CN115979229A - Intelligent mapping system is used in city survey and drawing based on thing networking - Google Patents
Intelligent mapping system is used in city survey and drawing based on thing networking Download PDFInfo
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Abstract
The invention discloses an intelligent mapping system for urban mapping based on the Internet of things, which belongs to the field of urban mapping and is used for solving the problems that the current three-dimensional data acquisition time of a building is too long and the building does not have a reference value in the working process of urban mapping.
Description
Technical Field
The invention belongs to the field of urban surveying and mapping, relates to an intelligent surveying and mapping technology, and particularly relates to an intelligent surveying and mapping system for urban surveying and mapping based on the Internet of things.
Background
Urban surveying and mapping refers to surveying and mapping work performed for planning design, construction, operation management and the like of urban construction, urban control measurement, leveling measurement and aerial photogrammetry work performed for establishing urban planes and elevation control networks, urban planning and large-scale topographic maps required by urban construction, and the compiling and drawing of various thematic maps, construction lofting of municipal works, deformation observation of important buildings and the like. The data of urban mapping mainly reflects the characteristics, positions, sizes, forms, names, distributions, categories and other information of natural, social and economic factors of cities. The city mapping data can visually reflect the basic appearance of the city, the city planning needs the mapping of the city to provide basic data, and the correctness and the accuracy of the mapping data directly influence and determine the formulation of the city planning and the implementation of the city construction. The city mapping content comprises: surveying and mapping a current urban large-scale topographic map, urban planning road alignment, urban plane measurement, elevation control network measurement, underground pipeline measurement, construction boundary line setting, construction lofting and completion measurement of a building, settlement measurement of the building and the like;
in the actual urban surveying and mapping working process, the current three-dimensional data of the building is acquired too long, so that the current three-dimensional data of the building does not have reference value any more, and the surveying and mapping work cannot be effectively carried out when relevant work is carried out according to the current three-dimensional data of the building;
therefore, an intelligent mapping system for city mapping based on the Internet of things is provided.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide an intelligent mapping system for urban mapping based on the Internet of things.
The technical problem to be solved by the invention is as follows:
how to accurately update the three-dimensional data of the target surveying and mapping object based on the historical characteristic factors of the building.
The purpose of the invention can be realized by the following technical scheme:
an intelligent mapping system for urban mapping based on the Internet of things comprises a management terminal, a mapping storage terminal, a structure analysis module, a comprehensive real-time mining module, a comprehensive mapping module, a three-dimensional matching module and a server; the management terminal is used for importing the building number of the target surveying and mapping object and sending the building number to the surveying and mapping storage terminal through the server; the mapping storage terminal is used for storing historical three-dimensional virtual diagrams of different target mapping objects and building historical characteristic data of the historical three-dimensional virtual diagrams; the mapping storage terminal sends the historical three-dimensional virtual map of the target mapping object and the historical building feature data of the historical three-dimensional virtual map to a server according to the building number, and the server sends the historical building feature data to a structure analysis module and sends the historical three-dimensional virtual map to a three-dimensional matching module;
the structure analysis module is used for determining the structure complexity level of the target surveying and mapping object, the structure analysis module is further used for setting the number of surveying and mapping samples of the target surveying and mapping object, the structure analysis module sends the structure complexity level and the number of surveying and mapping samples of the target surveying and mapping object to the server, the server sends the number of surveying and mapping samples of the target surveying and mapping object to the comprehensive real mining module, and the server obtains real mining surveying and mapping data of the target surveying and mapping object according to the structure complexity level and sends the real mining surveying and mapping data to the comprehensive real mining module;
the comprehensive real-mining module comprises an artificial real-mining unit and a nuclear detection real-mining unit, wherein the artificial real-mining unit is used for carrying out artificial real mining on the target surveying and mapping object to obtain building fixed-point characteristic data, and the building fixed-point characteristic data is sent to the comprehensive surveying and mapping module through the server; the comprehensive mapping module is used for comprehensively mapping the real-time three-dimensional virtual image of the target mapping object to obtain a real-time three-dimensional virtual image and sending the real-time three-dimensional virtual image to the three-dimensional matching module through the server; the three-dimensional matching module is used for comparing and matching the three-dimensional virtual image of the target surveying and mapping object to generate a building normal signal or a building verification signal;
the comprehensive surveying and mapping module obtains a three-dimensional virtual verification map of a target surveying and mapping object based on the building verification feature data and sends the three-dimensional virtual verification map to the three-dimensional matching module through the server; and the three-dimensional matching module compares the real-time three-dimensional virtual image with the verified three-dimensional virtual image to generate a building normal signal or a building updating signal.
