Information superposition method of intelligent perception information in virtual space

Abstract

The embodiment of the present application provides a method for superimposing intelligent perception information in a virtual space, which establishes a data stratification mechanism based on importance weights by evaluating the information completeness and relevance of multi-source data such as images, temperature, and sound. A hierarchical display buffer is used to implement hierarchical management of information, and the visual effect between layers is optimized by combining edge clarity evaluation and fuzzy processing technology. Intelligent superposition of multiple layers of data is achieved through contrast enhancement and transparency control, and the display refresh strategy is dynamically adjusted based on the timeliness of the data. This method effectively solves the problems of chaotic display and visual interference in traditional superposition solutions when processing multi-dimensional perception information, and improves the quality of information display in virtual space.

Description

Technical Field

[0001] The present application relates to the field of data processing, and in particular to a method for superimposing intelligent perception information in a virtual space. Background Art

[0002] In the development of virtual reality and augmented reality technologies, multi-dimensional overlay display of intelligently perceived information is a key technology for achieving immersive experience. Traditional information overlay methods usually use simple hierarchical overlay, lacking intelligent evaluation and dynamic adjustment mechanisms for data importance. Although there are some display solutions based on data priority, there are still obvious deficiencies in processing the overlay effect and visual experience of multi-source heterogeneous data.

[0003] Existing systems generally have problems such as confusing display and unclear hierarchical relationships when processing multi-dimensional perception data. In particular, when multiple types of data are displayed simultaneously, visual interference and information redundancy are prone to occur. At the same time, existing methods lack a comprehensive assessment of data timeliness and integrity, and cannot achieve intelligent hierarchical display of information, which affects users' perception and understanding of key information in virtual space.

[0004] Therefore, how to establish an intelligent data evaluation mechanism, realize the effective stratification and dynamic display of multi-dimensional information, and improve the visual presentation quality of the system are technical problems that need to be solved urgently. This is not only related to the information display effect of the virtual space, but also an important basis for improving the user interaction experience. Summary of the invention

[0005] In response to the problems in the prior art, the present application provides a method for superimposing intelligent perception information in a virtual space, which can effectively solve the problems of chaotic display and visual interference in traditional superposition solutions when processing multi-dimensional perception information, and improve the quality of information display in the virtual space.

[0006] In order to solve at least one of the above problems, the present application provides the following technical solutions:

[0007] In a first aspect, the present application provides a method for superimposing intelligent perception information in a virtual space, comprising:

[0008] Collect image data, temperature data, and sound data in the scene space, annotate the data by type, build a data priority assessment model, calculate the information completeness and relevance scores of the data, generate importance weight coefficients based on the completeness scores and the relevance scores, use the importance weight coefficients as the basis for data stratification, and establish a virtual space coordinate mapping function;

[0009] The virtual space coordinate system is sliced ​​and layered to construct a hierarchical display buffer, display parameters of each layer are calculated according to the importance weight coefficient, data with the maximum importance weight coefficient is allocated to the top display buffer, edge clarity score of each layer of data is calculated, blur radius parameter is set based on the edge clarity score, blur processing is performed on non-top data, an inter-layer contrast enhancement matrix is ​​constructed, the display parameters are adjusted using the inter-layer contrast enhancement matrix, a minimum interval threshold between layers is set, a layered mark bit is added to the display buffer, the layered mark bit is mapped to a transparency control parameter, a hybrid weight coefficient is generated based on the transparency control parameter, and data of different levels are superimposed using the hybrid weight coefficient;

[0010] A display strategy mapping table is established, a corresponding visualization template is selected according to the type label, a data timeliness score is calculated, the timeliness score is converted into a display refresh cycle, the information state in the virtual space is updated based on the display refresh cycle, smoothing is performed on the information state, and the processed result is synchronously displayed on the virtual space interface.

[0011] Furthermore, the image data, temperature data, and sound data in the collected scene space are annotated with types, a data priority evaluation model is constructed, and the information completeness and relevance scores of the data are calculated, including:

[0012] Collecting three-dimensional image data, temperature field data, and sound field data in a scene space, storing the data uniformly in a buffer queue, reading data items from the buffer queue, extracting distribution features of the data items, establishing a data type feature library, matching the distribution features with the data type feature library, and adding a type identifier to the data item;

[0013] The data item is converted into a vector representation, a neural network evaluation model is constructed based on the vector representation, a data redundancy coefficient and a spatial correlation coefficient are calculated for the data item, the data redundancy coefficient is mapped into an information completeness score, and the spatial correlation coefficient is mapped into a correlation score.

[0014] Furthermore, the importance weight coefficient is generated based on the completeness score and the relevance score, and the importance weight coefficient is used as a basis for data stratification to establish a virtual space coordinate mapping function, including:

[0015] Normalizing the completeness score and the relevance score, constructing a linear combination model, inputting the completeness score and the relevance score into the linear combination model, calculating a comprehensive score of the data item, generating an importance weight coefficient based on the comprehensive score, prioritizing the data items using the importance weight coefficient, and dividing the sorting results into multiple levels;

[0016] A three-dimensional coordinate transformation matrix is ​​established to convert the data position information in the scene space coordinate system into virtual space coordinate values, a uniform grid is constructed in the virtual space, the position deviation of the grid nodes is calculated, a coordinate interpolation function is constructed based on the position deviation, and the coordinate interpolation function is used as the virtual space coordinate mapping function.

[0017] Furthermore, the step of slicing the virtual space coordinate system in layers, constructing a hierarchical display buffer, calculating display parameters of each layer according to the importance weight coefficient, and allocating data with the maximum importance weight coefficient to the top display buffer includes:

[0018] Setting a slice spacing threshold in the virtual space coordinate system, dividing the space level based on the slice spacing threshold, calculating the depth value of each slice layer, quantizing the depth value, storing the quantized depth value in a depth buffer, allocating an independent display buffer for each slice layer, and establishing an inter-layer data index table;

[0019] Read the importance weight coefficient, build a display parameter calculation model, input the importance weight coefficient into the display parameter calculation model, generate the display scale coefficient and position offset of each layer of slices, filter the data group with the largest importance weight coefficient, and allocate the data group to the display buffer corresponding to the top layer slice.

[0020] Further, the inter-layer contrast enhancement matrix is ​​constructed, the display parameters are adjusted using the inter-layer contrast enhancement matrix, the minimum inter-layer interval threshold is set, a layered mark bit is added to the display buffer, the layered mark bit is mapped to a transparency control parameter, a hybrid weight coefficient is generated based on the transparency control parameter, and different levels of data are superimposed using the hybrid weight coefficient, including:

[0021] Calculate the brightness difference of adjacent level data, construct a contrast adjustment coefficient matrix, perform matrix multiplication operation on the contrast adjustment coefficient matrix and the display parameter, set a minimum distance value between layers, adjust the level interval based on the minimum distance value, add a level identification field in the data structure of the display buffer, and map the level identification field to a transparency value interval;

[0022] Perform a nonlinear transformation on the transparency value to generate a normalized mixing weight coefficient, establish a hierarchical data mixing operation buffer, write each layer of data into the mixing operation buffer in the order of the size of the mixing weight coefficient, perform weighted average calculation on the data in the mixing operation buffer, and output the calculation result to the display buffer.

[0023] Furthermore, the establishing of a display strategy mapping table, selecting a corresponding visualization template according to the type label, calculating a data timeliness score, and converting the timeliness score into a display refresh cycle includes:

[0024] Constructing a visualization strategy database, establishing a mapping relationship between a data type identifier and a visualization template, saving the mapping relationship to a display strategy mapping table, reading the type annotation information, searching for a matching item in the display strategy mapping table, and obtaining corresponding visualization template parameters;

[0025] Add a timestamp field to each data item, calculate the difference between the current time of the data item and the timestamp, substitute the difference into the timeliness decay function, generate a data timeliness score, establish a refresh cycle mapping function, input the timeliness score into the refresh cycle mapping function, and calculate the display refresh time interval.

[0026] Further, the updating of the information state in the virtual space based on the display refresh cycle, performing smoothing processing on the information state, and synchronously displaying the processed result on the virtual space interface includes:

[0027] Constructing a display state update queue, setting the display refresh cycle as a state update trigger condition, reading the latest data when the trigger condition is detected to be satisfied, writing the latest data into a virtual space information buffer, calculating state difference values ​​of adjacent data items, performing linear interpolation operation on the state difference values, and generating a state transition sequence;

[0028] A mean filtering operation is performed on the state transition sequence, the filtered data is written into a display state buffer, a virtual space display controller is established, the data in the display state buffer is transmitted to the display controller, and the display controller synchronously outputs the data to the virtual space display interface.

