A virtual reality-based overall home design method and system

Abstract

The application provides a virtual reality-based home overall design method and system. Through a distributed temperature and humidity sensor array and a multispectral light sensor, indoor environment data is collected in real time in a spatial grid mode, and a spatial topology correlation engine is used to fuse heterogeneous data to generate a three-dimensional environment parameter set. Based on the spatial coordinate weight matrix of the parameter set, the micro-electromechanical execution unit of the dynamic optical reflection film layer adjusts the surface inclination and refractive index to form an optical reflection characteristic distribution map. Further, a three-dimensional light field model dynamically linked with physical light distribution is constructed in a virtual scene, and adaptive compensation operations of temperature and humidity parameters are triggered in real time according to changes in physical space light intensity, and the characteristic parameters of the reflection film layer are synchronously controlled in reverse, forming a closed-loop control link. The technical scheme provided by the application realizes full-dimensional accurate synchronization of material optical characteristics, temperature and humidity influence and light distribution in a home design scene.

Description

Technical Field

[0001] This application relates to the field of virtual reality and smart home system integration technology, and in particular to a method and system for overall home design based on virtual reality. Background Technology

[0002] In smart home design combined with virtual reality, users need to realistically simulate the impact of dynamic lighting changes and temperature and humidity distribution on material properties in a virtual environment. For example, dynamic changes in environmental parameters such as localized temperature increases caused by sunlight and humidity fluctuations caused by air conditioning operation need to be mapped in real time to the material reflection, transmission characteristics, and thermal radiation models in the virtual scene to ensure the feasibility and visual consistency of the design in the real environment. However, static parameter libraries and pre-calculated models cannot dynamically adjust the optical properties of materials, resulting in a disconnect between the virtual material reflection effect and the actual physical environment. Furthermore, lighting adjustments only affect global parameters, lacking fine-grained responses to local areas, causing distortion in material reflection and deviations in the simulation of temperature and humidity effects in the virtual scene.

[0003] Currently, the relevant technology adopts a scheme that combines a pre-calculated light field model with a fixed material parameter library: by pre-generating static light field data for different time periods, and with preset material reflectivity parameters, a pre-calculated light field model that matches the real-time light intensity collected by physical sensors is loaded into the virtual scene, and the global brightness and color temperature parameters are adjusted by linear interpolation. Summary of the Invention

[0004] This application provides a method and system for overall home design based on virtual reality, which solves the problem of material reflection distortion in virtual scenes in the prior art.

[0005] Firstly, this application provides a virtual reality-based home design method, including:

[0006] The temperature and humidity gradient data and multi-band light intensity distribution data of the indoor physical space are collected synchronously in a spatial gridded distribution mode by using a temperature and humidity sensor array and a multi-spectral light sensor in a distributed sensor network.

[0007] The temperature and humidity gradient data and multi-band light intensity data are input into the spatial topology association engine, and a set of three-dimensional environmental parameters including coordinate information, temperature and humidity parameters, light intensity and reflectivity association weights are constructed based on the gridded three-dimensional spatial structure generation algorithm.

[0008] Based on the spatial coordinate weight matrix in the set of three-dimensional environment parameters, the micro-electromechanical execution unit of the dynamic optical reflection film layer is driven to adjust the local inclination and refractive index of the film layer surface, and the scattering characteristic parameters of wood, metal and glass materials are matched in real time based on the indoor material surface characteristic database to generate an optical reflection characteristic distribution map;

[0009] Based on the real-time data of the optical reflection characteristic distribution map, a three-dimensional light field simulation model dynamically linked with the actual light distribution of the physical space is constructed in the virtual scene;

[0010] According to the real-time monitoring result of the change of the light intensity of the physical space, the light field distribution data of the three-dimensional light field simulation model are combined to trigger the adaptive compensation operation of the temperature and humidity parameters in the virtual scene, and the reflection characteristic parameters of the dynamic optical reflection film layer are adjusted synchronously to realize the bidirectional parameter collaborative optimization of the physical environment and the virtual light field.

[0011] Optionally, a spatial coordinate weight matrix is extracted from the set of three-dimensional environment parameters, and the spatial coordinate weight matrix contains a reflectivity correlation weight value corresponding to each grid node;

[0012] According to the reflectivity correlation weight value in the spatial coordinate weight matrix, the surface of the dynamic optical reflection film layer is divided into a plurality of dynamic adjustment regions, and the boundary of each dynamic adjustment region is determined by the weight difference value of adjacent grid nodes exceeding a preset segmentation threshold;

[0013] The reference scattering parameters of the current dynamic adjustment region corresponding to the material type are obtained from the material surface characteristic database, and the target adjustment amount of the local inclination and the target correction amount of the refractive index of the film layer surface are calculated according to the difference between the reflectivity correlation weight value of the current region and the reference scattering parameters;

[0014] Based on the target adjustment amount and the target correction amount, the inclination and the refractive index of the current region are synchronously adjusted to the physical state corresponding to the target adjustment amount by controlling the execution assembly to drive the film layer surface deformation mechanism;

[0015] The adjusted inclination value and the refractive index value of each dynamic adjustment region are combined according to the distribution rule of the spatial coordinate weight matrix, and the scattering characteristic parameters of wood, metal and glass materials are matched in real time based on the indoor material surface characteristic database to generate an optical reflection characteristic distribution map covering the film layer surface.

[0016] Optionally, the target adjustment amount and the target correction amount are input into a control signal conversion logic to generate a driving signal set corresponding to the physical deformation amount of the deformation mechanism, and the driving signal set contains an inclination driving signal component and a refractive index driving signal component;

[0017] According to a dynamic allocation strategy between components of the driving signal set, the tilt angle driving signal component and the refractive index driving signal component are synchronously and optimally allocated according to a preset priority rule to generate a set of collaborative control instructions executable by the deformation mechanism;

[0018] By controlling the signal analysis unit in the control execution component, the set of collaborative control instructions is converted into physical deformation parameters recognizable by the deformation driving unit, the physical deformation parameters including a deformation displacement, a deformation rate and a deformation direction;

[0019] The deformation driving unit is driven based on the physical deformation parameters to perform a deformation operation on the current region of the film layer surface, so that the local region of the film layer surface synchronously generates a tilt angle deformation displacement and a refractive index deformation displacement, a difference between the tilt angle deformation displacement and the target adjustment amount is not more than a preset deformation tolerance threshold, and a difference between the refractive index deformation displacement and the target correction amount is not more than a preset refractive index tolerance threshold;

[0020] The actual deformation parameters after the deformation driving unit is executed are fed back to the control signal conversion logic to update the signal component allocation proportion in the driving signal set, so that the tilt angle and the refractive index of the current region are synchronously adjusted to a physical state corresponding to the target adjustment amount.

[0021] Optionally, the light change rate of the target region in the physical space is monitored in real time, and the light intensity gradient value of the corresponding region is synchronously extracted from the three-dimensional light field simulation model;

[0022] Based on the correlation between the light change rate and the light intensity gradient value, a temperature and humidity compensation amount and a reflection characteristic adjustment amount of the target region are generated through adaptive compensation operation;

[0023] According to the temperature and humidity compensation amount, an environment parameter update instruction of the virtual scene is generated, and according to the reflection characteristic adjustment amount, a tilt angle and a refractive index correction instruction of the dynamic optical reflection film layer are generated;

[0024] By controlling the deformation driving unit to execute the tilt angle and refractive index correction instructions synchronously driven by the control execution component, and executing the environment parameter update instruction in the virtual scene, bidirectional parameter collaborative optimization of the physical environment and the virtual light field is realized.

[0025] Optionally, the temperature gradient value and the humidity gradient value in the temperature and humidity gradient data are data-associated according to the spatial coordinates to form a temperature and humidity distribution set, and the visible light band intensity value and the infrared band intensity value in the multi-band light intensity data are data-associated according to the same spatial coordinates to form a light intensity band distribution set;

[0026] Determine the reference plane of the three-dimensional coordinate system according to the wall structure boundary data of the physical space, and establish a three-dimensional grid division reference, divide the equidistant grid cells in the three-dimensional coordinate system based on the space coverage range of the temperature and humidity distribution set and the light intensity band distribution set;

[0027] Extract the temperature gradient mean value, humidity gradient mean value, visible light band intensity mean value and infrared band intensity mean value for each grid cell, and perform correlation calculation on the temperature gradient mean value and the visible light band intensity mean value to generate a temperature-light intensity correlation factor, and at the same time, perform correlation calculation on the humidity gradient mean value and the infrared band intensity mean value to generate a humidity band correlation factor;

[0028] Obtain the material reference reflectivity value of the area where the current grid cell is located from the indoor material surface characteristic database, generate the reflectivity correlation weight value of the current grid cell based on the weighted calculation result of the temperature-light intensity correlation factor and the humidity band correlation factor, and combine the material reference reflectivity value;

[0029] Combine the coordinate information, temperature gradient mean value, humidity gradient mean value, visible light band intensity mean value, infrared band intensity mean value and reflectivity correlation weight value of all grid cells in the order of three-dimensional coordinates to generate a three-dimensional environmental parameter set covering the physical space.

[0030] Optionally, extract the coordinate information, reflectivity weight value and material type identifier of each grid cell from the optical reflection characteristic distribution map, and obtain the corresponding surface scattering parameter and light absorption parameter from the material surface characteristic database according to the material type identifier;

[0031] Based on the visible light intensity mean value and the infrared light intensity mean value in the real-time lighting data of the physical space, combine the reflectivity weight value and the light absorption parameter to calculate the refractive index correction value and the light absorption correction value of each grid cell, and generate a dynamic refractive index parameter based on the refractive index correction value and the light absorption correction value and bind it with the grid cell coordinates;

[0032] Divide the scene space according to the grid cell coordinates in the virtual scene, adjust the propagation direction of the virtual light source according to the surface scattering parameter, and combine the light absorption correction value to attenuate the light brightness and thermal radiation intensity;

[0033] Based on the coordinate information, dynamic refractive index parameter and attenuation processing result of all grid cells, generate a three-dimensional light field simulation model covering the virtual scene.

