41 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.

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 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.

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.

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 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 application discloses a kind of genomic variation atlas visual interactive systems, system includes data access and pretreatment module, multidimensional variation atlas rendering module, interactive control module, dynamic query and filtering module and result output module.Data access and pretreatment module generates standardized variation feature vector set to multiple types of variation data, multidimensional variation atlas rendering module simultaneously renders the position, type, frequency and pathogenicity of variation with position, shape and color semantic coding triple dimensions;Interactive control module realizes continuous seamless zooming from whole genome macroscopic thermal view to single base resolution;Dynamic query and filtering module supports composite condition real-time filtering and atlas synchronous linkage through multidimensional inverted index;The application effectively solves the problems of insufficient multidimensional attribute coding, fragmented interaction levels and missing screening and atlas linkage in existing tools, significantly improves the efficiency of visual analysis of massive genomic variation data.

The application relates to a science and technology theme trajectory analysis system and method based on map visualization, wherein the system comprises: a map visualization module for collecting and processing geographical position information of global scientific research institutions to generate map tiles containing point position information, and rendering and interacting the geographical spatial distribution of the scientific research institutions; a multi-source data acquisition and processing module for acquiring paper data and / or patent data from at least one target database in a semantic manner; an AI analysis module for identifying institutions in a region and calculating scientific research density in the region through frame selection based on the paper data and / or the patent data, and generating a professional analysis report containing data insights according to a user-selected analysis object and target; and a user interaction interface module for dynamically adjusting display content according to user operations to perform point clustering, zooming adaptation and intelligent label display. Thus, the problems of weak geographical spatial visualization capability in the related art, inability to support large-scale real-time rendering and interactive regional analysis, data retrieval and analysis fragmentation and lack of AI automatic report generation function, and complicated user operation are solved.

The application relates to the technical field of infectious disease epidemic situation, and in particular to a dynamic map visualization method and system for a spatio-temporal evolution process of an infectious disease epidemic situation. The method first superimposes confirmed case coordinates and multi-time sequence risk resource points on an electronic map to construct an initial distribution layer; secondly, the layer is constrained by real-time reporting information to generate spatio-temporal evolution visualization rules; then, the initial layer is optimized in the spatio-temporal dimension based on the rules to obtain a hierarchical dynamic spatio-temporal data set; subsequently, a multi-level time sequence label and a visualized evolution layer are generated based on the data set and dynamically rendered with the electronic map to form a real-time dynamic interactive interface; finally, the interface and the label are combined to provide dynamic analysis support for epidemic prevention and control. The method realizes the transformation of epidemic data from static display to dynamic deduction, improves the data accuracy and the sense of hierarchy through real-time constraint and spatio-temporal optimization, effectively reveals the epidemic transmission context, and assists decision makers in accurately identifying risks, analyzing trends and formulating scientific prevention and control strategies.

Systems and methods are disclosed for analyzing an image of a slide corresponding to a specimen, the method including receiving at least one digitized image of a pathology specimen; determining, using the digitized image at an artificial intelligence (Al) system, at least one salient feature, the at least one salient comprising a biomarker, cancer, cancer grade, parasite, toxicity, inflammation, and / or cancer sub-type; determining, at the Al system, a salient region overlay for the digitized image, wherein the Al system indicates a value for each pixel; and suppressing, based on the value for each pixel, one or more non-salient regions of the digitized image.

The invention relates to the field of spatio-temporal data processing, and provides a spatio-temporal narrative map generation method and system and a storage medium, spatio-temporal knowledge is subjected to formalized representation by innovatively fusing the deep semantic understanding ability of a large language model (LLM), then a trusted reasoning and verification mechanism is introduced, and a verified structured spatio-temporal knowledge map is generated. And finally, visually presenting a complete reasoning chain by using an interactive map. Compared with a traditional method, the method has the core advantages that credibility and real-time updating of the space-time knowledge graph are achieved, transparency and intelligence of the reasoning process are achieved, the reliability of space-time decision support is greatly improved, and the depth and efficiency of information transmission are improved.

The invention provides a self-sensing and intelligent early warning method for stress of a numerical control machining aluminum alloy shell part, and particularly relates to the technical field of numerical control machining online intelligent monitoring and early warning. According to the method, micro piezoelectric ceramic units are embedded in the surface of an aluminum alloy shell part in a distributed mode, a conformal self-sensing array is formed, and piezoelectric charge signals are generated; after radio frequency identification back scattering modulation, a self-sensing signal containing stress information is sent; receiving the signal, synchronously obtaining real-time processing parameters of a numerical control processing system, and generating a real-time fusion feature vector through fusion processing of a self-adaptive weight distribution model; inputting a pre-trained pulse neural network model, and outputting a stress risk probability value; synchronizing to a digital twinborn model for three-dimensional thermodynamic diagram visual display; and according to the stress risk probability value and the dynamic early warning threshold value, generating an execution grading early warning or processing control instruction. According to the method, real-time, passive and distributed sensing and dynamic risk assessment of the machining stress state are realized, and the early warning timeliness and the machining autonomous controllability are improved.

