214 results about "Information visualization" patented technology

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 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 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 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 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 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 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 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.

The invention belongs to the technical field of layer fusion rendering, and particularly discloses a low-altitude digital twin multi-mode layer fusion rendering method and system, a terminal and a medium. Comprising the following steps: acquiring multi-source spatial data required by a low-altitude digital twinborn scene, performing format analysis and coordinate conversion on the multi-source spatial data, establishing a unified spatial coordinate reference, and generating multi-modal basic data with a unified resolution; the fused multi-modal scene data is formed; establishing a hierarchical index and spatial buffer system; and constructing a hierarchical rendering pipeline according to the spatial index system, and outputting a three-dimensional visualization result after fusion rendering, so that high-precision registration and fusion expression of multi-source heterogeneous spatial data can be realized, and the problem that multi-modal data in an existing low-altitude scene cannot be managed in a unified manner and cannot be dynamically visualized is solved. The method can be widely applied to the fields of urban low-altitude traffic supervision, unmanned aerial vehicle track display, meteorological situation awareness, three-dimensional geographic information visualization and the like.

Systems and methods are disclosed herein for visualizing and managing health information data, the system comprising: one or more subsystems adapted to receive health information data of one or more patients; a display device configured to display a viewing framework; a computing system communicatively coupled to the one or more subsystems, the display device, a memory, and a processor, wherein the processor comprises program instructions that, when executed, causes the processor to perform operations comprising: receiving the health information data; determining clinical context information of the health information data to generate contextualized data; converting the contextualized data into usable data using trained machine learning models; detecting viewing parameters; determining the viewing framework based on the usable data and viewing parameters; and sending the viewing framework to the display device automatically.

This interview information visualization device comprises: a recording unit configured to record, in a storage unit for each lifestyle habit that needs to be improved for an interviewee, content of an intervention of an interviewer, the intention for the intervention, and an activity plan planned on the basis of the intervention; and a display information generation unit configured to generate, with reference to the storage unit, display information for displaying, for each lifestyle habit, the content of the intervention, the intention for the intervention, and the activity plan in association with each other, thereby making it possible to share the intention for the interviewer's intervention with regard to the interviewee.

Systems and methods for intraoperative tracking and visualization are disclosed. A current minimally invasive surgical (MIS) instrument pose may be determined based on a live intraoperative input video stream comprising a current image frame captured by a MIS camera. In addition, an instrument activation state and at least one parameter value associated with the instrument may also be determined. Intraoperative graphic visualization enhancements may be determined based on the activation state of the instrument, and / or a comparison of parameter values with corresponding parametric thresholds. The visualization enhancements may be applied to a current graphics frame. The current graphics frame may also include visualization enhancements related to proximate anatomical structures with proximity determined from the instrument pose and an anatomical model. The current graphics frame may be blended with the current input image frame to obtain an output blended image frame, which may form part of an output video stream.

The invention belongs to the field of artificial intelligence, and discloses a distributed data acquisition system based on multi-agent collaborative decision and a construction method, and the method comprises the steps: 1, collecting heterogeneous data of production equipment, an environment sensor, a man-machine interaction terminal and an enterprise information system in real time through the deployment of a distributed data acquisition network, cleaning, de-noising and standardizing the edge computing nodes to generate a structured data stream; 2, automatically extracting features and laws of structured data through a multi-dimensional engine analysis model, and completing semantic alignment and fusion of heterogeneous data; 3, multiple agents are adopted to form empirical data according to a deterministic strategy gradient model in combination with a multi-dimensional reward function optimization model; and step 4, performing incremental learning on the empirical data to optimize the anomaly detection model, realizing multi-dimensional information visualization display of first-line decision and center command, and deploying corresponding functional agents according to the multi-dimensional information. The problems that a multi-agent system is low in control precision and low in efficiency are solved.

Techniques are described for generating visualizations of security framework information (such as, e.g., MITRE ATT&CK® information) displayed in connection with notable events detected by a data intake and query system. Data intake and query systems, SIEM systems, and other applications often provide user interfaces that display detected occurrences of incidents, sometimes referred to as “notable events,” within users' information technology (IT) environments. A data intake and query system is described herein that is capable of identifying notable events, assigning tactic and technique information to notable events (and optionally to associated risk objects), and causing display of tactic and technique visualizations which are intuitive and customizable, provide ready access to relevant documentation, and follow a format with which security analysts are familiar.

The invention relates to the technical field of artificial intelligence, and discloses an intelligent product life cycle management system and method based on a large model, a data layer is used for receiving multi-modal heterogeneous data input of different stages of a product full life cycle and is connected with a domain knowledge base; the model layer comprises a basic model and a task model, wherein the basic model is formed by fusing a large language model subjected to efficient parameter fine adjustment with a visual Transform hybrid architecture, and the task model is supported and driven by the basic model to run, and the model layer outputs a result based on the data layer; the data analysis module is used for analyzing heterogeneous data, constructing a knowledge graph for cross-source data intelligent retrieval and reasoning, and performing user demand analysis, semantic intelligent material classification, BOM full-life-cycle management, demand-driven optimization product design, supply chain risk prediction, dynamic process response and quality control and knowledge precipitation; and the application layer outputs a result based on the task model, and carries out real-time collaboration and key information visualization. According to the invention, automatic, intelligent and collaborative management of product life cycles of research, development and manufacturing enterprises is realized.