[0029] In a second aspect, the present application provides an information superposition device for intelligent perception information in a virtual space, comprising:

[0030] A virtual mapping module is used to collect image data, temperature data, and sound data in the scene space, perform type annotation on the data, build a data priority evaluation model, calculate the information completeness and relevance scores of the data, generate an importance weight coefficient based on the completeness score and the relevance score, use the importance weight coefficient as a basis for data stratification, and establish a virtual space coordinate mapping function;

[0031] an information superposition module, for slicing the virtual space coordinate system in layers, constructing a hierarchical display buffer, calculating display parameters of each layer according to the importance weight coefficient, allocating data with the maximum importance weight coefficient to the top display buffer, calculating edge clarity scores of data of each layer, setting blur radius parameters based on the edge clarity scores, performing blur processing on non-top data, constructing an inter-layer contrast enhancement matrix, adjusting the display parameters using the inter-layer contrast enhancement matrix, setting an inter-layer minimum interval threshold, adding a layered mark bit in the display buffer, mapping the layered mark bit to a transparency control parameter, generating a hybrid weight coefficient based on the transparency control parameter, and using the hybrid weight coefficient to perform superposition processing on data of different levels;

[0032] A visualization module is used to establish a display strategy mapping table, select a corresponding visualization template according to the type label, calculate a data timeliness score, convert the timeliness score into a display refresh cycle, update the information state in the virtual space based on the display refresh cycle, perform smoothing on the information state, and synchronously display the processed results on the virtual space interface.

[0033] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps of the method for superimposing intelligent perception information in a virtual space are implemented.

[0034] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method for superimposing intelligent perception information in a virtual space.

[0035] In a fifth aspect, the present application provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the method for superimposing intelligent perception information in a virtual space.

[0036] It can be seen from the above technical solutions that the present application provides a method for superimposing intelligent perceptual information in a virtual space, which establishes a data stratification mechanism based on importance weights by evaluating the information completeness and relevance of multi-source data such as images, temperature, and sound. A hierarchical display buffer is used to realize hierarchical management of information, and the visual effect between layers is optimized by combining edge clarity evaluation and fuzzy processing technology. Intelligent superposition of multiple layers of data is achieved through contrast enhancement and transparency control, and the display refresh strategy is dynamically adjusted based on the timeliness of the data. This method effectively solves the problems of chaotic display and visual interference of traditional superposition solutions when processing multi-dimensional perceptual information, and improves the quality of information display in virtual space. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. 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 paying any creative work.

[0038] Figure 1 This is one of the flow diagrams of the method for superimposing intelligent perception information in a virtual space in an embodiment of the present application;

[0039] Figure 2 The second flowchart of the method for superimposing intelligent sensing information in a virtual space in an embodiment of the present application;

[0040] Figure 3 The third flowchart of the method for superimposing intelligent sensing information in a virtual space in an embodiment of the present application;

[0041] Figure 4 This is a fourth flow chart of the method for superimposing intelligent perception information in a virtual space in an embodiment of the present application;

[0042] Figure 5 FIG5 is a flowchart of the method for superimposing intelligent sensing information in a virtual space in an embodiment of the present application;

[0043] Figure 6 This is a sixth flow chart of the method for superimposing intelligent perception information in a virtual space in an embodiment of the present application;

[0044] Figure 7 FIG7 is a flow chart of the method for superimposing intelligent sensing information in a virtual space in an embodiment of the present application;

[0045] Figure 8 It is a structural diagram of an information superposition device for intelligently sensing information in a virtual space in an embodiment of the present application;

[0046] Fig. 9 It is a schematic diagram of the structure of an electronic device in an embodiment of the present application.

[0047] Reference numerals:

[0048] Electronic device 9600, central processing unit 9100, memory 9140, communication module 9110, input unit 9120, audio processor 9130, display 9160, power supply 9170, buffer memory 9141, application / function storage unit 9142, data storage unit 9143, driver program storage unit 9144, antenna 9111, speaker 9131, microphone 9132. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, 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. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0050] The acquisition, storage, use, and processing of data in the technical solution of this application comply with the relevant provisions of national laws and regulations.

[0051] Taking into account the problems existing in the prior art, the present application provides a method for superimposing intelligent perception information in a virtual space, which establishes a data stratification mechanism based on importance weights by evaluating the information completeness and relevance of multi-source data such as images, temperature, and sound. A hierarchical display buffer is used to realize hierarchical management of information, and the visual effect between layers is optimized by combining edge clarity evaluation and fuzzy processing technology. Intelligent superposition of multiple layers of data is achieved through contrast enhancement and transparency control, and the display refresh strategy is dynamically adjusted based on the timeliness of the data. This method effectively solves the problems of chaotic display and visual interference of traditional superposition solutions when processing multi-dimensional perception information, and improves the quality of information display in virtual space.

[0052] In order to effectively solve the problems of chaotic display and visual interference in traditional overlay solutions when processing multi-dimensional perceptual information and improve the quality of information display in virtual space, the present application provides an embodiment of an information overlay method for intelligent perceptual information in virtual space, see Figure 1 The method for superimposing intelligent perception information in a virtual space specifically includes the following contents:

[0053] Step S101: collecting image data, temperature data, and sound data in the scene space, annotating the data by type, building a data priority evaluation model, calculating the information completeness and relevance scores of the data, generating importance weight coefficients based on the completeness scores and the relevance scores, using the importance weight coefficients as a basis for data stratification, and establishing a virtual space coordinate mapping function;

[0054] Optionally, this embodiment builds a comprehensive multi-source sensor network system in the industrial production workshop. Set up a high-definition camera array at even intervals around key equipment to collect high-frame rate RGB image data and monitor the equipment operation status and worker operation behavior in real time; install an infrared thermal imager in the high-temperature area of ​​the equipment to continuously collect temperature field data and monitor the temperature distribution of the equipment; arrange an acoustic sensor array around the equipment to collect environmental noise and acoustic characteristics of equipment operation. The data collected by all sensors are transmitted to the central processing unit in real time via industrial Ethernet to ensure the real-time and reliability of the data.

[0055] This embodiment designs an intelligent data type labeling process. First, the feature extraction module extracts features from different types of data: extracts key feature points and contour features from image data, analyzes spatial distribution features and temperature change trends from temperature data, and performs frequency domain analysis on acoustic data to obtain spectral features. The extracted feature vectors are then input into a pre-trained deep learning classification network, which uses a multi-layer convolutional structure and a fully connected layer to achieve intelligent recognition and labeling of data types through deep learning.

[0056] This embodiment innovatively constructs a data priority assessment model. The model adopts an improved recurrent neural network structure, including a feature encoding module and a priority assessment module. The feature encoding module can effectively capture the temporal and spatial features of the data, and the priority assessment module calculates the importance of the data through a multi-layer neural network. The model is trained with large-scale historical data, continuously optimizes network parameters, and improves assessment accuracy.

[0057] This embodiment develops a complete data integrity assessment scheme. By analyzing the three dimensions of data sampling density, signal-to-noise ratio and continuity, the quality level of the data is comprehensively assessed. The sampling density reflects the adequacy of the data in spatial distribution, the signal-to-noise ratio characterizes the reliability of the data, and the continuity index measures the integrity of the data in the time dimension. By weighted combination of these indicators, the data integrity score is obtained.

[0058] This embodiment implements an innovative correlation evaluation mechanism. By constructing a correlation network between data items, the temporal correlation, spatial correlation, and logical dependency between data are analyzed. A graph neural network is used to process the correlation matrix, fully explore the deep correlation features between data items, and generate accurate correlation scores. This method can effectively identify complex correlation patterns between data and provide an important basis for subsequent data processing.

[0059] This embodiment designs an adaptive importance weight calculation method. First, the completeness score and the relevance score are standardized, and then the weight ratio of the two scores is dynamically adjusted according to the needs of different application scenarios. For example, in the equipment fault diagnosis scenario, the weight of the relevance score is increased to better reflect the fault propagation characteristics; in the equipment status monitoring scenario, the weight of the completeness score is appropriately increased to ensure the quality of the monitoring data.

[0060] This embodiment adopts a hierarchical data organization strategy. Based on the calculated importance weights, the optimal hierarchical division scheme is determined through cluster analysis. By optimizing the inter-layer threshold, it is ensured that the data at different levels have obvious importance differences while maintaining the relative uniformity of the data within the layer. This hierarchical organization method provides a clear data structure for the subsequent virtual space display.

[0061] This embodiment implements a high-precision coordinate mapping algorithm. By establishing a correspondence between physical space and virtual space, accurate conversion of coordinate systems is achieved. An interpolation algorithm is used to perform surface fitting on sampling points to generate a continuous mapping function to ensure that the data position in the virtual space is consistent with the actual scene. This solution significantly improves the spatial accuracy of virtual display.

[0062] Through the above-mentioned technical implementation, this embodiment effectively solves the problem of processing multi-source heterogeneous data in industrial sites, significantly improves data processing efficiency and accuracy, provides reliable technical support for information superposition in virtual space, and achieves good results in practical applications.

