605 results about "Dynamic visualization" patented technology

The invention provides an intelligent visual management method and system for enterprise big data. The method comprises the following steps: extracting a space-time association rule of an operation and maintenance report fault field and an equipment log error code, and generating a dynamic mapping data stream to drive a three-dimensional visual association topology; the method comprises the following steps: collecting cabinet vibration energy data, and synchronizing a highlight energy sudden increase area and error log entries according to a timestamp; dynamically distributing a vibration energy weight, and generating a risk probability matrix in combination with an error increment; fusing the time sequence characteristics and the physical topology path, constructing an abnormal event timestamp graph, and marking a fault propagation chain; and based on the map density gradient and the causal association strength, superimposing and rendering the penetrating thermodynamic diagram, associating topology, a fault chain and an equipment structure, and adaptively adjusting the color gradation highlighting abnormal region. According to the technical scheme provided by the invention, the multi-source fault correlation analysis efficiency is improved, and the abnormal risk is dynamically, visually and accurately positioned.

An example operation may include one or more of displaying a report on a user interface of a software application on a user device, listening to a call between a user on the user device and a different user on a second user device that is connected to the user device via a network, executing a generative artificial intelligence (GenAI) model based on content that is heard during the call and content within the report displayed on the user interface to identify content within the displayed report that is discussed during the call, and modifying the displayed report to emphasize the identified content within the displayed report on the user interface.

The invention belongs to the technical field of fishery resource informatization management and ecological prediction, and particularly relates to a dynamic prediction method of a resource habitat dynamic prediction system based on multi-source heterogeneous data fusion, and the method comprises the steps: a multi-source heterogeneous data collaborative collection and standardization processing module synchronously collects cross-regional data, and generates a time-space aligned standardized data set; the multi-modal habitat adaptability evaluation and prediction model is used for receiving the standardized data set as input, constructing environmental, biological and social modalities based on multi-source fusion data, and generating a habitat adaptability prediction result; the three-dimensional dynamic visualization and decision support platform is used for receiving the habitat suitability prediction result and generating a habitat thermodynamic diagram, a resource abundance gradient and an environmental parameter dynamic visualization display and decision under multiple spatial and temporal scales; according to the method, an international data collaboration mechanism, an ecological niche model optimization algorithm and a lightweight visualization engine are subjected to system-level integration, and an engineering solution is provided for biological resource protection of a sea area.

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 relates to the technical field of coal mine safety monitoring, and discloses a coal mine safety data comprehensive analysis and early warning system which comprises a data integration module, a three-dimensional visualization module, a risk assessment module, a linkage control module, a model training module and a central processing unit and can further comprise a decision support module, a storage cluster and a communication gateway. The data integration module constructs a multi-source heterogeneous data acquisition channel and performs dynamic topology modeling; the three-dimensional visualization module dynamically renders the monitoring data based on the space-time reference axis; the risk assessment module generates a danger situation map through space-time correlation analysis; the linkage control module establishes a multi-level response mechanism; the model training module optimizes the risk prediction model; and the central processing unit schedules each module to operate. According to the system, integrated analysis, dynamic visualization, risk prediction and cross-system linkage disposal of coal mine safety data are achieved, and the intelligent level and emergency capacity of coal mine safety monitoring are improved.

The technology relates to systems and methods for generating context-aware, dynamic visualizations. In an example, a method includes extracting a dynamic context signal; based on the dynamic context signal, retrieving a first visualization; causing a display of the first visualization as part of an application user interface; at an expiration of a refresh period, extracting an updated dynamic context signal; based on the updated dynamic context signal, retrieving a second visualization; and replacing the first visualization with the second visualization as part of an application user interface.

The invention relates to the technical field of greenhouse gas monitoring, in particular to a greenhouse gas collaborative monitoring and analysis platform. According to the technical scheme, the system comprises a cross-modal data fusion module, a causal reasoning analysis engine, a holographic dynamic visualization system, a distributed edge computing node and a self-adaptive decision optimization module, and the cross-modal data fusion module is used for integrating satellite remote sensing data, a ground sensor network, unmanned aerial vehicle mobile monitoring data and industrial Internet of Things emission source data in real time; a dynamic weight distribution algorithm is adopted, the multi-source data fusion weight is automatically adjusted according to environmental parameters, and a space-time continuous greenhouse gas concentration field is generated; a causal reasoning analysis engine is based on a hybrid architecture. According to the method, data privacy is guaranteed and delay is reduced through multi-source data fusion, causal reasoning analysis, holographic visualization and edge calculation, and comprehensive and accurate monitoring, scientific prediction analysis, efficient decision execution and risk prevention and control of greenhouse gas are realized based on decision optimization of dynamic games and block chain smart contracts.

