116 results about "Built environment" patented technology

The invention relates to the technical field of urban rail transit station-city collaborative planning, in particular to an ontology-based station-city collaborative data integration and planning prediction method, which comprises the following steps of: obtaining rail transit station passenger flow data, resident travel behavior data and station periphery built environment index data; forming a space-time sample sequence according to the unified space-time granularity of the site walking service area; constructing an urban rail transit station-city cooperation ontology, and carrying out semantic annotation and semantic fusion on the space-time sample sequence to generate a feature sequence; inputting the feature sequence into a multi-task space-time diagram convolutional neural network prediction model to output a passenger flow prediction result and establish an environment index prediction result; and calculating a feature contribution degree based on a Shapley additive interpretation value, optimizing a background sample set by using a genetic algorithm to determine a key action element set, outputting a planning index threshold and an intervention measure parameter, and realizing an interpretable station-city collaborative prediction and planning decision closed loop.

This invention discloses a full lifecycle management system and method for scientific computing programs. The system includes a build environment subsystem and a production environment subsystem. The former provides computer resources for the build process of the scientific computing program throughout its lifecycle, while the latter provides computer resources for the testing and deployment processes. This invention, through a full lifecycle management method for scientific computing programs, operates on corresponding computing resources, encompassing a series of steps including querying, triggering scheduling, build execution, result distribution, and test deployment. It automatically generates the executable file of the scientific computing program and configures its runtime dependencies. Simultaneously, it automatically generates a corresponding description file recording the entire lifecycle process. Furthermore, based on version management of these description files and their sets, it achieves full lifecycle traceability and cross-platform migration and deployment of scientific computing programs in a high-performance computing environment.

A comprehensive spatial AI platform for neural 3D reconstruction and built environment analysis integrates foundation models, deep learning methods, and spatial reasoning capabilities to provide expert knowledge of the physical world. The platform combines symbolic AI and machine learning to facilitate 3D semantics for insurance, real estate, construction, robotics, and other business applications. The system processes captured images, videos, or point clouds through neural networks with low compute requirements, incorporating device-agnostic advanced spatial intelligence that delivers geometric, semantic, and relational data. The platform includes proprietary training innovations, comprehensive measurement and semantic understanding, external sensor integration, human-in-the-loop quality assurance, and API integration for programmatic access. Advanced spatial reasoning capabilities enable property damage assessments, construction progress tracking, robotics navigation, and real-time applications including room dimension validation and automated repair estimates, supporting enterprise workflows across various industry segments while enabling productivity improvements and new value-added spatial AI use cases.

The invention discloses a college dormitory noise multi-dimensional evaluation method based on psychoacoustic and sound field simulation, and belongs to the field of building environment and noise control. The objective of the invention is to solve the problem that an existing dormitory noise evaluation method is single in index and neglects subjective perception and spatial distribution heterogeneity. The method comprises the following steps: acquiring physical data and original audio of dormitory noise through multi-point synchronous acquisition; calculating loudness, sharpness, roughness, fluctuation intensity and comprehensive psychoacoustic annoyance (PA) by using a psychoacoustic model, and scientifically quantifying subjective interference of noise; meanwhile, sound field simulation is carried out based on the accurately established three-dimensional dormitory model, a sound pressure level distribution cloud picture is generated, and a standing wave phenomenon and a sound energy accumulation area are visually revealed; and finally, generating a targeted noise reduction optimization strategy by integrating subjective and objective and spatial analysis results. According to the method, full-chain diagnosis of physical characteristics-subjective perception-spatial distribution of dormitory noise is realized, and a scientific basis is provided for accurate and efficient noise treatment.

