76 results about "Map visualization" patented technology

The invention relates to the technical field of warehouse-in and warehouse-out management, in particular to a second-hand car warehouse-in and warehouse-out management system and method. The system comprises a vehicle RFID tag module, an intelligent electronic price tag module, a warehouse-in management module, a warehouse-out management module, an inventory monitoring and alarming module, a multi-point RFID positioning network module and an inventory map visualization module, and a unique encrypted RFID tag can be configured for each second-hand vehicle; binding an intelligent electronic price tag for each second-hand vehicle, and receiving verification to generate a verification result; collecting label information when the vehicle enters the parking lot; the label information is verified when the vehicle leaves; receiving the verification result of the intelligent electronic price tag and the vehicle in-library data of the database to lock the position of the abnormal vehicle; dense RFID reader nodes are arranged in the market to collect and output positioning data; and receiving the positioning data and the vehicle state information, generating a real-time inventory distribution map, and providing a scheduling and site planning decision basis for a manager. The scheduling and planning efficiency of managers can be improved.

The invention relates to the technical field of shopping, and discloses a map shopping method based on AI voice interaction. Through deep fusion of AI voice interaction and a map visualization technology, the user experience and the operation efficiency of a geographic shopping scene are remarkably improved. According to the method, a real-time association system of the map POI and the commodity inventory is constructed, multi-modal interaction of voice instructions, dragging operation and cross-shop settlement is supported, and intelligent complementation of fuzzy instructions and dynamic distribution route optimization are realized by adopting BERT semantic understanding and a Q-learning path planning algorithm, so that the order response speed is improved, and the distribution distance is optimal; voiceprint DTW verification and Redis distributed inventory management are integrated, and real-time inventory scheduling in a 3-kilometer business district is realized while payment security is guaranteed; full-link state visual management is established through SSE push and WebSocket positioning technologies, and closed-loop experience of'search-purchase-payment-tracking 'is formed in combination with a thermodynamic layer recommendation system, so that operation is convenient.

The invention relates to a map visualization rendering method and system based on a WebGPU engine and computer equipment, and the method comprises the steps: obtaining map data in a unified format; inputting the map data into a rendering layer, and performing layer division on the map data according to spatial levels and element types to obtain multiple pieces of layer data; distributing an independent rendering thread for each layer data; performing block processing on the map data to obtain picture blocks with pyramid structures; and calling a corresponding rendering thread in the current view range and the scaling to load the corresponding picture block for rendering display. By means of the method and device, the problem that the map visualization rendering performance is poor is solved.

Embodiments described herein relate to systems and methods for mapping molecules into interfaces. An example interface includes a visual interface having a map visualization. Example molecules include proteins, or any protein-like molecules or fragments thereof such as antibodies, antigens, proteins, lectins, receptors. Embodiments described herein relate to systems and methods for mapping molecules into interfaces by processing data using dimensionality reduction to generation representations of molecule maps (e.g. map visualizations).

The invention provides a geological map three-dimensional visualization method and system based on a database technology, and belongs to the field of geological map visualization. The method focuses on geological map resources, deeply fuses spatial information and attribute information of the geological map, designs a geological map three-dimensional coordinate system based on geological age strata, designs a geological map three-dimensional space data and attribute data storage structure, and provides a relatively effective solution for multi-modal geological resource association. The geological map resources and associated data thereof are systematically stored and managed through a database, the geological map resources are standardized and efficiently integrated, and the innovative purpose of effectively supporting true three-dimensional visualization expression and analysis of geological elements is achieved by relying on a three-dimensional visualization platform. The geological map three-dimensional visualization method based on the database technology comprises the following steps: step (1), data and association thereof; step (2), data processing; step (3), database design; step (4), application; multi-modal geological data is stored based on a database, and a geological map three-dimensional visualization platform is built in combination with a three-dimensional visualization engine.