[0034] Optionally, match the lighting change rate of the physical space with the light intensity gradient value of the corresponding area in the three-dimensional light field simulation model point by point according to the space coordinate alignment rule, and establish a product correlation model between the two;

[0035] generate a humidity compensation reference value and a reflection characteristic adjustment reference value based on the product correlation model;

[0036] generate a humidity compensation amount based on the humidity compensation reference value, by superimposing a deviation amount of a current humidity parameter of a target area and an expected parameter in the three-dimensional light field simulation model through a dynamic weight distribution rule, wherein the dynamic weight distribution rule is automatically adjusted according to a real-time fluctuation amplitude of an illumination change rate;

[0037] generate a reflection characteristic adjustment amount based on the reflection characteristic adjustment reference value, by combining a direction and amplitude of a light intensity gradient value and a current parameter of a reflection film layer, and through feedback optimization calculation.

[0038] In a second aspect, the present application provides a virtual reality-based overall home design system, comprising:

[0039] The acquisition module synchronously acquires humidity gradient data and multi-band illumination intensity distribution data of an indoor physical space in a spatial grid distribution mode through a humidity sensor array and a multi-spectral illumination sensor in a distributed sensing network.

[0040] The generation module inputs the humidity gradient data and the multi-band illumination intensity data into a spatial topology correlation engine, and constructs a three-dimensional environmental parameter set containing coordinate information, humidity parameters, illumination intensity and reflection rate correlation weights based on a grid three-dimensional space structure generation algorithm.

[0041] The matching module drives a micro-electromechanical execution unit of a dynamic optical reflection film layer to adjust a local inclination and refractive index of a film layer surface based on a spatial coordinate weight matrix in the three-dimensional environmental parameter set, and generates an optical reflection characteristic distribution map by combining real-time matching of scattering characteristic parameters of wooden, metallic and glass materials with an indoor material surface characteristic database.

[0042] The construction module constructs a three-dimensional light field simulation model dynamically linked with an actual illumination distribution of a physical space in a virtual scene based on real-time data of the optical reflection characteristic distribution map.

[0043] The adjustment module triggers adaptive compensation operation of humidity parameters in the virtual scene and synchronously adjusts reflection characteristic parameters of the dynamic optical reflection film layer to realize bidirectional parameter collaborative optimization of the physical environment and the virtual light field according to real-time monitoring results of illumination intensity changes of the physical space and in combination with light field distribution data of the three-dimensional light field simulation model.

[0044] In a third aspect, an embodiment of the present application provides a computing device comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a virtual reality-based overall home design method as described in the first aspect above.

[0045] In a fourth aspect, the embodiments of the present application provide a computer storage medium storing a computer program, which, when executed by a computer, implements the virtual reality-based overall home design method according to the first aspect.

[0046] In the scheme of the present application, the global synchronous perception of indoor environment parameters is realized through a distributed sensing network, providing a high-precision data substrate for virtual-real interaction; the three-dimensional environment parameter set constructed based on a space topology correlation engine forms a digital twin of the physical environment, solving the rendering misalignment problem caused by parameter discretization in traditional modeling; with the aid of nanoscale regulation and control of the dynamic optical reflection film layer and real-time matching of material scattering characteristics, atomic-level synchronization of the optical properties of the physical surface and the virtual model is realized; combined with the high-fidelity light field model generated based on the optical reflection characteristic data, the virtual scene light gradient is ensured to be consistent with the physical environment; finally, through the bidirectional parameter collaborative optimization mechanism, the cross-domain closed-loop feedback is achieved, the energy balance of the physical environment and the virtual light field is maintained in dynamic changes, the problems of material reflection distortion, local overexposure and response delay in traditional schemes are solved, and full-dimensional parameter coupling and millisecond-level synchronous optimization are realized.

[0047] Further, by extracting the space coordinate weight matrix in the three-dimensional environment parameter set, the surface of the dynamic optical reflection film layer is divided into multiple dynamic adjustment regions according to the judgment rule that the weight difference of adjacent grid nodes exceeds a preset threshold, realizing adaptive identification and accurate boundary division of the light mutation region; by matching the reference scattering parameters in the material surface characteristic database, the target adjustment amount of the film layer tilt angle and refractive index is calculated combined with the difference between the current region weight and the reference parameter, and the deformation mechanism is driven to execute parameter adjustment synchronously, ensuring the accurate matching of the optical properties of the physical film layer and the virtual material scattering behavior; finally, based on the weight matrix distribution law, the adjustment parameters of each region are integrated and an optical reflection characteristic distribution map is generated, forming a full-closed-loop control link from dynamic region segmentation to nanoscale parameter correction, solving the local reflection distortion problem caused by global adjustment in traditional methods, and realizing atomic-level synchronization of the virtual light field and the physical environment in the material reflection characteristic layer.

[0048] These and other aspects of the present application will become more apparent from the following description of some embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, a brief introduction will be given to the drawings needed in the embodiments or prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0050] Figure 1 A flow chart of a virtual reality-based overall home design method provided by the present application is shown;

[0051] Figure 2 A scene diagram of a virtual reality-based overall home design method provided by the present application is shown;

[0052] Figure 3 A structural schematic diagram of a virtual reality-based overall home design system provided by the present application is shown;

[0053] Figure 4 A structural schematic diagram of a computing device provided by the present application is shown. DETAILED DESCRIPTION

[0054] In order to enable persons skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application.

[0055] In some of the processes described in the specification and claims of the present application and the above-described drawings, a plurality of operations appear in a specific order, but it should be clearly understood that these operations can be executed or performed in parallel or in a sequence different from that in which they appear in the present text, and the serial numbers of the operations, such as 101, 102, etc., are only used to distinguish different operations, and the serial numbers themselves do not represent any execution sequence. In addition, these processes can include more or fewer operations, and the operations can be executed or performed in sequence or in parallel. It should be noted that the descriptions of “first”, “second”, etc. in the present text are used to distinguish different messages, devices, modules, etc., and do not represent the sequence, nor do “first” and “second” represent different types.

[0056] Researchers found that the traditional virtual reality home design system has the defect of environment parameter fragmentation: due to the static parameter library and the pre-computed model cannot dynamically adjust the optical properties of the material, resulting in the virtual material reflection effect being out of touch with the actual temperature and humidity, light state of the physical environment. At the same time, the light adjustment of the prior art only acts on the global parameters, lacks fine response to local areas such as the window periphery and the surface of furniture, causing distortion of the virtual scene material reflection and deviation of the temperature and humidity influence simulation, for example, the wood surface reflection rate deviates significantly from the true value, and the humidity compensation response delay is obvious. Therefore, there is an urgent need for a two-way optimization method that supports dynamic perception of the physical environment and real-time linkage of virtual light field parameters.

[0057] To solve the above problems, the application provides a virtual-real collaborative design method based on dynamic optical reflection film layer control, the core of which is to establish an atomic level parameter mapping and a bidirectional feedback mechanism between a physical environment and a virtual light field. Specifically, environmental parameters are collected in real time through a distributed sensing network, a three-dimensional parameter set is constructed through a space topology correlation engine, a micro-electromechanical execution unit is driven to accurately regulate the optical properties of the film layer, the scattering parameters are matched in combination with a material database, and a virtual-real interactive reflection characteristic distribution map is generated; based on a light field model and an adaptive compensation algorithm, the temperature and humidity parameters are quickly corrected and the reflection characteristics are synchronously adjusted, thereby significantly reducing the virtual material reflection distortion and the temperature and humidity simulation deviation. The method breaks through the limitations of the traditional static parameter library, greatly reduces the actual state error between the virtual material reflection effect and the physical environment, and solves the key problems of material reflection distortion and temperature and humidity simulation deviation by responding to the local light gradient in detail, such as quickly capturing the light intensity mutation of the window edge area.

[0058] The technical solution of the application can be applied to intelligent home virtual decoration design, high-precision indoor environment simulation and the like, and is especially suitable for immersive home decoration scheme verification and optimization which needs to reflect the dynamic changes of the physical space, such as day-night light difference and air conditioner temperature and humidity adjustment.

[0059] The technical solutions in the embodiments of the application will be clearly and completely described below with reference to the drawings in the embodiments of the application. Obviously, the described embodiments are only part of the embodiments of the application, rather than all the embodiments. Based on the embodiments in the application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the application.

[0060] Figure 1 A flowchart of a home overall design method based on virtual reality is provided for the embodiments of the application, as shown in Figure 1 The method comprises the following steps.

[0061] 101. Collecting temperature and humidity gradient data and multi-band light intensity distribution data of an indoor physical space in a spatial grid distribution mode through a temperature and humidity sensor array and a multi-spectral light sensor in a distributed sensing network;

[0062] In step 101, the distributed sensing network refers to a sensor node group connected through Zigbee or LoRaWAN communication protocols; the temperature and humidity sensor array refers to a collection of micro temperature and humidity detection units manufactured by MEMS technology; the multi-spectral light sensor refers to a light intensity detection device equipped with visible light, near-infrared and ultraviolet band filters; and the spatial grid distribution mode refers to a three-dimensional grid layout in which the indoor space is divided into 0.5m*0.5m*0.5m cubic units.

[0063] In this embodiment, firstly, an automated deployment robot equipped with a laser positioning module projects a 3D grid baseline onto the wall based on building information model (BIM) data, physically deploying the temperature and humidity sensor array and the multispectral light sensor according to the grid vertex coordinates. Secondly, the temperature and humidity sensor array activates its dual-channel acquisition module to simultaneously acquire the voltage value of the temperature-sensitive resistor and the charging and discharging time of the capacitive humidity detection unit at each grid point. Next, the multispectral light sensor drives a filter wheel via a stepper motor, sequentially switching between six preset wavelengths, including 450nm blue light, 550nm green light, and 650nm red light, continuously acquiring the photocurrent value of the silicon photodiode for 50ms in each wavelength band. Finally, all sensor nodes upload temperature and humidity gradient data with spatial grid encoding and multi-band light intensity distribution data to the edge computing gateway via the LoRaWAN protocol. After timestamp alignment and outlier removal, the gateway generates a structured spatial dataset containing 3D coordinates, temperature and humidity values, and six-band light intensity.

