165 results about "Urban building" patented technology

The invention relates to the technical field of unmanned aerial vehicle application and urban airspace management, in particular to an intelligent site selection method and system for unmanned aerial vehicle take-off and landing points in an urban building group, and the intelligent site selection system for the unmanned aerial vehicle take-off and landing points in the urban building group specifically comprises the following steps: S1, carrying out the multi-source heterogeneous data fusion and high-precision three-dimensional environment modeling; s2, fluid dynamics simulation and airflow field pre-calculation are calculated; s3, real-time meteorological monitoring and dynamic risk correction; s4, establishing a quantitative safety evaluation model and multi-objective optimization site selection; and S5, visual decision support and feedback learning. According to the scheme, by deeply fusing multi-source heterogeneous geographic information data and constructing a high-precision three-dimensional digital twinborn city environment, accurate simulation and risk assessment of an airflow field around a building group are realized, geometric, material and semantic information is automatically extracted by using oblique photography, laser point cloud and a building information model, and the construction efficiency is improved. A unified three-dimensional grid with physical attributes is formed, and a reliable basis is provided for subsequent fluid calculation.

The invention relates to the technical field of building disease detection, in particular to an urban building disease detection method and device, electronic equipment and a storage medium. Multi-modal image data formed by original visible light and thermal infrared image data is obtained, and an original thermal infrared image is subjected to geometric correction; calculating a mapping relation with an original visible light image so as to complete pixel-level registration, obtaining target multi-modal image data, inputting the target multi-modal image data into a hierarchical deep learning recognition model, recognizing building disease information, then performing three-dimensional space mapping, generating a building three-dimensional mesh model containing disease three-dimensional space setting coordinates, and finally performing three-dimensional mesh modeling. And then calculating a relationship between a model surface grid vertex and a disease point cloud density, generating a disease distribution thermodynamic diagram, analyzing disease aggregation characteristics in multiple dimensions according to the thermodynamic diagram, and quantitatively analyzing spatial correlation between the disease and a building construction node in combination with building component information. According to the invention, the urban building disease detection efficiency and precision are improved.

The invention relates to the technical field of data processing, and discloses a numerical simulation method for a synergistic effect of an urban heat island and high-temperature heat waves. The method comprises the following steps: collecting urban building form data to construct a data set, and combining remote sensing data to carry out local climate zoning; extracting a high-temperature heat wave process and performing grading by utilizing machine learning; analyzing the urban heat island intensity time sequence change based on the remote sensing data; constructing an urban canopy mode coupling hydrology and an artificial heat source; and inputting different levels of heat wave data to simulate a synergistic effect. The technical problem that the urban heat island effect and high-temperature heat wave synergistic effect mechanism cannot be accurately simulated in the prior art is solved, and the numerical simulation method for quantitatively evaluating the urban heat island intensity amplification coefficient under the condition of different grades of high-temperature heat waves is established.

The invention belongs to the technical field of three-dimensional modeling, and discloses a city building three-dimensional model refined construction method based on oblique photography. Comprising the steps of collecting inclined image data of a to-be-modeled urban area and performing data cleaning to obtain a modeling image data set; carrying out projection consistency analysis, identifying a boundary dislocation region and removing the boundary dislocation region to obtain a dislocation removal data set; shielding area identification is carried out, shielding compensation is carried out based on an identification result, and an enhanced three-dimensional point data set is output; executing detail reservation to obtain a triangular facet data set; normal optimization is carried out, plane adjustment is carried out on the triangular surface data set based on an optimization result, and a three-dimensional grid data set is obtained; constructing an initial three-dimensional model, and performing map mapping on the initial three-dimensional model to obtain a detail map set; constructing a fine building three-dimensional model in combination with the detail map set and the initial three-dimensional model; and the boundary definition, the structural integrity and the texture fineness of the urban building three-dimensional model are improved.

The invention relates to the technical field of photovoltaic distribution installation, in particular to a photovoltaic distribution decision-making method for a building group, which comprises the following steps: acquiring an original live-action image of a target area, and processing the original live-action image of the target area to obtain a target live-action image; obtaining meteorological characteristic data of the target area, and determining photovoltaic output data of the target area based on the target real scene image and the meteorological characteristic data of the target area to form a multi-scene power generation prediction data set; acquiring operation data of a power distribution system of the target building group, and establishing a comprehensive target function taking the total cost as an optimization target based on the operation data and the multi-scene power generation prediction data set; based on the constraint of the constraint condition set, solving the comprehensive target function, and obtaining and outputting a photovoltaic distribution target solution in the target area; according to the invention, the accuracy, safety and comprehensive economic benefits of distributed photovoltaic development of urban building groups are systematically improved.