A system includes a processor that is configured to detect occurrence of a disaster, activate a plurality of unmanned aerial vehicles and collect image and video data of a disaster-affected area, analyze the collected image and video data and generate a damage assessment as a three-dimensional map, visualize the generated three-dimensional map and distribute countermeasure instructions, receive information from residents of shelters and rescue workers, and extract important information by natural language analysis, and determine rescue activity instructions and support goods transport routes based on the extracted information.

The invention discloses a power distribution area load state monitoring method and system based on stereo portrait analysis, relates to the technical field of urban power grids, and effectively improves the positioning precision and response speed of a load fluctuation area by introducing a three-dimensional image reconstruction and dynamic partitioning mechanism; a graph neural network and space-time long-short-term memory network modeling method is combined, so that the trend perception capability of the load state evolution process is enhanced; further, multi-source fusion recognition of abnormal behaviors is realized through association matching of the image change track and the load feature sequence, and the monitoring accuracy and sensitivity are effectively improved; based on risk index assessment and a map visualization expression mode, an abnormal area positioning result is visual and transparent, and intelligent early warning and decision assistance are supported; the method has the advantages of high data fusion capability, high risk identification precision, high visual interactivity and the like, and the intelligent and practical level of load state monitoring of the power distribution area is remarkably improved.

The invention discloses a truck footprint map visualization method and system based on ETC passing data, and belongs to the technical field of visualization. The method comprises the following steps of: constructing a space coordinate passing record set by acquiring an original passing record, a toll station number table, a cost statistical table, a passing frequency table and a payment conservation record table of a truck ETC (Electronic Toll Collection), and calculating a continuity weight; generating a complete track data set; constructing a lightening node and a coverage area; constructing a lightening result set of the site layer and the region layer; performing layered color assignment on the state value of each lightening node in the lightening result set according to a continuous weight; constructing a time comparison panel; constructing a multi-dimensional information presentation result set; calculating a comprehensive achievement score, and mapping the comprehensive achievement score to the lighting result set; constructing an achievement progress set; the method achieves the precise restoration and dynamic display of the track of the truck, and has the advantages of being high in real-time performance, rich in visualization effect and comprehensive in evaluation dimension.

The embodiment of the invention discloses a power grid map visualization method, electronic equipment and a storage medium, and relates to the technical field of electric power, and the method comprises the steps: responding to a current map viewing operation of a user, and determining a current visual field range based on the current map viewing operation; determining aggregated visual points of interest and non-aggregated visual points of interest in the current field of view based on the spatial index; the spatial index is obtained by grouping and constructing a plurality of interest points based on attribute information of the plurality of interest points in a preset area; determining attribute information of representative points of the aggregated visual interest points in the same group, determining preset aggregated rendering attribute information and the attribute information of the representative points as rendering attribute information of the corresponding representative points, and performing instantiation based on the rendering attribute information of the representative points to obtain aggregated instances of the corresponding representative points; and a rendering engine is used for carrying out batch visual rendering on the aggregated instances of the representative points and the individual instances of the non-aggregated visual interest points, so that the requirement of a power grid scene on large-scale space object visualization is met.

The invention provides a multi-nozzle jet flow uniformity determination method based on vision, and relates to the technical field of thick plate hot rolling and computer vision. According to the method, key frame extraction and preprocessing are carried out on collected video data; jet region identification is carried out by using an image segmentation technology, and density reference values are calculated pixel by pixel for the identified region; designing an index for measuring the jet flow uniformity according to a density reference value and supporting thermodynamic diagram visualization and analysis; through a mode of combining visual image processing and linear calibration, efficient and accurate quantitative evaluation on the jet flow uniformity of the multiple nozzles is realized. Moreover, the method can be realized through laser jet visualization software developed on the basis of a Python language, necessary array acceleration operation is carried out in combination with a Cupy library, the calculation speed of a single 1080 * 720-pixel image is smaller than 800 ms, and the requirements of actual industrial deployment and real-time detection are met.