The invention discloses a building air conditioner energy consumption-electric charge-comfort level intelligent control method based on MMOE and ParetoMTL, and the method comprises the following steps: (1) collecting the cooling load data of a large commercial building air conditioner, carrying out the abnormal value detection, and completing the normalization preprocessing; (2) constructing an environment-price-behavior multi-source time sequence data set and performing grading standardization; (3) dividing a training set, a verification set and a test set according to building grouping; (4) completing feature fusion and realizing task decoupling under cooperative constraint by using an MMOE mechanism; (5) jointly training a three-branch expert network, an MLP gating network and a PCGrad shared parameter optimization model; (6) generating a multi-task prediction and Pareto solution set on the test set; and (7) evaluating prediction performance and trade-off efficiency by using a plurality of indexes. According to the method, multi-target conflict, physical consistency and Pareto solution set missing difficulty can be effectively solved, and a new scheme is provided for demand response HVAC intelligent control.

The invention discloses an intelligent fire-fighting hidden danger identification method based on multi-modal fusion, and the method comprises the steps: collecting multi-source heterogeneous data in a building environment, and carrying out the unified processing of the data, and obtaining standardized multi-modal original input data; event anchor point detection is carried out on the multi-modal input, key events are extracted, and a corresponding multi-modal event sequence is generated; constructing an event graph containing time and causal edges, and outputting an alignment event stream by using a space-time coupling causal alignment module; importing BIM and air duct structure information to establish a spatial topological graph, and fusing event streams to generate spatial constraint features; constructing a self-evolution semantic decision map based on the fusion features, and dynamically adjusting node weights and edge connection relationships; and carrying out hidden danger identification and grade division on the real-time data by using the decision map, and outputting an early warning signal and positioning information. According to the method, high-precision identification and intelligent early warning of fire-fighting hidden dangers are realized through space-time causal alignment, spatial topology fusion and self-evolution semantic decision of multi-modal data.

The invention discloses a space-time knowledge graph-based facility layout scheme generation method. The method comprises the steps of S1, constructing an urban facility layout knowledge base; s2, acquiring a reference case place set of the target grid to be optimized; s3, extracting a facility significant co-occurrence mode in the reference case place set, and taking the facility significant co-occurrence mode as a recommended facility configuration mode of the target grid to be optimized; and S4, according to the feature vector of the city built environment of the target to-be-optimized grid obtained in the S1, inputting the feature vector and the recommended facility configuration mode of the target to-be-optimized grid obtained in the S3 into the constructed facility layout generation model, and obtaining an output result which is a facility layout scheme. According to the method, the facility distribution rule knowledge and the facility layout optimization intelligence are integrated, and the facility configuration recommendation and the facility layout optimization scheme can be automatically output for a specific land parcel.

The invention discloses a building environment real-time regulation and control method, device and equipment based on the Internet of Things and a medium, and relates to the technical field of intelligent building control. Light, temperature and humidity data of a building environment are collected in real time through Internet of Things sensing equipment, frequency domain features of an environment data set are extracted through Fourier transform, classification and recognition are carried out in combination with a preset environment regulation and control model, and a dynamic weight algorithm is adopted to optimize and generate an environment control signal. And through a self-adaptive PID control algorithm of Kalman filtering denoising and reinforcement learning optimization, a deviation integral is calculated in real time to generate a precise regulation and control instruction, and environment regulation and control equipment is synchronously driven. Frequency domain feature analysis, dynamic weight adjustment and adaptive control technologies are fused, multi-parameter coordinated regulation and control of the building environment are realized, and the real-time performance, the stability and the energy efficiency ratio of environment regulation and control are effectively improved.

The application provides a kind of intelligent building environment adaptive regulation and control method based on digital twinning and AI, it is related to artificial intelligence technical field, including the following steps: based on time alignment after multi-source system data, extract dynamic characteristics to construct dynamic feature set;Multi-source system data is input to digital twinning, with the current building equipment state as boundary condition, iteratively simulates the key environmental parameters of multiple time steps in the future, and outputs multi-step prediction sequence;Again input model predictive controller, with the minimum overall energy consumption in the prediction period as the optimization goal, with the key environmental parameters not exceeding the comfort interval as the constraint condition, the equipment control instruction sequence in the first preset time in the future is solved;The first equipment control instruction in the equipment control instruction sequence is issued to the on-site actuator to realize the adaptive regulation and control of building environment, solve the disadvantage that the environment parameter is over-standard and then responds passively, significantly improve the rapid response capability of the system to sudden environmental changes.

