969 results about "Physical space" patented technology

The invention discloses a multi-welding-robot collaborative operation system based on digital twinning, and belongs to the technical field of intelligent manufacturing and robot control, the system comprises a physical space module, a virtual space module, a twinning data layer and a control module, and communication connection is established among the physical space module, the virtual space module, the twinning data layer and the control module; the physical space module comprises a plurality of welding robots, a sensor group and a data transmission network; the virtual space module comprises a multi-welding robot twinning body and a workpiece twinning model; the twin data layer is used for connecting the physical space module and the virtual space module; and the control module generates a welding path optimization scheme, a multi-welding-robot collaborative collision avoidance strategy and a welding quality feedback control instruction based on the twin data layer. According to the method, a closed-loop control framework of'physical-virtual 'bidirectional mapping is constructed, so that dynamic collaborative optimization of multi-robot motion trails, welding seam forming and thermal deformation is realized.

The invention relates to the technical field of intelligent agricultural robots, and provides a multi-agent collaborative anti-collision picking method based on digital twinning and deep reinforcement learning, which comprises the following steps: constructing a digital twinning model of a picking scene, and generating environmental geometric parameters, agent kinetic parameters and fruit position parameters through three-dimensional point cloud reconstruction; acquiring environment state data in real time and inputting the environment state data into the digital twin model for space-time alignment processing to generate synchronous state data; based on the synchronous data, a collaborative strategy containing a collision avoidance priority matrix, a path planning sequence and a task allocation weight is generated through a deep reinforcement learning network; an action instruction set is generated according to the strategy, and multiple agents are controlled to execute a picking task after virtual-physical space bidirectional verification of the digital twin model. According to the invention, efficient collision avoidance and accurate picking of multiple agents in a dynamic environment can be realized, and the picking efficiency, safety and system robustness are improved.

The invention discloses a property operation decision support system based on digital twinning and generative AI, which relates to the technical field of property operation management and comprises a sensing layer, a data layer, a digital twinning layer, a generative AI layer and a decision execution layer which are connected in sequence. In the invention, the generative AI layer is based on a special Transform architecture model, fuses historical operation data and digital twinning real-time data, can automatically generate an executable optimization strategy in multiple scenes such as facility maintenance, resource allocation, personalized service, emergency disposal and the like, verifies feasibility and effects in a virtual environment, and improves the implementation efficiency. The decision execution layer efficiently implements a strategy subjected to simulation verification into a physical space by using an intelligent scheduling and equipment linkage mechanism, performs quantitative evaluation and strategy iterative optimization based on an execution effect, deeply fuses a high-fidelity digital twin with a generative AI, constructs an AI decision closed-loop system based on simulation verification, and performs decision making on the AI decision closed-loop system. And a high-feasibility and feasible optimization scheme can be generated for a complex and dynamic property operation environment.

The invention relates to the technical field of robot visual perception and motion control, and discloses a motion control method and device based on physical reference, equipment and a medium, and the method comprises the steps: obtaining instruction information, a multi-view image and movable assembly pose information; processing the multi-view image according to the instruction information to generate target segmentation information; generating a scale normalization point cloud and a model estimation baseline; determining a physical reference baseline and generating a scale calibration factor; converting the scale normalization point cloud into a physical space point cloud by using a scale calibration factor; extracting a three-dimensional relative position of the target object relative to the movable component in combination with the target segmentation information; an action instruction is generated based on the multi-modal input. According to the method, physical scale alignment of the point cloud is realized through physical reference baseline calibration, so that a visual reconstruction result has real space significance, an accurate action instruction is generated, and the robot space understanding and operation precision is improved.

The invention provides an urban space intelligent processing method based on multi-modal fusion, and the method comprises the steps: taking multi-modal data as input, and constructing a unified data stream processing and feature alignment mechanism; a physical space is used as a core framework, and the multi-modal data is converted into a space behavior graph with space-time position semantics; constructing an entity attribute-relation type-influence weight ternary interaction model on the basis of an interaction layer of the spatial behavior map, and analyzing a human, object and environment ternary interaction relation in the city and the park based on the ternary interaction model; designing a space intelligent engine with time sequence modeling and dynamic prediction capabilities; and constructing a task processing system. According to the invention, through deep combination of multi-modal fusion and a space intelligent technology, full-link upgrading of urban space from data perception to intelligent decision is realized, and powerful technical support is provided for fine management, efficient operation and safety guarantee of complex space scenes.

