975 results about "Data visualization" patented technology

A management server system may obtain a request for image data from a computing device. The request may identify a subset of image data to be downloaded and / or streamed to the computing device. The management server system can provide an indication of a storage destination for the image data to a gateway device and initiate upload of the image data from the gateway device to the storage destination. The management server system may monitor the upload and, based on the monitoring, determine the upload is complete. The management server system can cause display of a user interface that includes a visualization of the image data for download of the image data from the storage destination to the computing device.

The invention relates to the technical field of data visualization and integration, in particular to a power equipment fault positioning and maintenance decision-making method based on knowledge graph reasoning, which comprises the following steps of: acquiring a structure parameter generation node, constructing a causal path positioning source component and outputting a maintenance link structure. In the invention, the time attribute is introduced through the node set constructed by the structure number and the operation parameter to strengthen the time sequence characteristic of the power equipment state identification, and the logic response sequence between the nodes is sorted through the causal relationship path chain to improve the accuracy of fault chain reasoning. A multi-path screening mechanism effectively avoids the problems of large path hop count and inconsistent response directions, path dominance identification ensures convergence and pertinence of fault positioning, and key components and maintenance suggested nodes are spliced so that a link structure not only has traceability, but also has operability. An ordered closed loop from structure identification, causal analysis and maintenance output of the power equipment is realized, and the fault processing accuracy and the performability of the power equipment are improved.

The invention discloses a pedestrian behavior simulation operation control method based on an unreal engine. Efficient and vivid pedestrian behavior simulation is realized through five core modules: a three-dimensional scene construction module converts a BIM model based on an unreal engine Datasmith plug-in and constructs an interactive dynamic scene; the pedestrian model construction module defines multi-dimensional pedestrian attributes and supports data-driven initial distribution configuration; the hierarchical behavior control module realizes refined regulation and control of pedestrian behaviors through macroscopic path planning, microcosmic behavior decision and emotion driving; the dynamic resource optimization module adopts level-of-detail control and multi-thread task allocation to improve the operation efficiency of the system; and the real-time interaction and data analysis module provides scene regulation and control, data visualization and simulation data recording and playback functions. According to the method, the authenticity, the dynamic response capability and the controllability of pedestrian simulation are remarkably improved, and reliable technical support can be provided for traffic planning, emergency drilling and building design evaluation.

The invention discloses a submarine cable insulation performance online monitoring and fault positioning method, a medium and equipment. The method comprises the following steps: S1, synchronously acquiring multi-source sensing data in real time; s2, multi-modal noise cooperative suppression and feature extraction; s3, insulation state degradation evaluation based on multi-feature fusion; s4, double-end traveling wave accurate fault positioning is carried out; and S5, carrying out data visualization and alarm linkage. According to the invention, marine complex environmental noise interference can be effectively suppressed, key parameters representing the insulation state of the submarine cable are monitored in real time in a multi-dimensional manner, and early warning of insulation degradation and preliminary judgment of a fault mode are realized through an intelligent fusion evaluation model. And the improved traveling wave accurate capture and wave velocity dynamic correction technology is utilized to realize accurate positioning of a fault point, so that the accuracy and sensitivity of submarine cable state monitoring and the fault positioning precision can be remarkably improved, and powerful technical support is provided for safe and economical operation of submarine cables.

The invention provides a user behavior tracking and portrait generation system, which is characterized in that multi-source original behavior data is acquired through a data acquisition module, and a standard behavior event stream is generated through cleaning and standardization; the behavior modeling module is used for carrying out cross-event association and self-defined time window combination modeling on a standard event flow based on a configurable rule engine to generate a complex event flow; the real-time processing and calculation module performs real-time aggregation calculation on the complex event stream, generates a real-time behavior index, a trigger signal and an incremental portrait snapshot in combination with a preset rule, and pushes a behavior trigger signal to a downstream service system; the user portrait management module dynamically updates user tag weights and values according to the real-time indexes, and generates a target user portrait tag library and a lightweight tag change event stream; the data storage and query module stores data of each link; and the visual configuration and operation and maintenance module issues a configuration instruction through a visual interface, and monitors full-link operation and task scheduling. And real-time accurate portrait construction and instant service response are realized.

