Home overall design method and system based on virtual reality

Abstract

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

Description

Technical Field

[0001] The present application relates to the technical field of integration of virtual reality and smart home systems, and in particular to a method and system for overall home design based on virtual reality. Background Art

[0002] In scenarios where smart home design and virtual reality are combined, users need to realistically simulate the effects of dynamic lighting changes and temperature and humidity distribution in physical spaces on material properties in a virtual environment. For example, dynamic changes in environmental parameters, such as local 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 model of 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 reflective effects of virtual materials and the actual state of the physical environment. At the same time, lighting adjustments only act on global parameters and lack a refined response to local areas, resulting in distortion of material reflections and deviations in the simulation of temperature and humidity effects in the virtual scene.

[0003] At present, relevant technologies adopt a solution 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, combined with preset material reflectivity parameters, a pre-calculated light field model that matches the real-time light intensity collected by the physical sensor is loaded into the virtual scene, and the global brightness and color temperature parameters are adjusted through linear interpolation. Summary of the Invention

[0004] The present application provides a method and system for overall home design based on virtual reality, which is used to solve the problem of material reflective distortion in virtual scenes in the prior art.

[0005] In a first aspect, the present application provides a method for overall home design based on virtual reality, comprising:

[0006] Through the temperature and humidity sensor array and multi-spectral light sensor in the distributed sensor network, the temperature and humidity gradient data and multi-band light intensity distribution data of the indoor physical space are synchronously collected in a spatial grid distribution mode;

[0007] Inputting the temperature and humidity gradient data and the multi-band light intensity data into a spatial topology association engine, and constructing a three-dimensional environmental parameter set including coordinate information, temperature and humidity parameters, light intensity, and reflectivity association weights based on a gridded three-dimensional spatial structure generation algorithm;

[0008] Based on the spatial coordinate weight matrix in the three-dimensional environmental parameter set, the micro-electromechanical actuator of the dynamic optical reflective film layer is driven to adjust the local inclination angle and refractive index of the film surface. 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.

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

[0010] Based on the real-time monitoring results of the changes in light intensity in the physical space and combined with the light field distribution data of the three-dimensional light field simulation model, adaptive compensation calculations of the temperature and humidity parameters in the virtual scene are triggered, and the reflection characteristic parameters of the dynamic optical reflective film layer are synchronously adjusted to achieve two-way parameter coordinated optimization of the physical environment and the virtual light field.

[0011] Optionally, a spatial coordinate weight matrix is ​​extracted from the three-dimensional environmental parameter set, wherein the spatial coordinate weight matrix includes a reflectivity association weight value corresponding to each grid node;

[0012] Dividing the surface of the dynamic optical reflective film layer into a plurality of dynamic adjustment regions according to the reflectivity-associated weight values ​​in the spatial coordinate weight matrix, wherein the boundary of each dynamic adjustment region is determined by whether the weight difference of adjacent grid nodes exceeds a preset segmentation threshold;

[0013] Obtaining a reference scattering parameter for the material type corresponding to the current dynamic adjustment area from a material surface property database, and calculating a target adjustment amount for the local tilt angle and a target correction amount for the refractive index of the film surface based on a difference between the reflectivity association weight value of the current area and the reference scattering parameter;

[0014] Based on the target adjustment amount and the target correction amount, the actuator is controlled to drive the film surface deformation mechanism so that the inclination angle and the refractive index of the current area are synchronously adjusted to the physical state corresponding to the target adjustment amount;

[0015] The adjusted inclination angle value and refractive index value of each dynamic adjustment area 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 in combination with the indoor material surface characteristic database to generate an optical reflection characteristic distribution map of the surface of the covering film layer.

[0016] Optionally, the target adjustment amount and the target correction amount are input into a control signal conversion logic to generate a drive signal set corresponding to the physical deformation amount of the deformation mechanism, wherein the drive signal set includes a tilt angle drive signal component and a refractive index drive signal component;

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

[0018] The signal parsing unit in the control execution component converts the collaborative control instruction set into physical deformation parameters that can be recognized by the deformation drive unit, wherein the physical deformation parameters include deformation displacement, deformation rate and deformation direction;

[0019] Driving the deformation driving unit to perform a deformation operation on the current area of ​​the film layer surface based on the physical deformation parameter, so that the local area of ​​the film layer surface synchronously generates an inclination deformation displacement and a refractive index deformation displacement, wherein the difference between the inclination deformation displacement and the target adjustment amount does not exceed a preset deformation tolerance threshold, and the difference between the refractive index deformation displacement and the target correction amount does not exceed a preset refractive index tolerance threshold;

[0020] The actual deformation parameters after the deformation drive unit is executed are fed back to the control signal conversion logic, and the signal component distribution ratio in the drive signal set is updated, so that the inclination angle and refractive index of the current area are synchronously adjusted to the physical state corresponding to the target adjustment amount.

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

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

[0023] Generate an environmental parameter update instruction for the virtual scene according to the temperature and humidity compensation amount, and generate an inclination angle and refractive index correction instruction for the dynamic optical reflective film layer according to the reflection characteristic adjustment amount;

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

[0025] Optionally, the temperature gradient value and the humidity gradient value in the temperature and humidity gradient data are data-associated according to 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 a reference plane of a three-dimensional coordinate system based on the boundary data of the wall structure of the physical space and establish a three-dimensional grid division reference, and divide the three-dimensional coordinate system into equally spaced grid units based on the spatial coverage of the temperature and humidity distribution set and the light intensity band distribution set;

[0027] Extracting the temperature gradient mean, humidity gradient mean, visible light band intensity mean, and infrared band intensity mean for each grid cell, correlating the temperature gradient mean with the visible light band intensity mean to generate a temperature-light intensity correlation factor, and correlating the humidity gradient mean with the infrared band intensity mean to generate a humidity band correlation factor;

[0028] Obtaining a material reference reflectance value of the area where the current grid unit is located from an indoor material surface property database, and generating a reflectance association weight value of the current grid unit based on a weighted calculation result of the temperature-light-intensity correlation factor and the humidity band correlation factor, combined with the material reference reflectance value;

[0029] The coordinate information, temperature gradient mean, humidity gradient mean, visible light band intensity mean, infrared band intensity mean and reflectivity associated weight values ​​of all grid cells are combined in the order of three-dimensional coordinate arrangement to generate a three-dimensional environmental parameter set covering the physical space.

[0030] Optionally, extracting coordinate information, reflectivity weight value and material type identification of each grid unit from the optical reflection feature distribution map, and acquiring corresponding surface scattering parameters and light absorption parameters from a material surface property database according to the material type identification;

[0031] Based on the average visible light intensity and the average infrared light intensity in the real-time illumination data of the physical space, combined with the reflectivity weight value and the light absorption parameter, a refractive index correction value and a light absorption correction value are calculated for each grid cell; a dynamic refractive index parameter is generated based on the refractive index correction value and the light absorption correction value, and the dynamic refractive index parameter is bound to the grid cell coordinates;

[0032] In the virtual scene, the scene space is divided according to the grid unit coordinates, the propagation direction of the virtual light source is adjusted according to the surface scattering parameter, and the brightness and thermal radiation intensity of the light source are attenuated in combination with the light absorption correction value;

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

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

[0035] Based on the product correlation model, generating a temperature and humidity compensation reference value and a reflectance characteristic adjustment reference value;

[0036] Based on the temperature and humidity compensation reference value, a temperature and humidity compensation amount is generated by superimposing 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 through a dynamic weight allocation rule, wherein the dynamic weight allocation rule is automatically adjusted according to the real-time fluctuation amplitude of the light change rate;

[0037] Based on the reflection characteristic adjustment reference value, combined with the direction and amplitude of the light intensity gradient value and the current parameters of the reflection film layer, a reflection characteristic adjustment amount is generated through feedback optimization calculation.

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

[0039] The acquisition module uses the temperature and humidity sensor array and multi-spectral light sensor in the distributed sensor network to synchronously collect temperature and humidity gradient data and multi-band light intensity distribution data of the indoor physical space in a spatial grid distribution mode;

[0040] A generation module inputs the temperature and humidity gradient data and the multi-band light intensity data into a spatial topology association engine, and constructs a three-dimensional environmental parameter set including coordinate information, temperature and humidity parameters, light intensity, and reflectivity association weights based on a gridded three-dimensional spatial structure generation algorithm;

[0041] A matching module drives the micro-electromechanical actuator of the dynamic optical reflective film layer to adjust the local inclination angle and refractive index of the film layer surface based on the spatial coordinate weight matrix in the three-dimensional environmental parameter set, and combines the scattering characteristic parameters of wood, metal, and glass materials in real time with the indoor material surface characteristic database to generate an optical reflection feature distribution map;

[0042] A construction module, based on the real-time data of the optical reflection characteristic distribution map, constructs a three-dimensional light field simulation model in a virtual scene that is dynamically linked to the actual illumination distribution of the physical space;

[0043] The adjustment module triggers adaptive compensation calculations for temperature and humidity parameters in the virtual scene based on the real-time monitoring results of changes in light intensity in the physical space and the light field distribution data of the three-dimensional light field simulation model, and synchronously adjusts the reflective characteristic parameters of the dynamic optical reflective film layer to achieve bidirectional parameter coordinated optimization of the physical environment and the virtual light field.

