679results about "Virtual/augmented reality" patented technology

This invention provides a comprehensive maritime shipbroking platform uniting digital twin modeling, AI-driven cargo allocation, blockchain-based contract management, predictive maintenance (AR / VR), route optimization, real-time tracking, and single-window compliance. The digital twin engine continuously simulates vessel performance, enabling data-driven decisions on stowage, scheduling, and maintenance. A cargo-freight matching module optimally allocates shipments, factoring in market rates, vessel metrics, and port congestion. Blockchain-secured smart contracts automate negotiations, ensuring transparency and tamper-proof enforcement. A predictive maintenance system applies advanced analytics to diagnose technical issues early, while the route optimization engine finds cost-effective, emission-compliant routes. Real-time tracking gives stakeholders constant visibility, and the single-window interface integrates Electronic Bill of Lading processes, satisfying IMO and IG P&I standards. Additionally, a dynamic vessel ranking system incorporates SIRE, RightShip, PSC, and user feedback for safer, more efficient chartering decisions. The invention addresses day-to-day operational challenges in maritime logistics, elevating efficiency and compliance.

The invention provides a multi-mode tailing pond dam break digital twinning emergency deduction and decision optimization method, which comprises the following steps of: firstly, constructing a high-precision three-dimensional scene model, performing simulation calculation on the high-precision three-dimensional tailing pond model based on a finite element model to obtain a dam body stress-strain field, and performing simulation calculation on the dam body stress-strain field based on ANSYS + reinforcement learning. And predicting a dam break probability distribution diagram by using the dam body stress-strain field and the current environment state, generating a rescue scheduling scheme based on the dam break probability distribution diagram and the resource distribution data, building a dynamic virtual deduction scene for exercise, and verifying and optimizing the rescue scheduling scheme according to exercise record data. And a final rescue scheduling scheme is obtained. According to the method, the ANSYS + reinforcement learning hybrid engine is utilized to reinforce the deduction precision, dam break path prediction, optimal resource scheduling and plan self-optimization closed loop are realized, the problems of data fusion distortion, deduction stiffness, decision lag and the like in the traditional technology are solved, and the method is particularly suitable for variable working conditions such as tailing pond seepage field sudden change and extreme weather.

The invention belongs to the field of digital delivery, and particularly relates to a digital delivery topology mapping method and system for multi-source real-time data fusion, and the method comprises the steps: obtaining factory building distribution, equipment distribution and operation control logic and preset function block operation logic, and constructing a hierarchical clustering function mapping space through combining an association analysis and clustering algorithm; in response to a target function demand, obtaining a layered response mapping path in combination with a deep search algorithm; layered synchronous response and distributed node anomaly monitoring are realized based on the path, the three-dimensional simulation model and the display system equipment performance and the network state. Tracing abnormities based on a monitoring result in combination with a hidden Markov algorithm and a forward reasoning model, performing iterative verification after conflict resolution until the function is free of abnormities, and updating a mapping space; and adjusting the demand repeating steps to obtain a complete and updated mapping space, and realizing accurate function and picture collaboration under multi-source data fusion.

The invention discloses an intelligent equipment management method and system based on digital twinning. The method comprises the following steps: constructing an initial digital twinning model based on a multi-source data fusion result; monitoring the operation state of the initial model in real time and collecting feedback data; based on difference analysis of feedback data and a fusion result, evaluating a model deviation degree; and iteratively correcting the parameters of the digital twinborn model according to the deviation degree to optimize the precision. The method can solve the problem of how to carry out iterative correction on the model precision according to the multi-source data fusion result so as to solve the problem of overlarge deviation of the digital twinborn model.