The invention provides a hydropower station fusion computing power intelligent server system, and relates to the technical field of carbon emission. The method comprises the following steps: an acquisition correction module acquires hydropower station generation power data and server cluster instantaneous energy consumption data in real time, establishes a time sequence corresponding relation between a power generation side and a power utilization side, and obtains clean energy supply quantity data; the prediction scheduling module generates a non-tampering carbon footprint tracking chain number, and predicts a clean energy supply fluctuation trend sequence by adopting a long short-term memory network algorithm; training a random forest model to predict a computing power demand trend sequence; optimizing task scheduling according to a carbon emission minimization target, and generating dynamic balance configuration data of a computing power task and clean energy supply; and the monitoring evaluation module outputs computing power task level carbon emission and a clean energy use ratio in real time through an application programming interface according to the dynamic balance configuration data, and generates quantitative evaluation data of a computing power service carbon neutralization target by adopting a data visualization technology monitoring technology.

The invention relates to the technical field of data processing, in particular to an intelligent supervision method and system based on a data visualization platform, and the method comprises the steps: collecting multi-source water conservancy data through dual-channel redundancy check, converting the multi-source water conservancy data into a standardized space-time matrix, carrying out the data cleaning through a containerization adaptation and variational auto-encoder, and marking the confidence; hierarchically storing the data based on a confidence threshold, and generating a routing strategy through reinforcement learning to distribute data fragments; calculating a flood peak evolution prediction result by using space-time diagram convolution, calculating an output risk assessment value by combining a Bayesian network and long and short-term memory, and activating federal learning parameter updating when the confidence coefficient is insufficient; the digital twin model loads physical constraint parameters to deduce a flood control scene, and a scheduling instruction set and a rehearsal animation are generated through multi-objective optimization; and dynamically rendering to generate an interactive visual interface, associating a causal deduction path, and triggering federal model parameter updating by user feedback, thereby realizing dynamic collaboration of the forecasting and early warning rehearsal plan function chain.

The invention belongs to the technical field of honey analysis, and particularly relates to a method for analyzing characteristic chemical components of Qinling Mountain medium-peak honey. The analysis method comprises the following steps: obtaining different extraction layers, and carrying out mass spectrometry on each layer of sample; constructing a molecular network by mass spectrum data through a GNPS platform, and comparing the mass spectrum data with a database to obtain primary identification; unmatched nodes predict the skeleton by using an NAP tool to obtain a secondary result; then fractions are separated, and an unknown structure is deduced by combining an SMART technology with nuclear magnetism; and finally, synthesizing the three types of results to determine the characteristic chemical components of the honey. Compared with a single chromatography-mass spectrometry technology, the analysis method provided by the invention not only realizes data visualization, but also reduces the dependence of chemical component identification on a database to a certain extent, and provides reference for rapid characterization of chemical components in a honey crude extract or fraction.

The invention discloses a coal loading and unloading equipment operation detection system based on visual identification, and relates to the technical field of visual identification. The system comprises a hardware architecture and a software architecture, the hardware architecture comprises an image acquisition unit, a data processing unit and a control feedback unit; the software architecture comprises an image processing layer, an intelligent analysis layer and a decision application layer; the image processing layer comprises an image acquisition subsystem, a preprocessing algorithm library and a feature extraction module; the intelligent analysis layer comprises a target detection and identification module, a three-dimensional reconstruction module and an abnormal behavior identification module; and the decision application layer comprises a rule engine, an alarm management subsystem and a data visualization platform. By deploying sensor equipment such as a multi-angle industrial camera and a laser radar and combining a deep learning algorithm and a computer vision technology, various illegal operations and abnormal conditions in the loading and unloading process are automatically identified, total-factor digital monitoring of the loading and unloading process is realized, the detection efficiency is improved, and the loading and unloading risk is reduced.