The invention discloses a camera quick calling and visualization method based on natural language understanding, and relates to the technical field of video monitoring and artificial intelligence crossing. Comprising the steps that S1, a full-amount camera database is constructed, S2, a camera space retrieval interface is provided, and S3, a map visualization front end is constructed; s4, providing an address-coordinate conversion service; s5, local privatization deployment: deploying a camera space retrieval interface, a front-end static resource and a large language model mirror image in an intranet GPU server; s6, constructing a large model knowledge newly establishing a knowledge base table Knowledgeprompt in the model mirror image for writing data, and constructing the large model knowledge base, and S7, receiving a query demand of a user for inputting a natural language in a dialog box; s8, performing semantic understanding, and calling an interface to return data; step S9, automatically dotting the map; and S10, playing the video stream as required.

The invention discloses a logistics positioning method for an intelligent port, and particularly relates to the field of dynamic map visualization. Arranging high-precision control points in the harbor district, and collecting first coordinates and second coordinates to construct a control point data set; adopting a weighted least square method to fit and generate seven-parameter coordinate transformation models corresponding to the plurality of areas; generating a fine tuning parameter group through the prediction model, and combining the fine tuning parameter group with the seven-parameter model to form an adaptive coordinate transformation model; converting the collected first coordinates into corrected second coordinates in real time, and synchronously mapping the corrected second coordinates to a digital harbor district map system to realize dynamic visualization and scheduling linkage of the target logistics object; the stability and environmental adaptability of the harbor area positioning system are improved, and the method is suitable for unmanned transportation, automatic scheduling, safety supervision and other application scenes in intelligent harbors.

The invention provides a client map drawing method and device and electronic equipment. The method comprises the following steps: acquiring a gray scale grid map file of a robot and a corresponding metadata file; based on analysis parameters in the metadata file, analyzing the gray grid map file to obtain map structure data; converting the map structure data from a robot map coordinate system to a terminal screen coordinate system based on coordinate parameters in the metadata file; and calling a custom drawing interface oriented to the native view component, executing drawing of a plurality of drawing layers based on the map structure data under the terminal screen coordinate system and user editing operation, and superposing the plurality of drawing layers to generate a pixel-level map to be displayed on a client interface. By adopting the method and the device, the system resource consumption can be effectively reduced while the map visualization precision is ensured, and the lightweight map drawing requirement of the client is met.

The present invention relates to the field of cyberspace surveying and mapping technology, and in particular to a method and system for visualizing a cyberspace entity map in collaboration with a support library. The method comprises: step 1: constructing a cyberspace support library; wherein the network support library comprises a model library, a symbol library, a style library, and a template library; step 2: constructing a cyberspace entity node graph based on the model library and performing preprocessing to obtain a cyberspace basic node graph; step 3: configuring symbols for the cyberspace basic node graph based on the symbol library to generate a cyberspace optimized node graph; step 4: bundling network edges of the cyberspace optimized node graph based on the model library to generate a cyberspace data graph; and step 5: overlaying the cyberspace data graph with a basic geographic information base map layer based on the template library to obtain a cyberspace entity map.

The present application belongs to the technical field of investment precision casting, and particularly relates to a turbine blade precision casting stress prediction system and method based on digital twinning. The system comprises a client for realizing sensor data acquisition and visual rendering in the turbine blade precision casting process; a server for realizing training on stress field finite element simulation data to obtain a proxy model; the client and the server realize data connection and information interaction through Socket communication to jointly constitute a digital twinning model of the turbine blade; and the digital twinning model is updated and optimized by using the sensor data collected by the client. Stress cloud map visualization is realized by using Unity3D, and the computer real-time rendering overhead is reduced based on the RBF interpolation method to solve the problems of real-time stress measurement difficulty and visualization impossibility in the turbine blade precision casting process. Compared with the average absolute error of 435.42 MPa of the finite element simulation stress prediction, the average absolute error of the present application is 97.05 MPa, which can effectively reduce the error and improve the prediction accuracy.