The invention discloses an unfamiliar area robot autonomous navigation and map creation method in a network-free state. The method comprises the following steps: S10, early-stage configuration: setting a robot to carry a 16-line laser radar, a 1080P high-definition camera, an object segmentation algorithm chip, an SSD storage module and an IMU inertial measurement unit; a user configures an autonomous exploration time length, a fan-shaped exploration angle, a passable channel width threshold value and an obstacle height threshold value through a control end; s20, triggering an exploration mode: the robot monitors a communication state with a control end in real time, when a communication broken link is detected, the robot is automatically switched to a network-free autonomous exploration mode, a laser radar and a camera are started, and a communication broken link origin O is recorded; s30, terrain recognition and trafficability judgment: based on a locally deployed object segmentation algorithm, combining terrain point cloud data and camera image data collected by a laser radar to recognize a terrain type; s40, performing fan-shaped path-finding exploration; and S60, visualizing the map.

The invention provides a dynamic map visualization method, device and equipment based on Vue component encapsulation and a medium, and belongs to the technical field of map dynamic visualization. The method comprises the steps that a Vue map component is encapsulated, and a props interface for receiving external dynamic configuration parameters is defined; creating a template view for the Vue map component, and initializing a map instance; in the Vue map component, receiving dynamic configuration parameters from a parent component of the Vue map component through a props interface; and establishing a response type monitor in the Vue map component, and when monitoring that the dynamic configuration parameters change, automatically calling an application program interface of the electronic map service, and dynamically updating the visual state and function of the map instance. Through dynamic configuration and componentized packaging, the development difficulty is reduced, multi-scene efficient application is achieved, map dynamics and interactivity are enhanced, and transparency control and real-time traffic refreshing functions are optimized.

The invention relates to the technical field of building engineering and information technology fusion, and particularly discloses a BIM-driven urban building integrated simulation and collaborative optimization system, which comprises the following steps of: acquiring static BIM data, identifying a construction activity list and generating a three-dimensional risk envelope to represent a dynamic operation space of a construction activity; calculating a space-time interference factor by using an interference factor quantification module, predicting potential conflicts, and visually presenting the potential conflicts through a dynamic operation map; meanwhile, the system is also integrated with a personnel and equipment information acquisition module, a high-risk space and time identification module is combined, and optimal resources are matched by utilizing intelligent nearby task docking logic; and finally, through a dynamic adjustment suggestion generation module, an adjustment suggestion is proposed based on the reverse flow traction logic, and active optimization of the construction plan is realized. According to the invention, the conflict early warning precision is improved, the resource allocation is optimized, and the construction efficiency and safety are enhanced.

This invention discloses a multi-source simulation map visualization integration method and system based on a 3D engine, belonging to the field of simulation visualization technology. To address the technical problems of existing systems, such as difficulty in adapting multi-source heterogeneous data, high rendering latency for a large number of dynamic entities, redundant memory management, and insufficient semantic representation, this invention constructs a situational information protocol layer to dynamically map multi-source raw data into normalized data. The normalized data is managed through resource pooling, using dynamic and static resource pools to classify and maintain entities, and smoothing and resource reclamation are performed based on motion states, outputting a real-time rendering situational flow. Based on this situational flow, parameters are extracted, and regional capability assessment data is generated using an evaluation model, which is then combined with geographic semantic mapping and spatial grid data and loaded into the 3D engine for rendering. This invention can significantly reduce integration costs, improve the smoothness and stability of high-concurrency rendering, and enhance situational understanding and decision-making capabilities in complex scenes.

The invention provides an intelligent exhibition map implementation method and system.The method comprises the steps of data access, address intelligent cleaning, coordinate mapping, map visualization and spatial analysis and intelligent decision making, intelligent complementation and standardization processing of unstructured customer addresses are achieved by means of large model semantic analysis and a structured knowledge base, and the intelligent exhibition map implementation efficiency is improved. The address data management precision is improved; through a geography-business two-dimensional linkage AI agent decision engine, natural language interaction is supported, combined matching is carried out by combining geospatial information with customer attributes and business opportunity data, and decision support information such as business opportunity recommendation and route planning is actively output. The problems of low address cleaning precision, poor coordinate mapping reliability, weak intelligent analysis, low interaction efficiency and the like in the prior art can be solved, the precision of the exhibition data, the map rendering performance and the decision intelligent level are greatly improved, the multi-scene exhibition requirements are met, and efficient support is provided for digital exhibition of financial institutions.

A system is provided.SOLUTION: A system comprising: means for real-time data collection from a plurality of information sources; means for pre-processing the collected information; means for integrating and analyzing the pre-processed information using a generative AI model; means for creating a disaster-affected map based on the analysis results; and means for visualizing and providing the disaster-affected map to a user.SELECTED DRAWING: Figure 1

The application relates to the field of natural epidemic disease network data communication, and particularly discloses a visual early warning platform based on vector ecology management, which comprises a collection module, a central server and an interaction module; the collection module is used for collecting original data of monitoring areas at municipal, district and county levels; the central server comprises a vector data processing module, a vector infection risk prediction module and a map visualization display module; the vector infection risk prediction module is used for predicting vector density and predicting vector infection risk; the map visualization display module is used for converting data of the vector data processing module into hierarchical color block diagrams on an electronic map; and a vector infection risk prediction method is further disclosed. The application solves the technical problem that the existing vector monitoring data has low visualization and cannot provide intuitive and timely decision basis for managers.