The invention discloses an urban agglomeration anti-seismic damage prediction method and system based on an unmanned aerial vehicle technology and a deep learning model. The method comprises the following steps: constructing a typical building multi-angle aerial image database and a building earthquake damage database under different load coupling effects; training an urban building group identification model based on the aerial photo database to identify the type, geometry and texture information of the building; constructing and training horizontal and vertical seismic oscillation amplification coefficient prediction models for correcting seismic oscillation intensities under different topographic conditions; a typical building earthquake damage prediction model is constructed and trained, and the building damage grade is predicted in combination with the corrected earthquake vibration intensity; and finally, realizing three-dimensional visualization of the damage condition of the urban building group through a damage grade imaging module. According to the method, the problems of inaccurate urban building group modeling information, large earthquake damage analysis workload and low precision in the prior art are solved, and a scientific basis is provided for construction and evaluation of tough cities.

The invention discloses a long-period regional scale building water retaining measure distribution method under typhoon flood, and the method comprises the steps: constructing a typhoon rainfall model of a research region, and obtaining a ten thousand-grade scale typhoon rainfall event library; constructing a training data set required by the typhoon rainfall-waterlogging maximum inundation proxy model; constructing a typhoon rainfall-waterlogging maximum inundation proxy model fusing the convolutional neural network and a gated circulation unit; determining urban building water retaining measure types and cost-benefit parameters; extracting all events of which the recurrence periods are smaller than a decision threshold; establishing an optimization model of a regional scale measure planning decision problem, and performing multi-objective optimization of minimum loss and minimum cost; and solving the optimization model of the regional scale measure planning decision problem to obtain a combined optimization solution of regional disaster reduction measures, and making a disaster reduction plan according to actual conditions. According to the method, cost-benefit optimization of different disaster reduction measure combinations under the regional scale is realized, and a scientific basis and decision support are provided for pre-disaster waterlogging prevention measure configuration.

The invention relates to the technical field of urban building energy consumption calculation, in particular to an urban building energy consumption calculation method and device based on local weather data, and the method comprises the steps: obtaining local built environment information data of a local climate region, and calculating local weather data through the local built environment information data; the two-dimensional building boundary vector graph in the local climate area is converted into a three-dimensional building model, and an urban building energy consumption model with building prototype information is constructed based on building functions and years; and distributing the local weather data to a subdivided local climate grid corresponding to the urban building energy consumption model to calculate the urban building energy consumption of the building group. Therefore, the problem that the calculation efficiency and precision of the urban building energy consumption cannot be effectively guaranteed due to the fact that the resolution ratio of a local weather grid cannot be freely defined, the local built environment cannot be subdivided, and the difference of different local climate heat island effects cannot be represented in the prior art is solved.

The invention discloses an anomaly detection and identification method for an urban building facade, relates to the technical field of building maintenance, solves the problem that a single detection technology, such as infrared thermal imaging detection or pure visual imaging detection, is obviously short, and locks a standard range through infrared thermal imaging and temperature value section density analysis. The method comprises the following steps of: accurately marking suspected abnormal partitions, matching and associating standard image areas through position vectors, and matching with height difference verification of three-dimensional point cloud scanning to realize multi-level accurate screening of the abnormal partitions, so that the problems of misjudgment and missed judgment of a single detection mode are effectively avoided; according to the method, field temperature data is dynamically determined, dependence on fixed parameters is not needed, the method can adapt to different types of building facade detection scenes in different environments, and the universality of the method is greatly improved.

The application provides a building group structure type identification method and device based on a multi-modal large model, and relates to the technical field of multi-modal large models.The method comprises the following steps: extracting observable building features through a multi-modal large model; establishing a graph-enhanced multi-modal large model to match and reason the features and a knowledge graph; introducing an expert review mechanism to correct the identification results, dynamically update the knowledge graph, and fine-tune the graph-enhanced multi-modal large model; establishing a city building group rapid identification system, using the knowledge graph to establish a rapid identification model based on deep learning and an interpretable identification system based on the graph-enhanced multi-modal large model.The application combines the rapid classification of deep learning and the interpretable reasoning ability of graph enhancement, and constructs a structure identification closed-loop system with self-learning and self-updating capabilities.The application is suitable for city building census, seismic evaluation, BIM-assisted modeling and other scenes, and has high accuracy, strong generalization and continuous evolution capabilities.