This invention relates to low-altitude security in petrochemical plant areas, specifically to a method and system for creating a three-dimensional safety map of petrochemical plant areas. The method involves multi-level grid subdivision of the petrochemical plant area based on GeoSOT, matching grid accuracy according to target size, and generating a unique BeiDou grid code for each grid cell. Multi-source data is unified to the BeiDou grid code spatiotemporal reference, an error compensation model based on environmental perception is established to suppress multipath interference, and multi-source data fusion is performed. The grid status is dynamically updated, partially updated, and version-managed to achieve real-time updates and historical backtracking of the airspace situation. Target threat assessment is conducted, and countermeasure resources are scheduled for rapid countermeasures against threatening targets. A three-dimensional map visualization rendering is performed, intuitively presenting the airspace situation, target trajectories, and countermeasure equipment status. This invention effectively overcomes the shortcomings of two-dimensional control, such as airspace blind spots, insufficient positioning accuracy in complex environments, inability to achieve three-dimensional fusion of multi-source data, and low efficiency in dynamic control response.

The invention discloses a multi-mode spatio-temporal data format GSS rendering method, a rendering engine, equipment and a medium. The method comprises the following steps: constructing story information, story animation and story element data; storing the story information, the story animation and the story element data as a multi-mode spatio-temporal data format GSS; on the basis of story logic, calling GSS data, and using a rendering engine to render and express a story; when the stories are expressed, base map elements in the story elements are visually presented in a map mode. According to the method, efficient storage, rapid retrieval and ordered management of story-related multi-modal data are realized by designing a multi-modal spatio-temporal data format specially adapted to story logic; according to the technical scheme, a rendering engine matched with the multi-modal spatial-temporal data is researched and developed, the multi-modal spatial-temporal data is accurately analyzed and rendered on the basis of a map, and dynamic visual presentation and interactive operation of story position information are realized, so that the expression mode of a story is innovated, and the immersion and participation sense of a user in the story reading and watching process are improved.

Embodiments described herein relate to systems and methods for mapping molecules into interfaces. An example interface includes a visual interface having a map visualization. Example molecules include proteins, or any protein-like molecules or fragments thereof such as antibodies, antigens, proteins, lectins, receptors. Embodiments described herein relate to systems and methods for mapping molecules into interfaces by processing data using dimensionality reduction to generation representations of molecule maps (e.g. map visualizations).

This invention provides a scene knowledge-driven map data visualization system, belonging to the field of map visualization technology. It includes: a scene parsing module, used to parse user scene commands into a structured scene parameter set, and then match it with a scene knowledge base to obtain the corresponding scene template and its corresponding strategy information; a map spatial axis module, used to determine the target spatial benchmark based on the structured scene parameter set; a data association and filtering module, used to filter the current scene-related data set based on the structured scene parameter set, strategy information, and target spatial benchmark; and a lightweight rendering module, used to generate a rendering plan based on the scene template, and then perform lightweight rendering on the current scene-related data set according to the selective rendering rules contained in the rendering plan to obtain the map visualization result. The beneficial effect is that by using a scene-based and focused map visualization method, data redundancy is eliminated, providing accurate and efficient data support for various government decision-making processes.

The application relates to the field of space-time data processing, and provides a space-time narrative map generation method and system and a storage medium, wherein deep semantic understanding ability of a large language model (LLM) is innovatively integrated, space-time knowledge is formally represented, a reliable reasoning and checking mechanism is introduced, a verified structured space-time knowledge graph is generated, and finally a complete reasoning chain is visually presented by using an interactive map. Compared with a traditional method, the core advantage of the application lies in that reliable and real-time updating of the space-time knowledge graph is realized, the reasoning process is transparent and intelligent, the reliability of space-time decision support is greatly improved, and the depth and efficiency of information transmission are improved.

