23 results about "Geographic maps" patented technology

The invention discloses a multi-unmanned aerial vehicle cooperative three-dimensional trajectory planning method based on a hybrid meta-heuristic algorithm, and the method comprises the steps: constructing an unmanned aerial vehicle cooperative trajectory planning model containing cooperative defense constraints, and constructing a three-dimensional geographic map containing a research region in the unmanned aerial vehicle cooperative trajectory planning model; an unmanned aerial vehicle cooperative system comprising N unmanned aerial vehicles is constructed, and an unmanned aerial vehicle cooperative trajectory planning model enables all the unmanned aerial vehicles of the unmanned aerial vehicle cooperative system to cooperatively search and simulate flight in a research area according to unmanned aerial vehicle flight tasks in a three-dimensional geographic map. And the unmanned aerial vehicle cooperative trajectory planning model constructs a population by taking the unmanned aerial vehicle flight trajectory as an individual, executes iterative optimization processing of a fusion cooperative defense strategy and ant lion optimization random walk based on a PHOENIX algorithm, and finally outputs an optimal unmanned aerial vehicle cooperative flight three-dimensional trajectory. According to the invention, efficient, safe and cooperative trajectory planning processing of multiple unmanned aerial vehicles in a complex three-dimensional environment is realized, and important technical support is provided for research and application of an intelligent autonomous system.

The invention relates to the technical field of meteorological services, and particularly discloses a meteorological forecasting method and system fused with high-precision geographic information, geographic data is obtained through a satellite, the influence of a macroscopic geographic environment on climate can be reflected, real-time monitoring data of an automatic meteorological station can provide accurate observation of microscopic point locations, and the accuracy of meteorological forecasting is improved. A macroscopic-microcosmic linkage complete data chain is formed, analysis deviation caused by a data surface is avoided, a positioning system of the automatic weather station ensures accurate binding of detection data and geographic coordinates, and by combining with a preset geographic layout boundary, the position fuzziness of the data can be avoided, so that each piece of climate data can anchor a specific geographic scene, and the accuracy of data analysis is improved. A precise space reference is provided for subsequent analysis, and the characteristics of precise data, clear monitoring, sensitive and reliable prediction and wide application range are cooperatively realized through multi-modal technology fusion.

This application discloses a target recognition, localization, and presentation method. The method includes: acquiring an aerial image; rotating the aerial image according to the heading angle information of the aerial photography device so that its direction is the same as the direction of the geographic map; establishing a target detection model; inputting the rotated aerial image into the target detection model to obtain an aerial image with the target object identified; establishing a first coordinate system in the identified aerial image and obtaining the pixel position of the target object according to camera parameters; establishing a second coordinate system between the aerial photography device and the identified aerial image, and obtaining the geographic coordinates of the target object according to the heading angle information of the aerial photography device, its relative ground height, and geographic coordinates; and visually annotating and presenting the located target on a pre-generated 3D digital terrain of the aerial photography area based on the geographic coordinates of the target object. This invention realizes the conversion from target detection pixel coordinates to physical world latitude and longitude coordinates, improving the accuracy of target localization.

The invention discloses a multi-source navigation announcement data model analysis processing display and PIB extraction method, which comprises the following steps: constructing a data identification model containing a navigation announcement standard database, and constructing the navigation announcement standard database according to announcement message types, application ranges and effectiveness levels; obtaining a multi-source navigation announcement data stream, performing structured disassembly on the navigation announcement data stream, and storing the navigation announcement data stream in a navigation announcement standard database according to a hierarchical structure and a standard data format; obtaining all associated data covering the research object from the navigation announcement standard database based on the research object, and forming a navigation announcement data report file of the research object; and extracting point, line and surface data of all associated data of the research object, and visually displaying the point, line and surface data on a GIS geographic map. According to the method, efficient management and query of the navigation announcement data are realized, the navigation announcement data report file of the research object is formed, and information technology support in the aspect of navigation announcement is provided for making a flight plan or flying.

This invention provides a computer implementation method for generating routes in waterways for the automatic control of marine vessels. [Solution] A computer implementation method for generating a route P in a channel 40 for the automatic control of an ocean vessel 10, comprising: acquiring position data of the ocean vessel; determining, based on the position data, that the ocean vessel is approaching or in the channel; identifying the starboard portion of the channel relative to the position of the ocean vessel from geographic map data; determining a collision-free route in the starboard portion 52 of the channel while moving through the channel; and providing an output of the determined collision-free route for the automatic control of the ocean vessel along the determined collision-free route.