[0064] 102. Input the temperature and humidity gradient data and multi-band light intensity data into the spatial topology association engine, and construct a set of three-dimensional environmental parameters including coordinate information, temperature and humidity parameters, light intensity and reflectivity association weights based on the gridded three-dimensional spatial structure generation algorithm.

[0065] Optionally, step 102 may specifically include the following steps:

[0066] 1021. The temperature gradient value and humidity gradient value in the temperature and humidity gradient data are correlated according to spatial coordinates to form a temperature and humidity distribution set, and the visible light band intensity value and infrared band intensity value in the multi-band light intensity data are correlated according to the same spatial coordinates to form a light intensity band distribution set.

[0067] 1022. Determine the reference plane of the three-dimensional coordinate system based on the boundary data of the wall structure in the physical space and establish a three-dimensional mesh division reference. Divide the three-dimensional coordinate system into equally spaced mesh units based on the spatial coverage of the temperature and humidity distribution set and the light intensity band distribution set.

[0068] 1023. Extract the mean temperature gradient, mean humidity gradient, mean visible light intensity, and mean infrared intensity for each grid cell. Calculate the temperature gradient mean and the mean visible light intensity mean to generate a temperature-light intensity correlation factor. Simultaneously, calculate the humidity gradient mean and the mean infrared intensity mean to generate a humidity band correlation factor.

[0069] 1024. Obtain the material reference reflectance value of the current grid cell area from the indoor material surface property database, and generate the reflectance correlation weight value of the current grid cell based on the weighted calculation results of the temperature light intensity correlation factor and humidity band correlation factor, combined with the material reference reflectance value.

[0070] 1025. Combine the coordinate information of all grid cells, the average temperature gradient, the average humidity gradient, the average intensity of the visible light band, the average intensity of the infrared band, and the reflectivity-related weight value in the order of the three-dimensional coordinates to generate a set of three-dimensional environmental parameters covering the physical space.

[0071] In the above scheme, the spatial topology association engine refers to the computational module that establishes spatial data association relationships through graph theory algorithms; the meshed 3D spatial structure generation algorithm refers to the computational method that constructs a spatial mesh based on the Delaunay triangulation principle; the 3D environmental parameter set is a structured dataset composed of 3D coordinate information, mean temperature gradient, mean humidity gradient, mean visible and infrared light intensity, and reflectance association weight values. The temperature and humidity distribution set is formed by associating the spatial coordinates of temperature and humidity gradient values. The temperature gradient values ​​originate from the temperature difference data of adjacent meshes collected by temperature sensors, and the humidity gradient values ​​originate from the humidity difference data of adjacent meshes collected by humidity sensors; the light intensity band distribution set is formed by aligning the light intensity data of the visible light band (400-700 nm) and the infrared band (700-1100 nm) obtained by multispectral sensors according to coordinates; the 3D mesh partitioning benchmark is established based on the coordinate system origin and axial parameters determined by the wall structure in the building information model, including a 0.5-meter spacing definition in the XYZ axes; the temperature and light intensity association factors... The correlation coefficient between the mean temperature gradient and the mean intensity of the visible light band is calculated to characterize the degree of linear correlation between the two. The humidity band correlation factor is generated based on the covariance analysis of the mean humidity gradient and the mean intensity of the infrared band, reflecting the correlation between their dynamic changes. The material reference reflectance value is extracted from a pre-set database, including the standard reflectance values ​​of materials such as wall tiles or wood flooring in the 380 to 2500 nanometer band. The reflectance correlation weight value is calculated using the entropy method, and is formed by weighting the temperature and light intensity correlation factor (40%), the humidity band correlation factor (30%), and the material reference reflectance value (30%).

[0072] In the embodiments of the present application, the temperature gradient value and the humidity gradient value of each grid point in the temperature and humidity gradient data are bound by key-value pairs through a spatial coordinate matching algorithm in step 1021 to generate a temperature and humidity distribution set containing three-dimensional coordinates, temperature gradient values and humidity gradient values. At the same time, the visible light band intensity value and the infrared band intensity value in the multi-band light intensity data are aligned through the same coordinate mapping method to form a light intensity band distribution set containing coordinates, visible light intensity and infrared light intensity. In specific implementation, a hash table storage structure is used to associate the temperature gradient value and the humidity gradient value to the same key value with three-dimensional coordinates as the unique key value, and the time sequence consistency of the visible light intensity and the infrared light intensity is maintained through a double-linked list structure.

[0073] Secondly, the wall boundary coordinate data in the building information model in step 1022 is used to determine the reference plane of the three-dimensional coordinate system through the Delaunay triangulation algorithm, the intersection point of the ground at the southwest corner of the room is selected as the origin, the extension direction of the main wall is selected as the X axis, the vertical direction is selected as the Y axis, and the height direction is selected as the Z axis to establish the coordinate system; then, according to the spatial coverage range of the temperature and humidity distribution set and the light intensity band distribution set, an equal-interval grid division algorithm is used to generate cubic grid units along the XYZ axis at a step length of 0.5 meters, each unit is assigned a unique identifier through a spatial position encoder to ensure that all sensor data are completely contained in the grid units.

[0074] Then, data aggregation calculation is performed on each grid unit through step 1023: the arithmetic mean of all temperature gradient values in the unit is extracted as the temperature gradient mean value through a sliding window mean algorithm, and the humidity gradient mean value is calculated using an exponential weighted moving average method to eliminate transient fluctuations; at the same time, the geometric mean algorithm is applied to the visible light band intensity and the infrared band intensity respectively to generate the corresponding mean values; then the temperature gradient mean value and the visible light intensity mean value are input into a Pearson correlation coefficient calculation module to generate a temperature-light intensity correlation factor ranging from -1 to 1 through joint calculation of covariance and standard deviation; at the same time, covariance analysis is performed on the humidity gradient mean value and the infrared intensity mean value, and the humidity band correlation factor is generated after eliminating the time sequence difference using a dynamic time warping algorithm.

[0075] Then, the grid unit identifier is associated with the indoor material database through step 1024, the spatial position hash retrieval technology is used to obtain the reference reflectivity value of the wall or ground material where the current unit is located; then the temperature-light intensity correlation factor is subjected to Z-score standardization processing to map it to the 0-1 interval, and the humidity band correlation factor is subjected to Sigmoid function normalization; then a weight allocation scheme is determined based on the entropy method, the temperature-light intensity factor accounts for 40%, the humidity band factor accounts for 30%, and the material reflectivity accounts for 30%, and the reflectivity correlation weight value is calculated through a weighted sum formula; finally, the calculation result is subjected to Gaussian smoothing filtering to eliminate local mutation noise.

[0076] Finally, all grid cells are sorted by XYZ coordinate priority through step 1025, and the data storage order is optimized using a space-filling curve such as the Z-order curve; then a data tuple containing the coordinates, temperature gradient mean value, humidity gradient mean value, visible light intensity mean value, infrared intensity mean value, and reflectivity correlation weight value is constructed for each cell; then a fast retrieval structure of the three-dimensional environmental parameter set is established through the octree spatial indexing algorithm; finally, the spatial topology correlation engine verifies the topological relationship of all tuples to ensure that the parameter values of adjacent cells meet the gradient continuity constraint, and finally a three-dimensional environmental parameter set covering the physical space is generated.

[0077] In practical applications, for example, a virtual reality home design system simulates a real living environment accurately, and constructs a dynamic environmental response model in a digital twin space. When a user plans an intelligent residence through a VR device, the system fuses indoor air conditioner airflow simulation data and humidifier atomized particle trajectories according to three-dimensional coordinates to generate a dynamic temperature and humidity cloud chart with spatial attributes, and maps the sunlight waveband of a virtual window and the infrared thermal field data of a floor heating radiator to the same coordinate system to form a light-heat coupling distribution layer. Based on the wall profile and floor elevation of the house building model, the living room, bedroom, and other areas are divided into a three-dimensional grid matrix with a precision of 0.05 meters. When the user drags a virtual furniture, the system automatically increases the grid density of the overlapping area of the sofa and the floor heating pipe, and calculates the retardation effect of velvet material on heat conduction in real time. For the kitchen island area, the system extracts the dynamic correlation value of the temperature gradient of the quartz countertop and the visible light intensity of the ceiling lamp to generate a light-heat interference coefficient, and analyzes the correlation between the steam diffusion of a hidden dishwasher and the infrared radiation of a heating strip of a skirting board to calculate a condensation risk index. When the user switches the wall material from latex paint to diatomite mud, the system synchronously retrieves the moisture absorption rate and reflectivity parameters of the material database, dynamically corrects the light rendering parameters based on the light-heat interference coefficient of the current grid, and if it detects that the humidity weight of the green wall area is abnormal due to virtual transpiration, it triggers a material conflict warning and generates an optimization scheme. The final output three-dimensional environmental parameter set contains tens of thousands of intelligent grid cells, supporting designers to view the predicted data of any coordinate point, such as the temperature and humidity fluctuation curve of the window area in the afternoon of winter, or the sunlight fading simulation of the walnut bookcase under the influence of infrared reflectivity weight. When the user virtually turns on the fresh air system, the airflow particle special effect is accurately correlated with the humidity gradient data, and the window curtain swing amplitude and temperature diffusion pattern caused by air flow are presented in real time in the VR view, realizing deep collaborative verification of aesthetic design and environmental physical parameters.

