CN113409549A - Landslide monitoring and early warning system in mountain canyon region - Google Patents
Landslide monitoring and early warning system in mountain canyon region Download PDFInfo
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Abstract
The invention belongs to the technical field of geological disaster prevention and control, and discloses a landslide monitoring and early warning system in a high mountain canyon region, which comprises the following components: the system comprises a meteorological information acquisition module, a geological information acquisition module, an image acquisition module, an unmanned aerial vehicle control module, a central control module, an information analysis module, an early warning region defining module, an inclination measuring module, a model construction module and a landslide early warning module. According to the landslide monitoring and early warning system for the high mountain canyon region, provided by the invention, the meteorological information, the geological information and the image of the high mountain canyon region are collected and then subjected to information analysis processing to obtain a landslide high-risk region, and the landslide high-risk region is used as an early warning region for key monitoring, so that the monitoring cost can be reduced, the early warning difficulty is reduced, and the monitoring effect is good; the slope of the mountain in the area is obtained through analysis of the collected information, then the model of the area is built, landslide early warning is carried out through landslide simulation results, and the method is convenient and rapid to carry out and high in early warning accuracy.
Description
Technical Field
The invention belongs to the technical field of geological disaster prevention and control, and particularly relates to a landslide monitoring and early warning system for a high mountain canyon region
Background
Landslide is the phenomenon of slippage of a slope rock-soil body along a through structural plane. The mechanism by which landslide occurs is that the shear stress on a structural surface exceeds the shear strength of that surface.
Severe landslides such as deep accumulation layer landslides and broken rock landslides in southwest high mountain canyon regions are large in scale, large in gliding impact force and serious in loss after landslides occur. However, landslide and peripheral traffic conditions are poor, the height difference of the front edge and the rear edge is large, the deformation of the ground surface is in a nonlinear characteristic, and the monitoring and early warning difficulty is large. The existing landslide monitoring and early warning method has a successful case for the landslide of a homogeneous soil type, such as the successful prediction of the landslide of the Gansu black square platform by the combined research results of the university of Chengdu Dou Johnson and the university of Changan (research of a sudden loess landslide monitoring and early warning theoretical method, taking the Gansu black square platform as an example, engineering geology newspaper 2020 and 28 (01); Shanxi Changan university research team successfully early warns the sudden loess landslide of the Gansu Yongjing county black square platform by using the Beidou technology for the third time, China daily newspaper network, 2021 month and 29 days in 2021 year). However, no feasible monitoring and early warning scheme is available for broken stone soil landslide or broken strong weathering layer rock landslide.
Through the above analysis, the problems and defects of the prior art are as follows: in the prior art, there is no case of successful early warning on landslides in high mountain canyon regions.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a landslide monitoring and early warning system in a high mountain canyon region.
The landslide monitoring and early warning system in the high mountain canyon region is realized in the way, and comprises the following components:
the system comprises a meteorological information acquisition module, a geological information acquisition module, an image acquisition module, an unmanned aerial vehicle control module, a central control module, an information analysis module, an early warning region demarcation module, an inclination measurement module, a model construction module and a landslide early warning module;
the meteorological information acquisition module is connected with the central control module and is used for acquiring meteorological information of the high mountain canyon region through a meteorological information acquisition program to obtain the meteorological information of the high mountain canyon region; the meteorological information comprises rainfall information, temperature information, humidity information, wind direction information and wind power information;
the acquisition of the meteorological information of the high mountain canyon region is carried out through a meteorological information acquisition program to obtain the meteorological information of the high mountain canyon region, and the acquisition method comprises the following steps:
acquiring position information of a high mountain canyon region;
entering position information of the high mountain canyon region in a webpage search box;
respectively determining the keywords as rainfall information, temperature information, humidity information, wind direction information and wind power information;
respectively searching the determined keywords to obtain meteorological information of the high mountain canyon region;
