; The speed ratio processing subunit is used to process each of the theoretical speeds through the target movement speed ratio to obtain the predicted travel speed at each predicted trajectory point. The target movement speed ratio includes one of the translational movement speed ratio and the variable movement speed ratio. The trajectory segment prediction subunit is used to obtain the predicted travel time for each trajectory segment distance based on the trajectory segment distance between each adjacent predicted trajectory point within the optimal travel path and the predicted travel speed; and The splicing subunit is used to splice the predicted travel time to obtain the predicted arrival time.

10. A monitoring method for a warning line monitoring system based on edge computing and BeiDou positioning as described in any one of claims 1-9, characterized in that, include: The coordinate acquisition unit obtains the real-time positioning coordinates of the moving target around the warning line, which is monitored by Beidou positioning. The real-time positioning coordinates are spatially calibrated in the geographic model by the coordinate calibration unit to obtain the actual spatial coordinates of the moving target. The parameter calculation unit determines the direction and speed of the moving target based on the movement path formed in the regional model according to the actual spatial coordinates. The movement analysis unit performs movement rhythm analysis based on the theoretical speed and the actual speed in the direction of travel according to the actual spatial coordinates, and obtains the movement speed ratio at the corresponding moment. The movement speed ratio includes the translational movement speed ratio and the variable movement speed ratio. When BeiDou positioning fails, the time prediction unit obtains the target's actual spatial coordinates, target movement speed ratio, target direction of travel, and regional model corresponding to the start time of failure, and performs a travel time prediction corresponding to the warning line to obtain the predicted arrival time. When the predicted arrival time is less than the warning value, the warning unit generates a warning signal to monitor and warn of the warning line.

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