[0078] In the complete scheme of step 102, through the fine fusion of multi-dimensional environmental parameters and dynamic weight calculation, accurate digital modeling of physical space environment characteristics is realized, the temperature and humidity gradient and multi-band light intensity are accurately associated according to the spatial coordinates, the strict correspondence of different environmental parameters to the spatial position is ensured, and the spatial misplacement distortion in the traditional simulation is eliminated; the reflectivity weight is dynamically generated by combining the temperature-light intensity factor and the humidity-band factor, and the influence of environmental parameters on the optical properties of the material is adaptively adjusted; the three-dimensional grid reference is constructed by the wall structure boundary, and the local parameter mean value is extracted to realize multi-scale feature analysis; at the same time, based on the material database, the reflectivity weight of the grid unit is matched in real time, and the dynamic optical properties of different materials under the change of temperature and humidity are accurately reflected, which breaks through the limitation of static reflectivity preset. This technology significantly improves the matching accuracy of the actual state of the virtual scene and the physical space, and lays a high credible data foundation for subsequent optical reflection feature generation and virtual-real collaborative optimization.

[0079] 103、based on the spatial coordinate weight matrix in the three-dimensional environmental parameter set, driving the micro-electromechanical execution unit of the dynamic optical reflection film layer to adjust the local inclination and refractive index of the film layer surface, combining the scattering characteristic parameters of wood, metal and glass materials in the indoor material surface property database to generate an optical reflection feature distribution map;

[0080] Optionally, step 103 can specifically include the following steps:

[0081] 1031、extract the spatial coordinate weight matrix from the three-dimensional environmental parameter set, the spatial coordinate weight matrix contains the reflectivity correlation weight value corresponding to each grid node;

[0082] 1032、according to the reflectivity correlation weight value in the spatial coordinate weight matrix, the surface of the dynamic optical reflection film layer is divided into multiple dynamic adjustment regions, and the boundary of each dynamic adjustment region is determined by the weight difference value of adjacent grid nodes exceeding a preset segmentation threshold;

[0083] 1033、obtain the baseline scattering parameters of the current dynamic adjustment region corresponding to the material type from the material surface property database, and calculate the target adjustment amount of the local inclination and the target correction amount of the refractive index of the film layer surface according to the difference between the reflectivity correlation weight value and the baseline scattering parameters of the current region;

[0084] 1034、based on the target adjustment amount and the target correction amount, the film layer surface deformation mechanism is driven by controlling the execution assembly to synchronously adjust the inclination and the refractive index of the current region to the physical state corresponding to the target adjustment amount;

[0085] The step 1034 can specifically include the following processes: inputting the target adjustment amount and the target correction amount into a control signal conversion logic, generating a driving signal set corresponding to the physical deformation amount of the deformation mechanism, the driving signal set including an inclination driving signal component and a refractive index driving signal component; according to a dynamic allocation strategy between the components of the driving signal set, synchronously optimizing and allocating the inclination driving signal component and the refractive index driving signal component according to a preset priority rule, to generate a set of cooperative control instructions executable by the deformation mechanism; converting, by a signal analysis unit in the control execution component, the set of cooperative control instructions into physical deformation parameters recognizable by the deformation driving unit, the physical deformation parameters including a deformation displacement amount, a deformation rate, and a deformation direction; driving the deformation driving unit to perform a deformation operation on the current region of the film layer surface based on the physical deformation parameters, so that the local region of the film layer surface synchronously generates an inclination deformation displacement and a refractive index deformation displacement, a difference between the inclination deformation displacement and the target adjustment amount being not more than a preset deformation tolerance threshold, and a difference between the refractive index deformation displacement and the target correction amount being not more than a preset refractive index tolerance threshold; feeding back the actual deformation parameters after the deformation driving unit is executed to the control signal conversion logic, and updating the signal component allocation proportion in the driving signal set, so that the inclination and the refractive index of the current region are synchronously adjusted to a physical state corresponding to the target adjustment amount.

[0086] 1035. Combining the adjusted inclination value and the refractive index value of each dynamic adjustment region according to the distribution rule of the spatial coordinate weight matrix, and combining the scattering characteristic parameters of wood, metal, and glass materials in real time by matching the indoor material surface characteristic database, to generate an optical reflection characteristic distribution map covering the film layer surface.

[0087] In the above scheme, the three-dimensional environment parameter set refers to a three-dimensional space data set containing spatial coordinates, reflectivity and material type, the spatial coordinate weight matrix refers to a matrix composed of grid node reflectivity associated weight values, used to represent the influence degree of different positions on optical reflection characteristics; the dynamic optical reflection film layer refers to an intelligent film that can adjust the surface inclination and refractive index through a micro-electromechanical execution unit, the micro-electromechanical execution unit refers to a micro driver that realizes film deformation based on MEMS technology; the material surface characteristic database refers to a structured data set storing the reference scattering parameters of wood, metal, glass and other materials; the scattering characteristic parameter refers to the reflectivity, scattering angle and polarization characteristic quantitative index related to the optical properties of the material surface; the dynamic adjustment region refers to the film layer surface partition divided according to the weight difference value, the segmentation threshold refers to the minimum weight difference value that triggers the region boundary division; the reference scattering parameter refers to the standard reflection characteristic parameter corresponding to the material type in the material database, the target adjustment amount refers to the film layer inclination change amount that needs to be adjusted to achieve the target reflectivity, the target correction amount refers to the refractive index change amount that needs to be adjusted; the control execution component refers to a hardware module including signal conversion and drive control, the deformation mechanism refers to a physical execution device that realizes synchronous adjustment of inclination and refractive index; the optical reflection characteristic distribution map refers to a spatial distribution map reflecting the reflectivity, scattering angle and other optical properties of each region on the film layer surface, which is generated by combining the real-time adjustment parameters and the material database.

[0088] In the embodiment of the application, through the three-dimensional grid data analysis algorithm of step 1031, the spatial coordinates of the three-dimensional environment parameter set are analyzed, and the original data containing X / Y / Z axis coordinates and reflectivity weight are extracted. Then, the spatial interpolation technology based on Gaussian kernel function is adopted to convert the discrete coordinate points into uniformly distributed grid nodes, and the reflectivity associated weight value of each node is calculated through the weighted fusion algorithm. The weight value is obtained by normalizing the product of ambient light intensity, line of sight incidence angle and material reflectivity. Secondly, the matrix compression encoding technology is used to map the grid node coordinates and weight values into a two-dimensional matrix structure, and a spatial coordinate weight matrix is generated. Finally, the data verification module detects the matrix integrity, and outputs the standardized weight matrix after removing the abnormal nodes, providing a data basis for dynamic region division.

[0089] Secondly, the spatial coordinate weight matrix is subjected to neighborhood gradient calculation through step 1032, and the Sobel edge detection algorithm is used to traverse each grid node to calculate the weight difference value of the eight adjacent nodes. Then, a dynamic segmentation threshold is set, when the weight difference value of the adjacent nodes is detected to exceed the threshold, the region boundary marker is triggered, and the boundary is extended to the surrounding through the region growing algorithm until the node with a weight difference value lower than the threshold is encountered, forming a closed dynamic adjustment region. Secondly, morphological closing operation is used to smooth the region boundary, eliminate the jagged edges, and merge the small fragmented regions through connected component analysis technology. Finally, a unique identification code is assigned to each dynamic adjustment region, and the material type code of the region center point is associated to generate a partition topology map with material properties, which is used for subsequent scattering parameter matching.

[0090] Then, the material code of the dynamic adjustment region is retrieved from the material surface characteristic database to retrieve the corresponding reference scattering parameters: the bidirectional reflectance distribution function model parameters are called for wood materials, the specular reflectance-angle of incidence curve is extracted for metal materials, and the transmittance-refractive index mapping table is loaded for glass materials. Then, the reflectivity associated weight value of the current region is compared with the reference parameters using the difference compensation algorithm: for wood regions, the deviation between the actual reflectivity and the target value is fitted by the least squares method to calculate the tilt angle adjustment amount; for metal regions, the refractive index correction amount is iteratively solved by using the gradient descent method to make the specular reflectivity approach the target value; for glass regions, the tilt angle and refractive index parameters are simultaneously optimized, and the Lagrange multiplier method is used to balance the weight relationship between transmission and reflection. Secondly, the feasibility of the target adjustment amount and the correction amount is verified through the physical constraint detection module, if it exceeds the maximum deformation range of the deformation mechanism, the parameter scaling algorithm is triggered to compress the adjustment amount in proportion. Finally, the partition control instruction set containing the tilt angle target adjustment amount, the refractive index target correction amount and the execution priority is generated and delivered to the control execution component.

[0091] Then, the target adjustment amount and the correction amount are converted into driving signals by a multi-channel signal converter in step 1034: the tilt angle control channel generates a piezoelectric ceramic driving voltage signal using pulse width modulation technology, and the refractive index control channel outputs a gradient electric field intensity required for the electrowetting effect through a digital-to-analog converter. Next, the deformation mechanism performs adjustment: for tilt adjustment, the piezoelectric ceramic array generates nanoscale deformation according to the voltage signal, the actual tilt angle is measured in real time by a laser interferometer, and a PID control algorithm is used to dynamically correct the driving signal; for refractive index adjustment, the electrowetting effect drives the molecular rearrangement of the medium layer, an ellipsometer is used to monitor the refractive index change online, and a fuzzy logic controller is used to compensate for the parameter drift caused by environmental temperature. Secondly, a time synchronization controller is used to ensure the phase consistency of the tilt angle and refractive index adjustment, and a hardware interrupt mechanism is used to coordinate the execution timing of the two types of driving signals. Finally, the actual deformation parameters are collected through multi-sensor fusion technology, and if the residual error between the actual value and the target value exceeds the tolerance threshold, the iterative adjustment process is triggered until the optical performance requirements are met.