the respectively searching the determined keywords comprises:
determining the synchronization frequency of a local object and a remote data source, wherein the remote data source is a database on a remote Web;
representing remote data source average variation frequency lambda by using Poisson processiWherein i is 1,2, …, n, n represents the number of remote data sources;
determining the average novelty:
from the resulting mean variation frequency λiDetermining objects, i.e. data items e in a remote Web databaseiCorresponding synchronization frequency fiMaking the average novelty of the local database meet the synchronous resource limitation
At the maximum, the number of the first,
determining the updating frequency according to the data timeliness:
the ith data record r maintained by the data capture system at time tiThe novelty of (c) is as follows:
then the average timeliness of the data record set S consisting of N data records is as follows:
the data record set S is averaged over time and measured:
calculating to obtain theoretical synchronization frequency of each object by using a Lagrange multiplier, and then synchronizing object data according to the theoretical synchronization frequency to enable the average novelty of a local database to reach the maximum value;
the synchronizing the object data according to the theoretical synchronization frequency comprises the following steps:
for all (s, a) initialization table entries Q0(s,a)＝0；
Wherein Q represents professional representation of computer machine learning field, i.e. Q is representation form of reinforcement learning, s represents state, a represents action, Q (s, a) represents result state of applying action a to state s; initializing to 0 value, namely not learning initialization value; in each episode, the extent to the data source is taken as its activity,get the return value Ri：
And updating the Q value in a time period 0-t:
wherein q isjRepresents the resultant state value, R, of the jth data record obtained by reinforcement learning in the time interval 0-tjRepresenting the return value obtained by reinforcement learning of the jth data record in the time interval 0-t;
under the premise of resource limitation, namely the maximum interaction times M with the server is a constant value, so that the novelty
Maximum value, F (F)i,λi) Representing the novelty of the corresponding ith data record, the novelty being derived from the timeliness of the data, i.e., the timeliness represents the frequency of update of the object, i.e., the smallest unit data item, in the record, and the novelty being the overall timeliness, ω, of the aggregate record of data items, i.e., the remote data sourceiIs the importance weight;
the geological information acquisition module is connected with the central control module and used for acquiring geological information of the high mountain canyon region through a geological information acquisition program to obtain geological information of the high mountain canyon region;
the image acquisition module is connected with the central control module and used for acquiring images of the high mountain canyon region through an unmanned aerial vehicle carrying a camera to obtain panoramic images of the high mountain canyon region;
the acquisition of the geological information of the high mountain canyon region through the geological information acquisition program comprises the following steps: acquiring position information of a high mountain canyon region, and acquiring geological information corresponding to the position information in a database;
the unmanned aerial vehicle control module is connected with the central control module and is used for controlling the flying height and the shooting angle of the unmanned aerial vehicle through an unmanned aerial vehicle control program;
the central control module is connected with the meteorological information acquisition module, the geological information acquisition module, the image acquisition module and the unmanned aerial vehicle control module and is used for controlling the operation of each connection module through a main control computer so as to ensure the normal operation of each module;
the information analysis module is connected with the central control module and used for analyzing the acquired panoramic high mountain canyon region image and the geological information of the high mountain canyon region through an information analysis program to obtain an information analysis result;
the early warning area planning module is connected with the central control module and used for obtaining a landslide high-risk area according to the information analysis result through an early warning area planning program and taking the landslide high-risk area as an early warning area;
the inclination measuring module is connected with the central control module and used for measuring the inclination of the mountain body in the early warning area according to the acquired information analysis result through an inclination measuring program to obtain the inclination of the mountain body in the early warning area;
the model building module is connected with the central control module and used for building the mountain model of the early warning area according to the obtained information analysis result through a model building program to obtain the mountain model of the early warning area;
and the landslide early warning module is connected with the central control module and used for carrying out landslide simulation test on the mountain model in the early warning area through a landslide early warning simulation program to obtain landslide early warning information.
