287 results about "Information visualization" patented technology

The invention discloses a topographic surveying and mapping system and method of an unmanned aerial vehicle, and belongs to the technical field of topographic surveying and mapping. The system comprises the following modules: a data acquisition module which is responsible for acquiring high-precision terrain and environmental parameter data of a target area by using an unmanned aerial vehicle platform; the data fusion and correction module is responsible for fusing multi-source data and meteorological information and eliminating errors among sensors; the multi-dimensional feature analysis and recognition module is used for performing feature extraction and classification on data of each sensor through multi-dimensional feature analysis, and recognizing and separating an environment interference signal and a real building deformation signal; the interference elimination and deformation extraction module is used for carrying out pattern recognition and quantitative analysis on periodic non-deformation interference and accurately extracting real deformation characteristics of a building from complex dynamic noise; the real-time analysis module is used for realizing real-time data processing and feedback and ensuring that high-precision building change information is quickly provided; and the visualization module provides multi-dimensional dynamic visualization display including a building change heat map, an interference distribution map and a time sequence curve.

The invention provides a particulate matter and ozone source monitoring method and system based on a distributed sensor, and relates to the technical field of pollution treatment. According to the invention, sensor nodes with geographic perception capability are deployed in a monitoring area in a high-density manner, pollutant concentration and meteorological parameters are collected in real time, and data are uploaded to a cloud platform for preprocessing and dynamic calibration; a machine learning model is constructed based on the combined features of the pollutants and the meteorological factors, a driving relation is mined, and pollutant influence factors are extracted; further performing joint modeling on the influence factors and regional emission source data, identifying the coupling strength between pollutants and emission sources by adopting a classification or clustering method, and judging the categories of main sources; backward trajectory simulation, source fingerprint analysis and multi-source regression decomposition are combined to realize pollution path inversion and source contribution rate quantification; and finally, constructing a geographic information visualization platform, displaying a pollution thermodynamic diagram, a contribution change diagram and an evolution path diagram, and providing support for multi-source pollution traceability and scientific management and control.

The invention provides a geographic information visualization intelligent analysis system based on unmanned aerial vehicle surveying and mapping, and belongs to the field of surveying and mapping, and the system comprises an unmanned aerial vehicle aerial survey module which carries out regional aerial survey based on a multi-source sensor carried by an unmanned aerial vehicle, obtains multi-modal geographic data, and carries out the preprocessing of the multi-modal geographic data; the data processing module is used for forming an initial geographic data set under a standard coordinate system; the three-dimensional modeling module is used for obtaining the fused geographic feature data, constructing a three-dimensional geographic information model, optimizing the three-dimensional geographic information model and embedding time dimension information to form a four-dimensional spatio-temporal data set; the analysis and decision module is used for generating an analysis report comprising a terrain evolution trend and disaster risk assessment; and the visual platform module is used for visualizing the analysis report through a preset visual interaction interface and adjusting the rendering precision of the optimized three-dimensional geographic information model in real time according to the change of the visual angle of the user. The system provides an efficient and intelligent solution for geographic surveying and mapping and disaster early warning.

The invention discloses an intelligent management system for nuclear power plant personnel situation prediction and risk assessment, and relates to the field of intelligent safety management systems, and the system comprises a data collection unit, a multi-dimensional situation awareness unit, a risk prediction and assessment unit, an intelligent decision intervention unit and a visual interaction unit. And multi-source data acquisition, real-time situation construction, dynamic risk prediction and evaluation, intelligent early warning intervention and information visualization are realized. According to the invention, real-time monitoring, dynamic risk prediction and intelligent management of the safety state of the operating personnel can be realized, and the defects of real-time monitoring, dynamic prediction and intelligent management of the operating personnel in a high-risk area in the prior art are overcome, so that the safety management level is improved, the life safety is guaranteed, and the accident occurrence probability is reduced.