[0092] Finally, the adjusted tilt angle and refractive index data of each dynamic adjustment region are spatially interpolated according to the distribution rule of the spatial coordinate weight matrix in step 1035: the double cubic spline interpolation algorithm is used to smooth the transition of the tilt angle value in the wood-dominated region, the inverse distance weighting method is used to interpolate the refractive index in the metal region, and the hybrid interpolation strategy based on the physical optics model is used in the glass region. Then, the material surface characteristic database is called to superimpose the material-specific scattering characteristics for each interpolation point: the Lambertian diffuse reflection model is superimposed in the wood region, the anisotropic highlight model is fused in the metal region, and the Fresnel transmission compensation parameters are integrated in the glass region. Secondly, the light ray tracing engine is used to simulate the optical reflection characteristics of the film surface, the Monte Carlo method is used to randomly sample the light path, and an optical spectrum containing reflectivity intensity distribution, scattering angle range and polarization state change is generated. Finally, the optical data is converted into a visual distribution map in the RGB color space through the visualization rendering pipeline, and embedded into the augmented reality system for real-time projection calibration, ensuring that the spatial matching accuracy of the optical reflection characteristics and the real environment meets the design requirements.

[0093] In practical applications, for example, a certain smart home virtual design platform simulates the light and shadow interaction in a sunlight room by dynamically adjusting the environment through a dynamic optical reflection film layer. When the user switches the material of the light control glass curtain wall in the virtual space to electrochromic film, the system first extracts the spatial coordinate weight matrix of the curtain wall area from the three-dimensional environment model, where each 0.1-meter-precision grid node carries a reflectivity-related weight value. The west pane has a weight value of 0.92 due to the simulation of strong afternoon sunlight, and the north bookshelf projection area has a weight of only 0.35. The system automatically detects the weight difference of adjacent grid nodes on the curtain wall surface, divides the area with a weight difference exceeding the preset threshold of 0.3 into 7 dynamic adjustment units, including a high-weight sunlight core area, a transition zone, and a low-weight shadow area, and the southeast corner forms an irregular polygon boundary due to the virtual green plant shading. Based on the reference scattering parameters of electrochromic glass, the system adjusts the optical parameters of the high-weight area: the surface inclination angle of the sunlight core area is adjusted to 12.5 degrees to weaken the incident angle of direct light, and the refractive index is modified to 1.48 to achieve selective attenuation of blue light bands; the shadow area maintains an inclination angle of 5 degrees and increases the refractive index to 1.55 to enhance diffuse reflection. The micro piezoelectric ceramic array on the virtual film surface responds synchronously, driving 120 actuation units to cooperatively deform and construct micro-prism structure groups, and through voltage control of liquid crystal molecule density, the refractive index is stabilized to the target value within 0.2 seconds. The generated dynamic optical reflection feature distribution map interacts with the material database in real time, the wooden decorative wall maps a soft light spot, the metal lampshade generates a sharp highlight cutoff line, and the glass tea table superimposes a Fresnel reflection special effect. When the user rotates the virtual sofa orientation, the system presents in real time how the diamond-shaped light spot on the west curtain wall shifts from the cortex sofa surface to the marble floor, while maintaining the indoor illuminance value in the comfortable range of 500 to 550 lux.

[0094] In the complete scheme of step 103, the physical optical reflection characteristics are precisely and dynamically regulated through real-time matching of the dynamic analysis of the spatial coordinate weight matrix and the material characteristics, and the technical effects are as follows: based on the reflectivity-related weight value, the dynamic optical reflection film layer is intelligently divided into regions, so that the adjustment region boundary accurately corresponds to the physical space structure characteristics; through real-time matching of the scattering characteristic reference parameters of wood, metal, and glass materials in the material surface characteristic database, the target adjustment amount of the inclination angle and the refractive index of the film layer is calculated in combination with the reflectivity weight difference, the micro-electromechanical execution unit is driven to realize nanoscale deformation control, and it is ensured that the film layer reflection characteristics are dynamically consistent with the material optical behavior of the virtual scene; the adjusted inclination angle, refractive index parameters, and material scattering characteristics are synchronously fused to generate an optical reflection feature distribution map covering the film layer surface, accurately simulating the reflection light intensity gradient change of different materials under the coupling effect of temperature, humidity, and light, providing high-fidelity physical optical parameter input for the virtual light field model, and significantly improving the real-time performance and optical consistency of virtual-real environment interaction.

[0095] 104. constructing a three-dimensional light field simulation model dynamically linked with the actual light distribution of the physical space in the virtual scene based on real-time data of the optical reflection feature distribution map;

[0096] Optionally, step 104 can specifically include the following steps:

[0097] 1041. extracting the coordinate information, reflectivity weight value and material type identifier of each grid cell from the optical reflection feature distribution map, and obtaining the corresponding surface scattering parameter and light absorption parameter from the material surface characteristic database according to the material type identifier;

[0098] 1042. calculating the refractive index correction value and light absorption correction value of each grid cell based on the average visible light intensity and the average infrared light intensity in the real-time light data of the physical space, combining the reflectivity weight value and the light absorption parameter, generating a dynamic refractive index parameter based on the refractive index correction value and the light absorption correction value, and binding the dynamic refractive index parameter with the grid cell coordinates;

[0099] 1043. dividing the scene space according to the grid cell coordinates in the virtual scene, adjusting the propagation direction of the virtual light source according to the surface scattering parameter, and performing attenuation processing on the light source brightness and thermal radiation intensity in combination with the light absorption correction value;

[0100] 1044. generating a three-dimensional light field simulation model covering the virtual scene based on the coordinate information, dynamic refractive index parameter and attenuation processing result of all grid cells.

[0101] In the above steps, the optical reflection feature distribution map refers to the data structure generated in step 103, which includes grid cell coordinates, reflectivity weight value and material type; the three-dimensional light field simulation model refers to a virtual light field model constructed by a ray tracing algorithm, which is dynamically linked with the real-time light distribution of the physical space; the material type identifier is a string composed of three codes, which is used to uniquely distinguish the surface material categories such as wall, floor or furniture; the surface scattering parameter is the Lambertian reflection coefficient extracted from the material database, which represents the diffuse reflection intensity of the material surface to light; the light absorption parameter refers to the light energy absorption rate percentage of the material in a specific waveband such as visible light and infrared; the refractive index correction value is a dynamic refractive index adjustment amount calculated by the Fresnel formula combining the reflectivity weight value and the light absorption parameter; the light absorption correction value is the product of the average infrared light intensity and the light absorption parameter, which reflects the actual energy attenuation ratio under the current lighting condition; the dynamic refractive index parameter is a dynamic adjustment parameter bound with the grid cell coordinates, which is used to update the light refraction behavior of the virtual scene in real time; the three-dimensional light field simulation model finally contains the spatial coordinates, dynamic refractive index parameter and light source attenuation data of all grid cells, and realizes the synchronous change of the virtual light field and the physical light through the bidirectional reflectance distribution function (BRDF) rendering engine.

[0102] In the embodiment of the present application, the data parsing engine reads the optical reflection feature distribution map through step 1041, uses regular expression matching algorithm to extract the XYZ coordinate value, reflectivity weight value and 8-bit material type identification code of each grid cell. Secondly, the material type identification code is input into the preset hash index database, and the binary search algorithm is used to quickly locate the corresponding surface scattering parameters, including diffuse reflection coefficient and specular reflection coefficient, and light absorption parameters, including visible light band absorption rate and infrared band absorption rate. Finally, through the data verification module, the parameter threshold range is compared, and the abnormal parameters exceeding the allowed value are automatically replaced with the default material parameters to ensure data reliability.

[0103] Secondly, the visible light intensity mean value and the reflectivity weight value are input into the Fresnel formula calculation module through step 1042, combined with the refractive index benchmark value in the material surface scattering parameter, the refractive index correction value is obtained by iterative method, the precision reaches four decimal places. Secondly, the infrared light intensity mean value and the light absorption parameter are substituted into the Beer-Lambert law, and the light absorption correction value is generated by using the linear interpolation algorithm. Then the refractive index correction value and the light absorption correction value are packaged into a dynamic refractive index parameter package in JSON format through the dynamic parameter binder, and a bidirectional mapping relationship is established between them and the corresponding grid cell coordinates by using the spatial coordinate hash algorithm, and they are written into the distributed memory database in real time.

[0104] Then, through the three-dimensional scene segmentation engine of step 1043, the virtual scene is divided into equal-volume cubic blocks according to the grid cell coordinates, and the octree spatial index algorithm is used to optimize the block management efficiency. Secondly, based on the diffuse reflection coefficient in the surface scattering parameter, the propagation path of the virtual light source is recalculated by using the Monte Carlo ray tracing algorithm, and the bidirectional reflectance distribution function model is used to adjust the light incidence angle and reflection angle. Finally, the light absorption correction value is input into the light attenuation calculation module, and the exponential decay function is applied to the RGB brightness value of the virtual light source, and the segmented linear interpolation algorithm is used to dynamically weaken the thermal radiation intensity, realizing the synchronous response to the physical space light change.

[0105] Finally, the coordinate information, dynamic refractive index parameter and light source attenuation parameter of all grid cells are normalized by the spatial data aggregator in step 1044, and the Z-order curve coding is used to realize the linearization storage of three-dimensional space data. Secondly, the layered bounding box acceleration structure is constructed in the ray tracing rendering engine, and the dynamic refractive index parameter and the bidirectional reflectance distribution function material property are bound to each triangular facet. Finally, through the real-time light field synthesizer, the path tracking calculation result and the photon mapping data are fused to generate a three-dimensional light field simulation model containing radiation brightness distribution, shadow gradient zone and thermal radiation intensity gradient, and the model data is realized real-time streaming to the VR head-mounted device through the WebGL interface.