[0063] Step S102: slicing the virtual space coordinate system in layers, constructing a hierarchical display buffer, calculating display parameters of each layer according to the importance weight coefficient, allocating data with the maximum importance weight coefficient to the top display buffer, calculating edge clarity scores of each layer of data, setting blur radius parameters based on the edge clarity scores, performing blur processing on non-top layer data, constructing an inter-layer contrast enhancement matrix, adjusting the display parameters using the inter-layer contrast enhancement matrix, setting an inter-layer minimum interval threshold, adding a layered mark bit in the display buffer, mapping the layered mark bit to a transparency control parameter, generating a hybrid weight coefficient based on the transparency control parameter, and using the hybrid weight coefficient to perform superposition processing on data of different levels;

[0064] Optionally, this embodiment first performs fine-grained hierarchical slicing on the virtual space coordinate system. According to the distribution characteristics of spatial data and business needs, an adaptive slicing algorithm is used to determine the optimal number of slices and slice thickness. In industrial field applications, the space is usually divided into 3-5 main levels, each corresponding to a different degree of business importance, such as the equipment core component layer, the operating status monitoring layer, the environmental parameter layer, etc. The spatial continuity of the data is considered during the slicing process to ensure smooth transition of information between layers.

[0065] This embodiment innovatively constructs a hierarchical display buffer architecture. For each slice level, an independent display buffer space is allocated, and a double buffer mechanism is used to ensure the smoothness of the data update and display process. The buffer size is dynamically adjusted according to the amount of data and the update frequency to avoid wasting memory resources. In industrial field applications, a larger buffer space is configured for the level where key information such as equipment failure warnings are located to improve the display response speed.

[0066] This embodiment develops a display parameter calculation method based on importance weight. By analyzing the importance weight coefficient of the data, display resources are dynamically allocated to each layer, including parameters such as resolution, refresh rate, and color depth. Data with higher importance weights are preferentially allocated to the top-level display buffer to ensure clear presentation of key information. For example, device abnormal status data has a higher importance weight and will be placed in the top layer and use the highest display quality parameters.

[0067] This embodiment implements an intelligent edge clarity evaluation mechanism. By calculating the image gradient and local variance, the edge feature significance of the data is evaluated. For each layer of data, an edge detection operator is constructed to calculate the edge clarity score, which reflects the visual clarity of the data. Based on the clarity score, the radius parameter of the Gaussian blur is adaptively set to perform different degrees of blur processing on non-top layer data to create a sense of hierarchy.

[0068] This embodiment designs an innovative inter-layer contrast enhancement strategy. By constructing a contrast enhancement matrix, analyzing the brightness and color differences between adjacent layers, and dynamically adjusting display parameters to enhance the visual distinction between layers. In industrial field applications, this strategy is particularly helpful in highlighting the difference between equipment failure information and normal operating status, and improving the recognition efficiency of abnormal status.

[0069] This embodiment establishes a strict inter-layer spacing control mechanism. By setting the minimum spacing threshold, it ensures that the different layers maintain an appropriate visual distance to avoid information mixing. In the virtual space, the setting of the inter-layer spacing takes into account the human eye perception characteristics and actual application needs, which not only ensures the clarity of the layer distinction, but also does not affect the coherence of the overall information.

[0070] This embodiment implements an accurate transparency control scheme. A layered marker is added to the display buffer, and a mapping relationship between the marker and the transparency parameter is established. Accurate control of the layered transparency is achieved by dynamically adjusting the marker. This method makes the important information layer have a higher opacity, while the secondary information layer presents a semi-transparent effect, forming a distinct visual effect.

[0071] This embodiment develops an adaptive data superposition processing algorithm. Based on the transparency control parameter, a mixing weight coefficient is generated, and the data of different levels are superimposed in a weighted mixing manner. The algorithm takes into account the importance, visual clarity and hierarchical relationship of the data, ensuring that the display effect after superposition maintains the integrity of the information and highlights the display effect of important data.

[0072] Through the above technical implementation, this embodiment effectively solves the display problem of multi-level data in virtual space, significantly improves the clarity and layering of information display, and provides intuitive and efficient visualization support for industrial site monitoring and decision-making. This solution has shown good display effect and stability in actual application and has been recognized by on-site operators.

[0073] Step S103: Establish a display strategy mapping table, select a corresponding visualization template according to the type label, calculate the data timeliness score, convert the timeliness score into a display refresh cycle, update the information status in the virtual space based on the display refresh cycle, perform smoothing on the information status, and synchronously display the processed results to the virtual space interface.

[0074] Optionally, this embodiment first establishes a comprehensive display strategy mapping table to formulate corresponding display strategies for different types of data in the industrial field. The mapping table contains key information such as data type, display template, update strategy, etc. For example, a dashboard display template is used for equipment operating parameters, a thermal map display template is used for temperature distribution data, and a waveform display template is used for vibration data. The establishment of this mapping relationship ensures that the display method of different types of data not only conforms to the data characteristics, but also is easy for operators to understand and use.

[0075] This embodiment intelligently selects the most suitable visualization template based on the data type annotation. By analyzing the time characteristics, spatial characteristics and business attributes of the data, the most suitable display mode is matched from the template library. For example, for device temperature data with spatial distribution characteristics, a three-dimensional thermal map template is selected; for device vibration data with strong time series, a real-time waveform display template is selected; for discrete device status data, a status indicator template is selected.

[0076] This embodiment innovatively develops a data timeliness evaluation mechanism. By calculating the difference between the data generation time and the current time, combined with the business importance of the data, the timeliness score of the data is comprehensively evaluated. The evaluation process takes into account factors such as the data update frequency requirements and business response time requirements. For example, equipment failure warning information has a higher timeliness requirement, and its timeliness score calculation will be more stringent.

[0077] This embodiment realizes the intelligent conversion of timeliness score to display refresh cycle. The display refresh cycle is dynamically adjusted according to different intervals of timeliness score. For data with high timeliness requirements, such as the real-time operation status of the equipment, a shorter refresh cycle is used; for data that changes slowly, such as environmental parameters, a longer refresh cycle is used. This differentiated refresh strategy ensures the timely update of key information and avoids the waste of system resources.

[0078] This embodiment designs a dynamic update mechanism for the virtual space information status. Based on the calculated display refresh cycle, various types of information in the virtual space are updated regularly. The update process uses double buffering technology to ensure the smoothness of the display process. For important data that requires real-time response, such as device alarm information, an interrupt update mechanism is implemented to ensure timely display of information.

[0079] This embodiment develops a smoothing algorithm for information status. In view of the jump phenomenon that may occur during the data update process, the sliding average and interpolation technology are used for smoothing. For example, a gradual transition effect is used for sudden changes in device parameters to avoid the jump feeling of display; a spatial interpolation algorithm is used for changes in temperature field to ensure the continuity of display. This smoothing process not only ensures the authenticity of the data, but also improves the visual experience of the display effect.

[0080] This embodiment implements a synchronous display mechanism for the virtual space interface. By establishing a mapping relationship between the display buffer and the virtual space interface, it is ensured that the processed data can be accurately synchronized to the display interface. The view synchronization technology is used in the display process to ensure the consistency of information display under multiple viewing angles. This synchronization mechanism provides operators with a stable and reliable information display effect.

[0081] Through the above technical implementation, this embodiment effectively solves the problem of visual display of complex data on industrial sites, significantly improves the intuitiveness and real-time nature of information display, and provides clear and timely data support for on-site operators. This solution shows good display effects and operational stability in actual applications, effectively improving the monitoring and management efficiency of industrial sites.

[0082] From the above description, it can be seen that the information superposition method of intelligent perception information in the virtual space provided by the embodiment of the present application can establish a data stratification mechanism based on importance weights by evaluating the information completeness and relevance of multi-source data such as images, temperature, and sound. A hierarchical display buffer is used to realize hierarchical management of information, and the visual effect between layers is optimized by combining edge clarity evaluation and fuzzy processing technology. Intelligent superposition of multiple layers of data is achieved through contrast enhancement and transparency control, and the display refresh strategy is dynamically adjusted based on the timeliness of the data. This method effectively solves the problems of chaotic display and visual interference of traditional superposition solutions when processing multi-dimensional perception information, and improves the quality of information display in the virtual space.

[0083] In one embodiment of the method for superimposing intelligent perception information in a virtual space of the present application, see Figure 2 , and can also include the following:

[0084] Step S201: collecting three-dimensional image data, temperature field data, and sound field data in a scene space, storing the data uniformly in a buffer queue, reading data items from the buffer queue, extracting distribution features of the data items, establishing a data type feature library, matching the distribution features with the data type feature library, and adding a type identifier to the data item;

[0085] Step S202: convert the data item into a vector representation, construct a neural network evaluation model based on the vector representation, calculate the data redundancy coefficient and the spatial correlation coefficient for the data item, map the data redundancy coefficient into an information completeness score, and map the spatial correlation coefficient into a correlation score.

[0086] Optionally, this embodiment first realizes data collection by deploying a multimodal sensor network in the industrial scene space. Specifically, a high-resolution industrial camera array is arranged to collect three-dimensional image data of the equipment, and the collection frequency is dynamically adjusted according to the motion characteristics of the equipment; an infrared thermal imager array is installed to collect temperature field data, and the spatial distribution of the thermal imager ensures that the temperature field of key equipment parts has no blind spot coverage; an acoustic sensor array is deployed to collect sound field data, and the position of the sensor is optimized through sound field simulation to obtain the best acoustic feature capture effect.

[0087] This embodiment implements unified storage management of heterogeneous data by designing a hierarchical buffer queue structure. The buffer queue adopts a three-layer architecture: the first layer is the raw data buffer, which is partitioned and stored by data type; the second layer is the pre-processed data buffer, which stores the noise-reduced and calibrated data; the third layer is the feature data buffer, which stores the extracted feature vectors. The data association relationship between each layer is maintained through a bidirectional linked list to ensure the continuity and traceability of data processing.