The invention discloses a security check door security check process optimization scheduling system and method based on big data, and belongs to the technical field of intelligent security check, a whole security check area is divided into a plurality of functional areas and mapped into network nodes according to security check process links and physical space distribution, directed edges among the nodes represent passenger flow paths, and the flow paths of passengers are distributed in the network nodes. A weight matrix of edges is calculated through historical flow data, and a security check area network topology model is constructed; fusing ticket business, historical security check and real-time sensor data, constructing a load evaluation model, and calculating a node load index and an influence conduction coefficient; based on passenger ticket business time and historical behavior records, establishing a time urgency index and risk level model, and forming a two-dimensional decision matrix to dynamically divide priorities; constructing and training a congestion propagation model, predicting a future congestion path in combination with priority distribution, and identifying bottleneck nodes; and according to a prediction result, cooperatively implementing a grooming strategy from four dimensions of personnel, channels, equipment and processes.

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 present invention discloses a distributed heuristic unmanned cluster brain-like swarm intelligence fusion search and capture method, comprising: step 1: completing single target detection on the basis of a Yolov5 network, and predicting the position of a next frame of target on the basis of a DeepSort algorithm; step 2, on the basis of the distance difference and the area difference, determining, by mapping, navigation end point coordinates formula (1) of an intelligent agent in a physical space; step 3, constructing a diffusion-contraction coordinated chaotic mapping algorithm, and mapping the update of the navigation end point coordinates into a uniformly distributed chaotic space; step 4: on the basis of target detection confidence decision information and regional position information of all intelligent agents, fusing and generating global search information formula (3) of a search space formula (2); step 5: on the basis of the intelligent agent global search information, fusing various sensing data in a multi-agent system, so as to estimate target position information; and step 6: performing measurement on the basis of a real-time position of the intelligent agent and an obstacle position. The present invention has high capture efficiency and can accurately update a capture end point of the intelligent agent to complete a task of encircling a moving target.

The invention discloses a self-adaptive sound effect management method and system with a scene analysis module, and relates to the field of self-adaptive sound effect management, and the method comprises the following steps: S1, collecting environmental acoustic characteristics and user behavior data in real time through the scene analysis module; s2, dynamically extracting user hearing preference parameters and scene classification labels; s3, constructing a virtual audition sweet zone matched with the physical space; and S4, dynamically adjusting the phase delay and the energy distribution proportion of each frequency band, and generating an optimal loudness equalization curve meeting the multi-scene constraint. According to the method, adaptive matching of sound field characteristics is realized in a complex dynamic scene through a multi-level perception-optimization closed-loop architecture, acoustic feature extraction and physical space modeling are deeply fused, the technical boundary of traditional pure signal processing is broken through, and the problem of multi-target conflict is solved based on cross-modal collaborative learning and a global optimization algorithm.

The invention belongs to the technical field of computer graphics and virtual reality, and discloses a virtual-real fusion-based panoramic roaming construction method for a digital exhibition hall, which effectively solves the problems of easy drift and offset in a virtual environment in a traditional system through a multi-sensor fusion algorithm and a closed-loop optimization mechanism. Under the complex environment of people flow change, illumination fluctuation and the like in an exhibition hall, accurate alignment of virtual content and physical space can still be kept, it is ensured that a user obtains coherent and stable visual experience in the roaming process, and a reliable space reference is provided for virtual-real interaction; the light and shadow effect and the material performance of the virtual content are naturally fused with the physical environment through the physical rendering and multi-sensory interaction technology, and meanwhile, a multi-dimensional immersion sense is constructed in combination with the spatial sound effect and interaction feedback; when the user interacts with the virtual exhibit, sensory experience close to reality can be obtained, and the sense of substitution and attraction of the digital exhibition hall are remarkably improved.