The invention discloses an electromagnet electromagnetic ultrasonic thickness measurement method and system based on an anti-collision unmanned aerial vehicle, and relates to the field of nondestructive testing, and the method comprises the steps: obtaining the coordinates of a preset detection point, controlling the flight path of the unmanned aerial vehicle, and determining the safety position information of the unmanned aerial vehicle located near the preset detection point; the motion of the multi-degree-of-freedom mechanical arm is controlled through a servo motor and an encoder, contact impact is reduced through a buffer mechanism, and attitude information of the electromagnetic ultrasonic sensor unit aligned with the surface of the to-be-detected object is determined; the magnetic attraction force is adjusted in real time through a closed-loop feedback system, and a linear frequency modulation pulse is adopted as an excitation signal to obtain an echo signal containing acoustic-electromagnetic coupling interference; acoustic-electromagnetic coupling interference is corrected and processed in an auxiliary mode through a multi-mode signal separation algorithm and machine learning, and final thickness data is obtained; and transmitting the final thickness data to a cloud platform, and providing a data visualization interface and an alarm function on the cloud platform. According to the invention, accurate thickness detection and remote monitoring of a complex structure material can be realized.

The invention provides an interactive multi-dimensional data visualization display sand table and method for business data analysis, and the method comprises the steps: carrying out the semantic mapping of state parameters in an interaction control operation when the interaction control operation is received, obtaining a plurality of pieces of visualization intention metadata, and generating a structured query instruction; based on the structured query instruction, extracting a target data subset rendered visually by the heterogeneous commercial data source from a multi-dimensional data cube of the commercial data source, performing visual optimization on the visually rendered chart type, the visual coding channel and the initial visual parameter through the cardinal number of the dimension field in the target data subset and the data distribution type and the numerical range of the measurement field to obtain a visual configuration set of the target data subset; and using the visualization configuration set to render and generate a multi-dimensional data visualization view, and outputting and displaying the data visualization view in a graphical user interface. Based on the scheme, automatic closed loop generation from heterogeneous data to interactive views can be realized.

A system can be used to generate interactive data visualizations and textual content. The system receives a layout of a content item. The content item can be a data visualization dashboard or an article. The system can generate a content structure tree based on the layout. The content structure tree represents hierarchical and semantic relationships between sections of the content item. The system can receive input adding content elements, such as data visualizations or textual paragraphs, to sections within the content item. The system can identify text roles for different sections based on the content structure tree and the content elements. The system can generate text suggestions for the content item based on the text roles. The system can also generate text content for a text suggestion using a large language model, display the generated text content within the content item, and iteratively refine the content item.

The invention relates to the technical field of cold-chain logistics, in particular to a digital collaborative tracing method and system for cold-chain logistics based on the Internet of Things. The method comprises the following steps: binding a unique identifier associated with a batch of goods with at least one Internet of Things sensor; in the process that the goods pass through the supply chain, the at least one Internet of Things sensor is used for continuously collecting environment and state data; transmitting the environment and state data to a data processing platform in real time, and processing the environment and state data by using a hybrid prediction model in the data processing platform so as to dynamically calculate the remaining shelf life of the goods; and outputting the dynamically calculated remaining shelf life, and presenting the information to logistics managers and consumers through a customized data visual interface. The invention aims to reduce corruption, enhance food safety and improve operation efficiency by changing passive monitoring to active intelligent prediction.

The invention relates to the technical field of direct-current large-current power supply testing, in particular to a direct-current large-current power supply testing method and device. According to the invention, temperature, voltage and current are synchronously acquired through multiple channels, and data validity is marked; after smoothing processing, calculating compensation resistance by using a two-item temperature compensation formula; according to current characteristics, an abnormal threshold value is dynamically adapted in a current increasing / stabilizing / decreasing period, and a normal / early warning / shutdown instruction is output in a grading manner; performing correlation analysis on temperature-resistance and voltage-current characteristics to identify hidden defects; the weighted linear regression predicts future temperature / resistance and gives an early warning; data are stored in a layered mode, visualized display is achieved, and a report containing A / B / C grade rating is automatically generated. The device comprises a corresponding functional unit and a processor-memory architecture, and is suitable for large-current testing of multi-scene electrical equipment.