[0088] This embodiment innovatively develops a multimodal data feature extraction algorithm. For three-dimensional image data, SIFT feature points and depth information are extracted to construct the three-dimensional contour features of the equipment; for temperature field data, the temperature gradient matrix and hot spot distribution features are calculated to identify temperature abnormality areas; for sound field data, time-frequency analysis is performed to extract spectrogram features and capture the acoustic characteristics of equipment operation. All features take into account time series correlation to form a dynamic feature description.

[0089] This embodiment establishes an adaptive data type feature library. The feature library adopts a hierarchical structure and contains feature templates for normal equipment operation, typical fault feature templates, and environmental interference feature templates. The feature library is continuously updated through an online learning mechanism. When a new feature pattern is detected, it is automatically added to the feature library after verification, thereby improving the accuracy and adaptability of feature matching.

[0090] This embodiment implements a data vectorization representation method based on deep learning. The encoder-decoder network structure is designed to map multimodal data to a unified feature space. The encoding process retains the physical properties and spatiotemporal correlation of the data to ensure the integrity of the vector representation. For example, the vectorization process of temperature field data retains the spatial continuity of temperature distribution, and the vectorization process of sound field data retains the temporal sequence of spectral features.

[0091] This embodiment constructs an innovative neural network evaluation model. The model adopts a multi-branch structure, including a redundancy evaluation branch and a correlation evaluation branch. The redundancy evaluation branch calculates the degree of information redundancy by comparing the similarity between the data item and the historical data; the correlation evaluation branch calculates the correlation strength by analyzing the spatial correlation between the data item and the surrounding data. The outputs of the two branches are weighted and fused to generate the final evaluation result.

[0092] This embodiment develops an adaptive scoring mapping mechanism. By establishing a nonlinear mapping function, the redundancy coefficient is converted into an information completeness score, and the correlation coefficient is converted into a correlation score. The mapping process considers the business importance of the data and adopts a stricter scoring standard for key equipment data. For example, the integrity requirement of the main bearing temperature data is higher than that of ordinary parts, and the mapping function adjusts the slope accordingly to improve the discrimination.

[0093] Through the above technical implementation, this embodiment effectively solves the problems of collecting, extracting features and evaluating multi-source heterogeneous data in industrial sites. This solution significantly improves the accuracy and real-time performance of data processing, and provides reliable data support for industrial equipment status monitoring and fault diagnosis. In practical applications, this solution demonstrates excellent adaptability and scalability, and can quickly respond to the processing needs of different types of data.

[0094] In one embodiment of the method for superimposing intelligent perception information in a virtual space of the present application, see Figure 3, and can also include the following:

[0095] Step S301: normalizing the completeness score and the relevance score, constructing a linear combination model, inputting the completeness score and the relevance score into the linear combination model, calculating a comprehensive score of the data item, generating an importance weight coefficient based on the comprehensive score, prioritizing the data items using the importance weight coefficient, and dividing the sorting results into multiple levels;

[0096] Step S302: Establish a three-dimensional coordinate transformation matrix, convert the data position information in the scene space coordinate system into virtual space coordinate values, construct a uniform grid in the virtual space, calculate the position deviation of the grid node, construct a coordinate interpolation function based on the position deviation, and use the coordinate interpolation function as the virtual space coordinate mapping function.

[0097] Optionally, this embodiment first performs adaptive normalization processing on the completeness score and the relevance score. A dynamic maximum and minimum value normalization method is used to regularly update the normalization parameters so that the normalization process can adapt to the dynamic changes in data distribution. According to the data characteristics in different industrial scenarios, a segmented normalization strategy is designed, and a more refined normalization interval division is used for key equipment data to improve the discrimination of the scores.

[0098] This embodiment innovatively designs a linear combination model with weighted adaptation. The model introduces a dynamic weight adjustment mechanism to automatically adjust the weight coefficients of the integrity score and the correlation score according to the equipment operating status and monitoring requirements. For example, when the equipment is in a fault warning state, the weight of the correlation score is increased to strengthen the correlation analysis between data; when performing equipment performance evaluation, the weight of the integrity score is increased to ensure the quality of the evaluation data.

[0099] This embodiment uses the cumulative probability distribution method to generate importance weight coefficients. By constructing a probability distribution function for the comprehensive score of the data, the score value is mapped to the weight coefficient. The mapping process takes into account the business value of the data and sets differentiated mapping curves for different types of data. For example, for the monitoring data of the core components of the equipment, a steep mapping curve is used to obtain a higher weight coefficient; for the environmental parameter data, a gentle mapping curve is used.

[0100] This embodiment implements a multi-level priority sorting mechanism. Based on the importance weight coefficient, an improved quick sorting algorithm is used to sort the data. The timeliness factor is introduced in the sorting process to give priority to data with high real-time requirements. The sorting results are divided into multiple levels according to actual application requirements, such as emergency processing layer, key attention layer, regular monitoring layer, etc., to facilitate subsequent hierarchical processing.

[0101] This embodiment develops a high-precision three-dimensional coordinate transformation solution. A complete transformation matrix containing a rotation matrix, a translation vector, and a scaling factor is constructed to achieve accurate mapping from scene space to virtual space. The transformation parameters are solved by the least squares optimization method to ensure the transformation accuracy. For the complex spatial structure of large equipment, a block transformation strategy is introduced to improve the mapping accuracy of local details.

[0102] This embodiment designs an adaptive grid division method. An octree-structured non-uniform grid is constructed in the virtual space, and the grid density is dynamically adjusted according to the data distribution characteristics. A more detailed grid division is used in key parts of the equipment and data-intensive areas to improve the accuracy of spatial expression. The grid structure supports dynamic refinement and merging to adapt to the spatial expression requirements of different scales.

[0103] This embodiment innovatively develops a grid node position deviation compensation algorithm. By analyzing the deviation between the actual mapping position and the ideal grid position, a local coordinate correction model is established. The deviation compensation process takes into account the spatial continuity constraint to ensure a smooth transition between adjacent areas. For areas with large deformation, an iterative optimization method is used to gradually reduce the position deviation.

[0104] This embodiment implements an accurate coordinate interpolation mechanism. A three-dimensional space interpolation function is constructed based on the radial basis function to achieve coordinate mapping of any point. The interpolation process adopts a local weighted strategy, taking into account the distance attenuation effect to ensure the smoothness and continuity of the interpolation result. In order to improve the calculation efficiency, the fast multipole expansion method is used to accelerate the interpolation calculation.

[0105] Through the above technical implementation, this embodiment effectively solves the evaluation and classification and spatial mapping problems of industrial field data. The solution has shown excellent adaptability and reliability in practical applications, significantly improved data processing efficiency and spatial display effects, and provided strong support for visual monitoring of industrial equipment. Especially in complex industrial environments, the solution can accurately reflect the spatial relationship of equipment and effectively support applications such as equipment status monitoring and fault diagnosis.

[0106] In one embodiment of the method for superimposing intelligent perception information in a virtual space of the present application, see Figure 4 , and can also include the following:

[0107] Step S401: setting a slice spacing threshold in the virtual space coordinate system, dividing the space level based on the slice spacing threshold, calculating the depth value of each slice layer, quantizing the depth value, storing the quantized depth value in a depth buffer, allocating an independent display buffer for each slice layer, and establishing an inter-layer data index table;

[0108] Step S402: read the importance weight coefficient, construct a display parameter calculation model, input the importance weight coefficient into the display parameter calculation model, generate a display scale coefficient and position offset for each layer of slices, filter the data group with the largest importance weight coefficient, and allocate the data group to the display buffer corresponding to the top layer of slices.

[0109] Optionally, this embodiment first sets a reasonable slice spacing threshold based on the spatial characteristics of the industrial scene. By analyzing the spatial distribution of the equipment and the density distribution of the monitoring data, an adaptive spacing setting method is adopted. In equipment-dense areas, a smaller slice spacing is selected to provide a more detailed spatial stratification; in equipment-sparse areas, the slice spacing is appropriately increased to optimize the display effect. For example, for the monitoring scenario of large mechanical equipment, the slice spacing in the core component area can be set smaller, while a larger spacing can be used in the peripheral area.

[0110] This embodiment innovatively develops a multi-level spatial partitioning algorithm. Based on the slice spacing threshold, a top-down recursive stratification method is used to ensure the uniformity of spatial coverage of each layer of slices. During the stratification process, the geometric characteristics of the equipment and the spatial distribution of the monitoring points are considered, and the number of levels is dynamically adjusted to avoid excessive concentration or sparseness of data.

[0111] This embodiment implements an efficient depth value calculation and quantization processing mechanism. A standardized depth value is calculated for each slice plane, and a nonlinear quantization strategy is adopted to use finer quantization levels in important areas. The quantization process takes into account the perceptual characteristics of the human eye and provides a more accurate depth expression in the visual key areas. The quantized depth value is stored in the depth buffer through compression encoding to improve storage efficiency.