Further, the unmanned aerial vehicle through carrying the camera carries out the collection of mountain canyon area image, obtains panorama mountain canyon area image, includes:
the mobile terminal sends a panoramic stitching instruction to the unmanned aerial vehicle in a wireless transmission mode;
the method comprises the steps that an unmanned aerial vehicle receives a panoramic stitching instruction, and images to be stitched are obtained through a tripod head camera carried by the unmanned aerial vehicle;
the unmanned aerial vehicle sends the acquired images to be spliced to the cloud server through wireless transmission;
the cloud server receives the image sent by the unmanned aerial vehicle, and a panoramic image is obtained through a panoramic stitching algorithm;
and the cloud server transmits the panoramic image to the mobile terminal in a wireless transmission mode to obtain a panoramic mountain canyon area image.
Further, unmanned aerial vehicle receives panorama concatenation instruction, acquires the image of treating the concatenation through unmanned aerial vehicle's own cloud platform camera, includes: panorama instruction control unmanned aerial vehicle keeps the horizontality autogiration 8 times, and rotation angle is 45 degrees, acquires many and treats the concatenation picture.
Further, the image that unmanned aerial vehicle sent is received to high in the clouds server, reachs panoramic image through panorama concatenation algorithm, includes:
extracting characteristic points with spliced images received by a cloud server; matching the extracted characteristic points to obtain an overlapping area of the images;
calculating a homography matrix between the images according to the characteristic points of the overlapping areas of the images; estimating rotation matrix parameters and focal length parameters of the camera according to the homography matrix;
performing image projection transformation on the plurality of images according to the parameters of the camera and the homography matrix; carrying out image exposure compensation according to the result of image projection transformation;
searching for a seam line of an overlapped part between images in image splicing; and fusing the overlapped parts of all the images according to the parameters of the seam lines, and splicing into a complete panoramic image.
Further, the high-risk landslide area is a rear edge area, a slope surface steep bank area and an area where a threat object is located.
Further, the building of the mountain model of the early warning area is performed according to the obtained information analysis result through the model building program to obtain the mountain model of the early warning area, and the building method comprises the following steps: taking the edge characteristics of the target area as topological constraint conditions to obtain three-dimensional point cloud with constraint; and then, a surface mesh model based on edge feature self-constraint is constructed by adopting a zone constraint triangulation algorithm based on local dimension reduction.
Further, the method for acquiring the edge feature of the target area comprises the following steps: adopting canny edge detection algorithm to obtain two-dimensional edge characteristics from the image of the early warning area in the panoramic high mountain canyon area image, including: smoothing the image by a Gaussian filter to remove noise; calculating gradient amplitude and direction by using first-order partial derivative finite difference; carrying out non-maximum suppression on the gradient amplitude, and accurately determining the position of the edge; edges are detected and connected using a dual threshold algorithm.
Further, the simulating landslide of the mountain model in the early warning area to obtain landslide early warning information includes:
and the landslide early warning system is used for simulating landslide of the mountain model in the early warning area by combining the information analysis result with the determined inclination as a simulation parameter, and generating landslide early warning information based on the simulation result.
Another object of the present invention is to provide an information data processing terminal, which is characterized in that the information data processing terminal is configured to implement the landslide monitoring and early warning system in the high mountain canyon region.
Another object of the present invention is to provide a computer-readable storage medium storing instructions which, when executed on a computer, cause the computer to apply the landslide monitoring and warning system in the high mountain canyon region.
By combining all the technical schemes, the invention has the advantages and positive effects that: the landslide monitoring and early warning system for the high mountain canyon region, provided by the invention, acquires the meteorological information and the geological information of the high mountain canyon region and analyzes the acquired information to obtain the landslide high-risk region, and the landslide high-risk region is used as a region to be monitored for key monitoring, so that the monitoring cost can be reduced, the early warning difficulty is reduced, and the monitoring effect is good; the slope of the mountain in the area is obtained through analysis of the acquired information, and then the model of the area is constructed, so that landslide early warning is more convenient and quicker, the early warning accuracy is high, and the complexity of construction and calculation of the early warning model by considering multiple factors in the traditional early warning method is reduced.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.
Fig. 1 is a block diagram of a landslide monitoring and early warning system in a high mountain canyon region according to an embodiment of the present invention.
Fig. 2 is a flowchart of a landslide monitoring and early warning method in a high mountain canyon region according to an embodiment of the present invention.