Further, the historical building characteristic data comprises the characteristic projection number, the characteristic depression number, the characteristic angle number, the characteristic arc number, the building height, the building floor area, the building floor number and the building longitude and latitude of the target surveying and mapping object;
the actual mining, surveying and mapping data comprise horizontal interval actual mining distances, elevation interval actual mining distances and mapping actual mining distances;
the building fixed-point characteristic data is the real-time characteristic projection number, the real-time characteristic recess number, the real-time characteristic angle number, the real-time characteristic arc number, the real-time building height, the real-time building floor area and the real-time building floor number of the target surveying and mapping object;
the building verification feature data are the verification feature convex number, the verification feature concave number, the verification feature angle number, the verification feature arc number, the building verification height, the building verification occupied area and the building verification floor number of the target surveying and mapping object.
Further, the determination process of the structural analysis module is specifically as follows:
obtaining building historical feature data of a target surveying and mapping object to obtain the number of feature bulges, the number of feature depressions, the number of feature angles and the number of feature cambered surfaces of the target surveying and mapping object;
calculating the structural complexity of the target mapping object;
comparing the structural complexity with the standard complexity to obtain a structural complexity grade of the target surveying and mapping object, wherein the structural complexity grade is a first structural complexity grade, a second structural complexity grade or a third structural complexity grade;
the structure complexity corresponding to the first structure complexity level is lower than the structure complexity corresponding to the second structure complexity level, and the structure complexity corresponding to the second structure complexity level is lower than the structure complexity corresponding to the third structure complexity level.
Further, the correspondence between the structure complexity level and the actual acquisition survey drawing data is specifically as follows:
the first structural complexity level corresponds to a first horizontal spacing distance, a first elevation spacing distance and a first mapping distance; the second structure complexity level corresponds to a second horizontal spacing distance, a second elevation spacing distance and a second mapping distance; the third structural complexity level corresponds to a third horizontal spacing distance, a second elevation spacing distance and a third mapping distance;
the first horizontal spacing distance is larger than the second horizontal spacing distance and the third horizontal spacing distance, the second horizontal spacing distance is larger than the third horizontal spacing distance, the first elevation spacing distance is larger than the second elevation spacing distance and the third elevation spacing distance, the second elevation spacing distance is larger than the third elevation spacing distance, the first surveying and mapping distance is larger than the second surveying and mapping distance and the third surveying and mapping distance, and the second surveying and mapping distance is larger than the third surveying and mapping distance.
Further, the setting process of the structure analysis module is specifically as follows:
reading the building height and the building occupied area in the historical building characteristic data;
calculating the mapping workload;
the method comprises the steps that the mapping workload and a mapping workload threshold value are used, and the number of mapping samples of a target mapping object is obtained to be a first mapping sample number, a second mapping sample number or a third mapping sample number;
wherein the first number of mapping samples is less than the second number of mapping samples;
the second number of mapping samples is less than the third number of mapping samples.
Further, the artificial mining process of the artificial mining unit is specifically as follows:
obtaining surveying and mapping points surveyed when the target surveying and mapping object is at different visual angles according to the horizontal spacing actual mining distance, the elevation spacing actual mining distance and the surveying and mapping actual mining distance;
and carrying out fixed-point surveying and mapping on the target surveying and mapping object at the surveying and mapping point to obtain the building fixed-point characteristics during the surveying and mapping.