The embodiment of the invention relates to the technical field of tunnel environment monitoring, and particularly discloses a tunnel environment monitoring method and system based on multi-source data fusion. According to the embodiment of the invention, multi-source monitoring is carried out on the target tunnel, and data synchronization and preprocessing are carried out on the multi-source monitoring data; performing spatial-temporal feature extraction on the multi-source standard data, and performing unified feature mapping; performing multi-source fusion on the multi-modal feature sequence; performing environment classification identification on the fused feature data; and constructing an information visualization platform, and monitoring and displaying the abnormal event data and the plurality of environment identification data. Multi-source monitoring, data synchronization and pre-processing, spatial-temporal feature extraction, multi-source fusion and environment classification identification, construction of an information visualization platform for monitoring display, data fusion processing of multi-source monitoring and comprehensive perception of multi-source data can be performed, so that linkage coupling analysis can be performed on various data, and multi-source data can be acquired. The abnormity identification capability and the response capability are improved, and the false alarm rate is effectively reduced.

The invention relates to the technical field of road engineering detection, in particular to a highway pavement crack image intelligent detection system and method, and the system comprises an image acquisition module, a deep learning module, an image enhancement module, a crack measurement and calculation module, a crack development trend prediction module and an information visualization module. The core innovation of the invention lies in that a differential geometry theory is introduced to construct a crack development trend prediction module, and the module comprises a crack characterization model based on a differential manifold, a multi-scale crack evolution tensor field analysis model and a nonlinear space-time crack development prediction model. A pavement is regarded as a two-dimensional differential manifold, cracks are represented as singular curves on the manifold, a multi-scale tensor field analysis technology and a non-linear kinetic equation are combined, accurate prediction of the future development trend of the cracks is achieved, the system supports multiple image acquisition modes, transverse, longitudinal and net cracks can be accurately detected, and the detection precision is high. The method adapts to complex illumination and background conditions, and predicts the expansion rate and severity change of the crack.

The invention discloses an intelligent city management information visualization comprehensive management method and system, particularly relates to the technical field of city management, and is used for solving the problem of misalignment of emergency response caused by false association and causal confusion in the prior art. Precise management is realized through multi-modal time sequence data feature alignment, causal chain network dynamic construction and a visual decision mapping technology, firstly, multi-dimensional event features of video monitoring, sensors and text work orders are extracted, a cross-modal association chain is constructed, interference chains are screened out through causal strength evaluation and anti-fact verification, and a visual decision mapping algorithm is established. According to the method, dynamic correction parameters are generated in combination with space-time weights and feedback priorities, finally, a visual guidance scheme is output by fusing a causal chain network and a geographic information system, decision optimization is driven through causal logic, and city event disposal accuracy and cross-department cooperation efficiency are remarkably improved.

The invention relates to the field of commodity visualization, in particular to a commodity display interaction visualization method and device. The method comprises the following steps: collecting a multi-azimuth image of a commodity, carrying out three-dimensional texture modeling, and constructing a three-dimensional texture mapping model; performing material light rendering on the three-dimensional texture mapping model to generate a material rendering result; collecting an environment detection image of a commodity display environment, and performing environment illumination adaptation compensation on a material rendering result to obtain an illumination compensation rendering commodity; carrying out attribute information visual layout on the illumination compensation rendering commodity to obtain a commodity visual space; and carrying out interaction response animation analysis according to the commodity visualization space, carrying out multi-target parallel rendering, and executing commodity interaction visualization operation. The form and surface details of the commodity in the real world are accurately restored, the visual reality sense is improved, and the interactive experience feeling of browsing the commodity by a user is enhanced.

The invention discloses a lightweight rice leaf disease identification method based on YOLO target detection. The method comprises the following steps: S1, inputting a rice leaf disease image; s2, carrying out super-resolution reconstruction on the image by using an improved Real-ESRGAN algorithm; s3, inputting the picture into an improved YOLOv8n target detection algorithm; s4, obtaining disease spot category and position information; and S5, visualizing the information on the image. The invention relates to the technical field of target detection, and has the beneficial effects that image super-resolution reconstruction is carried out aiming at the problems that a rice leaf scab target is relatively small and an image acquired in real time is relatively fuzzy, so that the resolution of the small target is improved, and the definition and texture features are improved. On the basis of a super-division model Real-ESRGAN, a group of residual dense modules containing five layers of cavity convolution layers are designed to help the network to acquire receptive fields and information of different scales.

