163 results about "Global Positioning System" patented technology

The invention discloses a mobile phone anti-theft system and method based on a camera and a GPS (Global Position System) of a mobile phone. The mobile phone anti-theft system comprises a mobile phone CPU (Central Processing Unit), a microprocessor, a camera driving module, an input module and an unlocking detection module, wherein the input module is connected with the unlocking detection module; the unlocking detection module is connected with the mobile phone CPU; and the mobile phone CPU is connected with the camera driving module through the microprocessor. Compared with the prior art, the mobile phone anti-theft system and method provided by the invention have the advantages as follows: an unlocking operation is carried out when the mobile phone is used after the mobile phone is lost or stolen, and a background operation program which is installed in the mobile phone is triggered and started when the unlocking operation is inaccurate; and a user who currently uses the mobile phone is positioned and photographed through a GPS module and the camera of the mobile phone; meanwhile, obtained information is sent to a mailbox or other addresses which are specified by the user in time, so that the user is convenient to alarm and can find the mobile phone back accurately in time, and the problems of the mobile phone loss and personnel information release of the user can be solved.

The invention relates to the technical field of aerospace, in particular to low-altitude traffic flow airspace-oriented real-time planning, and provides a centimeter-level precision detection network covering a low-altitude airspace by integrating multi-dimensional data sources such as radar electromagnetic feature recognition, ADS-B (Automatic Dependent Surveillance-Broadcast) automatic monitoring, Beidou or GPS (Global Positioning System) space-time reference positioning and the like. The three-dimensional trajectory and motion situation of the aircraft are solved in real time, intelligent reconstruction of an airspace sector and adaptive optimization of a flight corridor are realized by adopting a dynamic programming algorithm driven by reinforcement learning based on the real-time pose data of the aircraft, and a flight conflict prediction model constructed by combining a space-time convolutional neural network is used for predicting the flight conflict. According to the method, potential risks can be pre-judged, an optimal avoidance path can be generated, full-process digital management and control from identity verification to airspace authorization can be realized by constructing an aircraft digital identity authentication system and a dynamic access control mechanism, and modules such as a three-dimensional navigation information service module, a low-altitude digital communication private network module and an intelligent early warning and warning system module are integrated. And the guarantee of full-life-cycle service is provided for the low-altitude aircraft.

The invention discloses an unmanned aerial vehicle cluster intelligent cooperative positioning method and system based on machine learning, relates to the technical field of artificial intelligence and unmanned aerial vehicles, and aims to solve the problems that positioning signals are attenuated and drifted and the spraying precision is affected due to spray droplets of unmanned aerial vehicles in agricultural plant protection. According to the scheme, multi-source heterogeneous sensor data of a global positioning system, an inertial measurement unit, vision, ultra wide band and the like are acquired through each unmanned aerial vehicle in a cluster and are locally estimated; the central node cooperatively aggregates data, models fogdrop interference such as fogdrops by using a deep learning model, and dynamically corrects sensor noise; according to the method, the positioning robustness, the positioning precision and the self-adaptability are remarkably improved, and the spraying precision in a complex environment is ensured.

The invention discloses a construction site three-dimensional modeling method based on multi-sensor fusion. The method comprises the following steps: synchronously acquiring data by using a laser radar, a camera, an infrared sensor, a GPS (Global Positioning System) and an IMU (Inertial Measurement Unit); the method comprises the following steps of: performing denoising and filtering operation on collected original data, aligning a timestamp and a space of the collected data, fusing the collected multi-source data, and aligning and fusing the processed multi-source point cloud data through a point cloud registration and fusion algorithm to generate a complete three-dimensional point cloud model; generating a grid model by using a surface reconstruction algorithm based on the point cloud data, and performing texture mapping in combination with texture information collected by a camera; the model is simplified and the precision of the model is improved through a model optimization technology, and a reliable three-dimensional visualization foundation for construction management and analysis is formed; real-time detection and modeling of dynamic targets such as mobile equipment and workers on a construction site are realized, and the real-time response capability of the system in a complex construction site environment is ensured through combination of a lightweight neural network architecture and an edge computing technology.