Further, the working process of the comprehensive mapping module is as follows:
reading the fixed point characteristic data of the building;
respectively completing the surveying and mapping of a top view angle, a front view angle, a left view angle, a right view angle and a rear view angle by integrating the building fixed point characteristic data of each surveying and mapping point to obtain a plurality of groups of primary top view maps, primary front view maps, primary rear view maps, primary left view maps and primary right view maps of the target surveying and mapping object;
comparing the plurality of groups of initial overlook maps to obtain an optimal overlook map of the target surveying and mapping object, wherein the optimal overlook map is the initial overlook maps with the same number and the maximum number;
similarly, obtaining an optimal front view map, an optimal rear view map, an optimal left view map and an optimal right view map of the target surveying and mapping object;
preferably, the front view map, the rear view map, the left view map and the right view map together form a real-time three-dimensional virtual map of the target mapping object.
Further, the working process of the three-dimensional matching module is as follows:
comparing the historical three-dimensional virtual map with the real-time three-dimensional virtual map;
if the historical three-dimensional virtual image is matched with the real-time three-dimensional virtual image, generating a building normal signal;
and if the historical three-dimensional virtual graph is not matched with the real-time three-dimensional virtual graph, generating a building verification signal.
Further, the comparison process between the real-time three-dimensional virtual map and the verification three-dimensional virtual map is specifically as follows:
if the verified three-dimensional virtual image is matched with the real-time three-dimensional virtual image, generating a building updating signal;
if the verified three-dimensional virtual graph is not matched with the real-time three-dimensional virtual graph, comparing the verified three-dimensional virtual graph with the historical three-dimensional virtual graph:
if the verification three-dimensional virtual image is matched with the historical three-dimensional virtual image, generating a building normal signal;
and if the verified three-dimensional virtual graph is not matched with the historical three-dimensional virtual graph, generating a building updating signal.
Further, the three-dimensional matching module feeds back a building normal signal or a building updating signal to the server;
if the server receives the building normal signal, the building normal signal is sent to the management terminal;
and if the server receives the building updating signal, sending the verified three-dimensional virtual map of the target surveying and mapping object to the surveying and mapping storage terminal to replace the corresponding historical three-dimensional virtual map, and sending the building updating signal to the management terminal.
Compared with the prior art, the invention has the beneficial effects that:
the method comprises the steps of firstly determining the structural complexity grade and the mapping sample number of a target mapping object through a structural analysis module based on building historical characteristic data, carrying out multiple times of actual collection through a comprehensive acquisition module in combination with the structural complexity grade and the mapping sample number, then carrying out comprehensive mapping on a real-time three-dimensional virtual image of the target mapping object by using a comprehensive mapping module to obtain a real-time three-dimensional virtual image, sending the real-time three-dimensional virtual image to a three-dimensional matching module, comparing and matching the three-dimensional virtual image of the target mapping object by using the three-dimensional matching module, if the real-time three-dimensional virtual image is not matched with the three-dimensional virtual image of the target mapping object, carrying out comprehensive mapping on the target mapping object by using the comprehensive mapping module again to obtain a verified three-dimensional virtual image, sending the verified three-dimensional virtual image to the three-dimensional matching module, and finally carrying out secondary comparison on the real-time three-dimensional virtual image and the verified three-dimensional virtual image by using the three-dimensional matching module to generate a building normal signal or a building updating signal.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is an overall system block diagram of the present invention;
FIG. 2 is a functional block diagram of a comprehensive practice module of the present invention;
fig. 3 is a schematic diagram of the operation of the comprehensive mining module of the present invention.