The invention provides an emergency event visualization cooperation method and terminal equipment, and the method comprises the steps: obtaining a historical monitoring data set of an emergency event in a target region, carrying out the preprocessing, and generating a standardized event feature set; training a time sequence prediction model according to the dynamic environment parameters to obtain an event evolution prediction model; and constructing a geographic region matching model based on the static geographic parameters, and generating a visual layer template associated with the target region. And collecting a current environment data flow of the target area in real time, performing classification through the event evolution prediction model to obtain an event classification result, and calling a corresponding visual layer template from the geographic area matching model according to the event classification result. And fusing the diffusion path, the intensity level and the called visual layer template in the event classification result to generate a dynamic visual instruction set, and rendering and outputting an emergency event evolution situation map through an interactive interface. According to the invention, the timeliness of emergency response and decision reliability can be improved.

The invention discloses a meteorological service center data visualization and interaction platform, and particularly relates to the field of meteorological data visualization, which comprises a multi-source heterogeneous data acquisition and preprocessing module, a space-time fusion and data enhancement module, a distributed storage and intelligent index module, a dynamic visualization module, an intelligent decision and early warning module and an interaction module. According to the invention, multi-source meteorological data are collected through an API and a protocol, and wavelet transform noise reduction processing is carried out by using an edge computing node; carrying out space-time alignment and fusion, and filling missing data with LSTM; dynamic visualization and interaction are realized by using WebGL (Web Graphics Library) and ARCore / ARKit; the WRF and the Transform are integrated to generate early warning information, and decision suggestions are pushed through a natural language interface; according to the method, the WRF numerical model and the Transform algorithm are combined, accurate meteorological early warning is provided for the user, meanwhile, the geographic space index is constructed based on the GeoHash algorithm, efficient geographic space query and data retrieval are achieved, a real-time feedback mechanism and a multi-dimensional visual view are provided, and the operation process and experience of the user are optimized.

The invention discloses an intelligent substation safety measure checking method and system, and the method comprises the steps: obtaining a secondary system topological structure, equipment information and historical safety measure ticket data of a substation, and constructing a quaternary knowledge graph; according to the quaternary knowledge graph, extracting multi-modal features of the maintenance task and identifying the type of a maintenance scene by combining a memory guide reflection decision reasoning mechanism, optimizing a rule reasoning process through a distributed guide local search algorithm, and generating an optimal safety measure operation set for a specific maintenance scene; automatically identifying a correlation loop and determining a minimum safety isolation range through a memory guide decision reasoning mechanism, dynamically generating a minimum safety operation set according to the real-time state of the equipment, and adaptively adjusting operation steps; and an operation dependency relationship model is constructed in combination with unwrapping variational multi-graph representation learning and a distributed guide local search algorithm, and operation sequence compliance verification, risk level assessment and dynamic visual early warning are realized. According to the invention, accurate formulation, dynamic adjustment and risk early warning of safety measures of the intelligent substation are realized.

A system and method for dynamically visualize and modify user authority and security resource edge based on access behaviors in a cloud computing environment. The method provides a new access control perspective to ensure the credibility of database object usage patterns, build clearer and explicit security data consumption mode for data usage requests, and guide tenants to have a more comprehensive understanding and concise use. Processing components and method are configured to gather data and analytics including collecting data resource and database object usage tagging both resources and users with security level by machine learning and building an access model for each role. The method uses graph modeling with created, trained access patterns for users protected resources and produces in-memory implicit sub-groups for users with similar access requirements and limits their resource accesses according to their history behaviors. Further provided are outlier activities prediction and in-real time access authorization modification.