The invention relates to the technical field of meteorological data visualization, in particular to a meteorological data visualization method and device, electronic equipment and a storage medium. According to the meteorological data visualization method and device, firstly, a lightweight multi-resolution data organization unit is established based on a spatial index, a server-side pre-rendering slice is replaced, the storage pressure is reduced, and the data updating flexibility is improved; secondly, a dynamic thread pool and a load balancing mechanism are adopted, data processing tasks are intelligently decomposed and executed in parallel, client computing resources are fully utilized, the processing efficiency is remarkably improved, then coordinate conversion, interpolation and graph drawing are completed in a working thread through an off-screen rendering engine, calculation and rendering decoupling is achieved, and the system performance is improved. And finally, an incremental updating mechanism and a dirty marking technology are introduced, only local redrawing is carried out on a change area, and a cache multiplexing mechanism is combined, so that global rendering overhead is effectively avoided, and real-time, smooth and high-interactivity visualization of mass meteorological data is realized at a Web end.

One aspect of the present disclosure relates to a distributed energy data platform process, and more particularly, to a distributed energy data platform process capable of increasing efficiency of energy resources and ensuring flexibility in management by configuring an AIoT process based on a distributed energy data platform. The distributed energy data platform process includes a data collection unit for collecting IoT sensor data of an IoT sensor installed in an energy-consuming device in real time; a database for loading the IoT sensor data collected in real time from the data collection unit; a visualization unit for interacting with the database so as to visualize the IoT sensor data to monitor the IoT sensor data in real time; and a training unit for configuring an artificial intelligence life cycle operation for the IoT sensor data.

The invention relates to the technical field of complex industrial equipment monitoring and digital twinning, and discloses a gas turbine data visualization and intelligent interaction system which comprises a sensor array, a computing unit, a force feedback device, an eye tracker and a display terminal. The system constructs a three-dimensional physical field and corrects a velocity vector by using Kriging interpolation and Euler equation momentum balance, and generates a variable radius flow tube reflecting the compressibility of fluid; calculating mass, momentum and energy conservation residual errors to construct a generalized potential energy field, and generating gradient guide force and self-adaptive damping force by driving force feedback equipment; and dynamically adjusting solving precision and rendering parameters through sight tracking. According to the method, the flow field is reconstructed through physical constraint, multi-modal feedback is introduced, the problem that discrete data feature distortion and single visual interaction are difficult to perceive physical consistency is solved, and high-fidelity reduction of the gas turbine flow field and visual touch synchronous accurate diagnosis of fault types are achieved.

The invention discloses a transformer substation-oriented multi-source heterogeneous data checking method and system. The method comprises the following steps of obtaining various types of data sources, executing a preliminary data cleaning process and outputting standardized data; aiming at database systems of different manufacturers, designing a customized migration tool for each database; extracting specific attribute information contained by the special domain analysis module by constructing the special domain analysis module; sequentially verifying the source database and the target database by adopting a progressive consistency verification strategy, and recording data difference information detected in each stage; a change rationality verification module is configured to analyze an SCD file of the transformer substation, and change rationality judgment is performed on difference items from a source database to a target database; performing unified modeling and graphical display on the obtained difference information through a difference data visualization module; according to the method, the data consistency and correctness in the upgrading and transformation process of the transformer substation monitoring system database are comprehensively verified, so that the stability and the operation reliability of the system are improved.

The invention relates to the technical field of medical images, in particular to a medical image intelligent detection and auxiliary diagnosis system based on deep learning, and the system comprises a data access module which is used for obtaining medical image data and clinical text data of a patient; the data fusion module is used for generating a focus feature vector and a text feature vector, and performing cross-modal alignment and fusion to generate a fusion feature vector; the diagnosis analysis module is used for executing focus detection, focus segmentation and focus classification tasks, generating a diagnosis result and generating a diagnosis label based on the diagnosis result; the decision generation module is used for mapping the generated execution result to a preset medical knowledge base and performing deep reasoning to generate an auxiliary diagnosis decision; the decision auditing module is used for performing confidence scoring on the auxiliary diagnosis decisions and selecting the auxiliary diagnosis decision with the highest confidence score as the final auxiliary decision; and the data visualization module is used for carrying out visualization processing on the auxiliary decision and the diagnosis result.