Fig. 3 is a flowchart of acquiring weather information of a high mountain canyon region by a weather information acquisition program according to an embodiment of the present invention to obtain weather information of the high mountain canyon region.
Fig. 4 is a flowchart of acquiring an image of a mountain canyon region by an unmanned aerial vehicle carrying a camera to obtain a panoramic image of the mountain canyon region according to an embodiment of the present invention.
Fig. 5 is a flowchart illustrating that the cloud server receives an image sent by the unmanned aerial vehicle and obtains a panoramic image through a panoramic stitching algorithm according to the embodiment of the present invention.
In the figure: 1. a meteorological information acquisition module; 2. a geological information acquisition module; 3. an image acquisition module; 4. an unmanned aerial vehicle control module; 5. a central control module; 6. an information analysis module; 7. an early warning area defining module; 8. an inclination measuring module; 9. a model building module; 10. landslide early warning module.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides a landslide monitoring and early warning system in a high mountain canyon region, and the invention is described in detail with reference to the attached drawings.
As shown in fig. 1, the landslide monitoring and early warning system in the high mountain canyon region according to the embodiment of the present invention includes:
the meteorological information acquisition module 1 is connected with the central control module 5 and is used for acquiring meteorological information of the high mountain canyon region through a meteorological information acquisition program to obtain the meteorological information of the high mountain canyon region; the meteorological information comprises rainfall information, temperature information, humidity information, wind direction information and wind power information;
the geological information acquisition module 2 is connected with the central control module 5 and used for acquiring geological information of the high mountain canyon region through a geological information acquisition program to obtain geological information of the high mountain canyon region;
the image acquisition module 3 is connected with the central control module 5 and used for acquiring images of the high mountain canyon region through an unmanned aerial vehicle carrying a camera to obtain panoramic images of the high mountain canyon region;
the unmanned aerial vehicle control module 4 is connected with the central control module 5 and is used for controlling the flying height and the shooting angle of the unmanned aerial vehicle through an unmanned aerial vehicle control program;
the central control module 5 is connected with the meteorological information acquisition module 1, the geological information acquisition module 2, the image acquisition module 3, the unmanned aerial vehicle control module 4, the image analysis module 6, the early warning region defining module 7, the inclination measuring module 8, the model construction module 9 and the landslide early warning module 10, and is used for controlling the operation of each connection module through a main control computer and ensuring the normal operation of each module;
the information analysis module 6 is connected with the central control module 5 and used for analyzing the acquired panoramic high mountain canyon region image and the geological information of the high mountain canyon region through an information analysis program to obtain an information analysis result;
the early warning region planning module 7 is connected with the central control module 5 and used for obtaining a landslide high-risk region according to the information analysis result through an early warning region planning program and taking the region as an early warning region;
the inclination measuring module 8 is connected with the central control module 5 and used for measuring the inclination of the mountain in the early warning area according to the acquired information analysis result through an inclination measuring program to obtain the inclination of the mountain in the early warning area;
the model building module 9 is connected with the central control module 5 and used for building a mountain model of the early warning area according to the obtained information analysis result through a model building program to obtain the mountain model of the early warning area;
and the landslide early warning module 10 is connected with the central control module 5 and used for carrying out landslide simulation test on the mountain model in the early warning area through a landslide early warning simulation program to obtain landslide early warning information.