The invention discloses a cross-scale self-supervised spatio-temporal trajectory basic model training method, which comprises the following steps of S1, preprocessing original GPS (Global Positioning System) data to obtain trajectory data of different spatial granularities; s2, encoding the trajectory data of the spatial granularities to obtain trajectory representations corresponding to the spatial granularities; s3, on the basis of the trajectory representation of each spatial granularity, randomly selecting a part of elements to execute mask operation, and calculating the difference between the predicted trajectory data and the real trajectory data as mask reconstruction loss; s4, performing comparative learning training on the positive sample pair and the negative sample pair to construct comparative learning loss; s5, performing dynamic fusion on the trajectory representation of each spatial granularity and the importance weight to obtain a unified representation after trajectory fusion; and S6, performing weighted summation training on the mask reconstruction loss and the contrast learning loss through weight hyper-parameters to obtain total training loss of the model, updating model parameters to convergence by adopting a gradient descent algorithm, and generating a pre-training model.

A method for labeling vehicular sensor data includes accessing sensor data captured by a plurality of sensors disposed at a vehicle. The method also includes accessing global positioning system (GPS) sensor data of the vehicle. For each time step of a plurality of time steps associated with the sensor data, vehicle position information is extracted from the GPS sensor data that represents a respective geographic location of the vehicle at the respective time step. For each time step of the plurality of time steps of the recording of sensor data, respective location-based information associated with the respective geographic location of the vehicle at the respective time step is obtained from a database. For each time step of the plurality of time steps of the recording of sensor data, the recording of sensor data at the respective time step is labeled using the respective obtained location-based information.

The present application refers to a process and a system for collecting, storing, analyzing and visualizing electrocardiographic (ECG) data collected by portable ECG device (100) with embedded wireless communication technology, additionally containing a portable ECG device (100), a hermetically sealed box (200) of medicines containing a lock system comprising a lock (220), a first device (310) to be accessed by the patient, a second device (320) to be accessed by the medical professional, a platform for graphical display of ECG data, and a remote data storage and processing central. The hardware board of the portable ECG device contains wireless communication technology, global positioning system (GPS), start button (141), rechargeable battery charging port, and an equipment configuration and programming port. The battery (120) is Li-Ion type, containing LEDs indicating device operation, and waiting for connection. The battery status is displayed on the app display. In one embodiment, an electrode (130B) is positioned on the bottom cover (110B) of the housing (110A, 110B, 110C) of the ECG device (100).

A work vehicle including a chassis, a ground-engaging mechanism, an input device, a global positioning system, and a controller. The input device providing a bench surface. The global positioning system configured to provide a chassis heading signal, a chassis inclination signal indicative of a main fall angle, and a chassis roll signal indicative of a cross slope angle. The controller configured to receive the chassis heading signals, record the chassis heading signal from a first location to a second location; use the recorded chassis heading signal as a reference chassis heading signal; receive a current chassis heading signal; determine an orientation error based on the reference chassis heading signal and the current chassis heading signal; and send a command to actuate the ground-engaging mechanism to shift the current heading to align with the reference heading based on the orientation error.

The invention discloses an unmanned aerial vehicle real-time modeling method and system for a power transmission line disaster scene, relates to the technical field of power operation and maintenance, and aims at a global positioning system signal missing scene. The problem that the sub-graphs are difficult to align when the pose drifts and the common view is weak in the traditional method is solved. A global pose optimization model fuses historical constraints of preprocessing training data, a single-machine positioning result of local pose data and visual features of an operation key frame image set, an internal constraint system without external positioning signals is constructed, pose errors are corrected, strong dependence on an image common-view area is broken through, and the positioning accuracy of the operation key frame image set is improved. Multi-unmanned aerial vehicle pose stability and local data efficient fusion are achieved, early-stage data preprocessing, pose resolving and later-stage three-dimensional reconstruction are combined, the real-time dense map generation period is shortened, support is provided for fault positioning, damage assessment and emergency repair scheme making after power transmission line disasters, and the emergency response efficiency and reliability are improved.