This invention discloses a control method for a UAV positioning and control system based on urban low-altitude three-dimensional traffic, belonging to the field of three-dimensional traffic technology. The control system includes a ground-based UAV traffic control center, several UAVs, a positioning mechanism mounted on each UAV, and markers mounted on urban buildings. The control method includes: the UAVs obtaining their first coordinate position via a satellite positioning module; obtaining their second coordinate position by locking onto markers via the positioning mechanism; obtaining precise coordinates based on coordinate positions one and two; and the control center controlling the aerial three-dimensional traffic of the UAVs based on these precise coordinates. This invention, through the coordinated operation of the ground control center and the UAV control system, achieves precise positioning of the UAVs outside the intersection area, effectively ensuring the safe and orderly passage of the UAVs through the intersection area.

The application relates to a kind of city building agent reconstruction methods based on aerial image.The method comprises: obtaining the multi-view image corresponding to target building;Multi-view image includes near vertical view image and inclined view image;According to near vertical view image, the bottom contour of target building is determined;Determine the first depth difference between each pixel point in inclined view image;According to the camera pose parameter of multi-view image and the current predicted height of target building, rendering is carried out, and the rendering depth map of target building under the current predicted height is obtained;With the distance between the second depth difference of each pixel point in the rendering depth map and the first depth difference as the optimization target, the current predicted height is optimized, and according to the bottom contour and target measurement height, the three-dimensional building model corresponding to target building is constructed.Using the method can improve the efficiency and accuracy of city building agent reconstruction.

The invention provides an urban building civil engineering project construction progress delay risk early warning method, which comprises the steps of multi-dimensional data cleaning and alignment, construction risk knowledge graph automatic construction and topological optimization, dynamic causal path identification and expert rule calibration, and structural equation reverse reasoning and anti-fact intervention simulation. According to the method, multi-dimensional traceability of construction period risk causes, accurate identification of key factors and quantitative prediction of construction period response are realized, the real-time performance and scientificity of risk assessment are improved, and a data-driven technical support is provided for intelligent management and decision making of engineering projects.

The application discloses a kind of city scale-oriented multi-source heterogeneous data fusion carbon emission space distribution simulation method, solve the problem of low spatial resolution, insufficient accuracy of city carbon emission space distribution simulation estimation. Including defining city carbon emission accounting range;Collect multi-source heterogeneous data;Calculate the consumption of main energy types of seven big industry departments under city scale;The energy consumption of seven big industry departments in city is corrected;Seven big industry departments are matched with corresponding city building type, and the corresponding relationship between city industry department energy consumption and building function purpose category is established;Accounting carbon emission;Construct fine energy consumption carbon emission space distribution model, and distribute carbon emission space to each kind of single building.The present application comprehensively utilizes multi-source data, realizes the high resolution, dynamic estimation of city scale carbon emission space distribution, and overcomes the limitation that the existing method is coarse in spatial resolution and difficult to quantify the carbon emission of different energy consumption departments.

The invention provides an urban building deformation monitoring leak detection point identification method and system, and belongs to the technical field of urban building health monitoring. According to the method, the isotropic hypothesis of a traditional two-dimensional plane buffer area is abandoned, a parameterized three-dimensional confidence space conforming to an SAR side-looking imaging physical mechanism is additionally constructed on the basis of contour strong judgment, multiple factors such as the radar sight line direction, the incident angle, the building height and the shielding effect are fully considered, misjudgment of non-target scattering points is effectively avoided, and the detection accuracy is improved. The spatial affiliation relationship between the PS point and the building is more accurate, and the reliability of omission ratio evaluation is remarkably improved.

The utility model relates to city building technical field especially suitable for city building's city three -dimensional afforestation system, its technical scheme includes: grid frame, connecting piece, article groove, positioning mechanism and filter mechanism, every four between the grid frame is provided with the positioning mechanism of gear drive, and the grid frame is provided with multiple article grooves at equal intervals, and the article groove one side is provided with filter mechanism, the device operator manual rotation knob, drive driving wheel through the rotating rod, and then make driven wheel drive positioning block along the guide groove removal, realize the accurate locking of grid frame connecting piece, in the drainage and filtration aspect, when the water content in the article groove is excessive, the excess moisture enters the filter pipe through the water -permeable hole and the lateral wall drainage port, and the slight inclination design of the water channel promotes the flow of water to carry impurities to the filter screen, the shift block rotates under the action of the water flow, cooperates with the filter screen, effectively filters the impurities and realizes the filter screen cleaning, ensures that the drainage is unobstructed and the filtration effect.