A comprehensive spatial AI platform for neural 3D reconstruction and built environment analysis integrates foundation models, deep learning methods, and spatial reasoning capabilities to provide expert knowledge of the physical world. The platform combines symbolic AI and machine learning to facilitate 3D semantics for insurance, real estate, construction, robotics, and other business applications. The system processes captured images, videos, or point clouds through neural networks with low compute requirements, incorporating device-agnostic advanced spatial intelligence that delivers geometric, semantic, and relational data. The platform includes proprietary training innovations, comprehensive measurement and semantic understanding, external sensor integration, human-in-the-loop quality assurance, and API integration for programmatic access. Advanced spatial reasoning capabilities enable property damage assessments, construction progress tracking, robotics navigation, and real-time applications including room dimension validation and automated repair estimates, supporting enterprise workflows across various industry segments while enabling productivity improvements and new value-added spatial AI use cases.

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 relates to a thermal exposure risk calculation method based on urban trip people flow and built environment dynamics, and the method comprises the steps: obtaining the average radiation temperature calculation input data of an urban environment, and calculating the average radiation temperature of the urban environment according to the average radiation temperature calculation input data; calculating general thermal climate index distribution of the urban environment based on the average radiation temperature, and determining a thermal exposure time period based on the general thermal climate index distribution so as to obtain thermal exposure duration according to the thermal exposure time period; and acquiring the hourly travel pedestrian flow of the urban environment, counting the accumulated travel pedestrian flow in the thermal exposure time period based on the hourly travel pedestrian flow and the thermal exposure time period, and calculating the thermal exposure risk according to the accumulated travel pedestrian flow. Therefore, the problems that in the related technology, due to dependence on static population data, the people flow dynamic state of urban day and night travel with high temporal-spatial resolution is difficult to reflect, and a thermal risk calculation result based on the static population data cannot meet the requirements of urban space environment exposure refined analysis and early warning are solved.

A mixture includes carbon-coated oil-treated plastic particles and particles that include geomaterial. Treating the soil at a building site includes combining carbon-coated oil-treated plastic particles and geomaterial particles to yield a mixture and providing the mixture in a built environment to enhance soil stability under freezing conditions.

The application discloses a kind of deep learning crowd flow prediction methods of fusion built environment dynamic influence, comprising the following steps: S1, data acquisition and processing;S2, built environment dynamic influence modeling, the extraction of built environment dynamic influence effect is carried out;S3, construct spatiotemporal graph neural network fusion model;S4, the evaluation of model performance and the diagnosis of error are carried out;S5, output multi-time scale people flow prediction by spatiotemporal graph neural network fusion model.According to the present application, higher precision, stronger interpretability, crowd activity prediction can be adapted to multiple regions and multiple time periods.

This invention belongs to the field of fan control technology. It provides a laboratory exhaust gas-induced high-altitude jet fan control system, comprising: a multi-source data acquisition module for real-time acquisition of multi-dimensional time-series data related to laboratory exhaust gas emission safety, including fan operating parameters, building environment parameters, exhaust gas source equipment status parameters, and meteorological environment parameters; and a predictive maintenance and early warning module based on the multi-dimensional time-series data. By integrating multi-source data perception, chronic risk trend prediction, system vulnerability assessment based on digital twins, and graded resilience control strategies, a closed loop of "perception-prediction-assessment-decision-execution" is constructed. This achieves early identification, proactive early warning, and adaptive control of coupled risks between "equipment-building-environment-personnel," thereby enhancing the proactive safety capability to prevent toxic exhaust gases from entering the breathing zone of personnel.

Design and applications of a class of water-soluble small molecules represented by formula 1. The molecules, in their dilute aqueous solutions, exhibit lower critical solution temperature (LCST) phase transitions near room temperature, inducing a temperature triggered switching of opacity. Further, disclosed is a scalable smart window, akin to a radiative energy management system, that can be incorporated into the built environment for imparting energy efficiency. The window fabrication is facile wherein the aqueous solution is sandwiched between two transparent glass panes to enable modulation of light and heat transmission. The dynamic window of present invention represents with multifarious applications in developing scalable, smart energy management systems for indoor building environments is envisioned to be a major contribution towards cost effective smart glass technologies.