The invention relates to the technical field of computer vision and three-dimensional reconstruction, in particular to a large-scene three-dimensional reconstruction method based on adaptive partitioning and geometric optimization, which comprises the following steps: acquiring an original image set without a GPS (Global Positioning System) tag to construct a weighted image association graph; performing splitting processing on the weighted image association graph by adopting a self-adaptive partitioning method to obtain a plurality of blocks; independently executing Colmap on each block to obtain local sparse point clouds and camera parameters, and unifying all the local sparse point clouds to a global coordinate system by adopting a Umeyama algorithm to form a complete sparse point cloud; a complete sparse point cloud is adopted to pre-train the 3DGS model, and reliable Gaussian center points are screened to form a stable point cloud; constructing low-frequency shape constraint loss, and performing weighted optimization on the low-frequency shape constraint loss, color loss and structure loss to obtain a pre-trained 3DGS model; obtaining a large-scene three-dimensional reconstruction result through the optimized 3DGS model; the method has good adaptability to geometric structure dominated scenes, and the engineering feasibility and efficiency of large-scale scene reconstruction are effectively improved.

The invention relates to the technical field of unmanned aerial vehicle cable intelligent routing inspection, and discloses a GPS-free unmanned aerial vehicle cable autonomous routing inspection method based on laser radar SLAM, and the method comprises the steps: completing the initialization setting of a system through carrying a laser radar, an inertial measurement unit and an auxiliary sensor; starting a laser radar SLAM (Simultaneous Localization and Mapping) algorithm in an environment without GPS (Global Positioning System) signals to carry out real-time positioning and map construction, and generating an environment point cloud map; planning an autonomous inspection path and optimizing a flight path based on the point cloud map and the preset geographic information of the cable line; controlling the unmanned aerial vehicle to fly along the path, and updating the position in real time by using an SLAM algorithm to compensate the positioning error; synchronously acquiring laser point cloud data, visible light images and infrared thermal imaging data of the cable; identifying a cable structure and an abnormal state through multi-modal data fusion processing; and finally generating an inspection report containing the health condition and the abnormal position of the cable and transmitting the inspection report to a monitoring center. The continuity and coverage integrity of the routing inspection mileage are improved.

The invention relates to the technical field of unmanned aerial vehicles, provides an unmanned aerial vehicle fusion height estimation method, an unmanned aerial vehicle and a medium, and aims to solve the problem that a stable and credible height estimation value cannot be provided due to IMU measurement errors when both RTK and a barometer fail. The method comprises the following steps: performing high-frequency noise filtering on the original acceleration of the inertial measurement unit to obtain a first acceleration value; performing first-order difference on the speed of the global positioning system to obtain an acceleration compensation value; constructing a state space model containing a vertical speed, an acceleration and an accelerometer zero offset drift error; the first acceleration and the acceleration compensation value are fused through Kalman filtering, and drifting is estimated and stripped in real time; and outputting the smooth height by using trapezoidal integral. The device can output a whole-course continuous height estimation value with the drift distance smaller than 0.3 m / min and the bandwidth larger than or equal to 2 Hz, and is suitable for stable flight and uninterrupted operation when both the RTK and the barometer fail in complex scenes such as agricultural plant protection.

The invention discloses a gas pipe network leakage point accurate positioning method based on a multi-source signal attenuation model, and belongs to the technical field of gas pipe network safety monitoring. The method comprises the following steps: arranging monitoring nodes integrating pressure waves, sound waves and an optical fiber vibration module according to a triangular coverage principle, and synchronously acquiring signals through a GPS (Global Positioning System) or the Ethernet; performing targeted denoising on the three types of signals by adopting a wavelet threshold method, a self-adaptive noise cancellation method and an empirical mode decomposition method; constructing a single signal attenuation sub-model associated with the fuel gas viscosity, the density, the pipe diameter and the sound wave dominant frequency, and fusing the single signal attenuation sub-model into a unified attenuation model through information entropy dynamic weight; solving a leakage point coordinate enabling the error between the theoretical value and the measured value to be minimum by utilizing a gradient descent method; through actual coordinate verification, if an error is greater than 5 meters, attenuation coefficient iterative optimization is adjusted. The system adapts to different pressure grades, gas types and complex working conditions, has the advantages of being high in anti-interference capacity and low in operation and maintenance cost, and is suitable for daily operation and maintenance and emergency disposal of the pipe network.