The invention provides a dangerous goods vehicle abnormal aggregation real-time monitoring method based on ST-DBSCAN, and belongs to the technical field of spatio-temporal data clustering analysis, and the method comprises the following steps: S1, preprocessing original vehicle coordinate data, and storing the data in a time sequence database; s2, sliding a time window to read the track of the dangerous goods vehicle; s3, the track of the dangerous goods vehicle is subjected to duplicate removal according to license plate numbers; step S4, an ST-DBSCAN algorithm is initialized; step S5, an improved ST-DBSCAN clustering process is executed; s6, noise points in the clustering set are removed; and S7, carrying out map visualization and automatic early warning. According to the invention, the reliability of aggregation alarm can be improved, and false alarms are significantly reduced; cooperative management of dangerous goods transportation is assisted, and the safety level of the whole transportation chain and public travel confidence are improved.

The present application discloses a remote sensing image feature quality evaluation method, including: determining remote sensing image feature quality evaluation indicators, the evaluation indicators including: inter-class discrimination and intra-class aggregation; determining the value range of inter-class discrimination and the value range of intra-class aggregation through calculation and feature map visualization to evaluate the evaluation indicators; establishing a quantitative evaluation strategy for remote sensing image feature quality for evaluating remote sensing image feature quality. According to the determined evaluation indicators, based on statistical analysis technology, the value range of inter-class discrimination and intra-class aggregation is determined, and a quantitative evaluation method for feature quality is established to evaluate the quality of feature extraction results. It achieves the extraction of features with both high inter-class discrimination and high intra-class aggregation. The goal of further improving feature quality can be achieved based on quality evaluation in the future, which has far-reaching significance for remote sensing image feature quality evaluation and remote sensing image information extraction.

A system and method for analyzing images of a slide corresponding to a specimen is disclosed, the method including receiving at least one digital image of the pathology specimen, using the digital image with an artificial intelligence (AI) system to determine at least one salient feature, the salient feature including a biomarker, cancer, cancer grade, parasite, toxicity, inflammation, and / or cancer subtype, determining with the AI ​​system an overlay of salient regions of the digital image, the AI ​​system indicating a value for each pixel of the overlay, and suppressing one or more non-salient regions of the digital image based on the value of each pixel.

The application provides a self-sensing and intelligent early warning method for stress of numerically controlled machining aluminum alloy shell parts, and particularly relates to the online intelligent monitoring and early warning technical field of numerically controlled machining. The method forms a conformal self-sensing array by distributing and embedding micro piezoelectric ceramic units on the surface of the aluminum alloy shell part, generates a piezoelectric charge signal, sends a self-sensing signal containing stress information after radio frequency identification backscattering modulation, receives the signal and synchronously acquires real-time machining parameters of the numerically controlled machining system, generates a real-time fusion feature vector through fusion processing of a self-adaptive weight distribution model, inputs a pre-trained pulse neural network model, outputs a stress risk probability value, synchronizes to a digital twin model for three-dimensional thermal map visualization display, and generates an execution hierarchical early warning or machining control instruction according to the stress risk probability value and a dynamic early warning threshold. The application realizes real-time, passive and distributed sensing and dynamic risk assessment of the machining stress state, and improves the timeliness of early warning and the self-controllability of machining.

The invention discloses an intelligent identification method and system for an investment subject based on map visualization, and the method comprises the following steps: intelligently judging the type label of the investment subject based on the research and judgment data of the investment subject; generating a weak early warning prompt in response to the fact that the type tag of the investment subject is inconsistent with the type tag selected by the user; positioning the investment subject on a map, and displaying a type label of the investment subject; and providing a map visualization service to allow a user to view the type labels of the investment subjects in the different investment areas of the map through a webpage or a mobile terminal. Therefore, big data analysis and artificial intelligence technologies can be utilized, and the advantages of map visualization are combined, so that the information of the investment subjects can be displayed more intuitively and comprehensively, and a user can intuitively know the distribution conditions of the investment subjects in different investment areas.

