44 results about "Urban building" patented technology

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 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.

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 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.

This invention belongs to the field of risk prediction technology for mountainous cities, and discloses a CNN-based method for quantifying and predicting landslide susceptibility in mountainous cities by integrating multi-source data. The specific steps are as follows: Step 1: Multi-source data collection and processing, collecting remote sensing image data, geological data, topographic data, and building data. This invention achieves deep fusion of multi-source data by integrating remote sensing images, geological maps, topographic data, building distribution, and other multi-dimensional data; it automatically extracts deep features from the data through the convolutional and pooling layers of CNN, eliminating the need for manual feature design and improving feature extraction capabilities; through the construction of a CNN model that integrates heterogeneous data fusion and multi-source data fusion, it can directly capture spatial neighborhood relationships, improving spatial correlation; compared with traditional techniques, this method significantly improves the accuracy and robustness of landslide susceptibility prediction in complex mountainous cities through multi-source data complementarity and deep feature extraction.

The application discloses a kind of urban multiscale wind field fast prediction method based on geometric driving neural operator.Firstly, the high-fidelity expression of urban building geometry is carried out using signed distance field (SDF).By extracting multi-scale global geometry code, the input features of the query point containing local geometric features, position information and signed distance field are constructed, and the complex global wind field prediction is transformed into efficient local problem solving.The trained model can directly predict the wind speed amplitude and turbulent kinetic energy of any point in space according to the input building geometry data, and then reconstruct the continuous flow field distribution.The method realizes the decoupling of computational complexity and spatial resolution, has high precision and second-level reasoning speed, can capture building detail flow and street scale wake characteristics, and significantly improves the generalization ability and engineering application value in large-scale complex urban environment.

This invention belongs to the field of smart city information technology, specifically involving a closed-loop management method for the lifecycle risk of smart city building safety using a digital twin. Specifically, it includes constructing a dynamic mapping model of the building's full lifecycle digital twin, designing a core system encompassing full lifecycle data fusion algorithms, virtual-real linkage risk evolution, and closed-loop management iterative optimization. Through digital twin modeling, full-cycle fusion, virtual-real linkage, and closed-loop iteration, it achieves precise management of building safety risks throughout its entire lifecycle, from design, construction, operation and maintenance to decommissioning.

This invention discloses a method, apparatus, and computer equipment for extracting buildings in complex building areas. The method includes acquiring remote sensing images of the buildings to be extracted; inputting the remote sensing images into an AFL U-Net model and converting them into vector-form roof data; wherein the model training process includes: collecting and processing high-resolution remote sensing images and Sentinel-2 satellite images, resampling them to a uniform resolution, and calculating the urban building index; using an extended spatial particle swarm optimization algorithm to perform optimized sampling and select representative samples; using the representative samples, training the U-Net model through an improved Focal_Loss loss function parameter self-prediction mechanism to optimize the learning efficiency for difficult-to-classify samples, thus forming the AFL U-Net model. By implementing the method of this invention, the loss function parameters can be adaptively predicted, optimizing the model's focus on difficult-to-classify samples and improving the overall accuracy of building extraction.

The application provides a hydrodynamic grid construction method and device for urban buildings and multi-source data, and belongs to the technical field of hydrodynamic grid construction. In the process of hydrodynamic grid construction, the method can achieve fine delineation of micro-landforms and boundaries of buildings in the city, improves the generalization of the hydrodynamic grid for the actual ground object categories and terrain features of the city, and further improves the effect of urban flood simulation by the hydrodynamic grid, which is helpful for urban flood control and drainage planning and emergency management.