[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, an embodiment of the present application provides a computer storage medium storing a computer program. When the computer program is executed by a computer, it implements a virtual reality-based overall home design method as described in the first aspect.

[0046] In the present application, global synchronous perception of indoor environmental parameters is achieved through a distributed sensor network, providing a high-precision data base for virtual-reality interaction; a three-dimensional environmental parameter set constructed based on a spatial topology association engine forms a digital twin of the physical environment, solving the rendering inaccuracy problem caused by parameter discretization in traditional modeling; with the help of nano-scale regulation of dynamic optical reflective film layers and real-time matching of material scattering characteristics, atomic-level synchronization of the optical properties of the physical surface and the virtual model is achieved; a high-fidelity light field model generated by combining optical reflection feature data is used to ensure that the light and shadow gradient of the virtual scene is consistent with the physical environment; finally, a cross-domain closed-loop feedback is achieved through a two-way parameter collaborative optimization mechanism, maintaining the energy balance between the physical environment and the virtual light field in dynamic changes, and comprehensively solving the problems of material reflection distortion, local overexposure and response delay in traditional solutions, realizing full-dimensional parameter coupling and millisecond-level synchronous optimization.

[0047] Furthermore, by extracting the spatial coordinate weight matrix from the three-dimensional environmental parameter set, the surface of the dynamic optical reflective film layer is divided into multiple dynamic adjustment areas according to the judgment rule that the difference in weights of adjacent grid nodes exceeds a preset threshold, thereby realizing adaptive identification and precise boundary division of the illumination mutation area; by matching the benchmark scattering parameters in the material surface property database, the target adjustment amount of the film layer inclination angle and refractive index is calculated based on the difference between the current area weight and the benchmark parameter, and the deformation mechanism is driven to synchronously perform parameter adjustment to ensure that the optical properties of the physical film layer and the scattering behavior of the virtual material are accurately matched; finally, based on the distribution law of the weight matrix, the adjustment parameters of each area are integrated and an optical reflection feature distribution map is generated, forming a fully closed-loop control link from dynamic area segmentation to nanometer-level parameter correction, solving the problem of local reflection distortion caused by global adjustment in traditional methods, and realizing atomic-level synchronization between the virtual light field and the physical environment at the material reflective property level.

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

[0049] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0050] Figure 1 A flowchart of a method for overall home design based on virtual reality provided by the present application is shown;

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

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

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

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

[0055] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this document or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any order of execution. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this document are used to distinguish different messages, devices, modules, etc., and do not represent a sequential order, nor do they limit "first" and "second" to being different types.

[0056] Researchers have found that traditional virtual reality home design systems suffer from the defect of fragmented environmental parameters: because the static parameter library and pre-calculated model cannot dynamically adjust the optical properties of the material, the reflective effect of the virtual material is disconnected from the actual temperature, humidity, and lighting conditions of the physical environment. At the same time, the lighting adjustment of existing technologies only acts on global parameters and lacks a refined response to local areas such as window perimeters and furniture surfaces. This causes material reflective distortion in the virtual scene and deviations in the simulation of temperature and humidity effects. For example, the reflectivity of the wooden surface deviates significantly from the actual value, and the humidity compensation response is significantly delayed. Therefore, there is an urgent need for a two-way optimization method that supports the dynamic perception of the physical environment and the real-time linkage of virtual light field parameters.

[0057] In response to the above problems, the present invention proposes a virtual-reality collaborative design method based on dynamic optical reflective film layer control, the core of which is to establish an atomic-level parameter mapping and two-way feedback mechanism between the physical environment and the virtual light field. Specifically, the environmental parameters are collected in real time through a distributed sensor network, and a three-dimensional parameter set is constructed through a spatial topology association engine to drive the micro-electromechanical execution unit to accurately control the optical properties of the film layer. The scattering parameters are matched with the material database to generate a virtual-reality linkage reflection feature distribution map; based on the light field model and the adaptive compensation algorithm, the temperature and humidity parameters are quickly corrected and the reflection characteristics are adjusted synchronously, which significantly reduces the virtual material reflective distortion and temperature and humidity simulation deviation. This method breaks through the limitations of the traditional static parameter library, greatly reducing the error between the reflective effect of the virtual material and the actual state of the physical environment. At the same time, through the refined response to the local illumination gradient, such as quickly capturing the sudden change in illumination intensity in the window area, it completely solves the key problems of material reflective distortion and temperature and humidity simulation deviation.

[0058] The technical solution of this application can be applied to scenarios such as smart home virtual decoration design and high-precision indoor environment simulation. It is especially suitable for the verification and optimization of immersive home decoration solutions that need to reflect the dynamic changes of physical space in real time, such as the difference in lighting between day and night, and the temperature and humidity adjustment of air conditioning.

[0059] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0060] Figure 1 A flowchart of a method for overall home design based on virtual reality is provided for the embodiment of the present application, such as Figure 1 As shown, the method includes:

[0061] 101. Using the temperature and humidity sensor array and multi-spectral light sensor in the distributed sensor network, the temperature and humidity gradient data and multi-band light intensity distribution data of the indoor physical space are synchronously collected in a spatial grid distribution mode;

[0062] In step 101, the distributed sensing network refers to a group of sensor nodes connected via the Zigbee or LoRaWAN communication protocol; the temperature and humidity sensor array refers to a collection of miniature temperature and humidity detection units manufactured using MEMS technology; the multispectral light sensor refers to a light intensity detection device equipped with visible light, near-infrared, and ultraviolet band filters; and the spatial grid distribution pattern refers to a three-dimensional grid layout that divides the indoor space into 0.5m×0.5m×0.5m cubic units.

[0063] In an embodiment of the present application, first, an automatic deployment robot equipped with a laser positioning module is used to project a three-dimensional grid baseline on the wall according to the building information model data, and the temperature and humidity sensor array and the multi-spectral light sensor are physically deployed according to the grid vertex coordinates. Secondly, the temperature and humidity sensor array starts the dual-channel acquisition module to synchronously obtain the voltage value of the temperature-sensitive resistor and the charge and discharge time of the capacitive humidity detection unit at each grid point. Then, the multi-spectral light sensor drives the filter wheel through a stepper motor to switch six preset bands in sequence, including 450nm blue light, 550nm green light, 650nm red light, etc., and collects the photocurrent value of the silicon photodiode for 50ms in each band. Finally, all sensor nodes upload the temperature and humidity gradient data and multi-band light intensity distribution data with spatial grid coding to the edge computing gateway through the LoRaWAN protocol. After the gateway aligns the timestamps of the data and removes outliers, it generates a structured spatial data set containing three-dimensional coordinates, temperature and humidity values ​​and six-band light intensity.

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

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

[0066] 1021. Associating the temperature gradient values ​​and the humidity gradient values ​​in the temperature and humidity gradient data according to spatial coordinates to form a temperature and humidity distribution set, and associating the visible light band intensity values ​​and the infrared band intensity values ​​in the multi-band light intensity data according to the same spatial coordinates to form a light intensity band distribution set;

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

[0068] 1023. Extracting the temperature gradient mean, humidity gradient mean, visible light band intensity mean, and infrared band intensity mean for each grid cell, correlating the temperature gradient mean with the visible light band intensity mean to generate a temperature-light intensity correlation factor, and correlating the humidity gradient mean with the infrared band intensity mean to generate a humidity band correlation factor.

[0069] 1024. Obtain a material base reflectance value of the area where the current grid unit is located from an indoor material surface property database, and generate a reflectance association weight value of the current grid unit based on a weighted calculation result of the temperature-light intensity correlation factor and the humidity band correlation factor, combined with the material base reflectance value;

[0070] 1025. The coordinate information, temperature gradient mean, humidity gradient mean, visible light band intensity mean, infrared band intensity mean, and reflectivity associated weight values ​​of all grid cells are combined in the order of the three-dimensional coordinate arrangement to generate a three-dimensional environmental parameter set covering the physical space.