The invention discloses an intelligent construction method, system, equipment and medium based on a digital twin tunnel, and aims to construct a high-precision physical entity model by fusing dynamic and static data in real time through multiple types of sensors so as to improve data acquisition comprehensiveness; based on tunnel-level, soil-level and ground building-level multi-level modeling and finite element analysis, fine mechanical stability simulation is realized; multi-dimensional data features are extracted by combining a convolutional neural network algorithm, security risks are evaluated, and a reinforcement scheme is optimized through dynamic iteration; a closed-loop regulation and control mechanism of data monitoring, numerical simulation and dynamic feedback is formed by utilizing a collaborative architecture of a sensing layer, a simulation layer and a display layer, so that environmental disturbance is effectively reduced, and construction safety is guaranteed; according to the method, digital twinning, BIM, finite element analysis and deep learning are fused, real-time monitoring and intelligent optimization of the whole construction process are achieved, efficiency and safety are remarkably improved, and influences on the surrounding environment are reduced.

The invention discloses a failure restoration retreatment decision-making method based on dynamic occlusion analysis, and the method comprises the steps: constructing a four-dimensional virtual biomechanical model which comprises a patient anatomical structure and a dynamic function through multi-modal data fusion, and enabling the model to be embedded into a real three-dimensional mandibular movement track of a patient to simulate functional movement, thereby breaking through a static analysis blind area, and achieving the real three-dimensional mandibular movement of the patient. The missed diagnosis rate of dynamic interference is reduced; based on quantitative indexes and thresholds such as occlusal contact displacement, occlusal contact distribution symmetry and adjustment quantity of the maximum tooth tip staggering position and the median relation position, experience judgment of doctors is replaced, objectivity, repeatability and accuracy of failure repair and retreatment decision are improved, and excessive or insufficient adjustment is avoided; the treatment effect rehearsal is realized through virtual presetting, the irreversible operation risk is avoided, and the number of times of re-visit and the trial and error cost of a patient are reduced; and meanwhile, the four-dimensional virtual model can be connected with transition and design and manufacturing of a final restoration, so that the accuracy, safety and efficiency of retreatment of a failed restoration are improved.

The invention provides an intelligent decision-making method based on multi-dimensional risk coupling modeling of new energy ships and related equipment. The method comprises the following steps: fusing multi-modal data of each new energy ship to obtain a target multi-modal feature vector; mining risk implicit association strength by using a large language model, and constructing a risk knowledge graph; performing risk time sequence evolution prediction by adopting a dynamic Bayesian network based on the atlas to obtain a single-ship risk prediction result; constructing a graph structure according to the single ship risk and the operation parameters, and carrying out space coupling modeling by adopting a graph convolutional network to obtain a cluster risk prediction result; and generating an optimal operation and maintenance strategy by adopting reinforcement learning based on a cluster risk prediction result and a reward function by taking a high-fidelity digital twinborn body as a virtual environment. Therefore, according to the method, the problem of closed-loop adaptive control from risk deduction to decision response in a complex navigation scene is effectively solved by constructing a unified modeling mechanism of multi-dimensional risk coupling and linking real-time control strategy generation.

The invention discloses a zero-carbon park planning method and device, a storage medium and a computer program product, and relates to the technical field of carbon emission management, and the method comprises the steps: collecting the original space data of a target park, and obtaining the environment parameters of the target park, constructing a park three-dimensional digital twinborn model according to the original spatial data of the target park and the environmental parameters of the target park; dividing the park three-dimensional digital twinborn model into a plurality of grid units, respectively calculating the photovoltaic theoretical generating capacity of the plurality of grid units, and generating a plurality of candidate zero-carbon park planning schemes according to the photovoltaic theoretical generating capacity; performing economic cost measurement and calculation and carbon efficiency income measurement and calculation on each candidate zero-carbon park planning scheme to obtain an economic carbon efficiency measurement and calculation result; and selecting an optimal zero-carbon park planning scheme from the candidate zero-carbon park planning schemes according to an economic carbon effect measurement result. Zero-carbon park quantitative simulation is carried out in the planning stage, high cost of later modification of the park is avoided, and the economic carbon-efficiency ratio of the zero-carbon park is increased.