As shown in fig. 2, the landslide monitoring and early warning method in the high mountain canyon region provided by the embodiment of the invention includes the following steps:
s101, acquiring meteorological information of the high mountain canyon region by using a meteorological information acquisition program through a meteorological information acquisition module to obtain meteorological information of the high mountain canyon region, wherein the meteorological information comprises rainfall information, temperature information, humidity information, wind direction information and wind power information;
s102, acquiring geological information of the high mountain canyon region by using a geological information acquisition program through a geological information acquisition module to obtain geological information of the high mountain canyon region; acquiring images of the high mountain canyon region by using an unmanned aerial vehicle carrying a camera through an image acquisition module to obtain panoramic images of the high mountain canyon region;
s103, controlling the flying height and the shooting angle of the unmanned aerial vehicle by using an unmanned aerial vehicle control program through an unmanned aerial vehicle control module; the central control module controls the operation of each connecting module by using a main control machine, so that the normal operation of each module is ensured;
s104, analyzing the acquired panoramic high mountain canyon region image and geological information of the high mountain canyon region by using an information analysis program through an information analysis module to obtain an information analysis result; obtaining a landslide high-risk area by using an early warning area planning program according to an information analysis result through an early warning area planning module, and taking the area as an early warning area;
s105, measuring the inclination of the mountain body in the early warning area by using an inclination measuring module according to the acquired information analysis result by using an inclination measuring program to obtain the inclination of the mountain body in the early warning area;
s106, constructing the mountain model of the early warning area by using a model construction module according to the obtained information analysis result through a model construction program to obtain the mountain model of the early warning area; and performing landslide simulation test on the mountain model in the early warning area through the landslide early warning module to obtain landslide early warning information.
As shown in fig. 3, the acquiring of weather information of a high mountain canyon region by a weather information acquisition program according to an embodiment of the present invention to obtain weather information of a high mountain canyon region includes:
s201, acquiring position information of a high mountain canyon region;
s202, entering position information of the high mountain canyon region in a webpage search box;
s203, respectively determining the keywords as rainfall information, temperature information, humidity information, wind direction information and wind power information;
and S204, respectively searching the determined keywords to obtain meteorological information of the high mountain canyon region.
The method for respectively searching the determined keywords provided by the embodiment of the invention comprises the following steps:
determining the synchronization frequency of a local object and a remote data source, wherein the remote data source is a database on a remote Web;
representing remote data source average variation frequency lambda by using Poisson processiWherein i is 1,2, …, n, n represents the number of remote data sources;
determining the average novelty:
from the resulting mean variation frequency λiDetermining objects, i.e. data items e in a remote Web databaseiCorresponding synchronization frequency fiMaking the average novelty of the local database meet the synchronous resource limitation
At the maximum, the number of the first,
determining the updating frequency according to the data timeliness:
the ith data record r maintained by the data capture system at time tiThe novelty of (c) is as follows:
then the average timeliness of the data record set S consisting of N data records is as follows:
the data record set S is averaged over time and measured:
calculating to obtain theoretical synchronization frequency of each object by using a Lagrange multiplier, and then synchronizing object data according to the theoretical synchronization frequency to enable the average novelty of a local database to reach the maximum value;
the synchronizing the object data according to the theoretical synchronization frequency comprises the following steps:
for all (s, a) initialization table entries Q0(s,a)＝0；
Wherein Q represents professional representation of computer machine learning field, i.e. Q is representation form of reinforcement learning, s represents state, a represents action, Q (s, a) represents result state of applying action a to state s; initializing to 0 value, namely not learning initialization value; in each scenario, the range to the data source is taken as its activity, resulting in a reward value of Ri：
And updating the Q value in a time period 0-t:
wherein q isjRepresents the resultant state value, R, of the jth data record obtained by reinforcement learning in the time interval 0-tjRepresenting the return value obtained by reinforcement learning of the jth data record in the time interval 0-t;
under the premise of resource limitation, namely the maximum interaction times M with the server is a constant value, so that the novelty
Maximum value, F (F)i,λi) Representing the novelty of the corresponding ith data record, the novelty being derived from the timeliness of the data, i.e., the timeliness represents the frequency of update of the object, i.e., the smallest unit data item, in the record, and the novelty being the overall timeliness, ω, of the aggregate record of data items, i.e., the remote data sourceiIs the importance weight.
The method for acquiring the geological information of the high mountain canyon region through the geological information acquisition program provided by the embodiment of the invention comprises the following steps: and acquiring position information of the high mountain canyon region, and acquiring geological information corresponding to the position information in a database.