[0071] In the above scheme, the spatial topology association engine refers to a calculation module that establishes spatial data association relationships through graph theory algorithms; the gridded three-dimensional spatial structure generation algorithm refers to a calculation method that constructs a spatial grid based on the Delaunay triangulation principle; the three-dimensional environmental parameter set is a structured data set composed of three-dimensional coordinate information, temperature gradient mean, humidity gradient mean, visible light and infrared band light intensity mean, and reflectivity association weight value. Among them, the temperature and humidity distribution set is formed by associating the spatial coordinates of the temperature gradient value and the humidity gradient value. The temperature gradient value comes from the temperature difference data of adjacent grids collected by the temperature sensor, and the humidity gradient value comes from the humidity difference data of adjacent grids collected by the humidity sensor; the light intensity band distribution set is a set formed by aligning the coordinates of the light intensity data of the visible light band of 400 to 700 nanometers and the infrared band of 700 to 1100 nanometers obtained by the multispectral sensor; the three-dimensional grid division benchmark is established according to the coordinate system origin and axial parameters determined by the wall structure in the building information model, including the 0.5-meter spacing definition in the XYZ three-axis direction; the temperature and light intensity association factor The coefficient is obtained by calculating the Pearson correlation coefficient of the mean temperature gradient and the mean visible light band intensity, which is used 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 infrared band intensity, reflecting the correlation between the dynamic changes of the two; the material benchmark reflectance value is extracted from the preset database, which contains the standard reflectance values ​​of materials such as wall tiles or wooden floors in the 380 to 2500 nanometer band; the reflectance correlation weight value is calculated using the entropy method, which is formed by the weighted result of the comprehensive temperature-light intensity correlation factor accounting for 40%, the humidity band correlation factor accounting for 30%, and the material benchmark reflectance value accounting for 30%.

[0072] In the embodiment 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 key-value bound by a spatial coordinate matching algorithm in step 1021 to generate a temperature and humidity distribution set including three-dimensional coordinates, temperature gradient values, and humidity gradient values. At the same time, the same coordinate mapping method is used to align the visible light band intensity value and the infrared band intensity value in the multi-band light intensity data to form a light intensity band distribution set including coordinates, visible light intensity, and infrared light intensity. In specific implementation, a hash table storage structure is used, with three-dimensional coordinates as the unique key value, to associate the temperature gradient value and the humidity gradient value with the same key value, and a double-linked list structure is used to maintain the temporal consistency of the visible light and infrared light intensities.

[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 of the southwest corner of the room and the ground is selected as the origin, and a coordinate system is established with the extension direction of the main wall as the X-axis, the vertical direction as the Y-axis, and the height direction as the Z-axis. Then, based on the spatial coverage of the temperature and humidity distribution set and the light intensity band distribution set, an equally spaced grid division algorithm is used to generate cubic grid units along the X, Y, and Z axes with a step size 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 unit.

[0074] Then, data aggregation calculation is performed on each grid cell through step 1023: the arithmetic mean of all temperature gradient values ​​in the cell is extracted as the temperature gradient mean through the sliding window mean algorithm, and the humidity gradient mean is calculated by the exponentially 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 to generate corresponding means; then the temperature gradient mean and the visible light intensity mean are input into the Pearson correlation coefficient calculation module, and the temperature-light intensity correlation factor ranging from -1 to 1 is generated by jointly calculating the covariance and standard deviation; covariance analysis is simultaneously performed on the humidity gradient mean and the infrared intensity mean, and the humidity band correlation factor is generated after eliminating the time series difference using the dynamic time warping algorithm.

[0075] Then, the indoor material database is associated with the grid cell identifier in step 1024, and the spatial location hash retrieval technology is used to obtain the baseline reflectance value of the wall or floor material where the current cell is located. Next, Z-score normalization is applied to the temperature and light intensity correlation factors to map them to the 0-1 interval, and the humidity band correlation factors are normalized using the Sigmoid function. Then, the weight distribution scheme is determined based on the entropy method, with the temperature and light intensity factors accounting for 40%, the humidity band factors accounting for 30%, and the material reflectance accounting for 30%. The reflectance correlation weight value is calculated using the weighted summation formula. Finally, the calculation results are Gaussian smoothed to eliminate local mutation noise.

[0076] Finally, in step 1025, all grid cells are sorted according to the priority of the XYZ coordinate axis, and a space filling curve such as a Z-order curve is used to optimize the data storage order; then, a data tuple containing coordinates, temperature gradient mean, humidity gradient mean, visible light intensity mean, infrared intensity mean, and reflectivity association weight value is constructed for each cell; then, an octree spatial indexing algorithm is used to establish a fast retrieval structure for the three-dimensional environmental parameter set; finally, a spatial topology association engine is used to verify 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 accurately simulates real-world living environments by building a dynamic environmental response model within a digital living space. When users plan their smart homes through VR, the system integrates simulated indoor air conditioning airflow data with humidifier atomizer particle trajectories in three-dimensional coordinates to generate a dynamic temperature and humidity cloud map with spatial attributes. Simultaneously, the sunlight wavelengths from virtual windows and infrared thermal field data from floor heating radiation are mapped to the same coordinate system, forming a photothermal coupling distribution layer. Based on the wall contours and floor elevations of the building model, areas such as the living room and bedroom are divided into a 3D grid matrix with a precision of 0.05 meters. As users drag virtual furniture, the system automatically increases the grid density in the area where the sofa overlaps with the floor heating pipes, calculating in real time the velvet material's resistance to heat conduction. For the kitchen island area, the system extracts the dynamic correlation between the quartz countertop temperature gradient and the visible light intensity of the chandelier to generate the photothermal interference coefficient. It also analyzes the correlation between steam diffusion from a concealed dishwasher and the infrared radiation from the baseboard heaters to calculate the condensation risk index. When the user switches the wall material from latex paint to diatom mud, the system simultaneously retrieves the moisture absorption and reflectivity parameters from the material database, and dynamically corrects the light and shadow rendering parameters based on the photothermal interference coefficient of the current grid. If it detects that the humidity weight in the green wall area is abnormal due to virtual transpiration, it triggers a material conflict warning and generates an optimization plan. The final output of the three-dimensional environmental parameter set contains 100,000 intelligent grid units, which supports designers to see the predicted data of any coordinate point - such as the temperature and humidity fluctuation curve of the bay window area in the winter afternoon, 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 effects are accurately associated with the humidity gradient data, and the curtain swing amplitude and temperature diffusion pattern caused by air flow are presented in real time in the VR field of view, realizing the deep collaborative verification of aesthetic design and environmental physical parameters.

[0078] In the complete solution of step 102 above, precise digital modeling of the physical space environment characteristics is achieved through the refined integration of multi-dimensional environmental parameters and dynamic weight calculation. The temperature and humidity gradients are precisely associated with multi-band light intensity according to spatial coordinates, ensuring that different environmental parameters strictly correspond to spatial positions and eliminating spatial dislocation distortion in traditional simulations. Reflectance weights are dynamically generated by combining temperature-light intensity factors and humidity-band factors to adaptively control the impact of environmental parameters on the optical properties of materials. A three-dimensional grid benchmark is constructed through the boundary of the wall structure, and the local parameter mean is extracted to achieve multi-scale feature analysis. At the same time, the reflectance weights of the grid cells are matched in real time based on the material database to accurately reflect the dynamic optical properties of different materials under temperature and humidity changes, breaking through the preset limitations of static reflectance. This technology significantly improves the matching accuracy of the actual state of the virtual scene and the physical space, laying a high-trust data foundation for subsequent optical reflection feature generation and virtual-reality collaborative optimization.

[0079] 103. Based on the spatial coordinate weight matrix in the three-dimensional environmental parameter set, drive the micro-electromechanical actuator of the dynamic optical reflective film layer to adjust the local inclination angle and refractive index of the film layer surface, and combine the indoor material surface property database to match the scattering characteristic parameters of wood, metal, and glass materials in real time to generate an optical reflection feature distribution map;

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

[0081] 1031. Extracting a spatial coordinate weight matrix from the three-dimensional environmental parameter set, wherein the spatial coordinate weight matrix includes a reflectivity association weight value corresponding to each grid node;

[0082] 1032. Divide the surface of the dynamic optical reflective film layer into a plurality of dynamic adjustment regions according to the reflectivity-associated weight values ​​in the spatial coordinate weight matrix, wherein the boundary of each dynamic adjustment region is determined by whether the weight difference of adjacent grid nodes exceeds a preset segmentation threshold;

[0083] 1033. Obtain a reference scattering parameter for the material type corresponding to the current dynamic adjustment area from a material surface property database, and calculate a target adjustment amount for the local tilt angle and a target correction amount for the refractive index of the film surface based on a difference between the reflectivity association weight value of the current area and the reference scattering parameter;

[0084] 1034. Based on the target adjustment amount and the target correction amount, the actuator is controlled to drive the film surface deformation mechanism so that the inclination angle and the refractive index of the current area are synchronously adjusted to a physical state corresponding to the target adjustment amount.