The invention proposes a smart park energy consumption management system and method based on artificial intelligence, and relates to the technical field of smart park energy consumption management, and the system comprises a data collection module which collects original time sequence energy consumption data and equipment state information; the data preprocessing module is used for performing data quality processing on the original time sequence energy consumption data to obtain preprocessed time sequence energy consumption data; the topology management module is used for constructing an energy consumption relation graph and generating node topology representation characteristics; the feature engineering module is used for obtaining a space-time-business joint feature tensor; the anomaly monitoring module is used for obtaining an anomaly score and outputting anomaly positioning information based on an interpretable analysis method; and the visual display module is used for generating an alarm report and performing visual display. According to the invention, accurate anomaly identification and intelligent positioning analysis of multi-level and multi-energy-type energy consumption data of the park can be realized, and the automation level and the operation and maintenance efficiency of park energy management are improved.

The invention discloses a drainage pipeline multi-parameter sensing trenchless repair dynamic regulation and control method and system. Through a fusion technology path of multi-source comprehensive data acquisition, edge calculation real-time cross validation of abnormity, pipeline state simulation analysis of defect levels, intelligent algorithm dynamic adjustment of repair parameters and geographic information visualization platform full-process monitoring, closed-loop management from abnormity identification to repair regulation and control is realized. A comprehensive data set is formed through multi-source data acquisition, an edge computing technology is utilized to quickly identify abnormities, a simulation technology is combined to evaluate the severity of defects, then process parameters are optimized and repaired based on defect levels, and a regulation and control instruction is generated through linkage of a visual platform and a pump station dispatching system. And finally, a pipeline repair and operation regulation and control scheme is formed through integration, and the repair effect and the system stability are ensured. According to the method, the pipeline abnormity processing accuracy and the repairing efficiency are remarkably improved, and a technical guarantee is provided for safe and stable operation of an urban drainage system.

The invention provides a spatial path visualization method and device for coupling a place name label and a Voronoi diagram, and relates to the technical field of geographic information visualization, and the method comprises the steps: carrying out the preprocessing of obtained initial path data, and generating a path point sequence; obtaining a point-of-interest score corresponding to the specific type parameter of each city in the path point sequence, and determining a first display space corresponding to each city based on the sum of the point-of-interest scores, determining a second display space corresponding to the specific type parameters of each type in the first display space based on the interest point scores of the specific type parameters of different types in each city; and performing word cloud rendering on the second display space to generate a visual path parameter display diagram. According to the method, the spatial region is hierarchically divided through the weighted Voronoi graph, and the sub-regions are filled with the corresponding POI word cloud information, so that the path visualization has higher information bearing capacity and a more intuitive semantic expression effect.

The invention relates to the technical field of ultrasonic detection, and provides an aero-engine fuel control valve leakage amount ultrasonic detection method, which forms a coherent technical link through leakage ultrasonic signal acquisition, leakage signal separation, leakage feature extraction, leakage area positioning, offset compensation and cross validation of a sensor, and the links are mutually verified and optimized. A leakage signal is separated through a dynamic threshold value, the identification degree of a deep belief network is enhanced through multi-dimensional features, environment interference is compensated and corrected through working condition parameters, positioning deviation caused by single-link error accumulation in a traditional method is effectively restrained, accurate capturing and positioning of a micro leakage signal are achieved, and the method is suitable for large-scale popularization and application. The leakage thermodynamic diagram integrates leakage rate grading, coarse positioning area and micro leakage point information, the analysis and decision-making time of maintenance personnel is greatly shortened through a visual presentation mode, and rapid interpretation of fault positions and severity is achieved.

To provide an efficient system that overcomes information incompleteness in the Partially Observable Markov Decision Processes (POMDP) and simultaneously optimizes multiple competing objective functions.SOLUTION: The present invention provides a multi-objective optimization system using a hierarchical adaptive manifestation mechanism in a POMDP. The system hierarchically clusters a state space to construct a hierarchical belief support MDP, and calculates a strategy that optimizes a weighted sum of a plurality of objective functions. Additionally, the system includes an adaptive manifestation mechanism that dynamically switches between exploration actions and goal-achieving actions according to uncertainty of belief states, and a continuous manifestation mechanism that corresponds to continuous state and action spaces. This enables improvement in computational efficiency and realization of multi-objective optimization.SELECTED DRAWING: None

The invention discloses an AI-based household condition gridding six-dimensional element holographic display system and method, and relates to the technical field of gridding social governance information, and the system comprises a data aggregation module which integrates data across departments and carries out cleaning processing; the data modeling module is used for constructing a space-time model based on a GIS (Geographic Information System) and integrating a multi-source map, and automatically generating and realizing dynamic division of various types of grids for social governance based on the multi-source map; the social governance module is used for collecting data through an AR mobile terminal, processing the data through a clustering algorithm and arranging events according to priorities; the user condition grid module is used for dividing grids, associating six-dimensional data and dynamically associating with workers at all levels; the six-dimensional element module is used for carrying out multi-dimensional statistics on six elements; the holographic display module is used for realizing grid drilling and information visualization; and the intelligent AI module analyzes the data and generates early warning. According to the invention, intelligent analysis and dynamic display of grid information are realized through AI and holographic technologies, and an AI intelligent scheme and an efficient digital scheme are provided for social governance.