[0106] In practical applications, for example, a virtual home design system simulates the light and shadow effect of a duplex villa. When the user replaces the natural marble tea table in the center of the living room with an acrylic material through the VR handle, the system immediately extracts the grid data of the tea table area from the current optical reflection characteristic distribution map, including 256 grid unit coordinates with a precision of 0.05 meters, reflectivity weight values, and material identification codes, and retrieves the surface scattering rate 0.78 and infrared absorption coefficient 0.32 of the acrylic material from the material database. Combined with the visible light intensity 920 lux and infrared radiation intensity 150 watts per square meter data projected by the south-facing floor-to-ceiling window obtained by the real-time lighting engine, the system calculates the refractive index correction value of each grid unit: adjusts the original marble refractive index 1.55 to 1.49 for acrylic material, and at the same time, according to the incident angle of the afternoon sunlight, the light absorption correction value is increased, and a dynamic optical parameter set bound to the grid is generated. The virtual scene engine immediately segments the three-dimensional space where the tea table is located, adjusts the 56 virtual light sources of the ceiling lamp to a soft light projection mode with a diffusion angle of 42 degrees according to the anisotropic scattering characteristics of the acrylic material, and performs a 22% gradient attenuation process on the infrared radiation intensity penetrating the tea table. When the user rotates the viewing angle to observe, the system presents the change of light in real time: the rainbow halo on the acrylic surface due to the decrease of refractive index is enhanced compared with the original marble material, and the focal spot area of infrared heat radiation on the wooden floor is reduced to 1 / 3 of the original. The final generated three-dimensional light field model contains 47,000 dynamic parameter nodes. When the outdoor simulation weather is switched to the rainy mode, the system automatically triggers a secondary correction based on the humidity sensor simulation data to increase the refractive index of the glass sliding door area by 0.07 to enhance the water mist refraction effect, so that the deviation rate of the light ray trajectory between the fog metal chandelier and the velvet sofa in the virtual space and the real physical experiment data is reduced.

[0107] In the complete scheme of step 103, the grid unit coordinates, reflectivity weight, and material type are extracted based on the real-time data of the optical reflection characteristic distribution map, accurately mapping the light distribution characteristics of the physical space; the refractive index correction value and the light absorption correction value are dynamically calculated based on the material surface scattering parameters and light absorption parameters, ensuring that the refractive behavior of the virtual light field is synchronized in real time with the actual light changes of the physical space; the scattering attenuation effect of different material surfaces is accurately simulated through dynamic adjustment of the propagation direction of the virtual light source and brightness attenuation processing; finally, the three-dimensional light field model covering the virtual scene is generated by fusing the dynamic refractive index parameters and the attenuation processing results, so that the spatial light intensity gradient distribution, material reflection characteristics, and actual light state of the physical space of the virtual light field remain atomically consistent, effectively solving the light distortion and response delay problems caused by static parameter preset in traditional virtual light field modeling, and providing high-precision light field data support for bi-directional collaborative optimization of virtual and real environments.

[0108] 105、According to the real-time monitoring result of the change of the illumination intensity of the physical space, in combination with the light field distribution data of the three-dimensional light field simulation model, adaptive compensation operation of the temperature and humidity parameters in the virtual scene is triggered, the reflection characteristic parameters of the dynamic optical reflection film layer are synchronously adjusted, and bidirectional parameter collaborative optimization of the physical environment and the virtual light field is realized.

[0109] Optionally, step 105 can specifically include the following steps:

[0110] 1051、Real-time monitoring of the light change rate of the target region of the physical space, and synchronously extracting the light intensity gradient value of the corresponding region from the three-dimensional light field simulation model;

[0111] 1052、Based on the correlation between the light change rate and the light intensity gradient value, the temperature and humidity compensation amount and the reflection characteristic adjustment amount of the target region are generated through adaptive compensation operation;

[0112] Wherein, step 1052 can specifically include the following contents: the light change rate of the physical space and the light intensity gradient value of the corresponding region in the three-dimensional light field simulation model are matched point by point according to the space coordinate alignment rule, and the product correlation model of the two is established; based on the product correlation model, the temperature and humidity compensation reference value and the reflection characteristic adjustment reference value are generated; based on the temperature and humidity compensation reference value, the deviation amount between the current temperature and humidity parameters of the target region and the expected parameters in the three-dimensional light field simulation model is superimposed through a dynamic weight distribution rule to generate a temperature and humidity compensation amount, wherein the dynamic weight distribution rule is automatically adjusted according to the real-time fluctuation amplitude of the light change rate; based on the reflection characteristic adjustment reference value, in combination with the direction and amplitude of the light intensity gradient value and the current parameters of the reflection film layer, the reflection characteristic adjustment amount is generated through feedback optimization calculation.

[0113] 1053、According to the temperature and humidity compensation amount, the environment parameter update instruction of the virtual scene is generated, and according to the reflection characteristic adjustment amount, the inclination and refractive index correction instruction of the dynamic optical reflection film layer is generated;

[0114] 1054、Through the control execution assembly, the inclination and refractive index correction instruction is synchronously driven to execute the deformation driving unit, and the environment parameter update instruction is executed in the virtual scene, so as to realize the bidirectional parameter collaborative optimization of the physical environment and the virtual light field.

[0115] In the above steps, the light intensity change rate refers to the change amount of the light intensity of the target area of the physical space collected by the multi-spectral sensor in real time per unit time, quantified in units of lux per second; the light intensity gradient value refers to the change rate of the light intensity on the X, Y, Z axis direction of the specific spatial coordinate point extracted from the three-dimensional light field simulation model, which is calculated by the central difference algorithm; the adaptive compensation operation refers to the calculation process of dynamically calculating the target area temperature and humidity and the optimization amount of the reflective film layer parameters based on the fuzzy PID control algorithm; the temperature and humidity compensation amount refers to the temperature and humidity adjustment value generated by the weighted integral operation according to the deviation value of the real-time monitoring data and the expected model parameters; the reflection characteristic adjustment amount refers to the reflection film layer inclination angle and refractive index correction value obtained by iterative optimization according to the difference between the light field distribution data and the physical reflection characteristics through the gradient descent method; the environmental parameter update instruction refers to the control signal containing the target temperature, humidity set value and change rate, which is used to drive the virtual scene rendering engine to update the environmental parameters; the inclination angle and refractive index correction instruction refers to the digital control instruction set containing the stepping motor rotation angle, piezoelectric ceramic driving voltage and other execution parameters; the control execution component refers to the hardware system composed of a stepping motor, a servo driver and a DAC module, which is used to physically execute the reflective film layer parameter adjustment action; the deformation driving unit refers to a reflective film layer physical deformation execution mechanism made of shape memory alloy or micro-electro-mechanical system, which can accurately control the film surface curvature and inclination angle; the two-way parameter collaborative optimization refers to the synchronous optimization process of realizing the linkage of the entity space and the digital scene parameters through the closed-loop feedback mechanism of the physical environment sensor data and the virtual light field simulation results.

[0116] In the embodiment of the present application, the light intensity time series data of the target area of the physical space is acquired in real time by the multi-thread data acquisition system of step 1051, and after the sensor noise is eliminated by using the Kalman filtering algorithm, the light intensity change rate in each 0.5 second time window is calculated, with the unit being lux / second. Secondly, the coordinate mapping relationship in the three-dimensional light field simulation model is matched by using the spatial encoder, and the light intensity gradient value of the corresponding grid element in the X / Y / Z axis direction is extracted by using the octree fast retrieval algorithm. Finally, the light intensity change rate and the light intensity gradient value are aligned by time stamp and stored in the ring buffer, providing a real-time data source for subsequent associated calculation.

[0117] Secondly, the light intensity change rate and the light intensity gradient value are input into the fuzzy PID control algorithm through step 1052, the correlation between the two is quantified into a fuzzy rule matrix by using the membership function, and the preliminary value of the temperature and humidity compensation amount is generated by de-fuzzification operation. Secondly, the gradient descent method is used to iteratively calculate the reflection characteristic adjustment amount based on the normalized XYZ components of the direction vector of the light intensity gradient value and the current inclination angle parameter of the reflective film layer, so that the thermal radiation distribution of the virtual light field is minimized. Finally, the preliminary value of the temperature and humidity compensation amount and the historical compensation data are subjected to sliding average filtering by using the weighted fusion algorithm, and the final compensation amount and adjustment amount are output.

[0118] Then, the temperature and humidity compensation values are converted into virtual scene environment parameter update instructions by step 1053: the temperature compensation value is mapped to the set value range of the virtual temperature control system by a linear interpolation algorithm, and the humidity compensation value generates a gradual adjustment curve by an exponential smoothing algorithm. Both are packaged into a JSON format instruction package. Next, the tilt angle correction value in the reflection characteristic adjustment value generates a stepping motor rotation angle instruction by a quaternion conversion algorithm, and the refractive index correction value is converted into a 0-10V analog voltage signal by a DAC module to form a digital control instruction set containing execution timing. All instructions are synchronized by a time stamp synchronization module to ensure millisecond-level synchronization between physical execution and virtual update.

[0119] Finally, the tilt angle and refractive index correction instructions are issued to the control execution component through the CAN bus of step 1054: the stepping motor driver receives the pulse signal to drive the deformation driving unit such as the piezoelectric ceramic actuator to realize the nanoscale tilt angle adjustment of the reflective film layer, and the DAC module outputs the voltage signal to adjust the refractive index of the liquid crystal layer. Next, the virtual scene rendering engine analyzes the environment parameter update instruction, smoothes the transition of temperature and humidity parameters by a bilinear interpolation algorithm, and synchronously updates the medium absorption coefficient in the light ray tracing calculation. Finally, through a closed-loop feedback mechanism, the deviation between the physical sensor data and the virtual light field simulation result is compared, and if it exceeds the threshold, the compensation amount is recalculated until the two-way parameter collaborative optimization reaches steady state convergence.