This application provides a map generation method and system based on multi-source heterogeneous geographic information processing. It acquires three types of heterogeneous data: a geographic element attribute database, a geographic coordinate semantic database, and a geographic reference image database. Spatial spectrum reconstruction processing is then performed to generate a spatial spectrum cube. Belief propagation fusion processing is then used to construct a belief network from the spatial spectrum data. Combined with spatially constrained probability field optimization and D-S evidence synthesis, a geographic evidence chain is generated. Next, spatiotemporal field reconstruction processing is performed to separate the static and dynamic states of the geographic evidence chain and couple them into fields, constructing a hyperdimensional spatiotemporal map. Finally, holographic projection conversion processing is used to perform phase field compression and coherent diffraction reconstruction on the hyperdimensional spatiotemporal map, generating a holographic geographic projection map that supports 3D interaction. This method achieves the automatic generation of a structurally unified, highly reliable geographic map that supports dynamic behavioral reasoning and true 3D interaction from multi-source heterogeneous geographic data, significantly improving the decision-making value and cognitive efficiency of geographic information.

A method for visualization of geospatial positioning and management of electrical infrastructure assets involves assigning a data set with visual data, spatiotemporal data, geo-positional data, and point cloud data to a data pool. The method maps the data set to a geographic information system as at least one virtual asset. The method visualizes the at least one virtual asset with a placemark on virtual geographic map. The method applies severity annotations to the at least one virtual asset. The method groups the at least one virtual asset with at least one other virtual asset based on proximity of the placemark on the virtual geographic map. The method generates an assets report comprising the severity annotations for the at least one infrastructure asset. The method generates an encroachment report comprising encroachment severity from the point cloud data of the at least one infrastructure assets.

The invention discloses a space-time mapping knowledge domain construction method based on a large language model and Beidou grid coding. The method comprises the steps that semantic partitioning is conducted on an input text through the large language model LLM, fact declarative sentence extraction is conducted on each block, and triple extraction, time entity extraction and space geographic entity extraction are conducted on the fact declarative sentences respectively; performing time attribute coding on the time entity; constructing a gridded Beidou satellite geographic map and obtaining a Beidou grid coding data set, and performing associated grid matching coding on spatial geographic entities to form corresponding spatial attributes; and collecting the time entity containing the time attribute, the space geographic entity containing the space attribute and the triple to construct the space-time knowledge graph. According to the method, attribute coding is carried out on the time entities and the space geographic entities, the coded time entities, the coded space geographic entities and the triple are collected and constructed to obtain the space-time knowledge graph, space-time information in the entities can be deeply mined, and the space-time reasoning capability is improved.

An example operation may include one or more of receiving a geographic map that comprises tasks assigned to a plurality of vehicles, and routes for the plurality of vehicles to follow to perform the tasks, clustering the routes into a plurality of subsets of routes based on travel times from geographic locations of the routes in the geographic map, wherein each subset of routes corresponds to a different geographic location, executing a large neighborhood search (LNS) on the plurality of subsets of routes to generate a plurality of modified subsets of routes for the plurality of vehicles to follow to perform the tasks, updating the geographic map based on the plurality of modified subsets of routes, and dispatching the tasks to the plurality of vehicles via a communication channel based on the updated geographic map.

The invention relates to the technical field of data processing, and discloses a forest grass informatization-oriented ecological space multi-source data integration method and system, and the method comprises the steps: endowing forest grass business data and Internet of Things sensing data with geographic coordinates and forest grass compartment codes based on a forest region geographic base map, and constructing a time-space fusion modeling data set in combination with a time label; extracting space coordinates of the unmanned aerial vehicle aerial image and the remote sensing image based on the space-time fusion modeling data set to obtain a first coordinate point set, and splicing the unmanned aerial vehicle aerial image and the remote sensing image to obtain a forest region static geographic map; based on the space-time fusion modeling data set, a control point is determined from the static geographic map of the forest region, a second coordinate point set is obtained from the real-time video of the unmanned aerial vehicle, and then the real-time video of the unmanned aerial vehicle and the static geographic map of the forest region are fused to obtain a dynamic geographic map layer of the forest region; and obtaining forest region multi-source data corresponding to the forest grass ecological space based on the forest region dynamic geographic map layer, the space-time fusion modeling data set, the forest grass business data and the internet-of-things perception data.