The invention belongs to the field of safety monitoring of wind power equipment, and provides a multi-source data fusion and safety early warning system and method in the hoisting process of a wind turbine generator, and the system comprises a data collection and preprocessing module which collects and preprocesses multi-source sensor data such as a tower inclination angle and a suspension arm inclination angle; the state manifold construction module is used for mapping the preprocessed data to a multi-dimensional space to construct a state manifold and generating an ideal geodesic line; the trajectory analysis and risk assessment module is used for calculating the deviation degree between the real-time state trajectory and the ideal geodesic line and generating a risk score; the dynamic threshold generation module constructs a risk tensor field based on environmental parameters, and extracts a risk threshold curved surface after wind speed adjustment; the early warning decision module is used for comparing the risk score with a threshold curved surface to determine an early warning level and sending information; and the visual display module is used for displaying the state manifold, the track, the tensor field and the early warning information. By introducing a differential geometry theory, state manifold representation and geodesic deviation measurement are constructed, and accurate assessment of the hoisting process risk is realized.

The invention belongs to the technical field of industrial production control, and particularly relates to a diamond roller machining workshop production line process control system which comprises an order management unit, a workshop production line supervision unit and an information visualization unit. The workshop production line supervision unit comprises a real-time data acquisition and processing module, a process parameter intelligent optimization module, an automatic cooperative control execution module and an online closed-loop feedback module; according to the invention, the real-time data acquisition and processing module acquires data and generates a standardized data stream, the process parameter intelligent optimization module dynamically generates optimal process parameters, and the automatic cooperative control execution module performs corresponding control operation on a processing workshop production line. The online closed-loop feedback module conducts online detection on the finished diamond roller and feeds back the detection result to the intelligent technological parameter optimization module, efficient, accurate and intelligent diamond roller machining is achieved, intelligent control over the whole diamond roller machining process is facilitated, and the production efficiency and the product quality are remarkably improved.

The invention relates to the technical field of new energy automobile charging, and discloses an efficient electromagnetic induction wireless charging system for a new energy automobile. The system can receive and analyze vehicle battery state information in real time through the charging control module and automatically adjust the output power of the transmitting module according to the charging power requirement and time, the transmitting module efficiently transmits electric energy to the receiving end from the transmitting end according to the electromagnetic induction principle, high-frequency alternating current is generated according to instructions, power transmission is optimized, and the charging efficiency is improved. The receiving module is responsible for converting the received alternating current into direct current to ensure that the energy loss in the charging process is reduced to the minimum, the data acquisition and analysis module integrates data from all the modules to generate a detailed charging report, and the information visualization module visually displays the charging state and the analysis result through a liquid crystal screen. By means of the overall design, the technical problems of a traditional wireless charging system in the aspects of charging efficiency and monitoring capacity are effectively solved.

The present application relates to the technical field of road engineering detection, in particular to a highway pavement crack image intelligent detection system and method thereof, comprising an image acquisition module, a deep learning module, an image enhancement module, a crack measurement and calculation module, a crack development trend prediction module and an information visualization module, the core innovation of the present application lies in introducing differential geometry theory to construct the crack development trend prediction module, which includes a crack representation model based on differential manifold, a multi-scale crack evolution tensor field analysis and a nonlinear spatiotemporal crack development prediction model. By regarding the pavement as a two-dimensional differential manifold and the crack as a singular curve on the manifold, combined with multi-scale tensor field analysis technology and nonlinear dynamics equation, the accurate prediction of the future development trend of the crack is realized, the system supports multiple image acquisition methods, can accurately detect transverse, longitudinal and network cracks, adapts to complex lighting and background conditions, and predicts the expansion rate and severity change of the crack.