Detailed Description
The technical solutions of the present invention will be described clearly and completely with reference to the following embodiments, and it should be understood that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-3, an intelligent mapping system for city mapping based on the internet of things includes a management terminal, a mapping storage terminal, a structure analysis module, a comprehensive real mining module, a comprehensive mapping module, a three-dimensional matching module, and a server;
the management terminal is used for importing the building number of the target surveying and mapping object, the management terminal sends the building number of the target surveying and mapping object to the server, and the server sends the building number of the target surveying and mapping object to the surveying and mapping storage terminal;
the mapping storage terminal is used for storing historical three-dimensional virtual diagrams of the target mapping objects distinguished based on the building numbers and building historical characteristic data of the historical three-dimensional virtual diagrams;
specifically, the historical building feature data is the number of feature projections, the number of feature depressions, the number of feature angles, the number of feature arcs, the building height, the building floor area, the number of building floors, the building longitude and latitude, and the like of the target surveying and mapping object, and is not specifically limited and described herein;
the method comprises the steps that a mapping storage terminal reads a building number of a target mapping object, and sends a historical three-dimensional virtual map of the building number and building historical feature data of the historical three-dimensional virtual map to a server, the server sends the historical building feature data to a structure analysis module, and the server sends the historical three-dimensional virtual map to a three-dimensional matching module;
furthermore, the characteristic protrusion is an obvious protrusion part which is fixed on the surface of the building and does not belong to the building body, such as a balcony, an air conditioner outdoor unit and the like, the characteristic recess is a glass window frame and the like with obvious recess compared with the surface of the building, the characteristic angle is an included angle between turning surfaces appearing on the surface of the building except for 90 degrees and 180 degrees, and the characteristic cambered surface is a turning surface with radian on the surface of the building;
the structure analysis module is used for determining the structure complexity level of the target surveying and mapping object according to the historical building feature data, and the specific determination process of the structure complexity level is as follows:
step B1: obtaining building historical feature data of a target surveying and mapping object to obtain the feature projection number St, the feature depression number Su, the feature angle number Sa and the feature cambered surface number Sc of the target surveying and mapping object;
and step B2: calculating the structural complexity Fh of the target surveying and mapping object according to a formula Fh = St × s1+ Su × s2+ Sa × s3+ Sc × s4, wherein s1, s2, s3 and s4 are proportionality coefficients with fixed values, and the values of s1, s2, s3 and s4 are all larger than zero;
it can be understood that the larger the numerical value of the structural complexity, the higher the structural complexity of the target surveying object, and the more detailed features of the surface of the target surveying object;
and step B3: comparing the structural complexity of the target surveying and mapping object with the standard complexity to obtain a structural complexity grade;
if Fh is less than T1, determining the structural complexity level of the target surveying and mapping object as a first structural complexity level;
if Fh is more than or equal to T1 and less than T2, determining the structural complexity level of the target surveying and mapping object as a second structural complexity level;
if T2 is less than or equal to Fh, determining the structural complexity level of the target surveying and mapping object as a third structural complexity level;
it should be further noted that T1 and T2 are both standard complexity, T1 is greater than 0 and less than T2, the structural complexity corresponding to the first structural complexity level is lower than the structural complexity corresponding to the second structural complexity level, and the structural complexity corresponding to the second structural complexity level is lower than the structural complexity corresponding to the third structural complexity level;
the structural analysis module is used for setting the mapping sample number of the target mapping object according to the building historical characteristic data of the target mapping object, and the setting method specifically comprises the following steps:
the method comprises the following steps: reading a building height BH and a building occupied area BS in the historical building characteristic data;
step two: calculating to obtain a surveying and mapping workload CG according to a formula CG = BH multiplied by a1+ BS multiplied by a 2; in the formula, a1 and a2 are proportionality coefficients with fixed numerical values, and the numerical values of a1 and a2 are both larger than zero;
step three: and comparing the mapping workload with the mapping workload threshold to obtain the mapping sample number of the target mapping object, wherein the specific mode is as follows:
if CG is less than R1, the number of the mapping samples of the target mapping object is the first number of the mapping samples;
if the R1 is less than or equal to CG and less than R2, the number of the surveying samples of the target surveying object is the second number of the surveying samples;
if R2 is less than or equal to CG, the number of the surveying and mapping samples of the target surveying and mapping object is the third number of the surveying and mapping samples;
specifically, the values of the mapping workload thresholds R1 and R2 are both greater than zero, R1 is less than R2, the number of first mapping samples is less than the number of second mapping samples, and the number of second mapping samples is less than the number of third mapping samples;