The utility model discloses a kind of recycling devices for urban construction aggregate regeneration, including pulverization box, the top of the outer surface of the pulverization box is fixedly provided with feed passage, conveying frame is fixedly installed in the inside of feed passage, the one side of conveying frame is fixedly installed with feeding mechanism, the surface of feed passage is fixedly installed with closure mechanism, the outer surface of the pulverization box is fixedly installed with B servo motor.The recycling device for urban construction aggregate regeneration, by the setting of feeding mechanism and closure mechanism, building aggregate is put on the conveyor belt, external power supply is connected, hydraulic rod is opened, and the closure plate is opened, the A servo motor drives the conveyor belt to rotate, and the building aggregate is conveyed into the pulverization box through the feed passage, so that the effect of facilitating feeding is achieved, and after feeding is completed, the closure plate closes the feed passage, so that the pulverization of the building aggregate is carried out in the closed pulverization box, dust can be prevented, and environmental pollution can be avoided.

This invention relates to an experimental method and apparatus for simulating deep karst collapse induced by overloading of dense building complexes. The apparatus includes: a model test chamber for placing test soil; a karst channel mechanism with karst channels of different sizes distributed throughout; a loading mechanism for simulating the application of loads to dense urban building complexes and soil consolidation; an intelligent display mechanism; an image acquisition mechanism for observing changes in the overlying soil layer and the underlying karst channels during the loading process; a data analysis mechanism; a karst collapse soil collection mechanism for collecting collapsed soil; and a support mechanism for providing reaction forces to balance the applied load. Compared with existing technologies, this invention can provide technical support for studying deep karst collapse induced by static overloading of dense urban building complexes, reveal the mechanism of deep karst collapse under static overloading of dense urban building complexes, determine the critical disaster-causing and destructive conditions of deep urban karst collapse, and provide reference value for the treatment and prevention of deep urban karst collapse.

The present application relates to the technical field of unmanned aerial vehicle inspection and urban lighting operation and maintenance, in particular to a city building light belt anomaly identification method based on unmanned aerial vehicle vision, comprising the following steps: unmanned aerial vehicle image acquisition, image preprocessing, light emitting area identification, light belt segmentation identification, light belt structure template construction, template matching and calibration, and light belt loss determination. The city building light belt anomaly identification method based on unmanned aerial vehicle vision can automatically identify the light belt loss area; the structure template is introduced to reduce false detection and missed detection; it is suitable for various building facades and light belt arrangement forms; it is suitable for large-scale urban night scene lighting inspection; and the artificial inspection cost and safety risk are significantly reduced.

This invention discloses a remote sensing interpretation method for complex urban buildings based on human-machine collaboration, belonging to the field of remote sensing information technology. The method includes: receiving remote sensing interpretation requirements input by a user; obtaining analytical results based on a pre-constructed professional domain-adapted interpretation model for complex urban buildings; detecting the user's selection of a specific interpretation mode option when inputting the remote sensing interpretation requirements; determining the current remote sensing interpretation type based on the selection result; inputting the analytical results into a professional domain interpretation resource library for complex urban buildings that is compatible with the current remote sensing interpretation type for feature matching; and outputting accurate remote sensing interpretation results associated with the analytical results. This invention analyzes the user's accuracy requirements through mode options, calls a professional domain interpretation resource library containing building planning standards and material spectral characteristics for feature matching, and achieves accurate interpretation in complex scenarios based on professional data.

This invention pertains to computational fluid dynamics and machine learning technologies, specifically a physical mechanism-guided heterogeneous extrapolation method for high-resolution, meter-level dynamic fields of urban buildings. The method includes the following steps: selecting representative urban blocks to form a sample block set; using a WRF model to provide a regional-scale meteorological background field for the target city; driving a LES model to perform flow field calculations on the sample block set, generating high spatiotemporal resolution flow field data for the sample blocks, and pairing this data with corresponding meteorological background data to generate a training database; constructing and training a deep learning model for latent space injection of meteorological information, establishing an end-to-end nonlinear mapping relationship from the coupling characteristics of urban geometry and meteorological boundaries to the LES fine flow field through a dual-path encoding path and latent space injection mechanism; and dividing the target urban area into multiple local computational units to extrapolate the high-resolution dynamic field of the entire urban area. This invention balances computational efficiency, prediction accuracy, and physical consistency, enabling rapid response to urban dynamic fields.