The invention discloses a concrete material strength detection and analysis system, and relates to the technical field of constructional engineering quality detection. The system comprises a data acquisition module, a data preprocessing module, a fusion and analysis module, a fusion and analysis module and a visual report generation module. Wherein the data acquisition module is used for acquiring multi-source original data of concrete strength; the data preprocessing module is used for performing cleaning, format standardization and invalid value elimination operation on the multi-source original data and storing the multi-source original data in the central database; the fusion and analysis module is used for carrying out strength prediction in future time by adopting a dual-mode comparison prediction method, and sending warning information to detection personnel when a strength prediction value exceeds a prediction threshold value; and the visual report generation module is used for automatically generating a detection report and an analysis chart conforming to a standard format. According to the method, the analysis and evaluation of the concrete strength can be realized by fusing the multi-source detection data and the process data and utilizing a machine learning algorithm.

The invention provides a pork processing full-chain traceability information visualization method based on RFID and a two-dimensional code, and the method comprises the steps: firstly, setting a key control point under the guidance of an HACCP system, and determining possible hazard links in a pork traceability whole process; secondly, an image acquisition device is used, the electronic tag is used as a traceability information carrier, and traceability picture information is written into a storage area of the electronic tag; finally, paper two-dimensional codes are adopted for marking information of pork at all parts after pork segmentation, and consumers inquire pork traceability information by scanning the two-dimensional codes. According to the method, the HACCP system is used as guidance, the harm in the whole process is analyzed, key control points are set, and links which are prone to problems in the live pig product production process are determined. For the links, pictures of field operation are shot and stored in the traceability system, so that the authenticity and the accuracy of traceability information are improved, and the credibility of consumers on pork quality is improved.

The invention discloses an AI-based college entrance examination voluntary reporting scheme recommendation method and a related device, and relates to the technical field of artificial intelligence recommendation, and the method comprises the steps: determining the admission probability of different majors of each college through the combination of the obtained historical college entrance examination admission data and the personal admission basic information of examinees; then determining character characteristics of examinees through an examinee personal evaluation module, a chat content collection module and an AI large model analysis module; and finally, according to the admission probability of different majors of each college and the subjective character characteristics and objective character characteristics of the examinees, generating a plurality of volunteer filling schemes, and displaying the plurality of volunteer filling schemes to the examinees and parents of the examinees in detail through an information visualization display module in a graphical interface for reference. According to the scheme, on the basis of ensuring admission to the maximum extent, a comprehensive and deep personalized volunteer filling scheme can be provided, it is ensured that the recommendation scheme of each examinee is unique, and the satisfaction degree of volunteer filling of the examinees is improved.

The present disclosure relates to a dental lesion detection method and a system to which the method is applied. A dental lesion information visualization method according to the present disclosure includes the steps of acquiring data of a lesion analysis model which outputs data on the type and location of a lesion included in a panoramic image obtained by capturing an image of the oral cavity of a patient, and inputting a panoramic image into the lesion analysis model to output data on the type and location of a lesion and a lesion detection confidence score.

The invention provides a forest fire fighting and rescue fire scene low-altitude meteorological monitoring service system and method. The system comprises a forest fire scene meteorological environment monitoring system, a data fusion analysis system and a data distribution service system. The forest fire scene meteorological environment monitoring system comprises an air-ground collaborative meteorological observation system and a forest fire scene space information remote sensing system, and is used for acquiring low-altitude meteorological environment, vegetation and terrain situation information in a forest fire scene boundary layer; the data fusion analysis system is used for observation data space-time normalization processing, observation data space-time scale expansion, three-dimensional fire scene situation construction based on terrain situation information, meteorological data fusion analysis and information visualization display; and the data distribution service system comprises a data link and data distribution service software and is used for distributing data of the forest fire scene meteorological environment monitoring system and the data fusion analysis system to different forest fire fighting rescue forces and hardware terminals. The overall efficiency and safety of forest fire scene fighting work can be effectively improved.