The invention discloses a rice seedling leaf age intelligent identification system based on a depth camera, and belongs to the technical field of agricultural intelligent equipment and machine vision. Comprising a monitoring point gridding path planning module, a mechanical arm cooperative positioning data acquisition module, an RGB-D data preprocessing module, a dynamic foreground seedling accurate extraction module, a leaf age recognition confidence evaluation module, a leaf age data visualization presentation module and an integrated control strategy feedback module. RGB color features and connected domain analysis are combined to optimize a mask, a front single seedling is accurately segmented, background interference is eliminated, the confidence coefficient is dynamically calibrated through a deep learning model and image quality features, texture definition and edge continuity features are combined to generate calibrated confidence coefficient, confidence coefficient evaluation is directly associated with an agricultural decision, and the accuracy of the agricultural decision is improved. The leaf age result is generated only based on reliable data, the personnel rechecking demand is reduced, and the decision-making efficiency is improved.

The invention discloses an automatic driving traffic accident intelligent analysis system based on sand table simulation, and relates to the technical field of vehicle automatic driving. The system comprises a sand table simulation scene construction module which is used for simulating a high-risk scene of an automatic driving traffic accident and providing a physical and digital twinborn combined experiment environment; the automatic driving data acquisition and perception module is used for acquiring vehicle sensor data in real time and realizing environment perception and behavior decision simulation; the traffic accident intelligent analysis core module is used for realizing accident cause analysis and responsibility determination based on multi-source data and a knowledge base; and the cloud control platform and data visualization module is used for monitoring sand table simulation data in real time and providing a visual interface and an interaction function. The system can simulate and analyze the performance of automatic driving in various complex traffic environments and perform analysis and prediction, the analysis and prediction accuracy is high, and the analysis effect is better.

The invention discloses a marine geological environment multi-dimensional data reconstruction and dynamic visualization mapping method and system, and belongs to the technical field of marine information technology and data visualization. In order to solve the problems that in the prior art, standard data asset structure is isolated, heterogeneous data deep fusion is difficult, and mass data visualization performance is bottleneck, the method mainly adopts the following technical scheme that standardized multi-source data is received, a data volume mapping rule is established, discrete observation data is reconstructed and fused into a unified and continuous three-dimensional data volume, and the three-dimensional data volume is obtained; and executing a three-dimensional space pattern recognition algorithm on the three-dimensional data volume to recognize a feature entity, and providing on-demand query and multi-resolution access services through a visual mapping interface. According to the method, efficient automatic modeling and high-performance interactive analysis of mass and multi-dimensional marine geological environment data can be realized.

The invention provides a method and system for displaying public funds based on multi-dimension and multi-granularity, and relates to the technical field of data visualization, and the method comprises the steps: obtaining multi-dimension data including fund positions, net value fluctuation and macroeconomic indicators, and carrying out the aggregation processing through a sliding window to generate asset distribution data. Extracting multi-dimensional features from the data to form an initial feature set, and organizing and constructing the initial feature set into a multi-granularity space by using a hierarchical structure; and reducing each layer of feature set based on a neighborhood relationship in the space to obtain key feature subsets, fusing the subsets, and inputting the subsets into a random forest model for processing to obtain an asset importance score. And finally, generating a three-dimensional display model by applying an instantiated grid technology based on the scoring data, and compressing model data through a spatial hash algorithm to realize overall visual display of the multi-dimensional and multi-granularity data of the public funds. According to the method, the visual display efficiency and definition of the hierarchical relationship of the complex fund data are improved.

In at least one aspect, a computer-implemented method includes: accessing, by an agricultural management system, first data from an operational database; accessing, by the agricultural management system, second data from a real-time data server; determining a metric based on the first data and the second data; generating a first graphical user interface (GUI) for display on a client device, where the first GUI includes at least one data visualization based on the metric; and adjusting, by the agricultural management system, a setting of a piece of equipment.

The invention relates to a geomechanical data visualization method, device and equipment and a medium thereof. The method comprises the following steps: acquiring original data containing rock mass structural characteristics and temperature and humidity environmental parameters, and completing grid division and load and displacement constraint boundary condition setting by adopting finite element analysis to obtain a rock mass stress distribution model; core mechanical parameter evolution of rock mass at different time nodes is simulated based on the model, and a dynamic stress distribution sequence is generated; identifying and marking stress overrun potential event association points through a threshold value, extracting a key time-space change trend, and inputting the key time-space change trend into the time-space dynamic model to obtain a risk prediction distribution diagram containing a risk level, a coverage range and an occurrence probability; and constructing a three-dimensional dynamic view by adopting visual rendering, analyzing a mechanical parameter full-cycle evolution path and geological event association mode, and outputting a three-dimensional dynamic result integrating multi-dimensional information. According to the method, the problems of static data presentation and event association deficiency in the traditional technology can be solved, and the scientificity and the high efficiency of geological engineering analysis are improved.