The invention discloses a construction method and system for a coal mine geological transparent working face, and relates to the technical field of intelligent mine and geological information, and the method comprises the following steps: collecting and preprocessing visible light, near-infrared images and point cloud data, extracting texture, reflectivity, curvature and density features, and calculating the texture, reflectivity, curvature and density features; the method comprises the following steps: constructing a three-dimensional structure reconstruction model, a rock stratum physical property inversion model and a geological stress prediction model, generating a three-dimensional geometric structure coordinate set, a rock stratum moisture content matrix and a vertical stress distribution matrix of each region, setting an anomaly judgment condition, outputting three-dimensional coordinates of an abnormal region, carrying out graded early warning, synthesizing a three-dimensional visual image, and predicting the geological stress. And holographic transparent expression of the working face geological state is realized. According to the method, centimeter-level three-dimensional reconstruction of the geological transparent working face of the coal mine, precise positioning of a hidden water-containing area and a stress abnormal area and construction of a full-attribute dynamic visual scene are achieved, the timeliness and accuracy of early warning of disasters such as water inrush and rockburst are remarkably improved, real-time geological decision support is provided for intelligent mining, and safe and efficient production is guaranteed.

The invention relates to the technical field of surveying and mapping information processing, and discloses a surveying and mapping information intelligent analysis and visualization system based on the Internet of Things. According to the system, a building space data acquisition terminal acquires geometric feature point cloud and environmental parameters of the surface of a building structure in real time through distributed Internet of Things nodes; the multi-source heterogeneous data fusion engine performs space-time alignment processing on the geometric feature point cloud to generate a building total-factor topological skeleton with an absolute coordinate system; the three-dimensional topological relation reconstruction module is used for extracting a spatial constraint relation of building components according to the topological skeleton and establishing a hierarchical building information model capable of being edited in a parameterized manner; and the dynamic visual rendering platform is used for generating a multi-scale spatial index based on the hierarchical building information model, and driving real-time light and shadow effects and interactive sectioning analysis. According to the system, full-process automatic processing and dynamic visualization of building surveying and mapping data are realized.

The invention relates to the technical field of smart city data visualization, in particular to a visual smart city display method, which comprises the following steps: S1, collecting traffic flow data, energy consumption data, environment monitoring data and city three-dimensional geographic information data in real time; s2, constructing a reference three-dimensional model with a space coordinate system; s3, mapping the data into a dynamic data layer with a timestamp; s4, superposing the dynamic data layer to the reference three-dimensional model according to space-time coordinates to generate a fused dynamic scene; s5, receiving deduction parameters input by a user, and calculating a corresponding evolution path in real time; and S6, converting the evolution path into a dynamic visualization effect, and outputting the dynamic visualization effect to a display terminal. According to the invention, through integrated processing of multi-source dynamic data fusion, space-time path deduction and visual output, continuous expression and dynamic evolution display of the operation state of the smart city are realized.

The invention relates to the technical field of power systems, and discloses a multi-scale intelligent load prediction and dynamic visualization display method and platform, and the method comprises the steps: determining a prediction period, and dynamically adjusting the prediction period; analyzing the space-time dependence of the power grid region by using the space-time diagram neural network model; determining a combined prediction model according to the adjusted prediction period, and dynamically adjusting the weight of each prediction model based on reinforcement learning and quantum heuristic optimization technologies; and performing intelligent load prediction by using the combined prediction model, fusing prediction results to obtain a final prediction result, and performing decision analysis and visual display. According to the method, the accurate and comprehensive load prediction service is provided for the user by integrating multiple algorithm combination prediction and weighted fusion results, and the prediction result is displayed in real time through a dynamic visual platform combining a real-time prediction panel, historical trend analysis, algorithm comparison optimization and a decision support report.

The invention discloses an intelligent data stream processing system based on Flink and an implementation method thereof, and belongs to the technical field of distributed streaming data processing, and the implementation method comprises the following steps: a data source access layer uniformly accesses multi-source data; the entity monitoring layer captures service entity change in a non-intrusive manner based on JPA, generates a standardized message body and asynchronously delivers the standardized message body to double channels; the unified event model layer maps the data into a standardized event and expands the standardized event; the Flink stream processing engine layer is used for complex event processing, state management and window calculation, and supports declarative pipeline definition and dynamic construction; the anomaly detection layer performs multi-dimensional anomaly detection; the distributed task scheduling layer schedules tasks according to a DAG model, and realizes load balancing through hotspot splitting and state transition; and the result storage and visualization layer adopts a cold and hot separation strategy to store data, and provides a dynamic visualization interface. The real-time performance, the consistency and the intelligent level of data processing are remarkably improved, and the development and maintenance cost is reduced.