Digital model platform that enables the streamlined creation and management of digital twins and physical twins by leveraging external feedback and artificial intelligence (AI) is disclosed. Methods and systems for a model collaboration platform that facilitate the integration of external feedback, whether from physical, virtual, or human sources, into the streamlined design, validation, verification, certification, assembly, operations, and maintenance processes of complex systems. Updated results are output to those external sources, including physical twins, other digital twins or models and simulations, and / or human users. External feedback includes feedback data from physical prototypes and their environment, virtual prototypes, simulations, and subject-matter experts. Embodiments are directed to integrating external feedback into the assembly and system-level assessment of digital twins, physical twins, digital threads, and the iterative design of constituting digital engineering models, including constructing, maintaining, and improving digital engineering models for the design, validation, verification, certification, operations, and maintenance of complex systems.

The invention provides a home overall design method and system based on virtual reality. Wherein indoor environment data are collected in real time in a spatial gridding mode through a distributed temperature and humidity sensor array and a multispectral illumination sensor, and heterogeneous data are fused by using a spatial topology association engine to generate a three-dimensional environment parameter set. And based on the space coordinate weight matrix of the parameter set, driving a micro-electro-mechanical execution unit of the dynamic optical reflection film layer to adjust the surface inclination angle and the refractive index so as to form an optical reflection characteristic distribution diagram. And a three-dimensional light field model dynamically linked with physical illumination distribution is further constructed in the virtual scene, adaptive compensation operation of temperature and humidity parameters is triggered in real time according to physical space illumination intensity changes, characteristic parameters of the reflecting film layer are synchronously and reversely regulated and controlled, and a closed-loop control link is formed. According to the technical scheme provided by the invention, the full-dimensional precise synchronization of the optical characteristics of the material, the temperature and humidity influence and the illumination distribution in the home design scene is realized.

The invention provides a bridge pier nonlinear earthquake random response analysis method based on a BWBN model, and belongs to the field of civil engineering structure random vibration analys.The method comprises the steps that discretization processing is conducted on a concrete bridge pier structure, and a finite element nonlinear analysis numerical model is constructed; constructing a BWBN model by combining linear and nonlinear differential equations, setting a hysteresis parameter value of the BWBN model, simulating by adopting an Euler-Bernoulli beam unit, and establishing a degraded beam finite element model; obtaining a unit hysteresis vector, constructing a system motion balance equation, solving an equivalent linearization coefficient, constructing a covariance matrix of random response of the concrete pier structure, performing random response analysis on the concrete pier structure, and exploring typical working conditions of random excitation. According to the method, the operation time is shortened, the calculation precision is improved, and meanwhile, the response characteristics of the reinforced concrete pier structure under nonlinear earthquake random excitation can be truly represented.

A method for predicting gas explosion. The method includes: obtaining a geometric model with spatial obstacles; determining a simulation dataset of the gas explosion based on the geometric model, where the simulation dataset is a dataset including process data of multiple gas explosion scenes in the geometric model, and a state vector of a spatial grid node in the simulation dataset includes a first moment, coordinate information and a target pressure value; optimizing, using the simulation dataset, a physics-informed GNN to obtain an optimized physics-informed GNN; and predicting the gas explosion in an obstructed gas explosion scenario using the optimized physics-informed GNN. This method is applied to use optimized physics-informed GNN to realize spatiotemporal second-level prediction of overpressure distribution and explosion wave propagations occurring in the obstructed gas explosion scenario, enhance the accuracy, the reliability and the efficiency of gas explosion prediction in the obstructed gas explosion scenario.