The invention provides an intelligent building inspection method and system based on wheel-foot combination and mechanical arm cooperation, and the method comprises the steps: constructing a mobile operation platform integrating a wheel-foot chassis and a six-degree-of-freedom mechanical arm, and collecting the environment and body state data of a building through a multi-mode sensor group; inputting the data into an edge calculation module, constructing a three-dimensional semantic map based on a multi-sensor fusion algorithm, and resolving a six-degree-of-freedom real-time pose; generating an optimal path covering a cross-layer area and a local dynamic obstacle avoidance strategy according to the inspection task; a moving posture closed-loop regulation and control mechanism is adopted, the chassis torque and the mechanical arm posture are cooperatively calculated based on model predictive control and a whole-body dynamics algorithm, and motion disturbance is compensated; and the target equipment state is recognized based on the visual language model, the mechanical arm is scheduled to execute refined operation, and end cloud data interaction is achieved. Through deep integration of software and hardware, the problems of poor cross-layer trafficability and lack of cooperation of dynamic and static operations in the prior art are solved.

The invention discloses a residential building intelligent ventilation control method, system and device based on health requirements and natural ventilation potential and a storage medium, and relates to the technical field of building environment and energy conservation, and the method comprises the steps: determining the minimum ventilation quantity of the health requirements of a target control region based on the dosage-reaction relation between the ventilation quantity and regional population health; collecting the real-time natural ventilation quantity of the target control area; according to the minimum ventilation quantity and the real-time natural ventilation quantity required by health, whether a mechanical ventilation system needs to be started or not is judged; and controlling the mechanical ventilation system to operate according to the optimal intermittent operation control strategy. According to the method, the health demand ventilation target is set based on the dose-reaction relationship between the ventilation quantity and the human health, and compared with control based on single pollutant concentration, the method can more comprehensively reflect the human health demand. The optimal intermittent operation strategy of the mechanical ventilation system is determined through a multi-objective optimization algorithm, the health risk and energy consumption are balanced, and energy-saving and efficient ventilation control is achieved.

This invention discloses a method for assessing the resilience of subway travel behavior during rainstorms, taking into account the impact of the built environment. It belongs to the field of urban transportation resilience assessment. The specific steps include: S1, collecting subway travel data, meteorological data, and built environment data around subway stations under rainstorm and ideal weather conditions; S2, quantifying the resilience value of subway travel behavior using the resilience triangle method; S3, constructing a spatially weighted geographic random forest model, using built environment data as features and resilience value as the objective, establishing a nonlinear mapping relationship between the two, and outputting the spatial distribution characteristics of resilience; S4, using the model to analyze the marginal contribution of each built environment factor to the resilience value, outputting the feature importance ranking, and identifying key built environment factors. This invention can quantify the disturbance and recovery capacity of subway travel behavior during rainstorms, reveal the mechanism by which the built environment affects travel behavior resilience, and provide a scientific basis for urban transportation resilience planning and rainstorm emergency management.

The invention discloses a multi-area linkage fresh air handling unit cooperative control system and method, and relates to the technical field of building environment control, and the auxiliary method comprises the specific steps that a multi-source data real-time collection module collects and transmits multiple types of data through distributed equipment; the data fusion processing module cleans and fuses the data to form a structured data set; the intelligent scene analysis and game modeling module identifies scenes, evaluates requirements, detects conflicts and quantifies utility values; the control mode decision module determines an optimal mode and parameters; the execution regulation and control module adjusts parameters, executes operation and feeds back data to form a closed loop; a multi-source data acquisition fusion framework is constructed, traditional limitation is broken through, an intelligent module automatically recognizes scenes, quantifies requirements, detects conflicts and optimizes resource allocation, meanwhile, full-process automation is achieved through closed-loop design, control economy is ensured through an algorithm, airflow interaction is optimized, energy consumption is reduced, energy efficiency and comfort are improved, and the method is suitable for large-scale popularization and application. And technical support is provided for efficient operation of green buildings.