The invention relates to the field of multi-unmanned aerial vehicle cooperative control, and discloses an unmanned aerial vehicle distributed pure azimuth formation control method without a global reference system, which comprises the following steps: designing a distributed preset time attitude estimator for each follower unmanned aerial vehicle, and using local communication information to estimate the attitude of each follower unmanned aerial vehicle; quickly converging the attitude estimation to a leader reference attitude within the time set by the user; a distributed pure azimuth formation control law is constructed, a finite time differentiator is introduced to estimate the change rate of azimuth errors, and direct measurement of azimuth derivatives is avoided; and generating control input according to the estimated attitude and the relative azimuth information under the local coordinate system. Through a specific robust gain design, the formation can still maintain an expected structure and realize accurate tracking under the condition that external disturbance and a time-varying expected trajectory exist. According to the invention, the dependence on an external sensor and a global positioning system is reduced, and the autonomy, robustness and implementability of the unmanned aerial vehicle formation in a complex environment are improved.

The application provides a method and system for detecting camouflaged targets by unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). The system ensures the synchronization of UAVs and UGVs through the global positioning system (GPS), and uses the infrared cameras, binocular cameras, and radar sensors carried by both to efficiently collect data in the target area. The system further preprocesses and analyzes the collected data, and uses improved SSD algorithms and pattern recognition techniques to identify potential camouflaged targets, and performs pattern matching and information fusion to improve the accuracy of the identification results. The SE attention module is introduced innovatively, which optimizes the feature fusion process, enhances the network's spatial correlation capture ability, and enables the system to use global information more effectively, improving the detection accuracy of camouflaged targets. The application solves the problem of poor reliability in traditional methods for detecting camouflaged targets, improves the real-time performance and effectiveness of the cooperative operation of UAVs and UGVs, and significantly improves the accuracy and response speed of camouflaged target identification in battlefield environments. It has important theoretical value and application prospect in various military crisis response.

A vehicular control system includes a vehicle dynamics sensor disposed at a vehicle and capturing vehicle dynamics data representative of a state of motion of the vehicle. The vehicular control system, when the vehicle is at a first location on a road the vehicle is traveling along, determines the state of motion of the vehicle via processing of vehicle dynamics data captured by the vehicle dynamics sensor. The vehicular control system, after the vehicle has traveled along the road from the first location to a second location, predicts a second location of the vehicle based on the state of motion of the vehicle at the first location. The vehicular control system determines a sensitivity of the state of motion of the vehicle to change and corrects the predicted second location of the vehicle based at least in part on a global positioning system of the vehicle.

In implementations of the present disclosure, there is provided an approach for an application of access point in the 6 GHz frequency band. A method comprises configuring a mode of the AP as a 6 GHz station mode in a case that the AP is enabled on a 6 GHz frequency band. Then, a list of target APs around the AP working on the 6 GHz frequency band is obtained. Next, the AP selects a target AP from the list of target APs and connects to the selected target AP by setting a power of the AP to be lower than a power of the target AP by a predetermined value. After the AP connects to the target AP, the AP sends a request including global positioning system (GPS) information to an automated frequency coordination (AFC) server via the target AP to obtain a response including allowed power information.

The invention discloses an Internet of Things equipment loss alarm tracking method, and provides a double-stage technical scheme for the problems of loss response lag, positioning technology limitation and the like of Internet of Things equipment without a GPS (Global Positioning System) environment: in the first stage, a real-time loss alarm method is realized through dynamic comparison of base station data, and connection data of equipment and a communication base station are compared in real time; once it is found that the equipment is switched to a strange base station, triggering a loss alarm; and the second stage is fused with the LBS technology to realize the trajectory tracking method. According to the scheme, through a dynamic base station comparison algorithm, in combination with acquisition of historical data of a handshake base station, equipment loss alarm is realized, passive response is changed into active response, and the response timeliness is improved; meanwhile, the method only depends on base station handshake data, energy consumption is not increased additionally, high positioning precision can be achieved in a GPS-free environment, and extra cost is not increased; and multi-dimensional analysis of a multi-layer display technology of a GIS can be fused, and space-time multi-dimensional analysis is realized through track visualization.

Methods and systems for the use of detected objects for image processing are described. A computing device autonomously controlling a vehicle may receive images of the environment surrounding the vehicle from an image-capture device coupled to the vehicle. In order to process the images, the computing device may receive information indicating characteristics of objects in the images from one or more sources coupled to the vehicle. Examples of sources may include RADAR, LIDAR, a map, sensors, a global positioning system (GPS), or other cameras. The computing device may use the information indicating characteristics of the objects to process received images, including determining the approximate locations of objects within the images. Further, while processing the image, the computing device may use information from sources to determine portions of the image to focus upon that may allow the computing device to determine a control strategy based on portions of the image.