The invention discloses an electric power corridor ecological sensitivity evaluation method and system based on multi-source data, and belongs to the field of electric power corridor ecological sensitivity evaluation.The method comprises the following steps that ecological sensitivity factor indexes are obtained, and according to the requirement of electric power engineering environment influence evaluation, the ecological sensitivity factors are obtained; determining an ecological sensitive factor index sensitive to the construction response of the electric power gallery; carrying out numerical value standardization processing on the ecological sensitive factor indexes sensitive to the construction response of the electric power gallery, and carrying out grading and assignment; constructing an electric power corridor ecological sensitivity evaluation index system; and calculating a comprehensive ecological sensitivity index through a weighted summation method, classifying the area units through a natural breakpoint method, calculating the ecological sensitivity index of each area unit, and visually displaying the electric power corridor ecological sensitivity grade map. According to the method, multi-source data are fused to construct a multi-dimensional ecological sensitive factor system, so that evaluation indexes are more comprehensive, analysis is more objective, and the influence of engineering construction on the ecological environment is reduced.

The invention relates to the technical field of gas pipe network monitoring and early warning, in particular to an intelligent recognition and early warning method and system for abnormal data of a gas pipe network, and the system specifically comprises a pipe network abnormality early warning center, a multi-dimensional data module, a multi-dimensional processing module, a troubleshooting false alarm module, an abnormality marking module, an operation and maintenance division module, a dynamic early warning module and an early warning module. Through multi-dimensional data acquisition and processing and preliminary screening and spatial correlation analysis and verification of a pipe network identification model, missing judgment of single data can be avoided, equipment fault misinformation can be accurately eliminated, meanwhile, by means of a triangulation positioning method and historical data deviation correction, a system can upgrade abnormal points from preliminary positioning to accurate coordinates, and the accuracy of the abnormal points is improved. Through GIS map visual marking, blind troubleshooting of operation and maintenance personnel is avoided, the operation and maintenance personnel are guided to deal with high-level risk events preferentially based on early warning level division, resource waste in a low-risk scene is avoided, operation and maintenance pertinence is improved, and management cost is reduced.

The present invention discloses a method and system for visualizing an isosurface map based on a many-core processor cluster. The method includes: each computing node reads its own point set data in parallel; each computing node first calculates the position offset of an isovalue point in each layer of data slice along the direction of the three edges of the voxel X, Y, and Z in a multi-core parallel manner, then traverses the coordinates of the isovalue points on each edge of the calculated voxel in parallel, and finally traverses each voxel in parallel to connect three isovalue points to construct a triangular primitive and form a local isosurface; merges the local isosurfaces of each computing node, draws a global isosurface, and outputs an isosurface map. The present invention can utilize the multi-computing nodes of the many-core processor cluster and the multi-cores of each computing node to realize the parallel execution of isosurface map visualization, requires less auxiliary memory, reduces redundant calculations, can effectively improve the efficiency of isosurface map visualization, and is particularly suitable for isosurface map visualization processing of large-scale data sets.

The invention discloses a method for dividing and screening urban tourism data, which comprises the following steps: S1, collecting entities with coordinate attributes and tourism values in a city to form tourism data, and carrying out regionalized spatial semantic modeling on the tourism data; and S2, dividing the tourism data into a plurality of tourism areas, and the like. According to the method, through regionalized spatial semantic modeling and accurate spatial definition of tourism POI data, scattered scenic spots, catering and accommodation data are converted into a'regionalized resource cluster ', and the'regionalized resource cluster' is visually presented through a tourism map. According to the method, tourists can quickly establish an urban tourism area framework, directly position high-value resources in combination with the scenic spot score sequence table, and do not need to depend on fuzzy administrative region or business district information, so that the travel planning time is effectively shortened, the decision-making pain point that regional distribution is not known and resources are difficult to select in a traditional scene is solved, and the decision-making precision and efficiency are improved.