The invention provides an environment-friendly water-based paint for buildings and a processing method thereof. The environment-friendly water-based paint comprises the following components: 40-60 parts of an elastic grafted hydrophobic emulsion, 5-10 parts of a low-temperature activated cross-linking agent, 3-8 parts of corrosion inhibitor microcapsules, 15-25 parts of pigments and fillers, 1-3 parts of a dispersing agent, 0.5-2 parts of a wetting agent, 0.3-1 part of a defoaming agent, 0.5-2 parts of a thickening agent, 1-4 parts of a coalescing agent and 10-20 parts of deionized water. The low-temperature activated modified isocyanate cross-linking agent is adopted, the activation temperature is low, rapid cross-linking curing can be achieved at the temperature of about 5 DEG C, the film forming time is greatly shortened, meanwhile, the modified cross-linking agent is good in compatibility with elastic grafted hydrophobic emulsion, the cross-linking density of a coating is improved, the adhesive force of the coating and a base material reaches the first level, and the coating is not prone to falling off. The coating is prevented from falling off and cracking in a low-temperature and high-humidity environment

The application relates to the technical field of building environment analysis, and discloses a building internal environment analysis method, device, equipment and medium, which comprises the following steps: constructing a three-dimensional geometric model of a target building interior; determining temperature-related data, speed-related data and material-related data of the target building interior; determining temperature boundary conditions according to the temperature-related data, determining speed boundary conditions according to the speed-related data, and determining material boundary conditions according to the material-related data; inputting the temperature boundary conditions, the speed boundary conditions and the material boundary conditions into a fluid simulation solver; and the fluid simulation solver couplingly calculates a preset iteration number of a temperature transport equation, a scalar transport equation of speed and a scalar transport equation of material to obtain temperature distribution data, airflow speed and material distribution data of the target building. The distribution data is real-time flow, and the application is more applicable.

The application discloses an indoor distribution cable path intelligent generation method combined with building environment characteristics, and comprises the following steps: constructing a semantic grid map capable of distinguishing different building function areas by performing layer identification, semantic annotation and space discretization on an input building plan design map; based on the semantic grid map, different basic passing generation values are given to different types of areas, and a dynamic engineering constraint function comprising a corner turning penalty and a wall sticking reward rule is defined; path search of an improved A* algorithm is performed, in an engineering constraint cost field fused with the basic passing generation value and the dynamic engineering constraint function, a heuristic search algorithm with a dynamic penalty term is used to calculate and generate a candidate cable path meeting engineering specifications; virtual convergence points are determined through node clustering, the path search algorithm is applied hierarchically, a backbone path limited in a public area is generated, branch paths entering rooms are generated, and a complete indoor distribution system cable path topology is generated by merging.

This invention discloses a method for identifying the suitable range of built environment features based on interpretable machine learning, comprising the following steps: S1, acquiring built environment data and preprocessing the data; S2, constructing and training a machine learning model; S3, extracting suitable intervals and identifying thresholds using the machine learning model; wherein, step S3 specifically includes the following steps: S31, performing interpretability analysis and main effect extraction using SHAP; S32, plotting fitting curves between built environment factors and target variables; S33, identifying the preliminary suitable range of built environment factors; S34, outputting the final suitable range of built environment factors; S35, performing difference identification analysis between actual built environment values ​​and suitable ranges. According to this invention, more accurate, interpretable, and people-oriented optimization of the urban built environment can be achieved.

This invention relates to the field of building environment, specifically disclosing an IoT-based building environment monitoring system. The system includes modules for data acquisition, constraint construction, data fusion, analysis model establishment, spatiotemporal variation verification and optimization, and environmental parameter evaluation. The data acquisition module establishes a three-dimensional coordinate system for the building and uses full-volume data. The constraint construction module preprocesses the data, calculates the spatial variation coefficient, temporal variation coefficient, and data fusion degree, and sets thresholds. The data fusion module extracts spatiotemporal features for multi-source fusion and outputs a standardized dataset. The analysis model establishment module outputs identification results through multi-dimensional analysis. The spatiotemporal variation verification and optimization module optimizes the identification results through multi-dimensional verification. The environmental parameter evaluation module calculates the deviation and comprehensive health index, and outputs tiered early warnings. This invention achieves three-dimensional dynamic monitoring, captures multi-parameter nonlinear coupling, and employs adaptive optimization strategies to improve evaluation accuracy.