As shown in fig. 4, the acquiring of the image of the high mountain canyon region by the unmanned aerial vehicle with the camera according to the embodiment of the present invention to obtain the panoramic image of the high mountain canyon region includes:
s301, the mobile terminal sends a panoramic stitching instruction to the unmanned aerial vehicle in a wireless transmission mode;
s302, receiving a panoramic stitching instruction by an unmanned aerial vehicle, and acquiring images to be stitched by a tripod head camera carried by the unmanned aerial vehicle;
s303, the unmanned aerial vehicle sends the acquired images to be spliced to a cloud server through wireless transmission;
s304, the cloud server receives the image sent by the unmanned aerial vehicle, and a panoramic image is obtained through a panoramic stitching algorithm;
s305, the cloud server transmits the panoramic image to the mobile terminal in a wireless transmission mode to obtain a panoramic mountain canyon area image.
The method for receiving the panoramic stitching instruction by the unmanned aerial vehicle and acquiring the images to be stitched through the tripod head camera of the unmanned aerial vehicle comprises the following steps: panorama instruction control unmanned aerial vehicle keeps the horizontality autogiration 8 times, and rotation angle is 45 degrees, acquires many and treats the concatenation picture.
As shown in fig. 5, the cloud server provided in the embodiment of the present invention receives an image sent by an unmanned aerial vehicle, and obtains a panoramic image through a panoramic stitching algorithm, where the method includes:
s401, extracting characteristic points with spliced images received by a cloud server; matching the extracted characteristic points to obtain an overlapping area of the images;
s402, calculating a homography matrix between the images according to the characteristic points of the overlapping areas of the images; estimating rotation matrix parameters and focal length parameters of the camera according to the homography matrix;
s403, performing image projection transformation on the multiple images according to the parameters of the camera and the homography matrix; carrying out image exposure compensation according to the result of image projection transformation;
s404, finding out a seam line of an overlapped part between images in image splicing; and fusing the overlapped parts of all the images according to the parameters of the seam lines, and splicing into a complete panoramic image.
The landslide high-risk area provided by the embodiment of the invention is a broken stone soil area or a broken strong weathering layer rock area.
The method for constructing the mountain model of the early warning area through the model construction program according to the acquired information analysis result to obtain the mountain model of the early warning area comprises the following steps: taking the edge characteristics of the target area as topological constraint conditions to obtain three-dimensional point cloud with constraint; and then, a surface mesh model based on edge feature self-constraint is constructed by adopting a zone constraint triangulation algorithm based on local dimension reduction.
The method for acquiring the edge characteristics of the target area provided by the embodiment of the invention comprises the following steps: adopting canny edge detection algorithm to obtain two-dimensional edge characteristics from the image of the early warning area in the panoramic high mountain canyon area image, including: smoothing the image by a Gaussian filter to remove noise; calculating gradient amplitude and direction by using first-order partial derivative finite difference; carrying out non-maximum suppression on the gradient amplitude, and accurately determining the position of the edge; edges are detected and connected using a dual threshold algorithm.
The landslide simulation of the mountain model in the early warning area provided by the embodiment of the invention to obtain the landslide early warning information comprises the following steps:
and the landslide early warning system is used for simulating landslide of the mountain model in the early warning area by combining the information analysis result with the determined inclination as a simulation parameter, and generating landslide early warning information based on the simulation result.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention, and the scope of the present invention is not limited thereto, and any modification, equivalent replacement, and improvement made by those skilled in the art within the technical scope of the present invention disclosed herein, which is within the spirit and principle of the present invention, should be covered by the present invention.