[0085] Among them, step 1034 may specifically include the following processes: inputting the target adjustment amount and the target correction amount into the control signal conversion logic to generate a drive signal set corresponding to the physical deformation amount of the deformation mechanism, wherein the drive signal set includes an inclination drive signal component and a refractive index drive signal component; according to the dynamic allocation strategy between the components of the drive signal set, the inclination drive signal component and the refractive index drive signal component are synchronously optimized and allocated according to the preset priority rules to generate a collaborative control instruction set executable by the deformation mechanism; through the signal parsing unit in the control execution component, the collaborative control instruction set is converted into physical deformation parameters identifiable by the deformation drive unit, and the physical deformation parameters are identifiable by the deformation drive unit. The physical deformation parameters include deformation displacement, deformation rate and deformation direction; the deformation driving unit is driven to perform 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 an inclination deformation displacement and a refractive index deformation displacement, and the difference between the inclination 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 distribution ratio in the drive signal set is updated, so that the inclination angle and refractive index of the current area are synchronously adjusted to the physical state corresponding to the target adjustment amount.

[0086] 1035. Combine the adjusted inclination angle value and refractive index value of each dynamic adjustment area according to the distribution law of the spatial coordinate weight matrix, and combine with 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 characteristic distribution map of the surface of the covering film layer.

[0087] In the above scheme, the three-dimensional environmental parameter set refers to a three-dimensional spatial data set containing spatial coordinates, reflectivity and material types; the spatial coordinate weight matrix refers to a matrix composed of weight values ​​associated with the reflectivity of grid nodes, which is used to characterize the degree of influence of different positions on the optical reflection characteristics; the dynamic optical reflective 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-actuator based on MEMS technology to realize film deformation; the material surface characteristic database refers to a structured data set that stores the benchmark scattering parameters of materials such as wood, metal, and glass; the scattering characteristic parameters refer to quantitative indicators of reflectivity, scattering angle and polarization characteristics related to the optical properties of the material surface. ; The dynamic adjustment area refers to the surface partition of the film layer divided according to the weight difference, and the segmentation threshold refers to the minimum weight difference value for triggering the boundary division of the area; the reference scattering parameter refers to the standard reflection characteristic parameter of the corresponding material type in the material database, the target adjustment amount refers to the change in the inclination angle of the film layer that needs to be adjusted to achieve the target reflectivity, and the target correction amount refers to the change in the refractive index that needs to be adjusted; the control execution component refers to the hardware module that includes signal conversion and drive control, and the deformation mechanism refers to the physical execution device that realizes the synchronous adjustment of the inclination angle and refractive index; the optical reflection characteristic distribution map refers to the spatial distribution map reflecting the optical characteristics such as reflectivity and scattering angle of each area on the surface of the film layer, which is generated by combining real-time adjustment parameters and the material database.

[0088] In an embodiment of the present application, the three-dimensional grid data parsing algorithm of step 1031 is used to perform spatial coordinate parsing on the three-dimensional environmental parameter set, and extract the original data including the X / Y / Z axis coordinates and reflectivity weights. Then, a spatial interpolation technique based on the Gaussian kernel function is used to convert discrete coordinate points into uniformly distributed grid nodes. Each node calculates the reflectivity-associated weight value through a weighted fusion algorithm. The weight value is obtained by normalizing the product of the ambient light intensity, the line of sight incident angle, and the material reflectivity. Secondly, the matrix compression coding technology is used to map the grid node coordinates and the weight values ​​into a two-dimensional matrix structure to generate a spatial coordinate weight matrix. Finally, the matrix integrity is detected by the data verification module, and the standardized weight matrix is ​​output after removing the abnormal nodes to provide a data basis for dynamic area division.

[0089] Secondly, the neighborhood gradient calculation of the spatial coordinate weight matrix is ​​performed through step 1032, and the Sobel edge detection algorithm is used to traverse each grid node and calculate the weight difference between it and the eight adjacent nodes. Then, a dynamic segmentation threshold is set. When the weight difference of adjacent nodes is detected to exceed the threshold, the region boundary mark is triggered, and the boundary is extended to the surrounding areas through the region growing algorithm until a node with a weight difference below the threshold is encountered, forming a closed dynamic adjustment region. Secondly, the region boundary is smoothed using morphological closing operations to eliminate jagged edges, and small fragmented regions are merged using connected domain analysis technology. Finally, a unique identification code is assigned to each dynamic adjustment region and associated with the material type code of the center point of the region to generate a partition topology map with material attributes for subsequent scattering parameter matching.

[0090] Next, in step 1033, the region's material encoding is dynamically adjusted, and the corresponding benchmark scattering parameters are retrieved from the material surface property database. For wood materials, the bidirectional reflectance distribution function model parameters are used; for metal materials, the specular reflectance-incident angle curve is extracted; and for glass materials, a transmittance-refractive index mapping table is loaded. A difference compensation algorithm is then used to compare the reflectance-related weights of the current region with the benchmark parameters. For wood regions, the deviation between the actual reflectance and the target value is fitted using the least squares method to calculate the tilt adjustment. For metal regions, the refractive index correction is iteratively solved using the gradient descent method to bring the specular reflectance closer to the target value. For glass regions, the tilt and refractive index parameters are simultaneously optimized, and the Lagrange multiplier method is used to balance the weights of transmission and reflection. The feasibility of the target adjustment and correction values ​​is then verified using the physical constraint detection module. If they exceed the maximum deformation range of the deformable mechanism, the parameter scaling algorithm is triggered to proportionally compress the adjustment values. Finally, a partition control instruction set containing the target tilt adjustment value, the target refractive index correction value, and the execution priority is generated and passed to the control execution component.

[0091] Next, in step 1034, a multi-channel signal converter converts the target adjustment and correction values ​​into drive signals. The tilt control channel uses pulse width modulation to generate a piezoelectric ceramic drive voltage signal, while the refractive index control channel outputs the gradient electric field intensity required for the electrowetting effect via a digital-to-analog converter. The deformation mechanism is then driven to perform adjustments. For tilt adjustment, the piezoelectric ceramic array undergoes nanoscale deformation based on the voltage signal. The actual tilt angle is measured in real time using a laser interferometer, and the drive signal is dynamically corrected using a PID control algorithm. For refractive index adjustment, the electrowetting effect drives molecular rearrangement in the dielectric layer. An ellipsometer monitors refractive index changes online, and a fuzzy logic controller compensates for parameter drift caused by ambient temperature. A time synchronization controller ensures phase consistency between tilt and refractive index adjustments, and a hardware interrupt mechanism coordinates the execution timing of the two drive signals. Finally, multi-sensor fusion technology is used to collect the actual deformation parameters. If the residual difference between the actual and target values ​​exceeds a tolerance threshold, an iterative adjustment process is triggered until the optical performance requirements are met.

[0092] Finally, in step 1035, the adjusted inclination and refractive index data for each dynamically adjusted area are spatially interpolated according to the distribution of the spatial coordinate weight matrix: a bicubic spline interpolation algorithm is used to smooth the inclination values ​​in the wood-dominated area, an inverse distance weighted method is used to interpolate the refractive index in the metal area, and a hybrid interpolation strategy based on a physical optics model is applied to the glass area. Next, a database of material surface properties is used to overlay material-specific scattering characteristics on each interpolation point: a Lambertian diffuse reflectance model is overlaid on the wood area, an anisotropic specular model is incorporated into the metal area, and Fresnel transmission compensation parameters are integrated into the glass area. Next, a ray tracing engine is used to simulate the optical reflection characteristics of the film surface. A Monte Carlo method is used to randomly sample ray paths to generate an optical map containing reflectivity intensity distribution, scattering angle range, and polarization state variations. Finally, a visual rendering pipeline converts the optical data into a visual distribution map in RGB color space. This is then embedded in an augmented reality system for real-time projection calibration, ensuring that the spatial matching of the optical reflection characteristics with the real environment meets the design requirements.