The invention belongs to the field of energy storage monitoring, and provides an energy storage facility safety early warning protection method and system, and the method comprises the steps: obtaining the temperature, heating rate and equivalent impedance data of each monitoring unit of a battery cluster; constructing a physical adjacency matrix based on the physical space arrangement relation of the monitoring units; fusing the physical adjacency matrix and the electrical adjacency matrix according to a preset weight; constructing a graph structure based on the comprehensive adjacent matrix, and calculating a Laplacian matrix of the graph; calculating a node neighborhood residual error for the temperature and the heating rate based on a Laplacian matrix to obtain a temperature consistency residual error; calculating a node neighborhood residual error for the equivalent impedance to obtain an electrical consistency residual error; calculating a temperature prediction residual error under the time sequence prediction model with graph regularization constraint; and constructing an early abnormal score of the node, adaptively setting a quantile threshold according to the healthy operation data distribution, and carrying out graded early warning judgment on the early abnormal score. The accuracy of safety early warning of the energy storage facility can be improved.

The invention discloses a die temperature field coordinated regulation and control method based on digital twinning, and relates to the technical field of die temperature control. The method comprises the following steps: constructing a mold temperature field digital twin model covering macroscopic, mesoscopic and microscopic scales; a distributed optical fiber temperature sensor is deployed to realize continuous temperature field sensing; physical-digital real-time synchronous mapping is established through ensemble Kalman filtering; performing model prediction control based on the digital twinborn body; three-dimensional visualization and multi-modal man-machine interaction of the temperature field are realized by adopting an augmented reality technology; and reinforcement learning is used to enable the digital twinborn body to have an autonomous optimization capability. Through deep fusion of a physical space and a digital space, precise sensing, real-time mapping and intelligent control of a mold temperature field are realized, and the temperature control precision and the self-adaptive capability of the system are remarkably improved.

The invention discloses a building outer wall falling risk detection method and system based on deep learning, and the method comprises the steps: obtaining an original surface image, extracting vertical face geometric features, constructing a homography matrix based on vanishing points, carrying out the geometric correction, and reconstructing an orthographic projection image; performing enhancement processing on the orthographic projection image, extracting an effective detection area and intercepting a detection image; inputting the detection image into a deep learning segmentation model into which edge weight constraint is introduced, and performing semantic segmentation, binaryzation and optimization to obtain a falling region; a mapping relation is established according to the actual physical size of the building outer wall, and pixel information of the falling area is converted into multi-dimensional parameters such as the actual physical area, the elevation, the width and the height; and combining the defect intensity input quantification risk assessment model to calculate a comprehensive risk index, determining a risk level and outputting a result. Automatic identification and quantitative evaluation can be realized, distortion and background interference are eliminated, accurate conversion from pixels to a multi-dimensional physical space is realized, and a scientific basis is provided for safety investigation.

The invention belongs to the technical field of robot kinetic parameter identification, and provides a robot kinetic parameter identification method, system, equipment and medium in order to solve the problems of poor accuracy, poor robustness and the like of an existing identification method. A robot excitation track is generated by adopting finite Fourier series, the robot excitation track is optimized under the condition that physical limitation of a robot body and real physical space collision constraint are met, and then the robot excitation track is determined as input data for identification; establishing a logarithmic Euclidean metric convex approximation regular term of the physical consistency matrix; sigmoid is used as a weight to weight the least square, and the inertial parameters and the nonlinear friction model are solved alternately by using double internal loops until the residual is converged. According to the method, the identification precision equivalent to that of long-time excitation can be rapidly obtained, pre-identification does not need to be carried out on the nonlinear friction model, and the calculation efficiency is greatly improved.

The invention provides a multi-source data integration and real-time decision-making system driven by an Al large model, and relates to the technical field of intelligent supervision, and the system comprises a standardization module which is used for dynamically accessing a multi-source heterogeneous data source of a supervision place through a configurable adapter matrix, and carrying out the processing and mapping of the multi-source heterogeneous data source to generate a global standardized data model; and the mapping module is used for establishing a mapping relationship between the physical space of the supervision area and the spatial coordinate attributes of the data sources based on the global standardized data model, and executing space-time alignment operation on the data sources with the spatial coordinate attributes to generate a space-time aligned data stream. According to the invention, integration, accurate analysis and dynamic optimization of multi-source heterogeneous data are realized, the timeliness and accuracy of decision making in a supervision scene and the resource utilization efficiency are improved, and the overall efficiency of physical space refined supervision is enhanced.