The embodiment of the invention discloses a charting method and device based on intelligent fusion of aviation elements and basic geographic elements. One specific embodiment of the method comprises the following steps: acquiring an aviation geographic data set from a preset aviation area and a preset earth surface area; carrying out mapping environment building on the aviation geographic data set to generate an environment building aviation geographic data set; cartographic data processing is carried out on the environment building aviation geographic data set to generate an aviation geographic cartographic; performing layout adjustment on the aviation geographic map to generate an adjusted aviation geographic map; and sending the adjusted aviation geographic drawing to drawing output equipment to obtain an aviation geographic drawing result. According to the implementation mode, accurate scale transformation can be realized while the integrity of the geographic elements is kept, manual intervention is reduced by improving the automation degree, and the manufacturing cost is remarkably reduced.

An embodiment relates to a system for generating automatically and predicting network coverage maps of autonomous vehicle, including a map-mapping unit that collects network speed and quality data for a plurality of base stations from a control center by time of day, day of the week, and date and maps them onto a geographic map to generate coverage maps representing network condition, a route search unit that searches for a driving route to the destination by linking with the map-mapping unit,; a data collection unit that collects data on current states of the autonomous vehicle including at least location, date, day of the week, time, network speed, and quality data of the autonomous vehicle; and a prediction algorithm that predicts network condition of coverages mapped on the driving routes, but predicts the network condition according to expected arrival time and date of the autonomous vehicle.

A method and system provide areas with lifestyle preferences selected by a user. Generally, a computing device receives a selection of one or more lifestyle preferences from the user. In response to the selected lifestyle preferences, a visual display of one or more areas of a geographic map that includes one or more of the lifestyle preferences that favorably compare to the lifestyle preferences of the user is presented to the user via a user interface of the computing device. Additionally, the user may submit a review of the lifestyle preferences available in a particular location.

This disclosure describes systems and methods for multi-modal search-based object detection and electric grid object search. Annotations and bounding boxes for images in an image database are determined. A first subset of images is determined from the images that share annotations. A textual token representing the first subset of images is generated and stored in a search index. A second subset of images that share visual features is determined from image pixels enclosed by the bounding boxes. An image token is generated based on the second subset of images and the shared visual features. A user interface configured to receive a search query input is provided for display on a user device. Search tokens are generated based on the search query input. A candidate image is identified and provided for display within the user interface at a position within a respective region of a geographic map of an electric grid.

The invention relates to a method for providing location-specific distributions of sensor information (Sref (x, o, t)) and / or location-specific sensor fingerprints (Dref (x, o, t)), in particular on a geographic map (K), which can be used to verify sensor information (S (xi, oi, ti)) of a vehicle (F) in comparison to a location-specific distribution of sensor information (Sref (xi, oi, ti)) and / or a location-specific sensor fingerprint (Dref (xi, oi, ti)) at a specific location (xi), at a specific orientation (oi) and / or at a specific time (ti).

A computer implemented method of creating a simulated realistic virtual model of a geographical area for training an autonomous driving system, comprising obtaining geographic map data of a geographical area, obtaining visual imagery data of the geographical area, classifying static objects identified in the visual imagery data to corresponding labels to designate labeled objects, superimposing the labeled objects over the geographic map data, generating a virtual 3D realistic model emulating the geographical area by synthesizing a corresponding visual texture for each of the labeled objects and injecting synthetic 3D imaging feed of the realistic model to imaging sensor(s) input(s) of the autonomous driving system controlling movement of an emulated vehicle in the realistic model where the synthetic 3D imaging feed is generated to depict the realistic model from a point of view of emulated imaging sensor(s) mounted on the emulated vehicle.

The invention discloses a power distribution network signboard optimization management method, system and device based on a power distribution network map and a storage medium, the layout of signboards in the map is determined according to offset parameters of the signboards relative to a power distribution network object, and information changes caused by signboard operation in a geographic map are captured in real time; the changed data are synchronously pushed to all opened power distribution network maps, and the map end refreshes the state of the signboard in an incremental updating mode; synchronously monitoring information change generated by signboard operation in the single line diagram of the power distribution network; the visual management and control process and cross-scene cooperative operation experience of the power distribution network signboard are optimized, efficient adding, deleting, modifying and checking operation of the signboard is achieved by means of fusion design of a geographic base map and a power distribution network object primitive, real-time synchronization of signboard information between multiple maps and single line diagrams is achieved, data consistency is effectively guaranteed, manual operation deviation is reduced, and operation efficiency is improved. The operation and maintenance work efficiency and the management accuracy of the power distribution network are improved, and efficient technical support is provided for a visual operation and maintenance scene of the power distribution network.