the structure analysis module sends the structural complexity grade and the mapping sample number of the target mapping object to the server, the server sends the mapping sample number of the target mapping object to the comprehensive real mining module, and the server obtains real mining mapping data of the target mapping object according to the structural complexity grade and sends the real mining mapping data to the comprehensive real mining module, wherein the structure analysis module specifically comprises the following steps:
the actual mining, surveying and mapping data comprise horizontal spaced actual mining distances, elevation spaced actual mining distances and mapping actual mining distances, the horizontal spaced actual mining distances are spacing distances of actual mining at each time in the horizontal moving process of the artificial actual mining units, the elevation spaced actual mining distances are spacing distances of actual mining at each time in the vertical moving process of the artificial actual mining units, and the mapping actual mining distances are relative distances between the artificial actual mining units and the building surface;
further, the corresponding relationship between the real-mining survey drawing data and the structure complexity level is as follows:
the first structural complexity level corresponds to a first horizontal spacing distance, a first elevation spacing distance and a first mapping distance;
the second structure complexity level corresponds to a second horizontal spacing distance, a second elevation spacing distance and a second mapping distance;
the third structural complexity level corresponds to a third horizontal spacing distance, a second elevation spacing distance and a third mapping distance;
it should be specifically noted that the first horizontal spacing distance is greater than the second horizontal spacing distance and the third horizontal spacing distance, the second horizontal spacing distance is greater than the third horizontal spacing distance, the first elevation spacing distance is greater than the second elevation spacing distance and the third elevation spacing distance, the second elevation spacing distance is greater than the third elevation spacing distance, the first mapping distance is greater than the second mapping distance and the third mapping distance, and the second mapping distance is greater than the third mapping distance;
understandably, the smaller the numerical values of the horizontal spacing distance and the elevation spacing distance are, the higher the surveying and mapping precision is, and the closer the comprehensive real-mining module is to the target surveying and mapping object is, the higher the surveying and mapping precision is;
the comprehensive real-mining module is divided into a manual real-mining unit and a nuclear detection real-mining unit, and in the actual use process, the comprehensive real-mining module can be a mapping vehicle, a fixed-point mapping station, an aerial photography mapping unmanned aerial vehicle and the like, and is not specifically limited and described herein;
the artificial real mining unit is used for carrying out artificial real mining on the target surveying and mapping object based on real mining surveying and mapping data and surveying and mapping sample number, and the artificial real mining process specifically comprises the following steps:
step Q1: obtaining surveying and mapping points of the target surveying and mapping object at different viewing angles according to the horizontal spacing real mining distance, the elevation spacing real mining distance and the surveying and mapping real mining distance, and carrying out fixed-point surveying and mapping on the target surveying and mapping object at the surveying and mapping points to obtain the building fixed-point characteristic information marked as D11, D12, \8230 \, dui, u =1,2, ..., x, x are positive integers, and i represents the number of the surveying and mapping points in surveying and mapping;
the building fixed-point characteristic data comprises the real-time characteristic projection number, the real-time characteristic depression number, the real-time characteristic angle number, the real-time characteristic arc number, the real-time building height, the real-time building floor area, the real-time building floor number and the like of a target surveying and mapping object;
step Q2: sending the building fixed point feature data to a server, wherein the server sends the building fixed point feature data to a comprehensive mapping module;
the comprehensive mapping module is used for comprehensively mapping the real-time three-dimensional virtual graph of the target mapping object, and the specific working process is as follows:
step N1: reading the fixed point characteristic data of the building;
and step N2: respectively completing the surveying and mapping of a top view angle, a front view angle, a left view angle, a right view angle and a rear view angle by integrating the building fixed point characteristic data of each surveying and mapping point to obtain a plurality of groups of primary top view maps, primary front view maps, primary rear view maps, primary left view maps and primary right view maps of the target surveying and mapping object;
and step N3: comparing the plurality of sets of initial overhead maps to obtain an optimal overhead map of the target surveying and mapping object, wherein the optimal overhead map is the most initial overhead maps with the same number;
similarly, obtaining an optimal front view map, an optimal rear view map, an optimal left view map and an optimal right view map of the target surveying and mapping object;
and step N4: preferably, the front-view map, the rear-view map, the left-view map and the right-view map form a real-time three-dimensional virtual map of the target surveying and mapping object;
the comprehensive mapping module unit sends the real-time three-dimensional virtual graph to a server, and the server sends the real-time three-dimensional virtual graph to a three-dimensional matching module;
the three-dimensional matching module is used for comparing and matching three-dimensional virtual images of a target mapping object, and the specific working process is as follows:
comparing the historical three-dimensional virtual map with the real-time three-dimensional virtual map;
if the historical three-dimensional virtual graph and the real-time three-dimensional virtual graph can be completely matched, generating a building normal signal;
if the historical three-dimensional virtual image and the real-time three-dimensional virtual image cannot be completely matched, generating a building verification signal and sending the building verification signal to the comprehensive practical acquisition module through the server;