[0093] In practical applications, for example, a smart home virtual design platform uses a dynamic optical reflective film layer to achieve adaptive environmental adjustment when simulating the interaction of light and shadow in a sunroom. When the user switches the material of the dimming glass curtain wall in the virtual space to an electrochromic film, the system first extracts the spatial coordinate weight matrix of the curtain wall area from the three-dimensional environmental model. Each grid node with a precision of 0.1 meters carries a reflectivity-associated weight value. The west window pane has a weight of 0.92 due to the simulated strong afternoon sunlight, while the north bookcase projection area has a weight of only 0.35. The system automatically detects the weight difference between adjacent grid nodes on the curtain wall surface and divides areas exceeding the preset threshold of 0.3 into seven dynamic adjustment units, including a high-weight sunlight core area, a transition zone, and a low-weight shadow area. The southeast corner has an irregular polygonal boundary due to the virtual greenery blocking the area. Based on the baseline scattering parameters of electrochromic glass, the system adjusts optical parameters in high-weighted areas: In the sunlit core, the surface tilt is adjusted to 12.5 degrees to reduce the angle of direct light incidence, and the refractive index is adjusted to 1.48 to achieve selective attenuation of blue light. In shadowed areas, the tilt is maintained at 5 degrees, and the refractive index is increased to 1.55 to enhance diffuse reflection. A micro-piezoelectric ceramic array on the virtual film surface responds synchronously, driving 120 actuators to coordinately deform and form a micro-prism structure. Voltage is used to control the density of liquid crystal molecules, stabilizing the refractive index to the target value within 0.2 seconds. The resulting dynamic optical reflectance feature distribution map interacts in real time with the material database, mapping a soft diffuse light spot on the wooden decorative wall, creating a sharp highlight cutoff on the metal lampshade, and overlaying a Fresnel reflection effect on the glass coffee table. As the user rotates the virtual sofa, the system displays how the diamond-shaped light spot on the west curtain wall shifts from the leather sofa surface to the marble floor, all while maintaining a comfortable indoor illumination balance of 500 to 550 lux.

[0094] In the complete solution of the above step 103, precise dynamic control of physical optical reflection characteristics is achieved through dynamic analysis of the spatial coordinate weight matrix and real-time matching of material characteristics. Its technical effects are reflected in: regional intelligent division of the dynamic optical reflection film layer based on the reflectivity-related weight value, so that the boundary of the adjustment area accurately corresponds to the physical space structure characteristics; real-time matching of the scattering characteristic benchmark parameters of wood, metal, and glass materials through the material surface characteristic database, and calculation of the target adjustment amount of the film layer inclination angle and refractive index combined with the reflectivity weight difference, driving the micro-electromechanical execution unit to achieve nano-level deformation control, ensuring that the reflection characteristics of the film layer are dynamically consistent with the optical behavior of the material in the virtual scene; synchronous fusion of the adjusted inclination angle, refractive index parameters and material scattering characteristics to generate an optical reflection characteristic distribution map covering the surface of the film layer, accurately simulating the gradient change of reflected light intensity of different materials under the coupling of temperature, humidity and illumination, providing high-fidelity physical optical parameter input for the virtual light field model, and significantly improving the real-time and optical consistency of the interaction between virtual and real environments.

[0095] 104. Based on the real-time data of the optical reflection characteristic distribution map, construct a three-dimensional light field simulation model in a virtual scene that is dynamically linked to the actual illumination distribution in the physical space;

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

[0097] 1041. Extract coordinate information, reflectivity weight value, and material type identifier of each grid cell from the optical reflection feature distribution map, and obtain corresponding surface scattering parameters and light absorption parameters from a material surface property database based on the material type identifier.

[0098] 1042. Based on the average visible light intensity and the average infrared light intensity in the real-time illumination data of the physical space, combined with the reflectivity weight value and the light absorption parameter, calculate the refractive index correction value and the light absorption correction value of each grid cell, generate a dynamic refractive index parameter based on the refractive index correction value and the light absorption correction value, and bind it to the grid cell coordinates;

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

[0100] 1044. Generate a three-dimensional light field simulation model covering the virtual scene based on the coordinate information, dynamic refractive index parameters, and attenuation processing results 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 contains the grid unit coordinates, reflectivity weight values ​​and material types; the three-dimensional light field simulation model refers to a virtual light field model constructed by a ray tracing algorithm and linked in real time with the physical space illumination distribution; the material type identifier is a string consisting of three digits, which is used to uniquely distinguish the surface material categories such as walls, floors or furniture; the surface scattering parameter is the Lambertian reflectance coefficient extracted from the material database, which characterizes the diffuse reflection intensity of the material surface to light; the light absorption parameter refers to the percentage of light energy absorption rate of the material in a specific band such as visible light and infrared; the refractive index The correction value is a dynamic refractive index adjustment calculated by combining the Fresnel formula with the reflectivity weight value and the light absorption parameter; the light absorption correction value is based on the product of the mean infrared light intensity and the light absorption parameter, reflecting the actual energy attenuation ratio under the current lighting conditions; the dynamic refractive index parameter is a dynamic adjustment parameter bound by the refractive index correction value and the grid unit coordinates, which is used to update the light refraction behavior of the virtual scene in real time; the three-dimensional light field simulation model ultimately contains the spatial coordinates, dynamic refractive index parameters and light source attenuation data of all grid cells, and realizes the synchronous changes of the virtual light field and physical lighting through the bidirectional reflectance distribution function (BRDF) rendering engine.

[0102] In the embodiment of the present application, the optical reflectance feature distribution map is read by the data parsing engine in step 1041, and the XYZ coordinate values, reflectance weight value, and 8-bit material type identification code of each grid cell are extracted using a regular expression matching algorithm. Secondly, the material type identification code is input into a preset hash index database, and a binary search algorithm is used to quickly locate the corresponding surface scattering parameters, including diffuse reflectance and specular reflectance, as well as light absorption parameters, including visible light band absorptivity and infrared band absorptivity. Finally, the parameter threshold range is compared through the data verification module, and abnormal parameters that exceed the allowable value are automatically replaced with default material parameters to ensure data reliability.

[0103] Next, in step 1042, the mean visible light intensity and reflectivity weight are input into the Fresnel formula calculation module. Combined with the refractive index reference value in the material surface scattering parameters, an iterative method is used to solve the refractive index correction value, with an accuracy of four decimal places. Next, the mean infrared light intensity and light absorption parameters are substituted into the Beer-Lambert law, and a linear interpolation algorithm is used to generate the light absorption correction value. The refractive index correction value and light absorption correction value are then encapsulated into a dynamic refractive index parameter package in JSON format through a dynamic parameter binder. A spatial coordinate hashing algorithm is used to establish a bidirectional mapping relationship between the package and the corresponding grid cell coordinates, and the package is written to the distributed memory database in real time.

[0104] Next, the 3D scene segmentation engine in step 1043 divides the virtual scene into equal-volume cubic blocks based on grid cell coordinates, and an octree spatial indexing algorithm is used to optimize block management efficiency. Secondly, based on the diffuse reflectance coefficient in the surface scattering parameters, the propagation path of the virtual light source is recalculated using a Monte Carlo ray tracing algorithm, and the incident and reflection angles of the light are adjusted using a bidirectional reflectance distribution function model. Finally, the light absorption correction value is input into the light attenuation calculation module, and an exponential attenuation function is applied to the RGB brightness values ​​of the virtual light source. Simultaneously, a piecewise linear interpolation algorithm is used to dynamically attenuate the thermal radiation intensity, achieving a synchronized response to changes in physical space illumination.

[0105] Finally, the spatial data aggregator in step 1044 normalizes the coordinate information, dynamic refractive index parameters, and light source attenuation parameters of all grid cells, and uses Z-order curve encoding to achieve linear storage of three-dimensional spatial data. Secondly, a layered bounding box acceleration structure is constructed in the ray tracing rendering engine, binding the dynamic refractive index parameters and bidirectional reflectance distribution function material properties to each triangle facet. Finally, a real-time light field synthesizer fuses the path tracing calculation results with the photon mapping data to generate a three-dimensional light field simulation model that includes radiant brightness distribution, shadow gradient bands, and thermal radiation intensity gradients. Real-time streaming of the model data to the VR headset is achieved through a WebGL interface.