The invention discloses a visual information monitoring method and system based on talent management, and relates to the technical field of talent management, and the method comprises the steps: collecting and preprocessing talent data, extracting talent features, carrying out dynamic label updating, and constructing cross-industry skill mapping based on dynamic labels. And generating a talent portrait based on a mapping result, predicting a talent loss risk, optimizing the talent portrait based on a prediction result, and performing talent recommendation. According to the method, semantic features in dynamic data are accurately extracted by introducing a BERT model and a dynamic exit mechanism and combining distillation optimization and a multi-level feature fusion method, cross-industry skill mapping based on a knowledge graph is constructed, the ability of versatility analysis and migration path modeling on skill nodes is improved, and the method is suitable for mass production. Through organic combination of a dynamic instrument panel and three-dimensional display, panoramic dynamic visual monitoring of talent distribution, post matching and industry migration is realized, and the intelligent level of an enterprise in talent management is remarkably improved.

The application relates to a dynamic visualization method and device for earthquake disasters. The method comprises: acquiring initial point cloud data of buildings and scenes in a target area; acquiring shake displacement data varying with time of the buildings by simulating an earthquake excitation on the buildings and the scenes; performing voxel downsampling and point cloud segmentation and extraction on the initial point cloud data to determine a ground point cloud and a point cloud of each building; updating in real time coordinates of each point of the point cloud of each building according to the shake displacement data; and rendering in real time the ground point cloud and the coordinates of each point of the point cloud of each building to generate a dynamic visual image for displaying. Accordingly, seismic scenes of regional buildings are presented more truly and visually, thus improving the visualization effect.

The invention relates to the technical field of reservoir dam safety monitoring, and discloses a reservoir dam siltation dynamic monitoring and early warning system. Multi-dimensional sensing node arrays of the system are arranged at key positions of a dam body structure and a reservoir area, and sediment thickness distribution data, water flow velocity field data and sediment concentration gradient data are synchronously collected. And the edge computing node receives the original monitoring data, executes data cleaning and space-time alignment processing, and generates a standardized siltation feature data set. And the cloud analysis platform receives the data set, calculates a deposition evolution trend matrix through a space-time coupling prediction model, and outputs a reservoir area deposition risk level distribution map. And the dynamic visualization engine analyzes the risk level distribution map, generates a three-dimensional dynamic deposition situation model, and marks the space coordinates of the abnormal deposition area. And the early warning decision center generates a graded early warning instruction set according to the space coordinates of the abnormal region, and triggers a corresponding emergency response strategy.

The present invention relates to the technical field of bridge structure monitoring, and specifically to a bridge disease monitoring method based on an inspection robot, comprising: obtaining a BIM model of a bridge, collecting GIS data of a location of the bridge and establishing associations with elements in the BIM model, and integrating the BIM model and the GIS data into a BIM+GIS fusion model; configuring a sensor and a communication module in the inspection robot, building a Web platform and establishing a communication connection with the inspection robot; when the inspection robot inspects the bridge, real-time data is collected through sensors, and the collected bridge structure data and position data of the inspection robot are sent to the Web platform; the Web platform receives and parses the position data, searches for a component corresponding to the position data in the BIM+GIS fusion model according to the position data, and maps the real-time position of the inspection robot to the corresponding component, thereby realizing accurate positioning and dynamic visualization of the position of the inspection robot.

The invention discloses a three-dimensional energy carbon data visualization terminal and a use method thereof. The visualization terminal comprises a data acquisition module, a data processing module, a visualization display module, an interaction control module and a communication transmission module. The data acquisition module acquires a voltage signal, a current signal and a carbon emission signal of the park power equipment in real time; the data processing module performs energy-carbon coupling analysis on the original data to generate an analysis result; the visual display module dynamically displays the energy and carbon monitoring data, the electric power parameter waveform change trend, the incidence relation between energy consumption and carbon emission and abnormal event information; the interaction control module receives a user instruction and adjusts display content; and the communication transmission module performs data interaction with a remote management platform. Through multi-module cooperation, real-time acquisition, coupling analysis and three-dimensional dynamic visualization of energy and carbon data are realized, comprehensive energy efficiency and carbon efficiency management support is provided for an industrial park, and the decision efficiency of energy optimization and carbon emission regulation is improved.