after the comprehensive practical acquisition module receives the building verification signal, a verification and practical acquisition unit, namely a second aerial photography surveying and mapping unmanned aerial vehicle, is started to perform verification and practical acquisition on a target surveying and mapping object according to practical acquisition and mapping data to obtain building verification feature data and a verification three-dimensional virtual map, wherein the obtaining process of the building verification feature data is the same as that of the building fixed point feature data, and the verification three-dimensional virtual map is obtained by analyzing the comprehensive surveying and mapping module;
the building verification feature data comprise the number of verification feature bulges, the number of verification feature depressions, the number of verification feature angles, the number of verification feature arcs, the building verification height, the building verification floor area, the number of building verification floors and the like of a target surveying and mapping object;
the comprehensive real mining module sends the verified three-dimensional virtual graph to the three-dimensional matching module through the server;
the three-dimensional matching module compares the real-time three-dimensional virtual map with the verification three-dimensional virtual map, and the specific comparison process is as follows:
if the verified three-dimensional virtual image is matched with the real-time three-dimensional virtual image, confirming that the building structure of the target surveying and mapping object is changed, and generating a building updating signal;
if the verified three-dimensional virtual graph is not matched with the real-time three-dimensional virtual graph, comparing the verified three-dimensional virtual graph with the historical three-dimensional virtual graph:
if the verification three-dimensional virtual image is matched with the historical three-dimensional virtual image, confirming that the building structure is not changed, and generating a building normal signal;
if the verified three-dimensional virtual graph is not matched with the historical three-dimensional virtual graph, confirming that the building structure is changed, and generating a building updating signal;
specifically, the comparison process of the three-dimensional virtual diagrams is to stack the three-dimensional virtual diagrams to be compared, and judge whether the three-dimensional virtual diagrams are matched by judging whether the overlapped parts are completely matched;
if the three-dimensional matching module generates a building normal signal, the building normal signal is sent to the management terminal through the server, if the building updating signal is generated, the verification three-dimensional virtual map is sent to the mapping storage terminal to replace the historical three-dimensional virtual map of the corresponding target mapping object, and meanwhile, the building updating signal is sent to the management terminal;
in the present application, if a corresponding calculation formula appears, the above calculation formula is all the dimensionless value calculation, and the weight coefficient, the scale coefficient, and other coefficients existing in the formula are set to be one result value obtained by quantizing each parameter, and the magnitudes of the weight coefficient and the scale coefficient may be set as long as the proportional relationship between the parameter and the result value is not affected.
The preferred embodiments of the invention disclosed above are intended to be illustrative only. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise forms disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best utilize the invention. The invention is limited only by the claims and their full scope and equivalents.
Claims (10)
1. An intelligent mapping system for urban mapping based on the Internet of things is characterized by comprising a management terminal, a mapping storage terminal, a structure analysis module, a comprehensive real acquisition module, a comprehensive mapping module, a three-dimensional matching module and a server;
the management terminal is used for importing the building number of the target surveying and mapping object and sending the building number to the surveying and mapping storage terminal;
the mapping storage terminal is used for storing historical three-dimensional virtual diagrams of different target mapping objects and building historical characteristic data of the historical three-dimensional virtual diagrams;
the structure analysis module is used for determining the structure complexity level of the target mapping object and setting the mapping sample number of the target mapping object;
the comprehensive real-mining module comprises an artificial real-mining unit and a nuclear detection real-mining unit;
the artificial real mining unit is used for carrying out artificial real mining on the target surveying and mapping object to obtain building fixed point characteristic data, and the building fixed point characteristic data is sent to the comprehensive surveying and mapping module through the server;
the comprehensive mapping module is used for comprehensively mapping the real-time three-dimensional virtual image of the target mapping object to obtain a real-time three-dimensional virtual image and sending the real-time three-dimensional virtual image to the three-dimensional matching module;
the three-dimensional matching module is used for comparing and matching the three-dimensional virtual image of the target surveying and mapping object to generate a building normal signal or a building verification signal;
the checking, practical and mining unit is used for carrying out checking, practical and mining according to the practical and mining surveying and mapping data to obtain building checking and mining characteristic data;
the comprehensive mapping module is used for obtaining a verification three-dimensional virtual map of the target mapping object based on the building verification feature data and sending the verification three-dimensional virtual map to the three-dimensional matching module;
and the three-dimensional matching module is also used for comparing the real-time three-dimensional virtual graph with the verified three-dimensional virtual graph to generate a building normal signal or a building updating signal.