[0106] In practical applications, for example, a virtual home design system uses dynamic light field reconstruction technology to achieve realistic rendering of the environment when simulating the lighting effects of a duplex villa. When the user uses the VR controller to replace the natural marble coffee table in the center of the living room with acrylic, the system immediately extracts the grid data of the coffee table area from the current optical reflection feature distribution map, including the coordinates of 256 grid cells with an accuracy of 0.05 meters, reflectivity weight values, and material identification codes. It also retrieves the surface scattering coefficient of 0.78 and infrared absorption coefficient of 0.32 for the acrylic material from the material database. Combined with the visible light intensity of 920 lux and infrared radiation intensity of 150 watts per square meter projected from the south-facing floor-to-ceiling window obtained by the real-time lighting engine, the system calculates the refractive index correction value for each grid cell: the original marble refractive index of 1.55 is adjusted to the acrylic material's 1.49, and the light absorption correction value is increased based on the incident angle of the afternoon sun, generating a dynamic optical parameter set bound to the grid. The virtual scene engine then segmented the three-dimensional space surrounding the coffee table. Based on the anisotropic scattering properties of acrylic, the 56 virtual light sources from the overhead chandelier were adjusted to a soft light projection mode with a 42-degree diffusion angle. The infrared radiation penetrating the coffee table was also gradiently attenuated by 22%. As the user rotated their viewing angle, the system displayed the changes in light intensity in real time: the iridescent halo created by the acrylic surface's reduced refractive index was stronger than that of the original marble, and the focal spot of infrared heat radiation on the wooden floor was reduced to one-third of its original size. The resulting three-dimensional light field model contained 47,000 dynamic parameter nodes. When the simulated outdoor weather switched to rainy mode, the system automatically triggered a secondary correction: based on simulated humidity sensor data, the refractive index of the glass sliding door area was increased by 0.07 to enhance the mist refraction effect. This reduced the deviation between the diffuse reflection trajectory of light between the matte metal chandelier and the velvet sofa in the virtual space and the real-world experimental data.

[0107] In the complete solution of step 103 above, grid unit coordinates, reflectivity weights and material types are extracted based on real-time data of the optical reflection feature distribution map to accurately map the lighting distribution characteristics of the physical space; the refractive index correction value and the light absorption correction value are dynamically calculated in combination with the material surface scattering parameters and light absorption parameters to ensure that the refractive behavior of the virtual light field is synchronized with the actual lighting changes in the physical space in real time; 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 dynamic refractive index parameters and attenuation processing results are integrated to generate a three-dimensional light field model covering the virtual scene, so that the spatial light intensity gradient distribution and material reflective characteristics of the virtual light field are consistent with the actual lighting state of the physical space at the atomic level, effectively solving the problems of lighting distortion and response delay caused by static parameter presets in traditional virtual light field modeling, and providing high-precision light field data support for the two-way collaborative optimization of virtual and real environments.

[0108] 105. Based on the real-time monitoring results of the changes in light intensity in the physical space and combined with the light field distribution data of the three-dimensional light field simulation model, an adaptive compensation operation of the temperature and humidity parameters in the virtual scene is triggered, and the reflection characteristic parameters of the dynamic optical reflective film layer are synchronously adjusted to achieve two-way parameter coordinated optimization of the physical environment and the virtual light field.

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

[0110] 1051. Real-time monitoring of the rate of change of illumination in a target area of ​​the physical space, and synchronous extraction of a light intensity gradient value of the corresponding area from the three-dimensional light field simulation model;

[0111] 1052. Based on the correlation between the illumination change rate and the light intensity gradient value, generate a temperature and humidity compensation amount and a reflectance characteristic adjustment amount for the target area through an adaptive compensation operation;

[0112] Among them, step 1052 may specifically include the following contents: matching the illumination 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 spatial coordinate alignment rule, and establishing a product correlation relationship model between the two; based on the product correlation relationship model, generating a temperature and humidity compensation reference value and a reflection characteristic adjustment reference value; based on the temperature and humidity compensation reference value, superimposing 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 through a dynamic weight allocation rule to generate a temperature and humidity compensation amount, wherein the dynamic weight allocation rule is automatically adjusted according to the real-time fluctuation amplitude of the illumination change rate; based on the reflection characteristic adjustment reference value, combined with the direction and amplitude of the light intensity gradient value and the current parameters of the reflective film layer, a reflection characteristic adjustment amount is generated through feedback optimization calculation.

[0113] 1053. Generate an environmental parameter update instruction for the virtual scene based on the temperature and humidity compensation amount, and generate an inclination angle and refractive index correction instruction for the dynamic optical reflective film layer based on the reflection characteristic adjustment amount;

[0114] 1054. Synchronously drive the deformation driving unit to execute the tilt angle and refractive index correction instructions by controlling the execution component, and execute the environment parameter update instruction in the virtual scene, thereby achieving two-way parameter collaborative optimization of the physical environment and the virtual light field.

[0115] In the above steps, the illumination change rate refers to the change in illumination intensity of the physical space target area collected in real time by the multispectral sensor per unit time, which is quantified in lux per second; the light intensity gradient value refers to the rate of change of illumination intensity in the X, Y, and Z axis directions at a 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 temperature and humidity of the target area 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 weighted integral operation based on the deviation value between 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 obtained by iterative optimization through the gradient descent method based on the difference between the light field distribution data and the physical reflection characteristics. Emissivity correction value; environmental parameter update instruction refers to a control signal containing the target temperature, humidity setting value and change rate, which is used to drive the virtual scene rendering engine to update the environmental parameters; the tilt and refractive index correction instruction refers to a digital control instruction set containing execution parameters such as the stepper motor rotation angle and piezoelectric ceramic drive voltage; the control execution component refers to a hardware system composed of a stepper motor, a servo driver and a DAC module, which is used to physically execute the parameter adjustment action of the reflective film layer; the deformation drive unit refers to a physical deformation actuator of the reflective film layer made of shape memory alloy or micro-electromechanical system, which can accurately control the curvature and tilt angle of the film surface; two-way parameter collaborative optimization refers to a closed-loop feedback mechanism of physical environment sensor data and virtual light field simulation results to achieve a synchronous optimization process of the linkage between physical space and digital scene parameters.

[0116] In an embodiment of the present application, the multi-threaded data acquisition system of step 1051 obtains the time series data of the light intensity of the target area in the physical space in real time. After using the Kalman filter algorithm to eliminate sensor noise, the rate of change of light in each 0.5 second time window is calculated in lux / second. Secondly, the coordinate mapping relationship in the three-dimensional light field simulation model is matched by the spatial encoder, and the light intensity gradient value of the corresponding grid cell in the X / Y / Z axis direction is extracted using the octree fast retrieval algorithm. Finally, the light change rate and the light intensity gradient value are aligned by timestamp and stored in a ring buffer to provide a real-time data source for subsequent correlation calculations.

[0117] Next, in step 1052, the illumination change rate and light intensity gradient are input into the fuzzy PID control algorithm. The relationship between the two is quantified into a fuzzy rule matrix using a membership function. A defuzzification operation is then performed to generate preliminary values ​​for temperature and humidity compensation. Next, based on the normalized X, Y, and Z components of the light intensity gradient direction vector and the current inclination angle parameters of the reflective film layer, a gradient descent method is used to iteratively calculate the reflective characteristic adjustment, minimizing the error between the thermal radiation distribution of the virtual light field and the measured data in the physical space. Finally, a weighted fusion algorithm is used to perform a sliding average filter on the preliminary temperature and humidity compensation value and historical compensation data, outputting the final compensation and adjustment values.

[0118] Next, step 1053 converts the temperature and humidity compensation values ​​into virtual scene environment parameter update instructions. The temperature compensation value is mapped to the set value range of the virtual temperature control system using a linear interpolation algorithm, while the humidity compensation value uses an exponential smoothing algorithm to generate a progressive adjustment curve. Both are encapsulated into a JSON-formatted instruction packet. Next, the inclination correction value in the reflectance characteristic adjustment value is converted into a stepper motor rotation angle instruction using a quaternion conversion algorithm. The refractive index correction value is converted into a 0-10V analog voltage signal via a DAC module, forming a digital control instruction set with execution timing. All instructions are synchronized with the virtual update at the millisecond level using a timestamp synchronization module to ensure millisecond synchronization between physical execution and virtual updates.

[0119] Finally, the tilt and refractive index correction instructions are sent to the control execution component via the CAN bus in step 1054: the stepper motor driver receives the pulse signal to drive the deformation drive unit, such as the piezoelectric ceramic actuator, to achieve nanometer-scale tilt adjustment of the reflective film layer, and the DAC module outputs a voltage signal to adjust the refractive index of the liquid crystal layer. Secondly, the virtual scene rendering engine parses the environmental parameter update instructions, uses a bilinear interpolation algorithm to smoothly transition the temperature and humidity parameter changes, and synchronously updates the dielectric absorption coefficient in the ray tracing calculation. Finally, through a closed-loop feedback mechanism, the deviation between the physical sensor data and the virtual light field simulation results is compared. If the deviation exceeds the threshold, the compensation value is recalculated until the bidirectional parameter collaborative optimization reaches steady-state convergence.