The embodiment of the invention provides a dike breach blocking method and system, electronic equipment and a storage medium, and belongs to the technical field of automatic emergency rescue. The method comprises the following steps: performing virtual three-dimensional space reconstruction according to collected water surface flow data in a breach area to obtain a three-dimensional flow field model; performing target feature extraction on the three-dimensional flow field model to obtain a flow field feature matrix; a first target function is used as an optimization target, throwing decision optimization is carried out according to the flow field characteristic matrix, the regional throwing state data and the available material data, an optimal throwing scheme is obtained, and the first target function represents at least one of the minimum flow velocity energy or the minimum material loss amount; and carrying out transportation decision optimization according to the optimal throwing scheme and the transportation resource data by taking a second target function as an optimization target, so as to obtain an optimal transportation scheduling scheme, carrying resource scheduling is carried out according to the optimal transportation scheduling scheme, and the second target function represents maximum transportation efficiency. The dike breach plugging efficiency can be improved.

The invention relates to a mine water depth sealing layer site selection evaluation method and system based on multi-parameter coupling. The method comprises the following steps: acquiring geological, hydrological and engineering parameters through geological exploration equipment and the like, and carrying out wavelet transform noise reduction and Kriging interpolation processing; determining a key parameter set and weight by using an analytic hierarchy process, constructing a comprehensive evaluation model coupling the analytic hierarchy process and fuzzy mathematics, and generating a membership matrix and a multi-field coupling numerical model; and calculating a fitness index through spatial overlay analysis, generating a sealing suitability partition map, outputting an evaluation report containing risk early warning, and generating an interactive three-dimensional site selection decision interface. The system comprises a data acquisition and preprocessing module, a parameter processing module, a weight distribution module and the like. The simulation precision and the risk positioning efficiency are improved, and a comprehensive evaluation scheme is provided for site selection of the sealing layer of the water depth of the mine.

The invention discloses an urban planning design method based on a live-action three-dimensional simulation system, relates to the technical field of urban planning, and is used for solving the problem of insufficient technology fusion depth in an existing method. Firstly, an initial data set is formed by collecting multi-source city data; performing cross-modal feature extraction and alignment based on a deep learning model to generate a fusion feature vector; constructing a dynamic three-dimensional city model by using the fusion feature vector, and embedding a GIS spatial analysis module to perform preliminary layout simulation; vR interaction logic is injected into the model, user behavior feedback is simulated, and environment influence indexes are calculated; according to simulation results and index feedback optimization planning parameters, multi-technology collaborative decision making is achieved; outputting an optimization scheme and generating a visual report, and supporting real-time iterative updating; according to the method, the technology fusion depth is remarkably improved, the response delay is shortened to millisecond level, the planning precision is improved, the environmental influence evaluation deviation is reduced, and efficient and sustainable urban planning practice is realized.

The invention discloses a parameter-controlled intelligent oil field shaft digital twinning modeling method, which belongs to the field of petroleum engineering and comprises the following steps of: generating well track data by adopting a multi-source data fusion mode, and optimizing a multi-source data fusion weight coefficient by adopting a genetic algorithm when a measurement depth is generated; well track curvature optimization is conducted based on the minimum curvature principle, a minimum curvature second derivative serves as a target function, and geological factors are introduced to dynamically adjust the smooth weight; a second-order Taylor expansion compensation item is provided for curvature factor dynamic correction, and three-dimensional coordinate data of the well track are generated; and based on the three-dimensional coordinate data of the wellbore track, parameterized-driven wellbore geometric modeling is carried out, and parameterized programmable control over the wellbore radius, the wellbore wall thickness and the section inclination angle is achieved. The invention provides an efficient and accurate wellbore three-dimensional modeling solution, and the wellbore modeling efficiency is greatly improved.

The invention provides a multi-modal fusion virtual simulation experiment teaching system, and relates to the technical field of virtual simulation, and the system comprises an information collection module which is used for obtaining the interaction information of a learner; the information fusion module is used for constructing a multi-modal input data set; the instruction analysis module is used for analyzing and generating an operation instruction sequence; the teaching intervention strategy generation module is used for generating a self-adaptive teaching intervention strategy; the teaching intervention strategy execution module is used for executing a self-adaptive teaching intervention strategy; and the learning effect evaluation module is used for quantifying the learning effect evaluation score. The technical problems that in traditional virtual simulation experiment teaching, multi-modal operation behaviors of learners are difficult to accurately capture in real time, personalized teaching intervention is lacked and learning effect evaluation is incomplete can be solved, and virtual experiment simulation and intelligent teaching intervention driven by multi-modal information fusion are achieved. And the experimental interaction experience and the learning effect evaluation precision are improved.