This invention discloses a method for recommending points of interest (POIs) in different locations based on user preferences and personalized preference transfer, belonging to the field of terminal location-based recommendation. The method includes: constructing a heterogeneous hypergraph for five different types of nodes, and obtaining user preference representations through training the hypergraph; constructing a POI-category graph, and learning POI representations through a continuous skipping word model; constructing an attention network with POI representations as input to obtain user-transferable features; constructing a parameter learning network using a multilayer perceptron and user-transferable features as input, and constructing a transfer network with user preference representations as input and the output of the parameter learning network as parameters to achieve personalized user preference transfer; constructing a geographic map between POIs based on latitude and longitude, and learning the embedding representations of different POIs through a convolutional network; calculating the score for each POI by combining the user's transferred preferences with the embedding representations of different POIs, thus completing the final recommendation.

The invention relates to a verbal identification method for a geographic area. The technical effect consists in improving the accuracy of identifying geographic areas of various sizes on the whole earth surface. The proposed computer-implemented method for identifying a geographic area comprises: creating a layer of a digital geographic map in the form of a grid of square cells of base size covering the entire earth surface using a geocentric coordinate system; extracting map making data about the geographic object of each created square cell from the corresponding map layer; iteratively subdividing each square cell containing at least a part of geographic objects into four equal square cells; at least one vocabulary and one vocabulary from a common spoken language vocabulary set are allocated to each square cell which is not divided, the at least one vocabulary represents a geographic name of a geographic object at least partially contained in the square cell, and the allocated vocabulary jointly forms a unique identification word group; and providing access to the created layer to the remote computing device by referencing the undivided square cells based on the geographic coordinates to obtain the corresponding unique identification phrases, or by referencing the unique identification phrases to obtain the geographic coordinates of the corresponding undivided square cells.

This invention discloses a method, system, vehicle, and storage medium for the coordinated control of unmanned aerial vehicles (UAVs) and vehicles. The method includes: acquiring UAV status information, environmental information, vehicle status information, and geographic map information; determining the reachable safe landing area of ​​the UAV based on the UAV status information and environmental information; determining the optimal landing point within the reachable safe landing area based on the geographic map information; and planning the optimal driving path for the vehicle from its current position to the optimal landing point, and the landing flight path for the UAV from its current position to the optimal landing point, based on the optimal landing point, geographic map information, and vehicle status information, so as to control the vehicle and UAV to synchronously reach the optimal landing point along their respective paths. This invention ensures the efficiency and safety of vehicle-assisted UAV recovery operations, improving the efficiency of air-ground coordinated operations and the safety of mission execution.

The invention provides a resource importance determination method and device, equipment, a medium and a program product. The method comprises the following steps: acquiring multi-source heterogeneous data of a plurality of network devices in an operator network; wherein the multi-source heterogeneous data comprises multiple pieces of geographic information system data, configuration management database data and network traffic logs; generating a network space geographic map of the operator network according to the multi-source heterogeneous data; according to a preset graph neural network, extracting a potential connection relationship between any two network devices in the network space geographic map; according to the potential connection relationship, performing enhancement processing on the network space geographic map to obtain an enhanced knowledge map; determining a real-time network situation vector of the operator network according to the enhanced knowledge graph and a preset real-time network situation vector calculation formula; and according to the knowledge graph after the real-time network situation vector enhancement, determining an importance score of the network equipment. Therefore, accurate importance evaluation and sorting of the network resources are realized.

This invention belongs to the field of geospatial intelligent analysis methods, specifically a method for automatically constructing multi-scale dynamic spatiotemporal geographic maps based on vector data. It includes the following steps: S1, data standardization and basic spatial relationship calculation; S2, spatiotemporal integrated geographic entity modeling and map updating; S3, road network-enhanced spatial relationship modeling, integration, and map updating; S4, automatic construction of multi-scale geographic hierarchical systems and map updating; S5, map output. The execution of steps S1 to S4 is driven by an intelligent agent module, which dynamically adjusts the execution order and parameters of each step. This invention achieves end-to-end automated construction of geographic knowledge maps with dynamic spatiotemporal reasoning capabilities from multi-source, multi-period vector data, supports full lifecycle tracking of geographic objects, upgrades traditional geometric relationships to real and quantifiable path semantic relationships, and realizes cross-level spatial cognition and reasoning functions.