[0120] In practical applications, for example, a smart home virtual design system uses bidirectional mapping technology to dynamically optimize the virtual-real environment when simulating an open kitchen and living room. When the transmittance of a smart dimming glass curtain wall in the real space increases over 30 seconds due to increased sunlight, the system simultaneously captures the illumination change rate of 180 lux / s in that area and extracts a 0.78 instantaneous light intensity gradient from the 3D light field model for the corresponding virtual area. An adaptive compensation algorithm calculates that the reflective properties of the quartz stone surface of the virtual island counter need to be enhanced by 19% to suppress glare, while the air speed of the virtual air conditioner outlet needs to be increased by 0.3 m / s to compensate for temperature fluctuations. The system immediately generates bidirectional control commands: in the physical space, it activates the micro-hydraulic actuator array of the dynamic reflective film layer, adjusting the tilt angle of the microprisms in a 0.6 square meter area on the southeast side of the curtain wall from 8 degrees to 14.5 degrees, while simultaneously injecting current to change the refractive index of the electrochromic layer to 1.53. In the virtual scene, this triggers an environmental parameter update protocol, increasing the simulated air flow rate of the air conditioner to 280 m / s. 3 / h, and added a Fresnel reflective layer to the surface of the acrylic chandelier model. When the user dragged a metal bar stool to a west-facing area in the VR environment, the system detected in real time that the infrared radiation intensity in the physical space increased by 25W / m 2, immediately reverse-optimizing the virtual material parameters—reducing the specular reflection weight of the chrome bar stool material by 0.22, while increasing the virtual air convection velocity in the seating area to stabilize the simulated surface temperature of the leather material within a comfortable range of 41°C ± 0.5°C. This two-way control mechanism completes a full-link response within 0.5 seconds. Dynamic adjustment reduces direct light heat accumulation on the physical curtain wall surface by 12%, and the color temperature offset of the light spot on the marble floor in the virtual scene is controlled within 150K. The optimized parameter set is synchronized to the smart air conditioning and lighting systems in the real space through the IoT interface, forming a cross-dimensional closed-loop control of environmental parameters, ultimately achieving the coordinated optimization of virtual design previews and real-life home energy consumption.

[0121] In the complete solution of step 105 above, dynamic closed-loop optimization of the physical environment and the virtual light field is achieved through collaborative analysis of illumination change monitoring and light field data. The technical effects are as follows: real-time capture of the illumination intensity change characteristics of the physical space, establishment of an environmental parameter correlation mapping based on the light intensity gradient data of the three-dimensional light field model, triggering the temperature and humidity compensation algorithm to intelligently generate adjustment parameters; synchronously driving the inclination angle and refractive index correction of the dynamic optical reflective film layer, and updating the virtual scene environment parameters to ensure real-time matching of the material reflective properties of the virtual and real environments with the temperature and humidity effects; through a two-way instruction collaborative execution mechanism, breaking through the hysteresis limitation of traditional one-way parameter adjustment, allowing the physical reflective characteristics and the virtual light field state to continuously converge to the optimal balance in dynamic changes, significantly improving the realism of environmental simulation in home design scenarios and the robustness of system response.

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

[0123] When simulating a living room environment, a smart home VR design platform uses a distributed sensor array to collect real-time indoor temperature and humidity gradients and multispectral lighting data, constructing a high-precision three-dimensional environmental parameter model. When a user adjusts the opening or closing of smart curtains in the virtual space, the system simultaneously analyzes the sensor data in the physical space, marking areas of sudden changes in light intensity within the 3D mesh model—for example, the high infrared radiation band created by direct sunlight on the west-facing windows. A corresponding light spot heat map is then automatically generated for the virtual scene. A dynamic optical reflective film layer adjusts its surface microstructure based on the reflectivity weights in the model. In areas of strong sunlight, the film's tilt angle increases by 10 degrees and its refractive index decreases, effectively dispersing direct light. The virtual engine also matches material parameters to add Fresnel reflections to the marble floor, ensuring that the lighting and shadow effects align with real-world physical laws. When physical sensors detect an abnormal temperature rise in a specific area, the system triggers a two-way increase in the virtual air conditioner's air speed and a fine-tuning of the film's refractive index, reducing thermal radiation intensity by 15% within 0.8 seconds while maintaining the simulated surface temperature of the leather sofa in the virtual scene within a ±0.5°C fluctuation range. The system uses real-time feedback from virtual and real environment parameters, allowing the lighting layout plan verified by the designer in VR to be directly output as intelligent lighting control parameters in the physical space, ensuring that the energy efficiency and light and shadow effect errors of the design plan are reduced when it is actually implemented.

[0124] Figure 3 The present invention provides a structural diagram of a home overall design system based on virtual reality, as shown in FIG. Figure 3 As shown, the system includes:

[0125] The acquisition module 31 uses the temperature and humidity sensor array and multi-spectral light sensor in the distributed sensor network to synchronously collect temperature and humidity gradient data and multi-band light intensity distribution data of the indoor physical space in a spatial grid distribution mode;

[0126] A generation module 32 inputs the temperature and humidity gradient data and the multi-band light intensity data into a spatial topology association engine, and constructs a three-dimensional environmental parameter set including coordinate information, temperature and humidity parameters, light intensity, and reflectivity association weights based on a gridded three-dimensional spatial structure generation algorithm;

[0127] Matching module 33 drives the micro-electromechanical actuator of the dynamic optical reflective film layer to adjust the local inclination angle and refractive index of the film layer surface based on the spatial coordinate weight matrix in the three-dimensional environmental parameter set, and combines the scattering characteristic parameters of wood, metal, and glass materials in real time with the indoor material surface characteristic database to generate an optical reflection feature distribution map;

[0128] A construction module 34 constructs a three-dimensional light field simulation model in a virtual scene based on the real-time data of the optical reflection characteristic distribution map, which is dynamically linked to the actual illumination distribution of the physical space;

[0129] The adjustment module 35 triggers the adaptive compensation calculation of the temperature and humidity parameters in the virtual scene based on the real-time monitoring results of the changes in the light intensity of the physical space and the light field distribution data of the three-dimensional light field simulation model, and synchronously adjusts the reflective characteristic parameters of the dynamic optical reflective film layer to achieve two-way parameter coordinated optimization of the physical environment and the virtual light field.

[0130] Figure 3 The virtual reality-based home design system can be implemented Figure 1 The implementation principles and technical effects of the virtual reality-based integrated home design method described in the illustrated embodiment will not be elaborated on here. The specific manner in which the various modules and units in the virtual reality-based integrated home design system in the aforementioned embodiment perform their operations has been described in detail in the relevant embodiments of the method and will not be elaborated on here.

[0131] In one possible design, Figure 3 A virtual reality-based home design system of the embodiment shown can be implemented as a computing device, such as Figure 4 As shown, the computing device may 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 used for the above Figure 1 The embodiment provides a method for overall home design based on virtual reality.

[0134] The processing component 42 may include one or more processors to execute computer instructions to perform all or part of the steps in the above method. Of course, the processing component may also be implemented as 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 components to perform the above method.

[0135] The storage component 41 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile memory device, or a combination thereof, 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 memory, flash memory, magnetic disk, or optical disk.

[0136] Of course, a computing device may 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 the peripheral interface module, which can be an output device, an input device, etc.

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

[0139] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0140] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 The embodiment shown is a method for overall home design based on virtual reality.

[0141] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0142] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0143] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the existing technology can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0144] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions 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: Through the temperature and humidity sensor array and multi-spectral light sensor in the distributed sensor network, the temperature and humidity gradient data and multi-band light intensity distribution data of the indoor physical space are synchronously collected in a spatial grid distribution mode; Inputting the temperature and humidity gradient data and the multi-band light intensity data into a spatial topology association engine, and constructing a three-dimensional environmental parameter set including coordinate information, temperature and humidity parameters, light intensity, and reflectivity association weights based on a gridded three-dimensional spatial structure generation algorithm; Based on the spatial coordinate weight matrix in the three-dimensional environmental parameter set, the micro-electromechanical actuator of the dynamic optical reflective film layer is driven to adjust the local inclination angle and refractive index of the film surface. 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. Based on the real-time data of the optical reflection characteristic distribution map, a three-dimensional light field simulation model dynamically linked to the actual illumination distribution in the physical space is constructed in the virtual scene; Based on the real-time monitoring results of the changes in light intensity in the physical space and combined with the light field distribution data of the three-dimensional light field simulation model, adaptive compensation calculations of the temperature and humidity parameters in the virtual scene are triggered, and the reflection characteristic parameters of the dynamic optical reflective film layer are synchronously adjusted to achieve two-way parameter coordinated optimization of 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 micro-electromechanical actuator of the dynamic optical reflective film layer is driven to adjust the local inclination angle and refractive index of the film layer surface. 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 feature distribution map, including: Extracting a spatial coordinate weight matrix from the three-dimensional environmental parameter set, wherein the spatial coordinate weight matrix includes a reflectivity association weight value corresponding to each grid node; Dividing the surface of the dynamic optical reflective film layer into a plurality of dynamic adjustment regions according to the reflectivity-associated weight values ​​in the spatial coordinate weight matrix, wherein the boundary of each dynamic adjustment region is determined by whether the weight difference of adjacent grid nodes exceeds a preset segmentation threshold; Obtaining a reference scattering parameter for the material type corresponding to the current dynamic adjustment area from a material surface property database, and calculating a target adjustment amount for the local tilt angle and a target correction amount for the refractive index of the film surface based on a difference between the reflectivity association weight value of the current area and the reference scattering parameter; Based on the target adjustment amount and the target correction amount, the actuator is controlled to drive the film surface deformation mechanism so that the inclination angle and the refractive index of the current area are synchronously adjusted to the physical state corresponding to the target adjustment amount; The adjusted inclination angle value and refractive index value of each dynamic adjustment area 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 in combination with the indoor material surface characteristic database to generate an optical reflection characteristic distribution map of the surface of the covering film layer.