The invention discloses a tunnel boring machine performance prediction and monitoring system and method based on digital twinning and machine learning. The system comprises a data acquisition module, a data preprocessing module, a model construction module, a performance analysis module and a visual analysis module. The data acquisition module is used for acquiring initial data of a tunnel boring machine on a construction site; the data preprocessing module is used for preprocessing the initial data to obtain preprocessed data; the model construction module constructs a prediction model and a digital twinborn model of the tunnel boring machine based on the preprocessed data; the performance analysis module predicts the tunneling speed and the propelling speed of the tunnel boring machine by using the prediction model to obtain a prediction result, and integrates the prediction result with the digital twinborn model; and the visual analysis module is used for constructing a virtual environment and checking the construction progress and the performance prediction result of the tunnel boring machine in real time in a digital twinborn model in the virtual environment.

The invention particularly discloses a time-space design method for a railway tunnel active support rock anchoring and shotcreting synergistic effect considering a time-space effect, and relates to the technical field of civil engineering. The method comprises the steps that firstly, expression characteristics of the load time effect, the material time effect, the tunnel face space effect and the rock anchor bearing arch space effect of active supporting are determined, a space-time effect characterization method is established, and then a tunnel active supporting rock anchor and shotcrete synergistic effect space-time calculation model is constructed; then determining calculation parameters of a rock anchor bearing arch and a sprayed concrete layer, and constructing a surrounding rock pressure calculation method and a safety evaluation method considering the advance support effect; and finally, according to a calculation result of the tunnel active support rock anchoring and shotcreting synergistic effect space-time calculation model, safety is judged, and design parameters of a pre-stressed anchor rod and shotcreting concrete are determined. The method can simply, quickly and accurately calculate the internal force distribution and safety of the tunnel rock anchor bearing arch and the sprayed concrete layer under different time, geological conditions and support design parameters, and has good engineering value.

The invention belongs to the technical field of SPH modeling, and particularly discloses an SPH particle model and surface geometric model automatic generation method and system, and the method comprises the steps: constructing raster data of a terrain elevation model and a source thickness distribution model, carrying out the data standardization processing, and achieving the unification of the spatial reference of the terrain elevation model and the source thickness distribution model; resampling the resolution of the standardized raster data to ensure that the size of the raster unit is matched with the physical characteristics of the particles; generating terrain boundary particles by adopting a hierarchical generation algorithm, and completing material source particle filling; and based on the grid vertex coordinate set, generating a surface geometric model in an STL format, outputting particle coordinates and an STL file meeting the requirements of an SPH solver, and completing automatic generation of the SPH particle model and the surface geometric model. The problems that an existing SPH modeling method is low in processing efficiency, high in data alignment error and insufficient in model surface geometric accuracy are solved.

The invention relates to the technical field of intelligent monitoring, in particular to an electronic guide vehicle steering system fault prediction method based on time sequence data analysis, which comprises the following steps: mapping a steering system into perception, decision and execution virtual computing nodes to construct a digital twin model; extracting inter-node time lag correlation through multivariable Granger causality operation, and constructing a virtual causality matrix; fault parameters such as current, angle and bias are injected into the model for numerical simulation, and a response sequence is generated through time domain iteration; using a dynamic time warping algorithm to calculate the morphological difference between the time sequence and the reference sequence so as to generate a time sequence feature; and constructing a digital twinning dynamic graph, inputting the dynamic graph attention network, and extracting spatio-temporal evolution characteristics to generate a fault prediction result. According to the method, accurate deduction of the full-life-cycle fault evolution process of the steering system is realized through digital twinning.