The invention discloses a real-time virtual environment view layout algorithm based on spherical space guidance. The algorithm comprises the following steps that an original view is acquired and preprocessed; abstracting into a circular structure and completely mapping to a constructed spherical view projection structure; weight analysis is carried out, a preset threshold value is compared, a high-weight standard view set and a low-weight standard view set are divided, and dynamic batch layout optimization processing is carried out on the high-weight standard view set; constructing a space pressure function field for the low-weight standard view set, and determining a target position by using a space pressure field guiding method; smooth movement from the current position to the target position is achieved through a Bezier curve interpolation method; and when the viewpoint or view angle change exceeds the threshold value, re-calculating the layout until the change amplitude is smaller than the threshold value, and generating a final layout. According to the method, the spherical space projection and the adaptive mechanical model are combined, the large-scale view layout is optimized, the method has the advantages of being efficient, stable and real-time, and the data visualization effect in the virtual environment is improved.

The invention discloses a building block report zero-code visualization dynamic design multi-terminal adaptation system and method, and relates to the technical field of data visualization and report generation. The method comprises the following steps: component templated multiplexing: generating a component template with a unique identifier by extracting complete configuration of a configured component, separating basic parameters from instance parameters by adopting a double-layer parameter structure, and maintaining a directed acyclic graph structure through a dependency tracking engine to realize batch synchronous updating; performing multi-terminal intelligent adaptation, constructing a terminal characteristic library to store different terminal parameters, setting adaptive rules for various components, and automatically adjusting the component size, layout and interaction mode by identifying an access terminal; and carrying out visual binding on the business rules, constructing business rule logic through a dragging operator, and establishing rule-component association mapping. According to the method, the component reuse rate is increased by 80%, the report development period is shortened by 70%, and an efficient, intelligent and easy-to-use complete solution is provided for enterprise-level zero code report development.

A method can include generating a visual group of datasets; receiving a visualization mesh that intersects at least two of the datasets; executing a shader using graphics hardware to generate values for the visualization mesh, where the values depend on data within at least one of the at least two datasets; and rendering a visualization to a display using the values.

The invention particularly relates to a patent data visualization system and method based on large model agent collaboration, and belongs to the field of data visualization. The system comprises a preprocessing module used for preprocessing a patent text; the natural language processing module is used for performing semantic analysis on the natural language query; the multi-agent cooperation module is used for outputting a visual file package through multi-agent cooperation; the data storage and retrieval module is used for storing patent data in a cold and hot layered architecture and supporting mixed retrieval; the user interaction module is used for providing a natural language input interface, rendering and displaying an interactive chart in the visual file package, and collecting user feedback data; and the adaptive optimization module is used for dynamically optimizing the chart type selection and generation strategy of the visual agent based on the user feedback data. The method uses the system to carry out patent data visualization. According to the method, full-process automation and dynamic optimization from natural language query to visual chart generation are realized.

The invention discloses an anti-resistance exercise training system for old people based on intelligent wearable equipment, and relates to the technical field. The problems that in the prior art, a dynamic action monitoring error correction mechanism is lacked, exercise intensity adjustment is not personalized and real-time, interaction and data feedback functions do not exist, and equipment portability and wearing adaptability are insufficient are solved. The system collects data in real time through the whole body position intelligent wearable device, corrects non-standard actions through the action recognition feedback module, dynamically regulates the intensity through the exercise intensity evaluation module, reduces the risks of muscle strain, cardiovascular burden and the like, takes standardized action guidance, personalized intensity adaptation and data visualization as the core, ensures target muscle activation, and improves the training efficiency. The training effect is quantified, the operation is simple, the use threshold is reduced through voice guidance, the boring feeling is relieved through personalized plans and summary reports, the training achievement feeling and compliance of the old people are enhanced, the muscle strength can be improved through whole body position training, and the anti-resistance exercise requirement of the old people is met.