[0112] This embodiment designs a hierarchical display buffer management architecture. An independent display buffer is configured for each slice layer, and a double buffer mechanism is used to ensure the smoothness of the display process. The buffer size is dynamically adjusted according to the amount of slice data, supporting real-time data updates. At the same time, a fast exchange and synchronization mechanism of buffer data is implemented to ensure the coordinated display of multiple layers of data.

[0113] This embodiment develops an efficient inter-layer data indexing mechanism. A hierarchical index table is constructed to record the spatial association relationship and data correspondence relationship between slices. The index table adopts a hash structure to support fast data location and retrieval. By maintaining the association between inter-layer data, cross-layer data linkage update and interactive operation are achieved.

[0114] This embodiment innovatively designs a display parameter calculation model based on data importance. The model adopts a multi-factor fusion calculation method, combines the importance weight coefficient with the spatial position information, and generates the display control parameters of each slice. The calculation of the display scale coefficient takes into account the business importance of the data, and important data obtains a larger display ratio; the calculation of the position offset takes into account the rationality of the spatial layout to avoid visual occlusion of important data.

[0115] This embodiment implements an intelligent data allocation strategy. By analyzing the distribution characteristics of the importance weight coefficient, key data groups are identified. A priority queue management method is adopted to ensure that important data is allocated to the top slice first, thereby improving the display effect. Spatial balance is considered during data allocation to avoid excessive concentration of data in a certain area.

[0116] This embodiment develops a dynamic display parameter adjustment mechanism. According to user interaction and display requirements, display parameters are adjusted in real time. For example, when a user focuses on a certain area, the display ratio and clarity of the slices in the area are automatically adjusted; when abnormal data is detected, the relevant area is highlighted to provide intuitive visual prompts.

[0117] Through the above technical implementation, this embodiment effectively solves the problem of multi-level visualization of industrial monitoring data. The solution shows excellent display effect and interactive experience in practical applications, can clearly display equipment status and abnormal information, and provides intuitive visualization support for the monitoring and management of industrial equipment. Especially in complex industrial environments, the solution can effectively highlight key information and support rapid status assessment and decision analysis.

[0118] In one embodiment of the method for superimposing intelligent perception information in a virtual space of the present application, see Figure 5 , and can also include the following:

[0119] Step S501: Calculate the brightness difference between adjacent level data, construct a contrast adjustment coefficient matrix, perform matrix multiplication operation on the contrast adjustment coefficient matrix and the display parameter, set the minimum distance value between layers, adjust the level interval based on the minimum distance value, add a level identification field to the data structure of the display buffer, and map the level identification field to a transparency value interval;

[0120] Step S502: Perform a nonlinear transformation on the transparency value to generate a normalized mixing weight coefficient, establish a hierarchical data mixing operation buffer, write each layer of data into the mixing operation buffer in the order of the size of the mixing weight coefficient, perform weighted average calculation on the data in the mixing operation buffer, and output the calculation result to the display buffer.

[0121] Optionally, this embodiment first develops an adaptive inter-layer contrast adjustment mechanism based on the display characteristics of industrial field monitoring data. The inter-layer brightness difference is calculated by analyzing the brightness distribution characteristics of adjacent layer data. The sliding window method is used to perform statistical analysis on the brightness differences in local areas to ensure the local adaptability of contrast adjustment. For example, in the equipment failure area, abnormal information is highlighted by increasing the brightness contrast; in the normal operation area, a moderate contrast is maintained to provide a comfortable visual effect.

[0122] This embodiment innovatively designs a contrast adjustment coefficient matrix. Each element of the matrix corresponds to a contrast adjustment parameter of a local area, taking into account the importance of the data and the spatial position relationship. Through matrix multiplication operations, the adjustment coefficient is integrated with the display parameters to achieve precise contrast control. Smooth constraints are introduced during the adjustment process to ensure a gradual transition between adjacent areas.

[0123] This embodiment implements an intelligent hierarchical interval adjustment mechanism. Based on the set minimum distance value, a dynamic programming method is used to optimize the hierarchical layout. In data-intensive areas, more display details are provided through detailed hierarchical division; in data-sparse areas, the hierarchical interval is appropriately increased to optimize space utilization. The hierarchical adjustment process takes into account the spatial continuity of the data to avoid display faults.

[0124] This embodiment develops an efficient level identification management solution. A level identification field is added to the data structure of the display buffer, and a bitmap encoding method is used to improve storage efficiency. A mapping relationship is established between the identification field and the transparency value. The mapping function takes into account the perception characteristics of the human eye and provides more refined transparency control at important levels.

[0125] This embodiment designs an innovative transparency nonlinear transformation algorithm. Based on the visual perception model, the linear transparency value is converted into a nonlinear perception space to provide a more natural hierarchical transition effect. The importance of the data is considered during the transformation process, and a steeper transformation curve is used for key information to enhance visual expression.

[0126] This embodiment implements an efficient hybrid weight calculation mechanism. Through normalization processing, the transparency value is converted into a hybrid weight coefficient. The weight calculation takes into account the temporal and spatial characteristics of the data, and recent data and data in important locations are given greater weights. The weight distribution process introduces an adaptive adjustment mechanism to dynamically optimize the weight distribution according to the display effect.

[0127] This embodiment innovatively develops a hierarchical data mixed operation buffer. A multi-level cache structure is adopted to support fast reading, writing and updating of data. The buffer is organized based on weight sorting to ensure that important data is processed first. By maintaining the dependency relationship of data, an efficient incremental update mechanism is achieved.

[0128] This embodiment implements an accurate weighted average calculation method. Based on the mixed weight coefficient, the buffer data is layered and weighted. The calculation process adopts a parallel optimization strategy to improve the operation efficiency. Gamma correction is performed when the result is output to ensure the accuracy of the display effect. In order to process large-scale data, a block calculation mechanism is introduced to support data streaming processing.

[0129] Through the above technical implementation, this embodiment effectively solves the problem of multi-level fusion display of industrial monitoring data. This solution has shown excellent display effects and operating efficiency in practical applications, can clearly display the data relationships at different levels, and provide intuitive visualization support for the status monitoring of industrial equipment. Especially in complex industrial environments, this solution can effectively handle display conflicts of multi-layer data, provide a smooth interactive experience, and support operators to quickly identify and handle abnormal conditions.

[0130] In one embodiment of the method for superimposing intelligent perception information in a virtual space of the present application, see Figure 6 , and can also include the following:

[0131] Step S601: construct a visualization strategy database, establish a mapping relationship between a data type identifier and a visualization template, save the mapping relationship to a display strategy mapping table, read the type annotation information, search for a matching item in the display strategy mapping table, and obtain corresponding visualization template parameters;

[0132] Step S602: Add a timestamp field to each data item, calculate the difference between the current time of the data item and the timestamp, substitute the difference into the timeliness decay function, generate a data timeliness score, establish a refresh cycle mapping function, input the timeliness score into the refresh cycle mapping function, and calculate the display refresh time interval.

[0133] Optionally, this embodiment develops an intelligent visualization strategy management mechanism for data visualization requirements of industrial monitoring scenarios. By building a visualization strategy database, the display schemes of different types of data are systematically managed. The database adopts a hierarchical architecture, including basic display templates, combined display rules and interactive control strategies, and supports flexible strategy expansion and updating.

[0134] This embodiment innovatively implements an intelligent mapping mechanism between data types and visualization templates. Corresponding specialized display templates are designed for different types of monitoring data such as temperature, pressure, and vibration. For example, temperature data is displayed in a heat map mode, pressure data is represented by contour lines, and vibration data is displayed by a waveform diagram. The mapping relationship is maintained through a display strategy mapping table, and a multi-level index structure is used to improve query efficiency.

[0135] This embodiment develops an efficient type annotation information processing mechanism. Through semantic analysis technology, the type characteristics and business attributes of data are accurately identified. The annotation information contains the physical meaning of the data, the unit of measurement, the display priority, etc., which provides a basis for selecting the appropriate display template. When processing complex type data, a combination of multiple templates is used to provide richer display effects.

[0136] This embodiment implements the intelligent matching and tuning functions of template parameters. Based on the statistical characteristics of the data and display requirements, the template parameters are dynamically adjusted. For example, the display scale is adjusted according to the fluctuation range of the data, and the animation effect is adjusted according to the update frequency of the data to ensure the rationality and intuitiveness of the display effect.

[0137] This embodiment designs an innovative timestamp management mechanism. High-precision timestamps are added to all monitoring data, and a unified time base is used to ensure the timing consistency of the data. The timestamp format is designed to take into account the special needs of industrial sites, support millisecond-level time accuracy, and facilitate tracking of rapidly changing process parameters.

[0138] This embodiment develops an advanced timeliness evaluation method. By calculating the real-time difference of the data, a nonlinear decay function is used to evaluate the timeliness of the data. The design of the decay function takes into account the characteristics of different types of data and adopts more stringent timeliness requirements for key process parameters. For example, parameters related to equipment safety use a fast decay curve, while environmental parameters can use a more moderate decay characteristic.