Claims (10)
1. A landslide monitoring and early warning system in a high mountain canyon region is characterized by comprising a meteorological information acquisition module, a geological information acquisition module, an image acquisition module, an unmanned aerial vehicle control module, a central control module, an information analysis module, an early warning region demarcation module, an inclination measurement module, a model construction module and a landslide early warning module;
the meteorological information acquisition module is connected with the central control module and is used for acquiring meteorological information of the high mountain canyon region through a meteorological information acquisition program to obtain the meteorological information of the high mountain canyon region; the meteorological information comprises rainfall information, temperature information, humidity information, wind direction information and wind power information;
the acquisition of the meteorological information of the high mountain canyon region is carried out through a meteorological information acquisition program to obtain the meteorological information of the high mountain canyon region, and the acquisition method comprises the following steps:
acquiring position information of a high mountain canyon region;
entering position information of the high mountain canyon region in a webpage search box;
respectively determining the keywords as rainfall information, temperature information, humidity information, wind direction information and wind power information;
respectively searching the determined keywords to obtain meteorological information of the high mountain canyon region;
the respectively searching the determined keywords comprises:
determining the synchronization frequency of a local object and a remote data source, wherein the remote data source is a database on a remote Web;
representing remote data source average variation frequency lambda by using Poisson processiWherein i is 1,2, …, n, n represents the number of remote data sources;
determining the average novelty:
from the resulting mean variation frequency λiDetermining objects, i.e. data items e in a remote Web databaseiCorresponding synchronization frequency fiMaking the average novelty of the local database meet the synchronous resource limitation
At the maximum, the number of the first,
determining the updating frequency according to the data timeliness:
the ith data record r maintained by the data capture system at time tiThe novelty of (c) is as follows:
then the average timeliness of the data record set S consisting of N data records is as follows:
the data record set S is averaged over time and measured:
calculating to obtain theoretical synchronization frequency of each object by using a Lagrange multiplier, and then synchronizing object data according to the theoretical synchronization frequency to enable the average novelty of a local database to reach the maximum value;
the synchronizing the object data according to the theoretical synchronization frequency comprises the following steps:
for all (s, a) initialization table entries Q0(s,a)＝0；
Wherein Q represents professional representation of computer machine learning field, i.e. Q is representation form of reinforcement learning, s represents state, a represents action, Q (s, a) represents result state of applying action a to state s; initializing to 0 value, namely not learning initialization value; in each scenario, the range to the data source is taken as its activity, resulting in a reward value of Ri：
And updating the Q value in a time period 0-t:
wherein q isjRepresents the resultant state value, R, of the jth data record obtained by reinforcement learning in the time interval 0-tjRepresenting the return value obtained by reinforcement learning of the jth data record in the time interval 0-t;
under the premise of resource limitation, namely the maximum interaction times M with the server is a constant value, so that the novelty
Maximum value, F (F)i,λi) Representing the novelty of the corresponding ith data record, the novelty being derived from the timeliness of the data, i.e., the timeliness represents the frequency of update of the object, i.e., the smallest unit data item, in the record, and the novelty being the overall timeliness, ω, of the aggregate record of data items, i.e., the remote data sourceiIs the importance weight;
the geological information acquisition module is connected with the central control module and used for acquiring geological information of the high mountain canyon region through a geological information acquisition program to obtain geological information of the high mountain canyon region;
the image acquisition module is connected with the central control module and used for acquiring images of the high mountain canyon region through an unmanned aerial vehicle carrying a camera to obtain panoramic images of the high mountain canyon region;
the acquisition of the geological information of the high mountain canyon region through the geological information acquisition program comprises the following steps: acquiring position information of a high mountain canyon region, and acquiring geological information corresponding to the position information in a database;
the unmanned aerial vehicle control module is connected with the central control module and is used for controlling the flying height and the shooting angle of the unmanned aerial vehicle through an unmanned aerial vehicle control program;
the central control module is connected with the meteorological information acquisition module, the geological information acquisition module, the image acquisition module and the unmanned aerial vehicle control module and is used for controlling the operation of each connection module through a main control computer so as to ensure the normal operation of each module;
the information analysis module is connected with the central control module and used for analyzing the acquired panoramic high mountain canyon region image and the geological information of the high mountain canyon region through an information analysis program to obtain an information analysis result;
the early warning area planning module is connected with the central control module and used for obtaining a landslide high-risk area according to the information analysis result through an early warning area planning program and taking the landslide high-risk area as an early warning area;
the inclination measuring module is connected with the central control module and used for measuring the inclination of the mountain body in the early warning area according to the acquired information analysis result through an inclination measuring program to obtain the inclination of the mountain body in the early warning area;
the model building module is connected with the central control module and used for building the mountain model of the early warning area according to the obtained information analysis result through a model building program to obtain the mountain model of the early warning area;
and the landslide early warning module is connected with the central control module and used for carrying out landslide simulation test on the mountain model in the early warning area through a landslide early warning simulation program to obtain landslide early warning information.