The invention discloses a dialogue type GIS visual scene generation method and system based on an LLM large model. The method comprises the steps that S1, an AI intelligent dialogue processing module receives and analyzes a natural language instruction input by a user; s2, the AI capability service module carries out standardized parameter packaging on the key information through an LLM large model; s3, analyzing the input parameters by the GIS capability service module, judging whether the scene code is empty or not, if yes, executing a step S4, and if not, executing a step S5; s4, the GIS capability service module judges whether latitude and longitude coordinates are contained in the place or not; s5, the GIS capability service module implements corresponding operation according to the operation type; s6, the GIS capability service module stores the created or updated scene; and S7, the AI intelligent dialogue processing module answers the question and presents the map thumbnail of the created or updated scene. According to the invention, full-link intelligentization of natural language-geographic analysis-dynamic visualization is realized through a modular architecture driven by LLM.

The present invention provides an automated control system and method for a mine ventilation system. The system comprises a precision sensor for key tunnel ventilation parameters, an automatic analysis and adjustment system for mine ventilation conditions, and a control feedback system for mine ventilation structures. The precision sensor for key tunnel ventilation parameters is used for real-time acquisition of key tunnel ventilation parameters and structure ventilation parameters of the mine ventilation system; a network solution simulation module is used for performing network solution on a three-dimensional dynamic visualization model to obtain the solved ventilation parameters; a scheme optimization decision module is used for determining an initial control scheme based on key tunnel ventilation parameters, structure ventilation parameters, and connection tunnel ventilation parameters; and based on the optimized three-dimensional dynamic visualization model, the initial control scheme is optimized to obtain a control decision scheme; and a mine ventilation structure control feedback system is used for receiving the control decision scheme and controlling ventilation equipment to perform ventilation adjustment.

The invention relates to the technical field of geographic information data, in particular to a GIS-based CRM customer ecosphere dynamic visual management system, which comprises the following steps: acquiring geographical location information, transaction data, customer relationship data and time sequence data of customers; constructing a customer ecosphere space model to analyze the geographic position information and the customer relationship data, obtaining space association strength and business association strength among customers, and generating a dynamic evolution matrix; performing real-time spatial clustering analysis on the transaction data, and identifying a client distribution hotspot area; based on the time sequence data and the geographic position information of the customer, constructing a customer space-time trajectory model, analyzing a space-time behavior pattern of the customer, and obtaining a space-time trajectory prediction result including a customer periodic behavior pattern and a space activity trend; and carrying out three-dimensional rendering on the spatial association strength, the business association strength, the customer distribution hotspot area and the spatio-temporal trajectory prediction result to obtain a three-dimensional visual interface.

The invention discloses a knowledge-guided visual simulation method for a railway bridge construction process, belongs to the field of railway bridge construction, and solves the problems that the railway bridge construction process in the prior art relates to many elements, is difficult in relation capture, is not clear in behavior state description, is continuously iterated and updated along with the promotion of the construction process, is complex in environment change, and is poor in reliability. And the incidence relation between the bridge main body model and the visual simulation environment is difficult to establish. The method comprises the following steps: acquiring railway bridge construction data including GIS data, field data and construction data; constructing an entity-process-behavior three-domain associated railroad bridge construction scene knowledge graph based on the obtained railroad bridge construction data; and performing knowledge-guided dynamic visual simulation of the railway bridge construction process based on the railway bridge construction scene knowledge graph. The method is used for visual simulation of the railway bridge construction process.