[0120] In actual application, for example, a certain intelligent home virtual design system simulates the linkage space of an open kitchen and a living room, and realizes dynamic optimization through virtual-real environment two-way mapping technology. When the intelligent dimming glass curtain wall in the real physical space causes the transmittance to increase within 30 seconds due to actual sunlight enhancement, the system synchronously captures the light change rate of the region reaching 180 Lux / s, and extracts the instantaneous light intensity gradient value 0.78 of the corresponding virtual region from the three-dimensional light field model. Through adaptive compensation algorithm calculation, it is concluded that the reflection characteristics of the virtual island table quartz surface need to be enhanced by 19% to suppress glare, and the air speed of the virtual air outlet of the air conditioner needs to be increased by 0.3 m / s to compensate for temperature fluctuations. The system immediately generates two-way control instructions: in the physical space, drive the micro-hydraulic actuator array of the dynamic reflective film layer, adjust the tilt angle of the micro-prism on the 0.6 m 3 2 ​immediately reverse-optimizes the virtual material parameters - reduces the mirror reflection weight of the bar stool chrome material by 0.22, and at the same time increases the virtual air convection speed in the seat area, so that the surface temperature simulation value of the leather material is stabilized in the comfortable interval of 41℃±0.5. This two-way control mechanism completes the full-link response within 0.5 seconds, and the physical curtain surface reduces the accumulation of direct light heat by 12% due to dynamic adjustment. The spot color temperature offset value of the marble ground in the virtual scene is controlled within 150K. The optimized parameter set is synchronized to the intelligent air conditioning and lighting system in the real space through the Internet of Things interface, forming a cross-dimensional environmental parameter closed-loop control, and finally realizing the cooperative optimization of virtual design preview and real home energy consumption.

[0121] In the complete scheme of the above step 105, through the cooperation of illumination change monitoring and light field data analysis, the dynamic closed-loop optimization of physical environment and virtual light field is realized, and the technical effect is embodied as: real-time capture of physical space illumination intensity change characteristics, combined with the light intensity gradient data of the three-dimensional light field model to establish the environmental parameter correlation mapping, triggering the temperature and humidity compensation algorithm to intelligently generate adjustment parameters; synchronously drive the inclination and refractive index correction of the dynamic optical reflection film layer, and update the virtual scene environmental parameters, to ensure that the material reflection characteristics and temperature and humidity influence effects of the virtual and real environments are matched in real time; through the two-way instruction cooperative execution mechanism, the hysteresis limitation of traditional one-way parameter adjustment is broken through, so that the physical reflection characteristics and virtual light field state continue to converge to the optimal balance in dynamic changes, significantly improving the authenticity of environmental simulation and the robustness of system response in the home design scene.

[0122] The following is a complete embodiment based on steps 101 to 105:

[0123] When simulating a living room environment, a certain intelligent home VR design platform collects indoor temperature and humidity gradient and multi-spectral illumination data in real time through a distributed sensor array, and constructs a high-precision three-dimensional environmental parameter model. When the user adjusts the opening degree of the virtual space intelligent curtain, the system synchronously analyzes the physical space sensor data and marks the light intensity mutation area in the three-dimensional grid model, such as the high infrared radiation belt formed by the sunlight directly shining on the west window, and automatically generates a light spot thermal map corresponding to the virtual scene. The dynamic optical reflection film layer adjusts the surface microstructure according to the reflectivity weight value in the model: in the strong light irradiation area, the film layer increases the tilt angle by 10 degrees and reduces the refractive index, effectively dispersing the direct light; the virtual engine synchronously matches the material parameters, adds the Fresnel reflection special effect to the marble floor, and makes the light and shadow effect conform to the real physical law. When the physical sensor detects that the temperature in a certain area abnormally rises, the system bidirectionally triggers the virtual air conditioner to increase the wind speed and the real film layer to fine-tune the refractive index, reducing the thermal radiation intensity by 15% within 0.8 seconds, while maintaining the virtual scene leather sofa surface temperature simulation value stable in the ±0.5℃ fluctuation range. The system realizes real-time mutual feedback between virtual and real environment parameters, so that the lighting layout scheme verified by the designer in VR can be directly output as the intelligent lighting control parameters of the physical space, ensuring that the energy efficiency and light and shadow effect error rate of the design scheme are reduced when it is actually implemented.

[0124] Figure 3 A structure diagram of a home overall design system based on virtual reality is provided for the embodiments of the present application, as shown in Figure 3 The system comprises:

[0125] The acquisition module 31 synchronously collects temperature and humidity gradient data and multi-band illumination intensity distribution data of the indoor physical space in a spatial grid distribution mode through a temperature and humidity sensor array and a multi-spectral illumination sensor in a distributed sensor network.

[0126] The generation module 32 inputs the temperature and humidity gradient data and multi-band illumination intensity data into a spatial topology correlation engine, and constructs a three-dimensional environmental parameter set containing coordinate information, temperature and humidity parameters, illumination intensity and reflectivity correlation weight based on a grid three-dimensional space structure generation algorithm.

[0127] The matching module 33 drives the micro-electromechanical execution unit of the dynamic optical reflection film layer to adjust the local tilt angle and refractive index of the film layer surface based on the spatial coordinate weight matrix in the three-dimensional environmental parameter set, and generates an optical reflection feature distribution map by combining the scattering characteristic parameters of wood, metal and glass materials in the indoor material surface characteristic database in real time.

[0128] The construction module 34 constructs a three-dimensional light field simulation model dynamically linked with the actual illumination distribution of the physical space in the virtual scene based on the real-time data of the optical reflection feature distribution map.

[0129] The adjustment module 35 triggers adaptive compensation operation of the temperature and humidity parameters in the virtual scene according to the real-time monitoring result of the physical space light intensity change, in combination with the light field distribution data of the three-dimensional light field simulation model, synchronously adjusts the reflection characteristic parameters of the dynamic optical reflection film layer, and realizes bidirectional parameter collaborative optimization of the physical environment and the virtual light field.

[0130] Figure 3 The virtual reality-based home overall design system can perform Figure 1 The virtual reality-based home overall design method of the embodiment has been described above. The specific operation of each module and unit of the virtual reality-based home overall design system in the above embodiment has been described in detail in the embodiment of the method, and will not be described in detail here.

[0131] In one possible design, Figure 3 The virtual reality-based home overall design system of the embodiment can be implemented as a computing device, such as a computer. Figure 4 As shown in the figure, the computing device can include a storage component 41 and a processing component 42.

[0132] The storage component 41 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 42.

[0133] The processing component 42 is configured to perform the above Figure 1 The virtual reality-based home overall design method of the embodiment.

[0134] The processing component 42 can include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component can also be one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors or other electronic elements, for executing the above method.

[0135] The storage component 41 is configured to store various types of data to support the operation of the terminal. The storage component can be realized by any type of volatile or non-volatile storage device or their combination, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0136] Of course, the computing device can also include other components, such as input / output interfaces, display components, communication components, etc.

[0137] The input / output interface provides an interface between the processing component and peripheral interface modules, which can be output devices, input devices, etc.

[0138] The communication component is configured to facilitate wired or wireless communication between the computing device and other devices, etc.

[0139] The computing device can be a physical device or an elastic computing host provided by a cloud computing platform, and the computing device can be a cloud server, and the processing component, the storage component, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0140] The embodiment of the application also provides a computer storage medium storing a computer program, and the computer program can implement the above-mentioned Figure 1 A home overall design method based on virtual reality is provided.

[0141] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-mentioned system, device and unit can refer to the corresponding process in the foregoing method embodiment, and will not be repeated here.

[0142] The device embodiments described above are only schematic, and the units described as separate components can or can not be physically separated, and the components displayed as units can or can not be physical units, that is, they can be located in one place, or distributed on multiple network units. Part or all of the modules can be selected according to actual needs to achieve the purpose of the embodiment scheme. Those skilled in the art can understand and implement without creative labor.

[0143] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be realized by means of software and necessary general hardware platform, and of course, it can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of software products, which can be stored in a computer readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and include a plurality of instructions to make a computer device (which can be a personal computer, server, or network device, etc.) execute the method described in each embodiment or some parts of the embodiment.

[0144] Finally, it should be noted that the above examples are only used to illustrate the technical solutions of the present application, and are not intended to limit the same; although the present application has been described in detail with reference to the foregoing examples, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing examples, or make equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for overall home design based on virtual reality, characterized in that, include: The temperature and humidity gradient data and multi-band light intensity distribution data of the indoor physical space are collected synchronously in a spatial gridded distribution mode by using a temperature and humidity sensor array and a multi-spectral light sensor in a distributed sensor network. The temperature and humidity gradient data and multi-band light intensity distribution data are input into the spatial topology association engine, and a three-dimensional environmental parameter set containing coordinate information, temperature and humidity parameters, light intensity and reflectivity association weight values ​​is constructed based on the gridded three-dimensional spatial structure generation algorithm. Based on the spatial coordinate weight matrix in the three-dimensional environmental parameter set, the microelectromechanical actuator of the dynamic optical reflection film is driven to adjust the local tilt angle and refractive index of the film surface. Combined with the indoor material surface characteristic database, the scattering characteristic parameters of wood, metal and glass materials are matched in real time to generate an optical reflection feature distribution map. Based on the real-time data of the optical reflection feature distribution map, a three-dimensional light field simulation model is constructed in the virtual scene that is dynamically linked to the actual light distribution in the physical space. Based on the real-time monitoring results of changes in physical space illumination intensity, combined with the light field distribution data of the three-dimensional light field simulation model, adaptive compensation calculations of temperature and humidity parameters in the virtual scene are triggered, and the reflection characteristic parameters of the dynamic optical reflective film are adjusted synchronously to achieve bidirectional parameter collaborative optimization between the physical environment and the virtual light field.