2. The landslide monitoring and pre-warning system according to claim 1, wherein the capturing of the image of the gorge area by the unmanned aerial vehicle with the camera to obtain the panoramic image of the gorge area comprises:
the mobile terminal sends a panoramic stitching instruction to the unmanned aerial vehicle in a wireless transmission mode;
the method comprises the steps that an unmanned aerial vehicle receives a panoramic stitching instruction, and images to be stitched are obtained through a tripod head camera carried by the unmanned aerial vehicle;
the unmanned aerial vehicle sends the acquired images to be spliced to the cloud server through wireless transmission;
the cloud server receives the image sent by the unmanned aerial vehicle, and a panoramic image is obtained through a panoramic stitching algorithm;
and the cloud server transmits the panoramic image to the mobile terminal in a wireless transmission mode to obtain a panoramic mountain canyon area image.
3. The landslide monitoring and early warning system in the alpine canyon region according to claim 3, wherein the unmanned aerial vehicle receives the panoramic stitching instruction, and the pan-tilt camera carried by the unmanned aerial vehicle acquires the images to be stitched, including: panorama instruction control unmanned aerial vehicle keeps the horizontality autogiration 8 times, and rotation angle is 45 degrees, acquires many and treats the concatenation picture.
4. The landslide monitoring and early warning system in the alpine canyon region as claimed in claim 3, wherein the cloud server receives the image sent by the unmanned aerial vehicle, and obtains a panoramic image through a panoramic stitching algorithm, including:
extracting characteristic points with spliced images received by a cloud server; matching the extracted characteristic points to obtain an overlapping area of the images;
calculating a homography matrix between the images according to the characteristic points of the overlapping areas of the images; estimating rotation matrix parameters and focal length parameters of the camera according to the homography matrix;
performing image projection transformation on the plurality of images according to the parameters of the camera and the homography matrix; carrying out image exposure compensation according to the result of image projection transformation;
searching for a seam line of an overlapped part between images in image splicing; and fusing the overlapped parts of all the images according to the parameters of the seam lines, and splicing into a complete panoramic image.
5. The landslide monitoring and pre-warning system in the alpine canyon region of claim 1, wherein the high risk region of landslide is a trailing edge and slope surface scarp region and a region where a threat object is located.
6. The landslide monitoring and early warning system according to claim 1, wherein the obtaining of the mountain model of the early warning region by constructing the mountain model of the early warning region according to the obtained information analysis result through a model construction program comprises: taking the edge characteristics of the target area as topological constraint conditions to obtain three-dimensional point cloud with constraint; and then, a surface mesh model based on edge feature self-constraint is constructed by adopting a zone constraint triangulation algorithm based on local dimension reduction.
7. The landslide monitoring and early warning system in the alpine canyon region according to claim 6, wherein the method for obtaining the edge feature of the target region comprises: adopting canny edge detection algorithm to obtain two-dimensional edge characteristics from the image of the early warning area in the panoramic high mountain canyon area image, including: smoothing the image by a Gaussian filter to remove noise; calculating gradient amplitude and direction by using first-order partial derivative finite difference; carrying out non-maximum suppression on the gradient amplitude, and accurately determining the position of the edge; edges are detected and connected using a dual threshold algorithm.
8. The landslide monitoring and early warning system in the alpine canyon region of claim 1, wherein the simulating landslide of the mountain model in the early warning region to obtain the landslide early warning information comprises:
and the landslide early warning system is used for simulating landslide of the mountain model in the early warning area by combining the information analysis result with the determined inclination as a simulation parameter, and generating landslide early warning information based on the simulation result.
9. An information data processing terminal, characterized in that the information data processing terminal is used for realizing the landslide monitoring and early warning system in the high mountain canyon region according to any one of claims 1-8.
10. A computer readable storage medium storing instructions which, when executed on a computer, cause the computer to apply the landslide monitoring and warning system in a high mountain canyon region according to any one of claims 1 to 8.
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