The application belongs to the technical field of earthquake disaster scenario construction, and discloses a method for constructing an earthquake disaster scenario based on big data, and the specific steps are as follows: step one: multi-source heterogeneous data acquisition and preprocessing ground structure data acquisition: the spatial distribution characteristics of urban building groups are obtained by using multi-platform remote sensing technology. By integrating multi-source data, a three-dimensional coupling model of underground pipe network and ground building is constructed, the defects of isolated analysis of ground and underground systems in traditional methods are solved, the synchronous simulation of the dynamic correlation process of pipe network rupture and building damage is realized, the additional influence of pipe network failure on building foundation stability and the chain effect of soil erosion caused by leakage fluid are accurately analyzed, and the space-time correlation rules of pipe network rupture events, building fire, fire fighting failure and other types of secondary disasters are established, the building group function paralysis risk and disaster diffusion range under different damage degrees are dynamically predicted, and the disaster evolution path is displayed in real time through a visual platform.

The application provides a building layering intelligent recognition method and system based on multi-modal remote sensing data, and belongs to the technical field of building detection. Multi-modal and multi-view remote sensing images including optical remote sensing images and radar remote sensing images are continuously acquired; the remote sensing images are input into a deep learning prediction model to realize accurate prediction of the height of urban building groups; the building height information predicted at multiple time nodes is calculated by a difference analysis method and a change vector analysis to obtain the change value of height data in different periods; the buildings whose height change values exceed a first threshold value are preliminarily marked as layering buildings; a weighted local spatial anomaly measurement method is further applied to calculate a spatial consistency index of height change in the region, and if the index exceeds a second threshold value, the building is finally determined as a layering building. The application can realize automatic and intelligent identification of illegal layering buildings in urban areas, and provide a scientific basis for urban management and law enforcement.

The application discloses a kind of three-dimensional geographic city building instance segmentation methods based on satellite-unmanned aerial vehicle cooperation, multi-scale feature extraction is carried out to satellite image, and satellite feature pyramid is obtained;Feature extraction and depth estimation are carried out to unmanned aerial vehicle image under each view angle, and cross-view attention aggregation of depth perception is carried out, to generate bird's eye view feature and height information map;Weight modulation is carried out to bird's eye view feature using height information map, and cross-view attention fusion is carried out to each level feature of satellite feature pyramid and modulated bird's eye view feature, to obtain enhanced feature pyramid;The enhanced feature pyramid is input into instance segmentation network, and the instance segmentation result of building in target area is output.The application effectively makes up the defect of insufficient single view information, can significantly improve the boundary integrity of building instance in complex urban scene, adjacent instance distinguishing ability and overall segmentation precision, and a good balance between large-scale coverage and local geometric details is achieved.

The utility model discloses an urban building monitoring device, which relates to the technical field of monitoring, and is technically characterized by comprising a monitor body, a guide rail mounted at the indoor top of a building, a U-shaped connecting frame arranged at the top of the monitor body, rollers rotatably connected to two sides of the inner wall of the connecting frame, rolling grooves matched with the rollers and arranged on two sides of the bottom of the guide rail, and the guide rail and the connecting frame are arranged in a staggered manner. A driving pulley and a driven pulley are rotationally arranged at the two ends of the guide rail respectively, a driving part for driving the driving pulley to rotate forwards and backwards is arranged on the guide rail, a traction rope is sleeved between the driven pulley and the driving pulley, and the two ends of the traction rope are connected with the two ends of the connecting frame; the system can monitor a larger range, and is suitable for monitoring the interior of a building with a large area.

The invention provides an urban photovoltaic potential assessment method and system based on land utilization, and relates to the technical field of photovoltaic potential assessment. The method comprises the following steps: constructing an urban three-dimensional building model based on multi-source data; performing solar radiation simulation on the urban three-dimensional building model through light environment simulation software, calculating space-time solar radiation distribution of the urban building roof under the condition of considering the shielding effect of surrounding buildings, and obtaining a space-time solar radiation distribution diagram of the urban building roof; obtaining a city land utilization property current situation map based on the AOI data of the city; and obtaining the photovoltaic potential of the urban building roof according to the urban land utilization property current situation map and the space-time solar radiation distribution map of the urban building roof. According to the method, the influence of the total area of the building roof and the shielding effect of surrounding buildings on solar radiation of the building roof and the influence of the structural characteristic difference of the building body on the available coefficient of the building roof are fully considered, and the accuracy of the photovoltaic potential evaluation result of the urban-scale building roof is improved.