The invention relates to a construction progress management method and system based on BIM space ternary mapping, and the method comprises the steps: carrying out the division based on the component information of a BIM model, obtaining physical spaces with actual construction significance, and constructing a space topology logic relation between the physical spaces; based on the physical space and the spatial topology logic relationship, constructing a ternary closed-loop mapping relationship among the WBS construction task, the BIM model component and the physical space; and managing the construction progress of the construction general control plan based on the current construction general control plan and the ternary closed-loop mapping relation. According to the method and the device, multi-stage dynamic closed-loop management is performed on the construction general control plan by using the ternary closed-loop mapping relation, disjunction conflicts between the actual construction progress and the predicted progress can be effectively processed, possible procedure chaos and operation conflicts among multiple construction teams and groups can be effectively coordinated, and the working efficiency is improved. The problem of how to improve the construction progress management efficiency based on the building information model is solved.

The invention discloses a safe evacuation path planning method under a strong wind condition of island engineering. According to the technical scheme, the method is characterized by comprising the steps that firstly, the physical space of an engineering site is discretized into a plurality of grid units, and a computable graph structure is constructed; then, acquiring multi-source dangerous area information generated in real time, and quantifying the dangerous area information into a dynamic risk value of each grid unit; then, acquiring the real-time position of the constructor as a starting point, and presetting an emergency exit as an ending point; and finally, on the constructed risk grid map, a heuristic search algorithm such as A * is adopted, and the geometric distance and the dynamic risk value between grid units are fused by a cost function of the heuristic search algorithm, so that an optimal evacuation path considering safety and efficiency is quickly searched. According to the method, the safety risk is quantified and fused into the path optimization process, so that the quick response to the dynamic environment and the real-time re-planning of the path are realized, and the efficiency and safety of personnel evacuation under the emergency condition are remarkably improved.

The invention provides an evacuation strategy generation method for a hydropower station, and the method comprises the steps: obtaining the physical space data of the hydropower station, including the landform, building structure and equipment layout data; constructing a dynamic risk model based on the physical space data, and identifying a risk source type and a diffusion path; the personnel distribution data is collected through the positioning terminal, and an evacuation demand map is generated. The safe traffic capacity of the limited evacuation channel is calculated, and an initial evacuation path set is generated in combination with the evacuation demand map; performing coupling optimization on the initial evacuation path set based on three factors of path length, risk exposure duration and crowd density change rate; the state change of a risk source is dynamically monitored through a risk sensor network, strategy updating is triggered when the risk diffusion speed exceeds a preset threshold value, and finally an optimized evacuation strategy is output to terminal execution equipment. The method can achieve the real-time updating and efficient optimization of the evacuation strategy of the hydropower station, and improves the evacuation efficiency and the personnel safety guarantee capability.

There is provided an enablement entity for a virtual experience service, the enablement entity in a wireless communication network, the enablement entity comprising a receiver, a processor and a transmitter. The receiver is arranged to receive an application service requirement corresponding to a plurality of devices, the plurality of devices operating in physical space, or in a virtual space of the virtual experience service, or both. The processor is arranged to decompose the application service requirement to a plurality of session requirements, wherein the session requirements apply to a plurality of communication sessions, the communication sessions provided between devices in both physical space and virtual space, and to derive a set of joint quality of service parameters for the plurality of sessions based on the session requirements. The transmitter is arranged to send the set of joint quality of service parameters to one or more network entities in the wireless communication network.

The invention relates to the technical field of metallurgical industry simulation and intelligent control, and discloses an intelligent metallurgical process virtual simulation method and system based on digital twinning. The method comprises the following steps: acquiring multi-modal high-dimensional data in a metallurgical process and reducing dimensions to obtain a feature vector set of a hidden layer space; performing disturbance injection simulation by using the feature vector set of the hidden layer space to obtain a multi-path state sequence with time dependence; predicting the abnormal path by using a recurrent neural network to obtain a predicted state evolution trajectory; utilizing a preset inverse mapping function to obtain multi-path state representation in the physical space; screening to obtain a risk path set; key evolution nodes are extracted from the set to be processed, and a virtual simulation scene is obtained; and performing optimization simulation on preset process adjustment parameters according to the virtual simulation scene, and determining optimized parameter configuration. The method can solve the problem that it is difficult to construct a comprehensive virtual simulation scene which truly restores the physical production rule.