The invention relates to the technical field of data visualization, in particular to a road construction information visualization analysis system which comprises a construction state layering module, a construction mode analysis module, a construction trend prediction module, an error dynamic correction module and an information storage management module. According to the method, the real-time performance and interactivity of the construction state are improved by performing multi-dimensional dynamic analysis on the road construction information, and the information such as equipment operation, construction duration and state fluctuation is accurately identified and sorted by combining the hierarchical state model and construction characteristic weight value analysis; the future construction trend can be dynamically predicted and corrected in time, meanwhile, the construction information storage mode is optimized, data management is more accurate and reliable, the defects of static display and lack of real-time updating in a traditional scheme are overcome, the strain capacity and flexibility in a complex construction environment are enhanced, and the construction efficiency is improved. Continuous tracking and adjustment of the construction information are guaranteed, and the management precision and the decision timeliness are improved.

The invention discloses a key feature in-situ recognition method for electronic nose smell recognition, which comprises the following steps of: acquiring a complex smell data sample for in-situ recognition, and ensuring high precision and high resolution of smell information through a multi-level and multi-dimensional data processing algorithm-multi-dimensional layered mapping technology; the in-situ identification is more accurate and rapid; a dynamic smell information extraction self-adaptive updating mechanism is adopted, specifically, deep microscopic characteristic extraction is carried out on a smell sample, comprehensive overall characteristic construction is carried out to represent smell information, and a smell recognition model is adjusted and optimized in a self-adaptive mode; visual representation based on smell evolution information is adopted; and an intelligent in-situ identification system of the electronic nose system from an information end to a decision end is established. According to the method disclosed by the invention, the key smell characteristics can be quickly identified and positioned in the in-situ identification process by constructing an efficient smell information visualization method, so that the high efficiency and accuracy of classification are ensured.

A method of security information visualization processing, an electronic device and a storage medium are provided. The method includes: in response to a security overview display instruction, displaying a security overview dashboard of a user group; displaying, in the security overview dashboard, anomaly aggregation information and security measure aggregation information; and aggregately displaying, in a display region corresponding to a security scenario, information of a plurality of anomaly categories associated with the security scenario.

The invention relates to the technical field of intelligent construction sites, in particular to an all-dimensional visual intelligent automatic control method for an intelligent construction site. According to the invention, the identity tag information of the personnel on the construction site is compared with the preset stored information to verify the identity tag information and ensure the reliability of identity verification, and through verification of the safety helmet wearing information and the safety helmet IP information with the safety level, the personnel entering the construction site can be ensured to wear the safety helmets according to requirements, and meanwhile, the safety helmet wearing safety is ensured. The safety helmet IP information and the positioning information of the workers in the construction site are utilized, the positioning information is compared with the authority subareas in real time, the track of the workers in the construction site containing illegal record registration is formed in real time, in addition, the health and safety of the workers in the construction site are monitored, the workers entering the construction site are monitored in an all-around and intelligent mode, and meanwhile the safety of the workers entering the construction site is improved. And construction site personnel can be effectively ensured not to leave the construction site by carrying construction site articles illegally, so that the comprehensive and intelligent monitoring effect on the construction site is achieved.

The present invention discloses a ground operation and application integrated system for high-resolution remote sensing satellites. Guided by the support for the operation and application of high-resolution satellites, an integrated space-ground system integrating the design, testing, operation control and application of high-resolution remote sensing satellites is first established to achieve the interconnection and interoperability of high-resolution remote sensing satellite design simulation, comprehensive test verification, on-orbit operation management, and comprehensive application of business data. Then, driven by requirements, an automated task planning and scheduling strategy is constructed to achieve task conflict resolution and optimal planning. Secondly, a training set of typical targets is established, and target intelligent interpretation is realized based on machine learning, effectively improving the timeliness and accuracy of target recognition and confirmation. Finally, data such as meteorology, hydrology, surveying and mapping, and basic maps are introduced to construct target information combined with the three-dimensional environment, and the overall situation awareness of the scene and the target is realized after visualization.

The invention provides an information visualization method and system, a medium, equipment and a program product, and relates to the technical field of information processing, and the method comprises the steps: obtaining heterogeneous input information; performing category detection on the heterogeneous input information by utilizing the classification model, and determining a category corresponding to the heterogeneous input information; calculating entity relevancy, information relevancy and information weight corresponding to the heterogeneous input information according to the category; inputting structured label information corresponding to the heterogeneous input information according to the entity relevancy, the information relevancy and the information weight; constructing an atlas data structure corresponding to the structured label information; and mapping the map data structure into visual elements to obtain visual information. According to the method, heterogeneous input information is converted into visual information, so that leap-type improvement from bottom-layer data quantification to top-layer cognitive perception is realized.