The application provides a kind of aerial data building height calculation method based on 3D Gauss technology, comprising obtaining aerial photograph;Carrying out data pretreatment;Carrying out geographic coordinate conversion;Taking all aerial photographs, calculating its position in local coordinate system before conversion, applying conversion function f_best (x, y, z), make local coordinate system and target coordinate system align;The internal parameter, external parameter, sparse point cloud of converted aerial photograph are input into 3DGS algorithm, and scene reconstruction is carried out;Obtain user click position;Calculate the building height of the user click position.The aerial data building height calculation method based on 3D Gauss technology proposed by the application introduces 3DGS technology into city building three-dimensional modeling, for high-definition image data collected by unmanned aerial vehicle, while taking into account the advantages of 3DGS technology, realizes interactive browsing and automatic height measurement task.

To address the problems of semantic structure destruction, geometric feature distortion, and difficulty in controlling multi-level errors in the LOD simplification process of existing 3D models, this application discloses a static LOD processing method, device, and storage medium for urban digital twin scenes, belonging to the field of computer graphics and 3D modeling technology. The method includes: semantic recognition and region division of the urban building 3D mesh model to construct a semantically labeled mesh; establishing a simplification control model based on the semantically labeled mesh and determining simplification constraints; performing mesh simplification processing under constraints; preserving geometric features of the simplification results; evaluating errors in each LOD level model and performing adaptive correction; and replacing semantic components that cannot be preserved to generate multi-level LOD model data. This application reduces model complexity while achieving the coordinated preservation of semantic consistency and geometric accuracy, making it suitable for efficient rendering and visualization applications of urban-level 3D scenes.

The invention relates to the field of building informatization, and discloses an ontology-based urban building industry multi-source heterogeneous data integrated treatment method and system, and the method comprises the steps: constructing an urban building domain ontology library; performing semantic analysis and metadata extraction on the urban construction industry multi-source heterogeneous data; and based on the building domain ontology library, the extracted metadata and the generated mapping comparison table, semantic association of cross-data-source business objects is established through a semantic reasoning engine, and a visual data asset directory is generated. According to the technical scheme, the problems of semantic barriers and islands of data in the building industry are solved.

A computer system for analyzing and mitigating risks associated with an event is provided. The computer system is configured to: (i) receive at least one of a city risk profile and a building risk profile from a database; (ii) receive city systems data from the city services computer system; (iii) utilize a trained machine learning model to determine at least one potential risk associated with the event; (iv) generate an event risk profile that includes the at least one potential risk associated with the event; and / or (v) generate a risk mitigation output based upon at least one of the city risk profile and the at least one potential risk, wherein the risk mitigation output includes at least one of a risk alert, a risk mitigation recommendation, and risk mitigation instructions. Computer systems for analyzing and mitigation risks associated with a city, a building, and a user are also provided.

The invention discloses a method and a system for generating and executing an anti-interference flight strategy of a C2 link of an unmanned aerial vehicle, and particularly relates to the technical field of unmanned aerial vehicle communication. The method comprises the following steps: acquiring urban building material parameters and unmanned aerial vehicle flight parameters; based on the parameters, combining a free space path loss model, a Rice fading model and a blade peak diffraction model to construct an urban environment channel model; injecting same-frequency Wi-Fi interference and building reflection interference signals to calculate a signal to interference plus noise ratio; based on the signal to interference plus noise ratio, calculating the bit error rate and evaluating the anti-interference performance, and generating an anti-interference optimization scheme including frequency band switching and flight height adjustment; and controlling the unmanned aerial vehicle to execute the strategy. Aiming at the problems of Wi-Fi co-frequency interference, building shielding, glass curtain wall multipath reflection and the like in a complex urban environment, frequency band self-adaptive switching and flight height optimization are realized through multi-model joint simulation and dynamic strategy generation, the bit error rate is reduced, the anti-interference capability is improved, and the method has the advantages of being simple in structure and convenient to operate. And the communication reliability and the flight safety of the unmanned aerial vehicle in a complex urban environment are effectively guaranteed.