The invention discloses an intelligent shooting range management system based on the Internet of Things, and relates to the technical field of shooting range management, and the intelligent shooting range management system is technically characterized by comprising an in-shooting range safety box which is provided with a plurality of safety boxes and is internally provided with shooting equipment; a safety door with an electronic lock is hinged to one side of the safe box, the electronic lock is connected with a remote server through an Internet of Things transmission module, data can be interacted, and unlocking records can be uploaded in real time; the shell of the shooting equipment is provided with a positioning module which comprises a GPS (Global Positioning System) positioning unit, a satellite signal transmitting unit and a power supply unit, a power supply supplies power, and the GPS unit transmits geographic information to a GPS satellite through the satellite transmitting unit; the remote server is provided with a control unit, a display unit, a satellite signal receiving unit and a data storage unit, the control unit remotely controls unlocking and locking of the electronic lock, the data storage unit stores records, the satellite signal receiving unit receives signals, and the display unit displays the unlocking and locking states of the safe box and positions the shooting equipment; the shooting device in the shooting range can be remotely managed by utilizing the Internet of Things technology.

The invention relates to the technical field of robot positioning, discloses a four-foot robot three-dimensional positioning method and system, a storage medium and a robot, and aims to solve the technical problems of height drift and foot end error accumulation of a four-foot robot in a visual degradation environment without a GPS (Global Positioning System) by a traditional positioning method. The method comprises the following steps: firstly, constructing an initial state vector containing motion states of a fuselage and four foot ends, and establishing a nonlinear continuous time state equation considering foot end dynamics; relying on an unscented Kalman filtering framework, a prior state is obtained through Sigma point sampling and time updating; a foot end observation value is corrected through foot bottom rolling compensation, a height absolute reference is provided by combining a local invariant elevation map, and multi-leg slippage detection and observation weight self-adaptive adjustment are synchronously completed; and finally, the optimal state is updated and output through observation. According to the invention, the visual sensor is used for topographic mapping instead of direct positioning, the height drift is effectively inhibited, the robustness and precision of positioning in a complex environment are improved, and the method is suitable for unstructured scenes such as rescue exploration and the like.

A refuse vehicle includes an electric motor powered by a battery, a hydraulic pump driven by the electric motor, a hydraulic actuator powered by the hydraulic pump, and one or more processing circuits being configured to: determine a location of the refuse vehicle including a global position system coordinate, determine a position on a route map using the location, control the hydraulic actuator based on the position on the route map, determine a state of charge of the battery and a threshold for the state of charge below which operation of the electric motor, the hydraulic pump, or the hydraulic actuator is adjusted, and dynamically update the threshold based on the position on the route map or a weight of refuse in a refuse compartment.

A computer-implemented method of image stitching of a plurality of digital images of an infrastructure surface for defect detection is disclosed. The method includes providing a plurality of partial digital images of the infrastructure surface. The method includes extracting global positioning system metadata from data corresponding to the partial digital images. The method includes determining feature descriptions of features in one or more of the partial digital images. The method includes performing a scheduled processing sequence of the partial digital images based on the extracted global positioning system metadata, including determining an affinity matrix using the feature descriptions of adjacent partial digital images to incrementally locate each of the partial digital images such that a full view image of the infrastructure surface is produced by iteratively digitally stitching together the plurality of partial digital images.

The embodiment of the application provides a slot antenna of a global positioning system and electronic equipment, the slot antenna comprises: a first metal segment, a first position of the first metal segment is grounded; a second metal segment, the second metal segment has a slot between the first metal segment, a second position of the second metal segment is connected to a feed point of the slot antenna; a third metal segment, the third metal segment intersects with the second metal segment; a third position of the third metal segment is grounded through a capacitor; wherein the first metal segment, the second metal segment and the third metal segment belong to a metal frame of the electronic equipment.

A driving assistance, a driving assistance device therefor, and a computer-readable non-volatile storage medium therefor are provided. The method includes storing a driving path of a vehicle based on forward driving of the vehicle, in response to the vehicle driving backward, correcting a position of the vehicle based on at least one of sensor information measured by an internal sensor of the vehicle, global positioning system (GPS) information of the vehicle, or feature information obtained through image information of the vehicle, and assisting backward driving of the vehicle based on the stored driving path and the corrected position of the vehicle.