The invention relates to the technical field of agricultural information, in particular to a vegetable planting mode intelligent recognition system and method based on stable isotopes. The system collects stable isotope data of delta 13C, delta 15N and the like of vegetables, constructs a multi-dimensional database containing production places and cultivation modes, integrates four machine learning models of PLS-DA, SVM, RF and ANN to realize automatic identification of the planting modes, and realizes user interaction through electronic map visualization sampling points, background support data uploading and model dynamic training and front-end applets. Innovation points comprise stable isotope and machine learning fusion, a multi-model layered recognition architecture, an incremental learning mechanism, geographic information visualization and the like. The system can efficiently and accurately identify the vegetable planting mode, and the agricultural supervision efficiency is improved.

The invention discloses a building electrical fire hazard intelligent monitoring system and a monitoring method thereof. The system comprises an infrared thermal imaging module, a current harmonic analysis module, an edge computing node, a self-healing protection module and a user interaction terminal. The infrared thermal imaging module collects temperature field data and dynamically adjusts an alarm threshold value. The current harmonic analysis module collects harmonic characteristic data and identifies load abnormity. The edge computing node fuses the multi-dimensional data based on a random forest algorithm to generate a risk level and a fault type; the self-healing protection module adopts a three-stage tripping strategy to realize graded protection, and improves the handling capacity through closed-loop verification and fire-fighting linkage; and the user interaction terminal realizes fault information visualization. Through multi-dimensional data perception, intelligent analysis and hierarchical active protection strategies, a whole-process closed-loop management system from hidden danger detection, risk assessment to self-healing treatment is constructed, and the problems of high false alarm rate, response lag and management fragmentation in the prior art are solved.

The invention discloses an SCD file processing method and device based on a knowledge graph, terminal equipment and a storage medium, and belongs to the field of file verification. The method comprises the steps that an SCD file of a transformer substation system is acquired; based on a preset analysis mode, analyzing the SCD file to generate a virtual terminal table and a soft pressing plate list; calculating a similar distance value according to the virtual terminal table and the soft pressing plate list; judging whether the similar distance value is smaller than a distance threshold value or not; and if yes, performing information visualization on the SCD file based on a knowledge graph model. And if not, marking that the SCD file is abnormal. Therefore, by implementing the method and the device, the problem of low SCD file verification efficiency in the prior art can be solved.

1. The name of the design product: time display graphical user interface for electronic devices. 2. The use of the design product: for time display; the design product can be used for watches or smart clocks. 3. The design points of the design product: in the front view. 4. The picture or photo that best indicates the design points: front view. 5. The use of the graphical user interface: for the visual display of time and environmental information on the screen of electronic devices, improving the user experience through the form of a personified smiling face. 6. The human-computer interaction mode of the graphical user interface: the front view is the default display interface, and the user can switch to other function interfaces (such as weather, calendar, etc.) through sliding, clicking, etc. However, this application only protects the smiling face time display interface shown in the front view.

The embodiment of the invention discloses an information visualization method and system applied to parallel turbulent transport, and belongs to the technical field of data visualization. According to the embodiment of the invention, trajectory integral operation is performed on flow field sampling points through a Lagrange tracking method, and an original streamline set containing time evolution information is generated; performing topological structure analysis processing on the original streamline set to generate a streamline topological characteristic spectrum containing branch points, sink points and saddle points; constructing a multi-scale parallel rendering task queue based on the map, and distributing an original streamline set to a plurality of computing nodes for collaborative rendering through a spatial region division algorithm to obtain a collaborative rendering intermediate result; and according to the result, streamline density self-adaptive adjustment processing is executed, a turbulent transport visualization image sequence with a dynamic detail level is generated, the turbulent transport visualization image sequence is used for presenting the spatial distribution characteristics and the time evolution trend of the turbulent transport phenomenon in the flow field, and the efficiency and the accuracy of flow field visualization are improved.

The application discloses a gantry crane operation state monitoring method and a monitoring system. The method comprises the following steps: acquiring load data, stress data and beam span deflection of the gantry crane; determining the maximum combined stress of a beam unit of the gantry crane and the displacement value of a node of the beam unit according to the load data; performing operation state early warning of the gantry crane according to the load data, the stress data, the beam span deflection, the maximum combined stress and the displacement value; generating a maximum combined stress cloud chart according to the maximum combined stress, generating a gantry crane deformation cloud chart according to the displacement value, displaying the maximum combined stress cloud chart, the gantry crane deformation cloud chart, the load data and the operation state early warning information on a three-dimensional model of the gantry crane. The method realizes comprehensive monitoring of the gantry crane state, improves the comprehensiveness and reliability of the operation state early warning of the gantry crane, and can more intuitively display the operation state of the gantry crane through various information visualization.