[0139] This embodiment implements an intelligent display refresh management mechanism. By establishing a refresh cycle mapping function, the timeliness score is converted into a reasonable display update interval. The mapping function adopts a segmented design, providing a higher refresh frequency when the data changes rapidly, and appropriately reducing the refresh frequency when the data is stable, thereby optimizing the use of system resources.

[0140] This embodiment innovatively develops an adaptive refresh control strategy. Based on the importance and change characteristics of the data, the refresh strategy is dynamically adjusted. For abnormal data or key process parameters, a more frequent refresh mechanism is adopted; for auxiliary information, a lower refresh frequency is adopted. Through differentiated refresh strategies, the real-time nature of important information is ensured while avoiding the waste of system resources.

[0141] Through the above technical implementation, this embodiment effectively solves the problem of intelligent visualization of industrial monitoring data. The solution shows excellent display effect and operation efficiency in practical applications, and can automatically select the appropriate display mode according to the characteristics of the data, providing operators with intuitive and timely information display. Especially in complex industrial environments, the solution can effectively handle the display requirements of different types of data, support rapid status assessment and decision analysis, and improve the monitoring efficiency of industrial production.

[0142] In one embodiment of the method for superimposing intelligent perception information in a virtual space of the present application, see Figure 7 , and can also include the following:

[0143] Step S701: constructing a display state update queue, setting the display refresh cycle as a state update trigger condition, reading the latest data when the trigger condition is met, writing the latest data into the virtual space information buffer, calculating state difference values ​​of adjacent data items, performing linear interpolation operation on the state difference values, and generating a state transition sequence;

[0144] Step S702: perform a mean filtering operation on the state transition sequence, write the filtered data into a display state buffer, establish a virtual space display controller, transmit the data in the display state buffer to the display controller, and the display controller synchronously outputs the data to the virtual space display interface.

[0145] Optionally, this embodiment develops an efficient display status management mechanism for the dynamic display requirements of the industrial virtual space. By constructing a display status update queue, orderly control of data updates is achieved. The queue adopts a priority management strategy to ensure that important status changes can be processed first, and at the same time, the cache mechanism is used to avoid data update congestion.

[0146] This embodiment innovatively designs a trigger mechanism based on the refresh cycle. The display refresh cycle is used as the trigger condition for status update, and the update timing is accurately controlled by the timer. The judgment of the trigger condition takes into account the importance and change rate of the data, and a shorter refresh cycle is used for the status of key devices to ensure the timeliness of status display.

[0147] This embodiment implements an efficient virtual space data caching strategy. Through the virtual space information buffer, a multi-level data cache structure is established. The buffer design takes into account the characteristics of the industrial site and supports fast access to large-scale equipment status data. For example, for parameters with high real-time requirements such as temperature and pressure, a dedicated fast cache area is used.

[0148] This embodiment develops an accurate state difference analysis method. By calculating the state difference values ​​of adjacent data items, the changing characteristics of the device state are accurately captured. The difference calculation process takes into account the characteristics of different types of data, such as using numerical difference calculation for continuous quantities and state code comparison for discrete states to ensure the accuracy of the difference analysis.

[0149] This embodiment implements an innovative state transition processing mechanism. Through linear interpolation operations, a smooth state transition sequence is generated. The interpolation algorithm takes into account the physical properties of the data to ensure that the state changes conform to the actual laws. For example, the parameter changes during the start and stop process of the equipment use a specific interpolation curve to reflect the actual transition characteristics.

[0150] This embodiment designs an advanced signal filtering processing scheme. A mean filtering operation is performed on the state transition sequence to effectively suppress data noise and interference. The parameters of the filtering algorithm are dynamically adjusted according to the data characteristics to ensure the stability of the display while maintaining the signal's rapid response capability.

[0151] This embodiment develops a professional display state buffer management mechanism. Through the display state buffer, smooth data transmission is achieved. The buffer is designed with a double buffer structure to support asynchronous data update and avoid flickering and jitter during the display process.

[0152] This embodiment implements an efficient virtual space display control mechanism. By establishing a virtual space display controller, the transmission and synchronization of display data are uniformly managed. The controller adopts an event-driven approach to dynamically adjust the display strategy according to the data update situation. For example, when the data changes rapidly, the display fluency is maintained by adjusting the rendering parameters.

[0153] This embodiment innovatively develops a display synchronization mechanism. By accurately controlling the transmission timing of data, the coherence of the virtual space interface display is ensured. The synchronization process takes into account the characteristics of different display terminals and supports the consistent display of multi-terminal data.

[0154] Through the above technical implementation, this embodiment effectively solves the problem of real-time display of equipment status in industrial virtual space. The solution shows excellent display effect and operation performance in practical applications, can smoothly display the dynamic change process of equipment status, and provide operators with an intuitive monitoring experience. Especially in complex industrial environments, the solution can effectively handle the status update display of a large number of devices, support operators to quickly discover and respond to abnormal conditions, and improve the monitoring efficiency of industrial production.

[0155] In order to effectively solve the problems of chaotic display and visual interference in traditional overlay solutions when processing multi-dimensional perceptual information and improve the quality of information display in virtual space, the present application provides an embodiment of an information overlay device for intelligently perceiving information in virtual space for realizing all or part of the content of the information overlay method of intelligently perceiving information in virtual space, see Figure 8 The information superposition device of the intelligent perception information in the virtual space specifically includes the following contents:

[0156] A virtual mapping module 10 is used to collect image data, temperature data, and sound data in the scene space, perform type annotation on the data, build a data priority evaluation model, calculate the information completeness and relevance scores of the data, generate an importance weight coefficient based on the completeness score and the relevance score, use the importance weight coefficient as a basis for data stratification, and establish a virtual space coordinate mapping function;

[0157] The information superposition module 20 is used to slice the virtual space coordinate system in layers, construct a hierarchical display buffer, calculate the display parameters of each layer according to the importance weight coefficient, allocate the data with the maximum importance weight coefficient to the top display buffer, calculate the edge clarity score of each layer of data, set the blur radius parameter based on the edge clarity score, perform blur processing on non-top data, construct an inter-layer contrast enhancement matrix, adjust the display parameters using the inter-layer contrast enhancement matrix, set the minimum interval threshold between layers, add a layer mark bit in the display buffer, map the layer mark bit to a transparency control parameter, generate a hybrid weight coefficient based on the transparency control parameter, and use the hybrid weight coefficient to perform superposition processing on data of different levels;

[0158] The visualization module 30 is used to establish a display strategy mapping table, select a corresponding visualization template according to the type label, calculate the data timeliness score, convert the timeliness score into a display refresh cycle, update the information status in the virtual space based on the display refresh cycle, perform smoothing on the information status, and synchronously display the processed results on the virtual space interface.

[0159] From the above description, it can be seen that the information overlay device of intelligent perception information in the virtual space provided by the embodiment of the present application can establish a data stratification mechanism based on importance weights by evaluating the information completeness and relevance of multi-source data such as images, temperature, and sound. A hierarchical display buffer is used to realize hierarchical management of information, and the visual effect between layers is optimized by combining edge clarity evaluation and fuzzy processing technology. Intelligent overlay of multiple layers of data is realized through contrast enhancement and transparency control, and the display refresh strategy is dynamically adjusted based on the timeliness of the data. This method effectively solves the problems of chaotic display and visual interference of traditional overlay solutions when processing multi-dimensional perception information, and improves the quality of information display in the virtual space.

[0160] From the hardware level, in order to effectively solve the problems of chaotic display and visual interference in traditional overlay solutions when processing multi-dimensional perception information and improve the quality of information display in virtual space, the present application provides an embodiment of an electronic device for implementing all or part of the content of the information overlay method of intelligent perception information in virtual space, and the electronic device specifically includes the following content:

[0161] Processor, memory, communication interface and bus; wherein the processor, memory and communication interface communicate with each other through the bus; the communication interface is used to realize information transmission between the information superposition device of intelligent perception information in virtual space and related devices such as core business system, user terminal and related database; the logic controller can be a desktop computer, tablet computer and mobile terminal, etc., and the present embodiment is not limited thereto. In the present embodiment, the logic controller can be implemented with reference to the embodiment of the information superposition method of intelligent perception information in virtual space and the embodiment of the information superposition device of intelligent perception information in virtual space in the embodiment, and the contents thereof are incorporated herein, and the repeated parts are not repeated.

[0162] It is understandable that the user terminal may include a smart phone, a tablet electronic device, a network set-top box, a portable computer, a desktop computer, a personal digital assistant (PDA), a vehicle-mounted device, a smart wearable device, etc. Among them, the smart wearable device may include smart glasses, a smart watch, a smart bracelet, etc.

[0163] In practical applications, part of the method for superimposing information in the virtual space of intelligent perception information can be performed on the electronic device side as described above, or all operations can be completed in the client device. The selection can be made based on the processing capability of the client device and the limitations of the user's usage scenario. This application does not limit this. If all operations are completed in the client device, the client device may also include a processor.

[0164] The client device may have a communication module (i.e., a communication unit) that can communicate with a remote server to achieve data transmission with the server. The server may include a server on the task scheduling center side, and other implementation scenarios may also include a server on an intermediate platform, such as a server on a third-party server platform that has a communication link with the task scheduling center server. The server may include a single computer device, or a server cluster consisting of multiple servers, or a server structure of a distributed device.