The invention relates to a panoramic image splicing method and system based on the real-time attitude of a ship body, and the method comprises the steps: synchronously collecting an original image, a rolling angle data and a pitch angle data through arranging a plurality of fisheye cameras in the circumferential direction of the ship body in combination with inertial navigation equipment; hardware-level clock synchronization is realized by using a second pulse signal of a global positioning system, and alignment of an image and attitude data is completed through a timestamp matching algorithm; the method comprises the following steps: acquiring internal and external parameters of a camera by adopting a Zhang's calibration method, performing de-preprocessing on an image, constructing a rotation matrix based on a real-time attitude, projecting pixel points to a stable world coordinate system, and generating a projection image; for an overlapping region between adjacent projection images, dynamically calculating a fusion weight according to an attitude angle change rate, and realizing adaptive weighted splicing; and finally, a seamless panoramic image is generated and coded and output to a display terminal and a storage device, panoramic image splicing in a ship body shaking scene is realized, and real-time performance, robustness and environmental adaptability are considered.

The invention relates to the technical field of aircraft power control, and discloses an artificial intelligence optimized vertical fixed wing power control method and system, and the method comprises the steps: obtaining the original airspeed data of an airspeed sensor, the ground speed data of a global positioning system and the acceleration data of an inertial measurement unit, and generating the ground speed of an aircraft based on the data fusion. Under the low-wind-speed condition, the ground speed of the aircraft is used as the reference airspeed, the difference between the original airspeed data of the airspeed sensor and the reference airspeed is continuously compared, and the sliding average value of the difference is calculated. When the sliding average value continuously exceeds the preset tolerance range, the method can identify that the airspeed sensor has continuous calibration drift. And then, according to the identified continuous calibration drift, performing real-time compensation on original airspeed data of an airspeed sensor to obtain calibrated airspeed data, and inputting the calibrated airspeed data into flight mode switching judgment logic to trigger an action instruction of a tilting mechanism.

A frost prevention device for protecting crops in open fields from frost damage. The device may include a housing that encloses both solid and liquid fuel storage compartments, a combustion chamber, a solid and liquid fuel feeding system, and an air intake and exhaust fan. The combustion chamber is configured to burn organic solid fuels or combustible liquids, generating heat to raise the ambient temperature around crops. The device may further include a control unit with thermal and moisture sensors configured to automate its operation based on environmental conditions, and a Global Positioning System module configured to assist in navigating through a field.

The invention provides a radio frequency power and antenna adjusting method and system based on position information, and the method comprises the steps: a wireless communication terminal obtains the position information of itself through a global positioning system GNSS, and periodically reports the position information to a wireless communication base station after completing the self-inspection; the wireless communication base station forwards the received position information to a computing server; the computing server generates a radio frequency power adjustment instruction and an antenna selection and angle adjustment instruction according to all the wireless communication terminals and the position information of the computing server, and sends the radio frequency power adjustment instruction and the antenna selection and angle adjustment instruction to the corresponding wireless communication terminals through the wireless communication base station; and the wireless communication terminal adjusts the transmitting power and selects a target antenna according to the received instruction, and adjusts the angle of the directional antenna. According to the method, the distance between the devices is judged based on the position information, the transmitting power is actively reduced in the near field, and the problem of near-field saturation when a plurality of high-power wireless communication devices work at the same time in a short distance is effectively solved.

The invention discloses a deep foundation pit supporting structure construction monitoring method and system, and relates to the technical field of intelligent monitoring, and the method comprises the steps: deploying a global positioning system (GPS) module, a vehicle attribute module and a vehicle weighing module on a heavy construction vehicle in a deep foundation pit supporting structure construction area, and combining a vehicle-mounted control terminal and a 5G wireless communication module, operation disturbance data can be collected in real time and transmitted to the BIM platform central processing unit in a unified packaging format. The BIM platform constructs a two-dimensional space positioning grid and path trajectory mapping mechanism based on the received data, further generates a vehicle path disturbance heat map reflecting disturbance intensity, divides the vehicle path disturbance heat map into disturbance analysis unit areas, and extracts a disturbance data set based on BIM model soil modeling information. The disturbance intensity is quantitatively output through a disturbance aggregation index D calculation formula which is clear in physical significance and consistent in dimension, and visual display of the disturbance level is achieved in combination with a disturbance evaluation threshold value.