The invention provides a curved surface grid generation method based on discrete grid parameterization, and belongs to the technical field of computer aided engineering (CAE) and computational geometry. Aiming at the problems of tedious geometric operation, parameter space fusion distortion, insufficient grid fitness and the like in grid subdivision of a complex curved surface formed by a plurality of sub-curved surfaces, the invention provides the following technical scheme: firstly, carrying out triangular grid pre-subdivision on an original curved surface, and constructing a virtual topological structure for inhibiting non-key features; the discrete grids are mapped to a low-distortion two-dimensional parameter space by adopting least square conformal mapping (LSCM), and seamless combination of multiple sub-surface parameter domains is realized; dynamically calculating a parameter space size field, and controlling grid density distribution; after a parameter space adaptive grid is generated through Delaunay triangulation, grid points are accurately attached to an original geometric surface by using a dual projection correction mechanism. According to the method, complex CAD geometric operation is avoided, the automation degree is remarkably improved, meanwhile, physical space grid uniformity and strict fitness are guaranteed, and the method is suitable for efficient and high-precision grid generation of complex curved surfaces in the fields of aerospace, automobiles, ships and the like.

The invention discloses an intelligent operation and maintenance method and system for an energy management platform, and relates to the technical field of intelligent operation and maintenance, and the method comprises the steps: analyzing data through employing an NLP technology, generating a multi-objective optimization function, constructing a user behavior portrait, adjusting the weight parameters of the multi-objective function through employing a reinforcement learning algorithm in combination with an Actor strategy network, and carrying out the operation and maintenance of a user. An energy scheduling scheme is obtained by using an improved bald eagle search algorithm and a prey escape energy mechanism, a digital twinborn model of mapping of a physical space and a virtual space is constructed, and the energy scheduling scheme is optimized and implemented by combining the digital twinborn model with a soft constraint mechanism. Through fusion of NLP technology semantic analysis and a reinforcement learning algorithm, a multi-target scheduling strategy is dynamically optimized, and an improved bald eagle search algorithm and a digital twin model are combined to realize simulation verification and closed-loop feedback, so that the intelligence and optimization level of energy system operation is improved, and the stability, economy and low-carbon operation capability of the system are also improved.

The invention discloses a hotel self-service equipment collaborative management system and method based on the Internet of Things, and relates to the technical field of hotel intelligent management, and the method comprises the steps: a sensing module monitors personnel distribution and behavior characteristics in an equipment operation radius in real time through a multi-source sensor network, and generates spatial state data; the scheduling engine module receives the spatial state data, divides a physical space into virtual grids, calculates a service pressure index and generates an equipment state control strategy; an equipment cooperation module responds to the equipment state control strategy, establishes an equipment cluster dynamic health baseline and executes cross-equipment micro-task scheduling and verification; and the user interaction module fuses the biological characteristics and the behavior data to generate a dynamic trust score, and controls equipment service activation. According to the invention, the problem of low efficiency caused by rigid spatial layout, uneven load and fault diffusion of hotel self-service equipment is solved, full-link collaborative optimization from a physical environment to digital resources is realized, the user experience is improved, and the operation and maintenance cost is reduced.

The present disclosure generally relates to illuminating a physical space, such as duplicating lighting conditions of an external environment, simulating light conditions, and / or storing one or more characteristics of lighting conditions.

The invention relates to a point cloud clustering method and device based on millimeter wave radar indoor perception. The method comprises the following steps: acquiring point cloud data obtained based on millimeter wave radar detection in a physical space, and mapping the point cloud data to a preset graph space to obtain a mapping graph corresponding to the point cloud data; performing feature accumulation updating processing on the mapping graph according to different time levels to obtain feature graph layers of the mapping graph on different feature dimensions; and performing point cloud clustering processing on the plurality of feature layers to obtain a clustering result corresponding to the point cloud data, wherein the clustering result is used for representing the distribution condition of the point cloud data in each feature dimension so as to detect and track an entity object in the physical space. By adopting the method, multi-feature modeling and refined clustering recognition can be performed on the point cloud data in an indoor millimeter-wave radar sensing scene, and high-precision structural support is provided for stable detection and precise tracking of entity objects in a physical space.