2. The method according to claim 1, characterized in that, Based on the spatial coordinate weight matrix in the three-dimensional environmental parameter set, the microelectromechanical actuator of the dynamic optical reflection film is driven to adjust the local tilt angle and refractive index of the film surface. Combined with the indoor material surface characteristic database, the scattering characteristic parameters of wood, metal, and glass materials are matched in real time to generate an optical reflection feature distribution map, including: Extract a spatial coordinate weight matrix from the set of three-dimensional environmental parameters. The spatial coordinate weight matrix contains the reflectance-related weight value corresponding to each grid node. The surface of the dynamic optical reflective film is divided into multiple dynamic adjustment regions based on the reflectivity-related weight values ​​in the spatial coordinate weight matrix. The boundary of each dynamic adjustment region is determined by the weight difference between adjacent grid nodes exceeding a preset segmentation threshold. The reference scattering parameters of the material type corresponding to the current dynamic adjustment area are obtained from the indoor material surface property database. Based on the difference between the reflectivity correlation weight value of the current area and the reference scattering parameters, the target adjustment amount of the local tilt angle of the film surface and the target correction amount of the refractive index are calculated. Based on the target adjustment amount and the target correction amount, the control execution component drives the film surface deformation mechanism to synchronously adjust the tilt angle and refractive index of the current region to the physical state corresponding to the target adjustment amount; The tilt angle and refractive index values ​​of each dynamically adjusted region are combined according to the distribution law of the spatial coordinate weight matrix, and the scattering characteristic parameters of wood, metal and glass materials are matched in real time with the indoor material surface characteristic database to generate an optical reflection characteristic distribution map of the coating film surface.

3. The method according to claim 2, characterized in that, Based on the target adjustment amount and the target correction amount, the tilt angle and refractive index of the current region are synchronously adjusted to the physical state corresponding to the target adjustment amount by controlling the execution component to drive the film surface deformation mechanism, including: The target adjustment amount and target correction amount are input into the control signal conversion logic to generate a set of driving signals corresponding to the physical deformation of the deformation mechanism. The set of driving signals includes tilt angle driving signal components and refractive index driving signal components. Based on the dynamic allocation strategy among the components of the drive signal set, the tilt angle drive signal component and the refractive index drive signal component are synchronously optimized and allocated according to a preset priority rule to generate a set of collaborative control commands that the deformation mechanism can execute. By controlling the signal parsing unit in the execution component, the set of cooperative control instructions is converted into physical deformation parameters that the deformation drive unit can recognize. The physical deformation parameters include deformation displacement, deformation rate and deformation direction. The deformation driving unit performs a deformation operation on the current area of ​​the film surface based on the physical deformation parameters, so that the local area of ​​the film surface synchronously generates tilt angle deformation displacement and refractive index deformation displacement. The difference between the tilt angle deformation displacement and the target adjustment amount does not exceed the preset deformation tolerance threshold, and the difference between the refractive index deformation displacement and the target correction amount does not exceed the preset refractive index tolerance threshold. The actual deformation parameters after the deformation driving unit is executed are fed back to the control signal conversion logic, and the signal component allocation ratio in the driving signal set is updated so that the tilt angle and refractive index of the current region are synchronously adjusted to the physical state corresponding to the target adjustment amount.

4. The method according to claim 1, characterized in that, Based on real-time monitoring results of changes in physical space illumination intensity, and combined with the light field distribution data of the three-dimensional light field simulation model, adaptive compensation calculations for temperature and humidity parameters in the virtual scene are triggered. Simultaneously, the reflectivity parameters of the dynamic optical reflective film are adjusted to achieve bidirectional parameter co-optimization between the physical environment and the virtual light field, including: Real-time monitoring of the rate of change of illumination in the target area of ​​physical space, and synchronous extraction of the light intensity gradient value of the corresponding area from the three-dimensional light field simulation model; Based on the correlation between the rate of change of illumination and the gradient value of light intensity, the temperature and humidity compensation amount and the reflection characteristic adjustment amount of the target area are generated through adaptive compensation calculation. Based on the temperature and humidity compensation amount, an environmental parameter update instruction for the virtual scene is generated, and an tilt angle and refractive index correction instruction for the dynamic optical reflective film is generated based on the reflection characteristic adjustment amount. By controlling the execution component to synchronously drive the deformation drive unit to execute the tilt angle and refractive index correction commands, and executing the environmental parameter update commands in the virtual scene, bidirectional parameter collaborative optimization of the physical environment and the virtual light field is achieved.

5. The method according to claim 1, characterized in that, The temperature and humidity gradient data and multi-band light intensity distribution data are input into a spatial topology association engine. Based on a gridded 3D spatial structure generation algorithm, a set of 3D environmental parameters is constructed, including coordinate information, temperature and humidity parameters, light intensity, and reflectivity association weights. The temperature gradient value and humidity gradient value in the temperature and humidity gradient data are correlated according to spatial coordinates to form a temperature and humidity distribution set, and the visible light band intensity value and infrared band intensity value in the multi-band light intensity distribution data are correlated according to the same spatial coordinates to form a light intensity band distribution set. The reference plane of the three-dimensional coordinate system is determined based on the boundary data of the wall structure in the physical space, and a three-dimensional mesh division reference is established. Based on the spatial coverage of the temperature and humidity distribution set and the light intensity band distribution set, equally spaced mesh units are divided in the three-dimensional coordinate system. For each grid cell, the mean temperature gradient, mean humidity gradient, mean visible light intensity, and mean infrared intensity are extracted. The mean temperature gradient and the mean visible light intensity are correlated to generate a temperature-light intensity correlation factor. At the same time, the mean humidity gradient and the mean infrared intensity are correlated to generate a humidity band correlation factor. The material reference reflectance value of the current grid cell is obtained from the indoor material surface property database. Based on the weighted calculation results of the temperature light intensity correlation factor and humidity band correlation factor, and combined with the material reference reflectance value, the reflectance correlation weight value of the current grid cell is generated. The coordinate information of all grid cells, the average temperature gradient, the average humidity gradient, the average intensity of the visible light band, the average intensity of the infrared band, and the reflectivity-related weight value are combined in the order of the three-dimensional coordinates to generate a set of three-dimensional environmental parameters covering the physical space.

6. The method according to claim 1, characterized in that, Based on real-time data from the optical reflection feature distribution map, a three-dimensional light field simulation model is constructed in the virtual scene, dynamically linked to the actual illumination distribution in the physical space, including: The coordinate information, reflectivity weight value and material type identifier of each grid cell are extracted from the optical reflection feature distribution map, and the corresponding surface scattering parameters and light absorption parameters are obtained from the indoor material surface characteristic database according to the material type identifier. Based on the average visible light intensity and average infrared light intensity in the real-time illumination data of physical space, combined with the reflectivity weight value and light absorption parameter, the refractive index correction value and light absorption correction value of each grid cell are calculated. Based on the refractive index correction value and light absorption correction value, dynamic refractive index parameters are generated and bound to the grid cell coordinates. In the virtual scene, the scene space is divided according to the grid cell coordinates. Based on the surface scattering parameters, the propagation direction of the virtual light source is adjusted, and the brightness and thermal radiation intensity of the light source are attenuated by combining the light absorption correction value. Based on the coordinate information of all grid cells, dynamic refractive index parameters, and attenuation processing results, a three-dimensional light field simulation model covering the virtual scene is generated.

7. The method according to claim 4, characterized in that, Based on the correlation between the rate of change of illumination and the gradient value of light intensity, temperature and humidity compensation and reflectance characteristic adjustment of the target area are generated through adaptive compensation calculation, including: The rate of change of illumination in the physical space is matched point by point with the light intensity gradient value of the corresponding region in the three-dimensional light field simulation model according to the spatial coordinate alignment rule to establish a product correlation model between the two. Based on the product correlation model, temperature and humidity compensation reference values ​​and reflection characteristic adjustment reference values ​​are generated. Based on the temperature and humidity compensation benchmark value, the deviation between the current temperature and humidity parameters of the target area and the expected parameters in the three-dimensional light field simulation model is superimposed by the dynamic weight allocation rule to generate the temperature and humidity compensation amount. The dynamic weight allocation rule is automatically adjusted according to the real-time fluctuation range of the light change rate. Based on the aforementioned reflection characteristics adjustment benchmark value, and combined with the direction and amplitude of the light intensity gradient value and the current parameters of the dynamic optical reflection film, the reflection characteristics adjustment amount is generated through feedback optimization calculation.

8. A home design system based on virtual reality, characterized in that, include: The acquisition module, through a distributed sensor network array of temperature and humidity sensors and a multispectral light sensor, synchronously acquires temperature and humidity gradient data and multi-band light intensity distribution data of the indoor physical space in a spatial gridded distribution mode. The generation module inputs the temperature and humidity gradient data and multi-band light intensity distribution data into the spatial topology association engine, and constructs a three-dimensional environmental parameter set containing coordinate information, temperature and humidity parameters, light intensity and reflectivity association weight values ​​based on the gridded three-dimensional spatial structure generation algorithm. The matching module, based on the spatial coordinate weight matrix in the three-dimensional environmental parameter set, drives the microelectromechanical actuator of the dynamic optical reflection film to adjust the local tilt angle and refractive index of the film surface, and combines the indoor material surface characteristic database to match the scattering characteristic parameters of wood, metal and glass materials in real time to generate an optical reflection feature distribution map. The construction module, based on real-time data from the optical reflection feature distribution map, constructs a three-dimensional light field simulation model in the virtual scene that dynamically links with the actual light distribution in the physical space. The adjustment module, based on the real-time monitoring results of changes in physical space light intensity and combined with the light field distribution data of the three-dimensional light field simulation model, triggers adaptive compensation calculations for temperature and humidity parameters in the virtual scene, and synchronously adjusts the reflection characteristic parameters of the dynamic optical reflection film, thereby achieving bidirectional parameter collaborative optimization between the physical environment and the virtual light field.

9. A computing device, characterized in that, It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are invoked and executed by the processing component to implement a virtual reality-based home design method as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that, The device contains a computer program that, when executed by a computer, implements a virtual reality-based home design method as described in any one of claims 1 to 7.

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