The application provides a kind of operation data analysis method and system of heating system, it is related to building environment and energy application engineering technical field, the method includes: if diagnosis result is no exception, based on the building historical room temperature in multi-source fusion data set, building characteristics and real-time meteorological parameters, generate different operation strategy;Obtain the meteorological prediction data of preset time period;Based on the different operation strategy and meteorological prediction data, the change of heat load demand is predicted by long short-term memory network;Based on the change of heat load demand, with room temperature standard and minimum energy consumption as optimization goal, the target output parameter set value is calculated, and the set value is sent to the boiler control system to execute.The application realizes closed-loop intelligent operation from abnormal accurate diagnosis to demand prediction regulation through multi-source data fusion and real-time analysis, so as to comprehensively improve the reliability, energy efficiency and comfort of heating system.

A cleaning optimization system 100 to detect, analyse and clean surface contaminants from a cleaning site on the surface of a built environment. The system comprises: a tracking unit 102 to identify

The invention discloses a building environment self-adaptive regulation and control method and system based on a space-time attention mechanism, and the method comprises the steps: collecting environment data, such as temperature, flow density, humidity and air pressure, and constructing a three-dimensional thermodynamic model through a dynamic weighted Bayesian collaborative fusion algorithm; the method comprises the following steps: processing environment data by virtue of a space-time cross attention network, and generating a regulation and control priority map with a dynamic space-time weight through operations of dynamic multi-feature embedding, parallel space-time self-attention, cross attention fusion and the like; and the fuzzy-PMV decision engine fuzzifies the atlas and PMV comfort indexes, outputs an equipment regulation and control instruction set through expert rule matching and defuzzification, and realizes closed-loop control from environmental data to equipment actions. Compared with the prior art, the method can accurately analyze the space-time correlation of building environment parameters, adaptively regulate and control equipment, improve the environment comfort and regulation and control efficiency, has the advantages of energy conservation and intelligence, and is suitable for the field of intelligent building environment control.

The utility model relates to the field of building environment engineering, in particular to an energy recovery type radiation pipeline. According to the energy recovery type radiation pipeline, heat in smoke can be recovered through water flow, resource waste is reduced, and the energy utilization efficiency is improved. An energy recovery type radiation pipeline comprises a gas pipeline, a valve, a radiation pipeline, an air inlet pipe and the like, the right side of the gas pipeline is connected with the valve, the right side of the valve is connected with the radiation pipeline, and the rear side of the left portion of the radiation pipeline is connected with the air inlet pipe. The water inlet pipe is externally connected with a water conveying pipeline, so that cold water enters the sleeve, the outer side of the air outlet pipe is filled with the cold water, heat in flue gas is absorbed through the cold water, water absorbing the heat is discharged through the water outlet pipe to be recycled, the heat in the flue gas can be recycled through water flow, resource waste is reduced, and the environment is protected. And the energy utilization efficiency is improved.

The invention discloses a built environment crowd perception space mapping and quantitative evaluation method oriented to an urban green land scene. The method comprises the following steps: acquiring and processing multi-source heterogeneous data; carrying out recreation perception semantic mining and quantification on the social media comment text, and constructing perception scores for different ecosystem culture service types; mapping the perception score space to geographic grid units based on semantic association, and calculating an accumulated perception index of each unit by adopting a differential weight distribution algorithm according to spatial scale characteristics; extracting built environment characteristics of each grid unit; and training a machine learning model based on the accumulated perception indexes and the built environment features, establishing a mapping relation between the accumulated perception indexes and the built environment features, and performing perception index deduction on the blank area by using the model to generate global CES perception distribution. According to the method, fine spatial mapping of coordinate-free texts is realized, a perception prediction model based on environmental characteristics is established, and data-driven decision support is provided for fine design and management of a green land.