The invention belongs to the technical field of intelligent manufacturing and industrial internet, and particularly relates to a dense storage digital twinning related system and method. The system adopts a five-layer architecture design and comprises a physical entity layer, a sensing layer, a data layer, a twin model and virtual debugging layer and an application layer, the system integrates the functions of three-dimensional modeling, virtual simulation, real-time data acquisition, OPC UA communication, Web visual interface, state monitoring and intelligent diagnosis, and aims to realize virtual debugging, efficient monitoring and predictive maintenance of dense storage equipment and remarkably improve the reliability and intelligent level of a storage system.

The invention relates to the technical field of electrical wiring. The invention discloses a method for generating a cable wiring path of a power distribution cabinet, and the method comprises the steps: firstly obtaining the multi-dimensional environment parameters of a to-be-wired power distribution cabinet, wherein the structural parameters comprise the three-dimensional layout in the cabinet, the positions of components and wire duct guide rails, the electrical parameters comprise the connection relation of the components, the cable specification and the like, and the physical constraint parameters are the allowable bending radius and the minimum electrical gap; constructing a digital twinborn model according to the parameters, and performing risk analysis on the model to obtain a safety risk level; and finally, a double-path scheme is generated and output in combination with the model and the grade, the first path is the optimal path of the prediction model, the second path is the standby path of the historical case, and the priority of the first scheme is higher. According to the method, the security risk is quantified in advance through multi-dimensional parameter acquisition, digital twin modeling and risk assessment. The current situation that traditional manual wiring depends on experience is changed through intelligent generation of an optimal path, reuse of a standard scheme of a standby path and real-time monitoring and early warning.

The invention relates to the technical field of information, and particularly provides a complete denture arrangement virtual simulation method and system, and the method comprises the steps: obtaining the medical record data of a user; the medical record data comprises edentulous jaw soft and hard tissue data, jaw bone data, alveolar ridge morphological parameters, jaw position relation data and facial feature data; determining an initial dental arch curve based on the medical record data; inputting the initial dental arch curve and preset aesthetic parameters into a preset deep learning model to obtain a plurality of initial tooth arrangement schemes; screening the plurality of initial tooth arrangement schemes according to tooth arrangement constraint conditions to obtain tooth arrangement schemes meeting constraints; the tooth position and angle of each tooth arrangement scheme meeting the constraint are adjusted until the preset occlusion balance condition is met, and the first tooth arrangement scheme is obtained, so that the tooth arrangement scheme efficiency of the complete dentures can be improved on the premise that the quality of the tooth arrangement scheme of the complete dentures is guaranteed.

The invention discloses a fracturing crack long and short axis difference expansion evaluation and control method which comprises the steps that working parameters and a fracturing technology of a fracturing area are obtained, and the working parameters comprise engineering parameters and geological parameters; establishing a physical model of the fracturing position according to the working parameters and the fracturing process, and establishing a numerical simulation model for the difference extension of the long axis and the short axis of the fracture based on the physical model; performing numerical simulation on the working parameters of the fracturing area through the numerical simulation model, analyzing the influence of each parameter on the crack long-short axis difference expansion behavior difference and size according to a numerical simulation result, and establishing a crack long-short axis difference expansion prediction model according to the influence; and according to the extension prediction model, predicting fracturing fracture long and short axis difference extension, and according to a prediction result, adjusting a fracturing process to realize fracturing fracture long and short axis difference extension control.

The invention provides a BIM (Building Information Modeling)-based engineering electromechanical installation method. The method comprises the following steps: establishing an engineering electromechanical BIM model; carrying out model collision check and optimization; construction simulation and scheme making are carried out; field installation and implementation; and installation acceptance and model filing. According to the method, the geometric and attribute integrated BIM model is constructed through data collection and digital drawing review, full-dimensional collision detection is carried out, key pipeline specification requirements are preferably guaranteed, model data reliability is guaranteed, construction disjunction caused by drawing errors is avoided, the problem of pipeline collision is solved in advance, and the construction efficiency is improved. Material waste and construction period delay of dismantling and reassembling in the construction stage are reduced, meanwhile, the risk of illegal acceptance of key pipelines is reduced, and the limited space utilization rate is increased.