The invention relates to the technical field of supply chain management, in particular to a digital visual management system and method applied to a building material supply chain. The method comprises the following steps: acquiring real-time position data, material attribute data and time sequence node data; performing data preprocessing and integration on the real-time position data, the material attribute data and the time sequence node data to obtain standard building material supply chain data; obtaining a construction drawing; basic building materials of the standard building material supply chain data are extracted based on the construction drawing, wherein the basic building materials comprise concrete, reinforcing steel bars and building blocks; building pouring abnormity monitoring is carried out based on the concrete, the steel bars and the building blocks, and pouring abnormity monitoring data is generated. Through multi-source data integration, ternary coupling analysis, scheduling optimization and three-dimensional dynamic visualization, the problems of information island, scheduling conflict and low management efficiency of the building material supply chain are solved, and intelligent, efficient and transparent management of the supply chain is realized.

The invention provides an industrial T-MOD module working state visualization method and system, and the method comprises the steps: carrying out the time dimension preprocessing and multi-dimensional feature analysis of original operation data collected by a T-MOD module, and generating a multi-dimensional dynamic feature vector, the method comprises the following steps: acquiring a multi-dimensional dynamic feature vector of a T-MOD module, constructing a digital twin three-dimensional model corresponding to the T-MOD module according to the multi-dimensional dynamic feature vector, inputting the multi-dimensional dynamic feature vector into a pre-trained large language model, performing semantic recognition and potential anomaly analysis on the running state of the T-MOD module, and generating structured analysis data; and generating a three-dimensional dynamic visual interface in the digital twin three-dimensional model according to the structured analysis data. According to the scheme, the working state of each component of the T-MOD module can be detected in real time through the three-dimensional dynamic visual interface, the manual inspection cost is effectively reduced, and the fault detection efficiency is improved.

The invention discloses a power distribution area fluctuation load early warning method and system, and relates to the technical field of power distribution network intelligent monitoring and control. The method comprises the following steps: constructing a digital twinborn model synchronous with an operation state, carrying out time domain and frequency domain conjoint analysis on a digital twinborn data set, extracting a power amplitude change rate and a phase jump index, and generating a load fluctuation vector; determining an adaptive threshold based on the statistical characteristics of the load fluctuation vector and historical load distribution, and generating a primary early warning signal when the fluctuation exceeds the limit; using a distributed collaborative analysis algorithm to identify a dominant load source and an imbalance category; performing correlation analysis on the identification result of the dominant load source and the primary early warning signal to generate comprehensive early warning information; and the comprehensive early warning information is output to a power distribution area monitoring platform, so that dynamic visualization and intelligent regulation and control are realized. According to the method, real-time identification and active early warning of the fluctuation load of the power distribution area can be realized, and the safety and the intelligent level of system operation are improved.

The invention discloses an intelligent data question answering and visualization system and method for leader decision making, and relates to the technical field of artificial intelligence, and the system comprises a knowledge base unit, an intelligent question answering module, a dynamic visualization unit, a quality control unit and a performance optimization unit. According to the method, the customized knowledge base is constructed through the knowledge base unit, cross-modal alignment and layered long context processing are weakly supervised during data fusion, the defects that cross-modal data labeling cost is high and long context processing is redundant can be overcome, and an interaction platform of the knowledge base and a data engine in the knowledge base unit is constructed through the intelligent question and answer module; the model mixing module mixes an NLP model, constructs a combined architecture of an LLM + field fine tuning model, ensures understanding of natural languages and intention analysis precision, introduces an online expert error correction mechanism, and reduces misjudgment during question answering, so that the processing capacity of long texts or complex logic can be ensured, missing of key information in question answering is avoided, and then the answering quality is ensured.

The invention relates to an energy digital metering monitoring and tracking method and system, and relates to the technical field of energy digital management, and the method comprises the steps: deploying a plurality of energy metering terminals in a physical energy network to collect energy consumption data in real time, and executing local energy carbon emission metering through an embedded carbon emission calculation assembly; uploading a metering result to a cloud monitoring center, and constructing a virtual mapping model based on a digital twinning technology in combination with topological information of a physical energy network; synchronizing the measurement data to the virtual mapping model, and performing visual tracking on the measurement data in combination with topology analysis and a particle tracking technology to generate an energy flow dynamic visual map; carbon emission footprint traceability tracking is carried out according to the atlas, and energy digitization metering is realized based on a traceability result. According to the invention, the problems of insufficient energy metering precision and incomplete carbon footprint traceability caused by the lack of dynamic visual tracking means due to the fact that differential adaptation is not carried out in combination with metering characteristics in traditional energy metering monitoring are solved.