3. The method according to claim 2, characterized in that Based on the target adjustment amount and the target correction amount, the inclination angle and the refractive index of the current area are synchronously adjusted to the physical state corresponding to the target adjustment amount by controlling the actuator to drive the film surface deformation mechanism, including: Inputting the target adjustment amount and the target correction amount into a control signal conversion logic to generate a drive signal set corresponding to the physical deformation amount of the deformation mechanism, wherein the drive signal set includes a tilt angle drive signal component and a refractive index drive signal component; According to a dynamic allocation strategy among the components of the drive signal set, the tilt drive signal component and the refractive index drive signal component are synchronously and optimally allocated according to a preset priority rule to generate a collaborative control instruction set executable by the deformation mechanism; The signal parsing unit in the control execution component converts the collaborative control instruction set into physical deformation parameters that can be recognized by the deformation drive unit, wherein the physical deformation parameters include deformation displacement, deformation rate and deformation direction; Driving the deformation driving unit to perform a deformation operation on the current area of ​​the film layer surface based on the physical deformation parameter, so that the local area of ​​the film layer surface synchronously generates an inclination deformation displacement and a refractive index deformation displacement, wherein the difference between the inclination deformation displacement and the target adjustment amount does not exceed a preset deformation tolerance threshold, and the difference between the refractive index deformation displacement and the target correction amount does not exceed a preset refractive index tolerance threshold; The actual deformation parameters after the deformation drive unit is executed are fed back to the control signal conversion logic, and the signal component distribution ratio in the drive signal set is updated, so that the inclination angle and refractive index of the current area are synchronously adjusted to the physical state corresponding to the target adjustment amount.

4. The method according to claim 1, wherein Based on the real-time monitoring results of changes in light intensity in the physical space, 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 reflective characteristic parameters of the dynamic optical reflective film layer are synchronously adjusted to achieve bidirectional parameter coordinated optimization of the physical environment and the virtual light field, including: Real-time monitoring of the rate of change of illumination in a target area of ​​the physical space, and simultaneous extraction of a light intensity gradient value of the corresponding area from the three-dimensional light field simulation model; Based on the correlation between the illumination change rate and the light intensity gradient value, a temperature and humidity compensation amount and a reflectance characteristic adjustment amount of the target area are generated through adaptive compensation calculation; Generate an environmental parameter update instruction for the virtual scene according to the temperature and humidity compensation amount, and generate an inclination angle and refractive index correction instruction for the dynamic optical reflective film layer according to 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 instructions, and executing the environment parameter update instructions 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 the multi-band light intensity 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 weights is constructed based on a grid-based three-dimensional spatial structure generation algorithm, including: The temperature gradient value and the humidity gradient value in the temperature and humidity gradient data are data-associated according to 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; Determine a reference plane of a three-dimensional coordinate system based on the boundary data of the wall structure of the physical space and establish a three-dimensional grid division reference, and divide the three-dimensional coordinate system into equally spaced grid units based on the spatial coverage of the temperature and humidity distribution set and the light intensity band distribution set; Extracting the temperature gradient mean, humidity gradient mean, visible light band intensity mean, and infrared band intensity mean for each grid cell, correlating the temperature gradient mean with the visible light band intensity mean to generate a temperature-light intensity correlation factor, and correlating the humidity gradient mean with the infrared band intensity mean to generate a humidity band correlation factor; Obtaining a material reference reflectance value of the area where the current grid unit is located from an indoor material surface property database, and generating a reflectance association weight value of the current grid unit based on a weighted calculation result of the temperature-light-intensity correlation factor and the humidity band correlation factor, combined with the material reference reflectance value; The coordinate information, temperature gradient mean, humidity gradient mean, visible light band intensity mean, infrared band intensity mean and reflectivity associated weight values ​​of all grid cells are combined in the order of three-dimensional coordinate arrangement to generate a three-dimensional environmental parameter set covering the physical space.

6. The method according to claim 1, characterized in that Based on the real-time data of the optical reflection feature distribution map, a three-dimensional light field simulation model dynamically linked to the actual illumination distribution in the physical space is constructed in the virtual scene, including: Extracting coordinate information, reflectivity weight value, and material type identification of each grid unit from the optical reflection feature distribution map, and acquiring corresponding surface scattering parameters and light absorption parameters from a material surface property database according to the material type identification; Based on the average visible light intensity and the average infrared light intensity in the real-time illumination data of the physical space, combined with the reflectivity weight value and the light absorption parameter, a refractive index correction value and a light absorption correction value are calculated for each grid cell; a dynamic refractive index parameter is generated based on the refractive index correction value and the light absorption correction value, and the dynamic refractive index parameter is bound to the grid cell coordinates; In the virtual scene, the scene space is divided according to the grid unit coordinates, the propagation direction of the virtual light source is adjusted according to the surface scattering parameter, and the brightness and thermal radiation intensity of the light source are attenuated in combination with the light absorption correction value; Based on the coordinate information, dynamic refractive index parameters and attenuation processing results of all grid cells, 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 illumination change rate and the light intensity gradient value, the temperature and humidity compensation amount and the reflectance characteristic adjustment amount of the target area are generated through adaptive compensation calculation, including: Matching the illumination 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 spatial coordinate alignment rule, and establishing a product correlation relationship model between the two; Based on the product correlation model, generating a temperature and humidity compensation reference value and a reflectance characteristic adjustment reference value; Based on the temperature and humidity compensation reference value, a temperature and humidity compensation amount is generated by superimposing 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 through a dynamic weight allocation rule, wherein the dynamic weight allocation rule is automatically adjusted according to the real-time fluctuation amplitude of the light change rate; Based on the reflection characteristic adjustment reference value, combined with the direction and amplitude of the light intensity gradient value and the current parameters of the reflection film layer, a reflection characteristic adjustment amount is generated through feedback optimization calculation.

8. A home overall design system based on virtual reality, characterized in that: include: The acquisition module uses the temperature and humidity sensor array and multi-spectral light sensor in the distributed sensor network to synchronously collect temperature and humidity gradient data and multi-band light intensity distribution data of the indoor physical space in a spatial grid distribution mode; A generation module inputs the temperature and humidity gradient data and the multi-band light intensity data into a spatial topology association engine, and constructs a three-dimensional environmental parameter set including coordinate information, temperature and humidity parameters, light intensity, and reflectivity association weights based on a gridded three-dimensional spatial structure generation algorithm; A matching module drives the micro-electromechanical actuator of the dynamic optical reflective film layer to adjust the local inclination angle and refractive index of the film layer surface based on the spatial coordinate weight matrix in the three-dimensional environmental parameter set, and combines the scattering characteristic parameters of wood, metal, and glass materials in real time with the indoor material surface characteristic database to generate an optical reflection feature distribution map; A construction module, based on the real-time data of the optical reflection characteristic distribution map, constructs a three-dimensional light field simulation model in a virtual scene that is dynamically linked to the actual illumination distribution of the physical space; The adjustment module triggers adaptive compensation calculations for temperature and humidity parameters in the virtual scene based on the real-time monitoring results of changes in light intensity in the physical space and the light field distribution data of the three-dimensional light field simulation model, and synchronously adjusts the reflective characteristic parameters of the dynamic optical reflective film layer to achieve bidirectional parameter coordinated optimization of 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 used to be called and executed by the processing component to implement a virtual reality-based home overall design method as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that A computer program is stored, and when the computer program is executed by a computer, the method for overall home design based on virtual reality as claimed in any one of claims 1 to 7 is implemented.

Images