2. The intelligent mapping system for urban mapping based on the internet of things as claimed in claim 1, wherein the historical building feature data are the feature projection number, the feature depression number, the feature angle number, the feature arc number, the building height, the building floor area, the building floor number and the building longitude and latitude of the target mapping object;
the actual mining, surveying and mapping data comprise horizontal interval actual mining distances, elevation interval actual mining distances and mapping actual mining distances;
the building fixed-point characteristic data is the real-time characteristic projection number, the real-time characteristic recess number, the real-time characteristic angle number, the real-time characteristic arc number, the real-time building height, the real-time building floor area and the real-time building floor number of the target surveying and mapping object;
the building verification feature data are the verification feature convex number, the verification feature concave number, the verification feature angle number, the verification feature arc number, the building verification height, the building verification occupied area and the building verification floor number of the target surveying and mapping object.
3. The intelligent mapping system for urban mapping based on the internet of things according to claim 2, wherein the determination process of the structural analysis module is specifically as follows:
obtaining building historical feature data of a target surveying and mapping object to obtain the number of feature bulges, the number of feature depressions, the number of feature angles and the number of feature cambered surfaces of the target surveying and mapping object;
calculating the structural complexity of the target mapping object;
comparing the structural complexity with the standard complexity to obtain a structural complexity grade of the target surveying and mapping object, wherein the structural complexity grade is a first structural complexity grade, a second structural complexity grade or a third structural complexity grade;
the structure complexity corresponding to the first structure complexity level is lower than the structure complexity corresponding to the second structure complexity level, and the structure complexity corresponding to the second structure complexity level is lower than the structure complexity corresponding to the third structure complexity level.
4. The intelligent mapping system for urban mapping based on the internet of things as claimed in claim 3, wherein the correspondence between the complex structure level and the real acquisition survey data is specifically:
the first structural complexity level corresponds to a first horizontal spacing distance, a first elevation spacing distance and a first mapping distance; the second structure complexity level corresponds to a second horizontal spacing distance, a second elevation spacing distance and a second mapping distance; the third structural complexity level corresponds to a third horizontal spacing distance, a second elevation spacing distance and a third mapping distance;
the first horizontal spacing distance is greater than the second horizontal spacing distance and the third horizontal spacing distance, the second horizontal spacing distance is greater than the third horizontal spacing distance, the first elevation spacing distance is greater than the second elevation spacing distance and the third elevation spacing distance, the second elevation spacing distance is greater than the third elevation spacing distance, the first mapping distance is greater than the second mapping distance and the third mapping distance, and the second mapping distance is greater than the third mapping distance.
5. The intelligent mapping system for urban mapping based on the internet of things according to claim 2, wherein the configuration analysis module is specifically configured as follows:
reading the building height and the building occupied area in the historical building characteristic data;
calculating the mapping workload;
the method comprises the steps that the mapping workload and a mapping workload threshold value are used, and the number of mapping samples of a target mapping object is obtained to be a first mapping sample number, a second mapping sample number or a third mapping sample number;
wherein the first mapping sample number is smaller than the second mapping sample number;
the second number of mapping samples is less than the third number of mapping samples.
6. The intelligent mapping system for urban surveying and mapping based on the internet of things according to claim 2, wherein the manual real-time mining process of the manual real-time mining unit is as follows:
obtaining surveying and mapping points surveyed when the target surveying and mapping object is at different visual angles according to the horizontal spacing actual mining distance, the elevation spacing actual mining distance and the surveying and mapping actual mining distance;
and carrying out fixed-point surveying and mapping on the target surveying and mapping object at the surveying and mapping point to obtain the building fixed-point characteristics during the surveying and mapping.