[0165] Fig. 9 FIG. 9 is a schematic block diagram of the system structure of the electronic device 9600 according to an embodiment of the present application. Fig. 9 As shown, the electronic device 9600 may include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. It is worth noting that Fig. 9is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunication functions or other functions.

[0166] In one embodiment, the function of the method for superimposing the intelligent sensing information in the virtual space can be integrated into the central processing unit 9100. The central processing unit 9100 can be configured to perform the following control:

[0167] Step S101: collecting image data, temperature data, and sound data in the scene space, annotating the data by type, building a data priority evaluation model, calculating the information completeness and relevance scores of the data, generating importance weight coefficients based on the completeness scores and the relevance scores, using the importance weight coefficients as a basis for data stratification, and establishing a virtual space coordinate mapping function;

[0168] Step S102: slicing the virtual space coordinate system in layers, constructing a hierarchical display buffer, calculating display parameters of each layer according to the importance weight coefficient, allocating data with the maximum importance weight coefficient to the top display buffer, calculating edge clarity scores of each layer of data, setting blur radius parameters based on the edge clarity scores, performing blur processing on non-top layer data, constructing an inter-layer contrast enhancement matrix, adjusting the display parameters using the inter-layer contrast enhancement matrix, setting an inter-layer minimum interval threshold, adding a layered mark bit in the display buffer, mapping the layered mark bit to a transparency control parameter, generating a hybrid weight coefficient based on the transparency control parameter, and using the hybrid weight coefficient to perform superposition processing on data of different levels;

[0169] Step S103: Establish a display strategy mapping table, select a corresponding visualization template according to the type label, calculate the data timeliness score, convert the timeliness score into a display refresh cycle, update the information status in the virtual space based on the display refresh cycle, perform smoothing on the information status, and synchronously display the processed results to the virtual space interface.

[0170] From the above description, it can be seen that the electronic device provided in the embodiment of the present application establishes a data stratification mechanism based on importance weights by evaluating the information completeness and relevance of multi-source data such as images, temperature, and sound. A hierarchical display buffer is used to realize hierarchical management of information, and the visual effect between layers is optimized by combining edge clarity evaluation and fuzzy processing technology. Intelligent superposition of multiple layers of data is achieved through contrast enhancement and transparency control, and the display refresh strategy is dynamically adjusted based on the timeliness of the data. This method effectively solves the problems of chaotic display and visual interference of traditional superposition solutions when processing multi-dimensional perceptual information, and improves the quality of information display in virtual space.

[0171] In another embodiment, the information superposition device of intelligent perception information in the virtual space can be configured separately from the central processing unit 9100. For example, the information superposition device of intelligent perception information in the virtual space can be configured as a chip connected to the central processing unit 9100, and the function of the information superposition method of intelligent perception information in the virtual space is realized through the control of the central processing unit.

[0172] like Fig. 9 As shown, the electronic device 9600 may also include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is worth noting that the electronic device 9600 does not necessarily have to include Fig. 9 In addition, the electronic device 9600 may also include Fig. 9 For components not shown, reference may be made to the prior art.

[0173] like Fig. 9 As shown, the central processing unit 9100 is sometimes also referred to as a controller or an operation control, and may include a microprocessor or other processor device and / or logic device. The central processing unit 9100 receives input and controls the operation of various components of the electronic device 9600.

[0174] The memory 9140 may be, for example, one or more of a cache, a flash memory, a hard drive, a removable medium, a volatile memory, a non-volatile memory or other suitable devices. The above-mentioned information related to the failure may be stored, and a program for executing the relevant information may also be stored. The CPU 9100 may execute the program stored in the memory 9140 to implement information storage or processing, etc.

[0175] The input unit 9120 provides input to the central processing unit 9100. The input unit 9120 is, for example, a key or a touch input device. The power supply 9170 is used to provide power to the electronic device 9600. The display 9160 is used to display display objects such as images and texts. The display may be, for example, an LCD display, but is not limited thereto.

[0176] The memory 9140 may be a solid-state memory, such as a read-only memory (ROM), a random access memory (RAM), a SIM card, etc. It may also be a memory that saves information even when the power is off, can be selectively erased, and is provided with more data, examples of which are sometimes referred to as EPROMs, etc. The memory 9140 may also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application / function storage unit 9142, which is used to store application programs and function programs or processes for executing the operation of the electronic device 9600 through the central processor 9100.

[0177] The memory 9140 may also include a data storage unit 9143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 9144 of the memory 9140 may include various drivers for communication functions of the electronic device and / or for executing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0178] The communication module 9110 is a transmitter / receiver that sends and receives signals via the antenna 9111. The communication module 9110 (transmitter / receiver) is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as the case of a conventional mobile communication terminal.

[0179] Based on different communication technologies, multiple communication modules 9110 may be provided in the same electronic device, such as a cellular network module, a Bluetooth module and / or a wireless LAN module. The communication module 9110 (transmitter / receiver) is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide an audio output via the speaker 9131 and receive an audio input from the microphone 9132, thereby realizing a common telecommunication function. The audio processor 9130 may include any suitable buffer, decoder, amplifier, etc. In addition, the audio processor 9130 is also coupled to the central processor 9100, so that recording can be performed on the local machine through the microphone 9132, and the sound stored on the local machine can be played through the speaker 9131.

[0180] The embodiments of the present application also provide a computer-readable storage medium capable of implementing all the steps of the information superposition method of the intelligent perception information in the virtual space in the above-mentioned embodiment, in which the execution subject is a server or a client. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, all the steps of the information superposition method of the intelligent perception information in the virtual space in the above-mentioned embodiment are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0181] Step S101: collecting image data, temperature data, and sound data in the scene space, annotating the data by type, building a data priority evaluation model, calculating the information completeness and relevance scores of the data, generating importance weight coefficients based on the completeness scores and the relevance scores, using the importance weight coefficients as a basis for data stratification, and establishing a virtual space coordinate mapping function;

[0182] Step S102: slicing the virtual space coordinate system in layers, constructing a hierarchical display buffer, calculating display parameters of each layer according to the importance weight coefficient, allocating data with the maximum importance weight coefficient to the top display buffer, calculating edge clarity scores of each layer of data, setting blur radius parameters based on the edge clarity scores, performing blur processing on non-top layer data, constructing an inter-layer contrast enhancement matrix, adjusting the display parameters using the inter-layer contrast enhancement matrix, setting an inter-layer minimum interval threshold, adding a layered mark bit in the display buffer, mapping the layered mark bit to a transparency control parameter, generating a hybrid weight coefficient based on the transparency control parameter, and using the hybrid weight coefficient to perform superposition processing on data of different levels;

[0183] Step S103: Establish a display strategy mapping table, select a corresponding visualization template according to the type label, calculate the data timeliness score, convert the timeliness score into a display refresh cycle, update the information status in the virtual space based on the display refresh cycle, perform smoothing on the information status, and synchronously display the processed results to the virtual space interface.

[0184] From the above description, it can be seen that the computer-readable storage medium provided in the embodiment of the present application establishes a data hierarchical mechanism based on importance weights by evaluating the information completeness and relevance of multi-source data such as images, temperature, and sound. A hierarchical display buffer is used to realize hierarchical management of information, and the visual effect between layers is optimized by combining edge clarity evaluation and fuzzy processing technology. Intelligent superposition of multiple layers of data is achieved through contrast enhancement and transparency control, and the display refresh strategy is dynamically adjusted based on the timeliness of the data. This method effectively solves the problems of chaotic display and visual interference of traditional superposition solutions when processing multi-dimensional perceptual information, and improves the quality of information display in virtual space.

[0185] The embodiments of the present application also provide a computer program product capable of implementing all the steps of the information superposition method of intelligently sensing information in a virtual space in the above-mentioned embodiment, where the execution subject is a server or a client. When the computer program / instruction is executed by a processor, the steps of the information superposition method of intelligently sensing information in a virtual space are implemented. For example, the computer program / instruction implements the following steps:

[0186] Step S101: collecting image data, temperature data, and sound data in the scene space, annotating the data by type, building a data priority evaluation model, calculating the information completeness and relevance scores of the data, generating importance weight coefficients based on the completeness scores and the relevance scores, using the importance weight coefficients as a basis for data stratification, and establishing a virtual space coordinate mapping function;

[0187] Step S102: slicing the virtual space coordinate system in layers, constructing a hierarchical display buffer, calculating display parameters of each layer according to the importance weight coefficient, allocating data with the maximum importance weight coefficient to the top display buffer, calculating edge clarity scores of each layer of data, setting blur radius parameters based on the edge clarity scores, performing blur processing on non-top layer data, constructing an inter-layer contrast enhancement matrix, adjusting the display parameters using the inter-layer contrast enhancement matrix, setting an inter-layer minimum interval threshold, adding a layered mark bit in the display buffer, mapping the layered mark bit to a transparency control parameter, generating a hybrid weight coefficient based on the transparency control parameter, and using the hybrid weight coefficient to perform superposition processing on data of different levels;

[0188] Step S103: Establish a display strategy mapping table, select a corresponding visualization template according to the type label, calculate the data timeliness score, convert the timeliness score into a display refresh cycle, update the information status in the virtual space based on the display refresh cycle, perform smoothing on the information status, and synchronously display the processed results to the virtual space interface.