The invention belongs to the technical field of construction management, and particularly relates to a construction data processing method and system based on big data, and the system comprises a data collection and editing preprocessing module, a time-space correlation modeling module, a multi-dimensional risk deduction module, a decision feedback optimization module and a construction supervision terminal. Multi-source heterogeneous data are efficiently accessed and processed through the data collecting and editing preprocessing module, the efficiency and accuracy of data processing are improved, the space-time correlation modeling module constructs dynamic digital twinborn bodies of construction elements, real-time mapping and correlation analysis of a physical space and a digital space are achieved, powerful support is provided for risk prevention and control, and the method is suitable for large-scale popularization and application. The multi-dimensional risk deduction module carries out risk quantitative evaluation and scene simulation based on the digital twinborn body, potential risks can be found in advance and early warning signals can be generated, the decision feedback optimization module converts risk early warning into a specific disposal scheme, the construction supervision difficulty can be reduced, and a powerful guarantee is provided for smooth proceeding of a construction project.

The invention discloses a queuing duration detection method and device, equipment and a storage medium. The method comprises the following steps: performing identification processing on at least one video data stream collected by different cameras, and determining a two-dimensional action track of a target person in a preset queue area; the two-dimensional action track is used for representing the coordinate change of the target person in the video picture in the time dimension; converting the two-dimensional movement track of the target person into a three-dimensional movement track of the target person according to a pre-established mapping relation between two-dimensional coordinates and three-dimensional physical coordinates of the image; the three-dimensional action track is used for representing the coordinate change of the target person in the three-dimensional physical space model in the time dimension; and calculating the queuing duration of the target person based on the in-column time and the out-column time determined from the three-dimensional action track of the target person. According to the method provided by the invention, queuing duration detection which is more in line with an actual application scene is realized, and the accuracy of queuing duration detection is improved.

The invention relates to the technical field of city updating simulation, and discloses a city updating multi-scene simulation evaluation system based on digital twinning. The system comprises a multi-source data acquisition module, a space grid division module, a scene simulation engine and a dynamic evaluation module. The multi-source data acquisition module acquires real-time monitoring data and historical city update project data of a city physical space, and the real-time monitoring data covers environmental parameters, infrastructure operation data and people flow dynamic data, so that a digital twinborn body is constructed. The space grid division module divides the digital twin into space grid units according to the urban functional area type and the updating target and gives attribute tags to the space grid units. And the scene simulation engine generates a simulation parameter combination based on the attribute tag, and drives the digital twin to carry out multi-scene dynamic simulation. And the dynamic evaluation module outputs a state evaluation value of each space grid unit according to a simulation result, the state evaluation value comprises an infrastructure load state and a people flow distribution state, and orderly promotion of city updating work is assisted.

The invention relates to the technical field of computers, in particular to a physical space script game delivery system and method supporting rapid deployment, and the method comprises the steps: receiving a request of a user side, and generating a space coordinate graph; constructing a spatial feature set containing function / topological attribute vectors and a task demand set containing function demand vectors, difficulty coefficients and the like; calculating a matching degree and screening candidate point locations; constructing a task logic chain and an accessibility matrix, and performing recursive verification to obtain a binding scheme; a playing process and a two-dimensional code are generated and issued to a code scanning tourist end; according to the method, the operation investment can be effectively reduced, the deployment period is shortened, the coordinate graph generation of any scene is supported, the dependence on specific field hardware is eliminated through standardized vector construction and logic matching, the problem that a traditional scheme is difficult to reuse is solved, and the method can adapt to any physical space to realize the rapid deployment of the script game.

A system and method for reconfiguring physical space having structural integrity, notably empowered by leveraging energy distribution that further leverages dynamic feedforward allocation of distributed energy storage, to maximize space utilization factor to accelerate return on investment, reduce system energy consumption, and maximize functional utilization of physical space particularly suited for modular construction with integral and approximately continuous updating of digital twin modeling to empower higher precision feedforward and feedback systems control resulting in high-performance buildings.