The present application relates to the field of energy simulation, and discloses a method and device for predicting urban building energy consumption, electronic equipment and medium. The method comprises: reconstructing each component in the urban climate state of the previous time step by mapping to determine the building boundary state; determining the energy consumption state quantity of the building according to the building boundary state; updating the urban climate state of the current time step according to the energy consumption state quantity, thereby predicting the urban building energy consumption of each time step. The present application can accurately depict the evolution law of urban building energy consumption under future climate change scenarios.

The present application relates to the technical field of risk prevention and control, and particularly relates to a city building safety risk intelligent prevention and control method, a platform and an electronic device, the method comprising the following steps: determining an interference radius according to structure data of a target region, dividing a spatial interference region with the interference radius, constructing a construction interference index, a geological interference index and a dust interference index of each spatial interference region, and performing hierarchical updating on the spatial interference region; collecting regional normal data in each spatial interference region, and constructing a risk index of the spatial interference region with the regional normal data; then determining a cross-domain risk coupling coefficient of each spatial interference region with the risk index of each spatial interference region, dividing the risk levels of each spatial interference region, establishing a risk point map of the target region with the cross-domain risk coupling coefficient of the target region, and performing risk alarm on the target region. The present application effectively improves the efficiency and accuracy of city risk alarm.

This invention discloses a multi-channel SAR moving target detection method and apparatus for complex urban scenarios, belonging to the field of synthetic aperture radar technology. The method addresses the problems of high false alarm rate and poor ATI phase reliability in traditional DPCA detection caused by strong scatterers in densely built-up urban areas. First, it performs registration and equalization preprocessing on the two-channel complex images. Then, it performs track-based interferometry and constructs a high-coherence mask using a coherence coefficient map to constrain the interferometric phase and eliminate low-reliability phases. Next, it constructs a weight function using the constrained interferometric phase to weight and fuse the DPCA differential amplitude results, enhancing the response of real moving targets and suppressing strong clutter residues. Finally, it performs constant false alarm rate detection on the weighted results, achieving robust detection of moving targets. This invention effectively solves the problem of high false alarm rate in moving target detection under complex urban backgrounds and significantly improves detection reliability.

The present invention refers to a Daytime Radiative Cooling Cementitious composite includingan OPC binder in the form of grains, with an amount of Fe2O3 lower than 0.05% by weight with respect to the total weight of the OPC binder, wherein the grain size is below 25 μm,water, wherein the weight ratio between water and the OPC binder is between 0.2 to 0.6,an addition in a proportion between 0.1% and 50% by weight with respect to the weight of the OPC binderand wherein the resulting DRCCC has a pore size below 6 μm as defined by mercury intrusion porosimetry, that can optionally comprise micropatterns, and to its use in the construction industry, such as building construction, in civil works such as reservoirs, bridges, dams and sewers, in solar cell technology or in urban architectural design.

This invention relates to the field of 3D modeling technology, specifically to a method and system for constructing 3D urban buildings for visualization. The method includes the following steps: extracting component outline coordinates, identifying directional changes to generate configuration groups, determining vertical relationships to generate structural chains, identifying repetitive features to construct style codes, extracting similar building relationships to generate meshes, and identifying facade boundaries to establish texture mapping relationship groups. In this invention, by extracting building outline nodes and boundary features, structured shape information is constructed, improving geometric analysis accuracy. Overlay chains are established based on the vertical arrangement relationship and spatial scale of components, achieving automatic restoration of structural levels. Repetitive pattern recognition and style classification enhance style recognition capabilities and batch assignment efficiency. Combined with spatial distribution relationships, regional structural expression is optimized. Facade partitions and attachment boundaries are extracted, and texture correspondence is established, improving facade visual consistency and expression accuracy. The overall process enhances modeling accuracy, structural logic, and result reusability.