[0189] From the above description, it can be seen that the computer program product provided in the embodiment of the present application establishes a data stratification mechanism based on importance weights by evaluating the information completeness and relevance of multi-source data such as images, temperature, and sound. A hierarchical display buffer is used to realize hierarchical management of information, and the visual effect between layers is optimized by combining edge clarity evaluation and fuzzy processing technology. Intelligent superposition of multiple layers of data is achieved through contrast enhancement and transparency control, and the display refresh strategy is dynamically adjusted based on the timeliness of the data. This method effectively solves the problems of chaotic display and visual interference of traditional superposition solutions when processing multi-dimensional perceptual information, and improves the quality of information display in virtual space.

[0190] It should be understood by those skilled in the art that embodiments of the present invention may be provided as methods, devices, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0191] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (apparatus), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0192] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0193] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0194] The present invention uses specific embodiments to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A method for superimposing intelligent perception information in a virtual space, characterized in that: The method comprises: Collect image data, temperature data, and sound data in the scene space, annotate the data by type, build a data priority assessment model, calculate the information completeness and relevance scores of the data, generate an importance weight coefficient based on the information completeness score and the relevance score, use the importance weight coefficient as a basis for data stratification, and establish a virtual space coordinate mapping function; The virtual space coordinate system is sliced ​​and layered to construct a hierarchical display buffer, display parameters of each layer are calculated according to the importance weight coefficient, data with the maximum importance weight coefficient is allocated to the top display buffer, edge clarity score of each layer of data is calculated, blur radius parameter is set based on the edge clarity score, blur processing is performed on non-top data, an inter-layer contrast enhancement matrix is ​​constructed, the display parameters are adjusted using the inter-layer contrast enhancement matrix, a minimum interval threshold between layers is set, a layered mark bit is added to the display buffer, the layered mark bit is mapped to a transparency control parameter, a hybrid weight coefficient is generated based on the transparency control parameter, and data of different levels are superimposed using the hybrid weight coefficient; A display strategy mapping table is established, a corresponding visualization template is selected according to the type label, a data timeliness score is calculated, the timeliness score is converted into a display refresh cycle, the information state in the virtual space is updated based on the display refresh cycle, smoothing is performed on the information state, and the processed result is synchronously displayed on the virtual space interface.

2. The method for superimposing intelligent perception information in a virtual space according to claim 1, characterized in that: The image data, temperature data, and sound data in the collected scene space are type-labeled, a data priority evaluation model is constructed, and the information completeness and relevance scores of the data are calculated, including: Collecting three-dimensional image data, temperature field data, and sound field data in a scene space, storing the data uniformly in a buffer queue, reading data items from the buffer queue, extracting distribution features of the data items, establishing a data type feature library, matching the distribution features with the data type feature library, and adding a type identifier to the data item; The data item is converted into a vector representation, a neural network evaluation model is constructed based on the vector representation, a data redundancy coefficient and a spatial correlation coefficient are calculated for the data item, the data redundancy coefficient is mapped into an information completeness score, and the spatial correlation coefficient is mapped into a correlation score.

3. The method for superimposing intelligent perception information in a virtual space according to claim 1, characterized in that: The generating of importance weight coefficients based on the completeness score and the relevance score, taking the importance weight coefficients as the basis for data stratification, and establishing a virtual space coordinate mapping function includes: Normalizing the completeness score and the relevance score, constructing a linear combination model, inputting the completeness score and the relevance score into the linear combination model, calculating a comprehensive score of the data item, generating an importance weight coefficient based on the comprehensive score, prioritizing the data items using the importance weight coefficient, and dividing the sorting results into multiple levels; A three-dimensional coordinate transformation matrix is ​​established to convert the data position information in the scene space coordinate system into virtual space coordinate values, a uniform grid is constructed in the virtual space, the position deviation of the grid nodes of the uniform grid is calculated, a coordinate interpolation function is constructed based on the position deviation, and the coordinate interpolation function is used as the virtual space coordinate mapping function.

4. The method for superimposing intelligent perception information in a virtual space according to claim 1, characterized in that: The step of slicing the virtual space coordinate system in layers, constructing a hierarchical display buffer, calculating display parameters of each layer according to the importance weight coefficient, and allocating data with the maximum importance weight coefficient to the top display buffer includes: Setting a slice spacing threshold in the virtual space coordinate system, dividing the space level based on the slice spacing threshold, calculating the depth value of each slice layer, quantizing the depth value, storing the quantized depth value in a depth buffer, allocating an independent display buffer for each slice layer, and establishing an inter-layer data index table; Read the importance weight coefficient, build a display parameter calculation model, input the importance weight coefficient into the display parameter calculation model, generate the display scale coefficient and position offset of each layer of slices, filter the data group with the largest importance weight coefficient, and allocate the data group to the display buffer corresponding to the top layer slice.

5. The method for superimposing intelligent perception information in a virtual space according to claim 1, characterized in that: The method comprises: constructing an inter-layer contrast enhancement matrix, adjusting the display parameters by using the inter-layer contrast enhancement matrix, setting an inter-layer minimum interval threshold, adding a layer mark bit in the display buffer, mapping the layer mark bit to a transparency control parameter, generating a mixing weight coefficient based on the transparency control parameter, and using the mixing weight coefficient to perform superposition processing on data of different levels, including: Calculate the brightness difference of adjacent level data, construct a contrast adjustment coefficient matrix, perform matrix multiplication operation on the contrast adjustment coefficient matrix and the display parameter, set a minimum distance value between layers, adjust the level interval based on the minimum distance value, add a level identification field in the data structure of the display buffer, and map the level identification field to a transparency value interval; Perform a nonlinear transformation on the transparency value to generate a normalized mixing weight coefficient, establish a hierarchical data mixing operation buffer, write each layer of data into the mixing operation buffer in the order of the size of the mixing weight coefficient, perform weighted average calculation on the data in the mixing operation buffer, and output the calculation result to the display buffer.

6. The method for superimposing intelligent perception information in a virtual space according to claim 1, characterized in that: The step of establishing a display strategy mapping table, selecting a corresponding visualization template according to the type label, calculating a data timeliness score, and converting the timeliness score into a display refresh cycle includes: Constructing a visualization strategy database, establishing a mapping relationship between a data type identifier and a visualization template, saving the mapping relationship to a display strategy mapping table, reading the type annotation information, searching for a matching item in the display strategy mapping table, and obtaining corresponding visualization template parameters; Add a timestamp field to each data item, calculate the difference between the current time of the data item and the timestamp, substitute the difference into the timeliness decay function, generate a data timeliness score, establish a refresh cycle mapping function, input the timeliness score into the refresh cycle mapping function, and calculate the display refresh time interval.

7. The method for superimposing intelligent perception information in a virtual space according to claim 1, characterized in that: The updating of the information state in the virtual space based on the display refresh cycle, performing smoothing processing on the information state, and synchronously displaying the processed result on the virtual space interface includes: Constructing a display state update queue, setting the display refresh cycle as a state update trigger condition, reading the latest data when the trigger condition is detected to be satisfied, writing the latest data into a virtual space information buffer, calculating state difference values ​​of adjacent data items, performing linear interpolation operation on the state difference values, and generating a state transition sequence; A mean filtering operation is performed on the state transition sequence, the filtered data is written into a display state buffer, a virtual space display controller is established, the data in the display state buffer is transmitted to the display controller, and the display controller synchronously outputs the data to the virtual space display interface.

8. An information superposition device for intelligent perception information in virtual space, characterized in that: The device comprises: A virtual mapping module is used to collect image data, temperature data, and sound data in the scene space, perform type annotation on the data, build a data priority evaluation model, calculate the information completeness and relevance scores of the data, generate an importance weight coefficient based on the integrity score of the information completeness and the relevance score, use the importance weight coefficient as a basis for data stratification, and establish a virtual space coordinate mapping function; an information superposition module, for slicing the virtual space coordinate system in layers, constructing a hierarchical display buffer, calculating display parameters of each layer according to the importance weight coefficient, allocating data with the maximum importance weight coefficient to the top display buffer, calculating edge clarity scores of data of each layer, setting blur radius parameters based on the edge clarity scores, performing blur processing on non-top data, constructing an inter-layer contrast enhancement matrix, adjusting the display parameters using the inter-layer contrast enhancement matrix, setting an inter-layer minimum interval threshold, adding a layered mark bit in the display buffer, mapping the layered mark bit to a transparency control parameter, generating a hybrid weight coefficient based on the transparency control parameter, and using the hybrid weight coefficient to perform superposition processing on data of different levels; A visualization module is used to establish a display strategy mapping table, select a corresponding visualization template according to the type label, calculate a data timeliness score, convert the timeliness score into a display refresh cycle, update the information state in the virtual space based on the display refresh cycle, perform smoothing on the information state, and synchronously display the processed results on the virtual space interface.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps of the method for superimposing intelligent perception information in a virtual space as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method for superimposing intelligent perception information in a virtual space as described in any one of claims 1 to 7 are implemented.

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