7. The intelligent mapping system for urban mapping based on the internet of things according to claim 6, wherein the working process of the comprehensive mapping module is as follows:
reading the characteristic data of the fixed point of the building;
respectively completing the surveying and mapping of a top view angle, a front view angle, a left view angle, a right view angle and a rear view angle by integrating the building fixed point characteristic data of each surveying and mapping point to obtain a plurality of groups of primary top view maps, primary front view maps, primary rear view maps, primary left view maps and primary right view maps of the target surveying and mapping object;
comparing the plurality of sets of initial overhead maps to obtain an optimal overhead map of the target surveying and mapping object, wherein the optimal overhead map is the most initial overhead maps with the same number;
similarly, obtaining an optimal front view map, an optimal rear view map, an optimal left view map and an optimal right view map of the target surveying and mapping object;
and preferably, the front view map, the rear view map, the left view map and the right view map form a real-time three-dimensional virtual map of the target surveying and mapping object.
8. The intelligent mapping system for urban mapping based on the internet of things according to claim 7, wherein the three-dimensional matching module specifically comprises the following working processes:
comparing the historical three-dimensional virtual map with the real-time three-dimensional virtual map;
if the historical three-dimensional virtual image is matched with the real-time three-dimensional virtual image, generating a building normal signal;
and if the historical three-dimensional virtual graph is not matched with the real-time three-dimensional virtual graph, generating a building verification signal.
9. The intelligent mapping system for urban mapping based on the internet of things according to claim 8, wherein the comparison process between the real-time three-dimensional virtual map and the verification three-dimensional virtual map is as follows:
if the verified three-dimensional virtual image is matched with the real-time three-dimensional virtual image, generating a building updating signal;
if the verified three-dimensional virtual graph is not matched with the real-time three-dimensional virtual graph, comparing the verified three-dimensional virtual graph with the historical three-dimensional virtual graph:
if the verification three-dimensional virtual image is matched with the historical three-dimensional virtual image, generating a building normal signal;
and if the verification three-dimensional virtual graph is not matched with the historical three-dimensional virtual graph, generating a building updating signal.
10. The intelligent mapping system for urban mapping based on the internet of things according to claim 9, wherein the three-dimensional matching module feeds back a building normal signal or a building update signal to the server;
if the server receives the building normal signal, the building normal signal is sent to the management terminal;
and if the server receives the building updating signal, sending the verified three-dimensional virtual map of the target surveying and mapping object to the surveying and mapping storage terminal to replace the corresponding historical three-dimensional virtual map, and sending the building updating signal to the management terminal.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2005017644A2 (en) * | 2003-08-13 | 2005-02-24 | Topcon Corp | 3-dimensional measurement device and electronic storage medium |
| US20050128212A1 (en) * | 2003-03-06 | 2005-06-16 | Edecker Ada M. | System and method for minimizing the amount of data necessary to create a virtual three-dimensional environment |
| CN106934720A (en) * | 2017-01-24 | 2017-07-07 | 久隆财产保险有限公司 | Equipment insurance intelligent pricing method and system based on Internet of Things |
| CN114184179A (en) * | 2022-02-16 | 2022-03-15 | 威海市城市规划技术服务中心有限公司 | Outdoor geographical mapping management and control system based on internet |
| CN115628720A (en) * | 2022-10-19 | 2023-01-20 | 中软航科数据科技(珠海横琴)有限公司 | Intelligent three-dimensional topographic map surveying and mapping method and system |
-
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050128212A1 (en) * | 2003-03-06 | 2005-06-16 | Edecker Ada M. | System and method for minimizing the amount of data necessary to create a virtual three-dimensional environment |
| WO2005017644A2 (en) * | 2003-08-13 | 2005-02-24 | Topcon Corp | 3-dimensional measurement device and electronic storage medium |
| CN106934720A (en) * | 2017-01-24 | 2017-07-07 | 久隆财产保险有限公司 | Equipment insurance intelligent pricing method and system based on Internet of Things |
| CN114184179A (en) * | 2022-02-16 | 2022-03-15 | 威海市城市规划技术服务中心有限公司 | Outdoor geographical mapping management and control system based on internet |
| CN115628720A (en) * | 2022-10-19 | 2023-01-20 | 中软航科数据科技(珠海横琴)有限公司 | Intelligent three-dimensional topographic map surveying and mapping method and system |
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