The application discloses a kind of city building high-fidelity three-dimensional reconstruction methods of air-ground multi-source data fusion, it is related to three-dimensional geographic information and point cloud processing technical field, city building high-fidelity three-dimensional reconstruction methods of air-ground multi-source data fusion mainly includes: through ground mobile equipment collection generation building facade fine point cloud, and it is accurately registered with the air point cloud obtained by unmanned aerial vehicle;Finally, based on the Gaussian sputtering technology of air-ground multi-source data, realize the high-fidelity reconstruction of building model from geometry to appearance.The air-ground multi-source data fusion city building high-fidelity three-dimensional reconstruction method provided by the application can improve the point cloud precision, the integrity of model and reconstruction fidelity.

The application belongs to the technical field of energy management, and discloses a building resistance-capacitance model parameter order-of-magnitude estimation method and system, which comprises the following steps: clustering and constructing a building geometric size dataset for the obtained urban building contour information dataset; simulating each type of building according to the clustering results and the geometric size dataset to obtain training data of the corresponding electrical equivalent resistance-capacitance (RC) model; setting a parameter order-of-magnitude range according to the training data, performing three rounds of iterative screening on the parameter order-of-magnitude in the parameter order-of-magnitude range based on a genetic algorithm, and obtaining a parameter order-of-magnitude combination corresponding to each type of building; constructing an RC model parameter order-of-magnitude prediction model based on the parameter order-of-magnitude combination; inputting the geometric information of a target building into the parameter order-of-magnitude prediction model that has completed optimization verification, and outputting a target parameter order-of-magnitude of the RC model corresponding to the target building; and the application can quickly obtain the parameter order-of-magnitude of the electrical equivalent resistance-capacitance model corresponding to the target building.

This application relates to a parametric generation method and system for the three-dimensional spatial form of urban buildings, belonging to the field of urban planning technology. The method includes: inputting a target spatial range and building layout parameters; generating building layout areas using a polygon segmentation algorithm; obtaining the two-dimensional base surface of the building to be generated using a maximum inscribed rectangle and orientation algorithm; obtaining building spacing buffers using a buffer algorithm; S5, obtaining the available remaining spatial range using a nine-intersection model algorithm; S6, repeatedly iterating the remaining spatial range to generate a set of all two-dimensional base surfaces of the buildings; performing three-dimensional extrusion on each surface of the set to generate a primary building model at LOD1 level; generating the three-dimensional geometry of the roof of each primary building model to obtain a building model at LOD2 level; applying textures and materials to the building model to obtain a building model at LOD3 level; and exporting the building model into a general three-dimensional model format. This application, through parameter-driven and intelligent iteration, can quickly generate three-dimensional building layouts and models that meet the requirements of the latest planning regulations.

The application discloses a kind of inflatable tornado power generation tower integrated turbine steady flow generator power generation device and method, adopt double-layer air-tight flexible inflatable tower body, with annular inflatable reinforcing rib and independent reinforcing inflatable column, improve structural stability;Hot source air inlet is additionally provided with automatic telescopic wind board, realizes efficient wind gathering and wind control;Variable-frequency wind-driven dual-purpose integrated machine is installed at top, and turbine steady flow power generation component is matched at bottom, can utilize industrial waste heat, agricultural greenhouse waste heat and high-rise building air conditioner outdoor unit waste heat and wind energy power generation.The device has the characteristics of active vortex generation, intelligent current stabilization, double power generation and folding portability, can be deployed in multiple scenarios, can still generate power stably and efficiently in weak heat source environment, effectively recycles waste heat wind energy, is suitable for distributed energy, near-zero energy consumption building, urban building energy saving and other fields, has outstanding novelty, creativity and practicality.