The invention provides a factory three-dimensional digital twin model reconstruction and incremental updating method for industrial space intelligence, and the method comprises the steps: obtaining a factory multi-view basic image for a factory panoramic scene, so as to train a bifurcated structure neural implicit field network containing a radiation field branch and an SDF branch, and generating an initial three-dimensional digital twin base; acquiring factory real-time inspection images acquired by the inspection robot under different inspection poses, rendering the initial three-dimensional digital twin base by using a radiation field branch to obtain a virtual reference view, and performing difference analysis on the virtual reference view and the factory real-time inspection images to position a structural change area in a factory; determining an axis alignment bounding box for changing the physical range of the entity in the area, taking the axis alignment bounding box as an effective boundary of the local space patch, and determining matched radiation field network weight and SDF network weight according to the effective boundary; and adjusting the radiation field network weight and the SDF network weight, and updating the radiation field network weight and the SDF network weight to the network in an incremental updating manner to generate a factory three-dimensional digital twinning model based on the implicit three-dimensional geometric field.

The invention provides a ship anti-mold-penetrating and collision-preventing method in combination with Beidou and virtual channel constraint in a digital twinborn scene, and the method solves a problem of ship position deviation caused by the installation position difference of a Beidou terminal through Beidou and AIS dual-mode fusion positioning correction. Constructing a refined collision detection adaptation mechanism based on the ship models associated with various goods types, and adapting to size differences of different ship models; and a'positioning-ship model-collision detection 'cooperative link is opened, so that multi-target priority collision avoidance is realized. According to the method, the ship position display precision and the anti-mold-penetrating and anti-collision accuracy in the digital twin scene are effectively improved, and the method is suitable for real-time supervision and simulation in a high-density ship traffic environment.

The invention discloses an intelligent construction simulation system based on BIM and virtual reality fusion, and the processing flow of the intelligent construction simulation system comprises the steps: constructing a three-dimensional digital model according to a design drawing, geological exploration data and a planned construction progress; a three-dimensional digital model is used as a core, a digital twinning model of a bridge is built in combination with the Internet of Things, a sensor and a big data analysis technology, the three-dimensional digital model and the digital twinning model are integrated to a VR development platform, and virtual simulation is performed on a bridge construction site; inputting real-time sensing data acquired by various sensors into the digital twinborn model, and constructing a dynamic risk field; and carrying out risk propagation path analysis and dynamic early warning threshold adjustment according to the dynamic risk field to obtain a risk thermodynamic diagram, an early warning level and a recommended coping strategy. According to the invention, the limitation of a traditional construction management mode is broken through, regulation and control can be carried out in advance according to the predicted risk, and a more comprehensive, accurate and real-time simulation and management means is provided for the bridge construction process.

A system and method for placing and configuring physical security sensors & barriers, are described. The system generates and analyzes a three-dimensional model of a customer's premises using non-imaging sensors to determine optimal sensor placement. Based on customer requirements, the system distributes sensor models within the premises while accounting for environmental obstructions, coverage gaps, and redundancy minimization. An extended reality (XR) interface allows users to visualize and refine sensor configurations before deployment. The system integrates AI-driven analytics to optimize surveillance coverage, adjust sensor orientations dynamically, and generate detailed reports outlining sensor locations and configurations. The sensor stand transmits real-time data to the system for continuous monitoring, predictive maintenance, and security threat analysis. The system enhances security planning by reducing design time, installation costs, preventing post-deployment modifications, and ensuring comprehensive monitoring coverage across diverse environments, including commercial, industrial, and critical infrastructure sites.