The method relates to the technical field of building simulation analysis, and particularly relates to a comprehensive evaluation method and apparatus for integrated urban buildings. The method comprises: acquiring building operational status information of each building region in integrated urban buildings to be evaluated; for each building region, performing dimensional partitioning on corresponding building operational status information thereof to obtain a plurality of feature sets of the building region; performing situational analysis on each feature set of the building region to obtain a basic operational feature subset and a dynamic operational feature subset that correspond to the feature set of the building region; and inputting the basic operational feature subset and the dynamic operational feature subset into a building region feature evaluation model to obtain a building region feature evaluation score corresponding to the feature set of the building region. The method can provide comprehensive evaluation of multi-dimensional characteristics of a building, can reflect changes in the operational status and performance of the building in a timely manner, thereby providing a more accurate evaluation result.

The application discloses a city construction waste intelligent cleaning and transporting scheduling method and system based on Internet of Things, and contents include construction of basic construction waste data set, waste generation demand prediction, task allocation and cleaning and transporting scheduling. The application relates to the technical field of city construction waste intelligent management, and particularly relates to a city construction waste intelligent cleaning and transporting scheduling method and system based on Internet of Things. Through trend decomposition, multi-scale time sequence coding and full-load time prediction, the scheme combines road traffic states to construct cleaning and transporting urgency, and improves the accuracy and foresight of demand identification. Then, task allocation is performed according to demand intensity, vehicle position, load and regional pressure, and the optimization result is repaired through constraint to reduce repeated vehicle dispatching. Finally, a cleaning and transporting path is generated according to scheduling priority, and re-scheduling is triggered in combination with real-time states to enhance the real-time performance, adaptability and executability of the cleaning and transporting process.

This invention discloses an online monitoring and early warning management system and method for the health status of urban building structures, relating to the field of building structure health monitoring technology. It includes a building structure acquisition module, a building data analysis module, a structural analysis module, and an early warning management module. The system collects building structure data, environmental data, and operational status data to form time-series data; it performs joint analysis of current and historical data to identify data drift points and calculate drift differences; it assesses building health status through drift compensation and an isolated forest anomaly detection model; it integrates health status levels, trend coefficients, and drift differences for comprehensive risk assessment to determine early warning levels; and it classifies structural units into safety point categories based on risk propagation values ​​and evolution rates, establishing a safe passage network and dynamically planning optimal evacuation paths. This invention achieves effective compensation for data drift and accurate identification of structural anomalies, improving early warning accuracy and emergency response capabilities.

The application discloses an unmanned aerial vehicle (UAV)-based city building fire hazard identification method, and belongs to the technical field of intelligent fire fighting, wherein a three-dimensional model of a city building is used to generate an autonomous cruise route, an UAV is controlled to fly and simultaneously collect visible light and infrared multi-modal images, a space geographic coordinate label is added in combination with an RTK positioning module, and the images are input into a fire hazard identification model pre-trained by a time-varying fuzzy intelligent optimization algorithm to output hazard information, so that the identification precision and robustness of the model for a complex fuzzy scene are significantly improved; subsequently, hazards are mapped into a three-dimensional model according to the space geographic coordinate label to generate a stereoscopic visual report, hovering and rephotographing are triggered when high-risk hazards or abnormally high temperatures are identified, and an alarm is pushed in real time, so that high-precision, dead-angle-free and space-visualized intelligent investigation and dynamic response of fire hazards are realized.

This invention discloses a method, apparatus, and equipment for building a database and analyzing the current status of urban existing space data, belonging to the field of urban spatial information management technology. The method includes the following steps: collecting multi-source basic data of the target city; standardizing the format, attribute fields, and spatial benchmarks of the multi-source basic data, and performing spatial trimming to form a basic data base; constructing an urban building information database by integrating building foundation data and building attribute information; spatially associating the urban building information database with spatial units based on land parcels, and calculating evaluation indicators by combining population, land use, industry, and planning approval data to construct an urban existing space status assessment database; comprehensively evaluating and analyzing the evaluation indicators, and outputting the urban existing space status assessment results. This invention achieves multi-dimensional assessment of urban development intensity, spatial structure, and service accessibility, which is helpful for tapping the potential of urban existing space resources, renovating and upgrading, and making planning decisions.