68 results about "Geohash" patented technology

The invention relates to an AIS data-based port ship unloading area analysis method. The method comprises the following steps of: 1, preprocessing AIS data, namely carrying out cleaning screening and attribute supplementation on original data; 2, ship staying leg extraction: defining a staying leg by using motion features and expressing the staying leg by using a Geohash grid; step 3, port destination text matching: matching irregular destinations with standard port names; 4, bidirectional destination retrieval: analyzing an accurate destination by using a ship trajectory, and determining an affiliation port of a staying grid; and 5, grid integration and route cutting: integrating grids belonging to different ports to obtain an unloading area, and cutting a whole-cycle route of the ship. According to the method, the problems of complex unloading mode and complex route staggering around a port are solved, and reliable technical support is provided for trade monitoring of bulk energy goods such as crude oil by utilizing the complementary advantages of time-space information and destination texts in AIS data.

The invention discloses a method for constructing a computable road network. Road data in the vector map are extracted, line string data or line segments obtained by splitting the line string data are used as connecting edges, geographic feature codes containing Geohash information are given to starting points and ending points of the connecting edges, and therefore a basic road network map is constructed. And extracting a middle vertex set of the basic road network diagram and an edge attribute set of middle vertex connection edges, and carrying out road network vertex optimization based on edge attributes to obtain an optimized computable road network. Geographic feature codes adopted by the method comprise spatial geographic information and have the characteristics of graph vertex coding, and the constructed road network graph can be used for graph calculation and verification and restoration of road connection relations. Furthermore, in combination with a representation point acquisition scheme provided by the invention, a road network map fusing facilities and equipment can be constructed, so that the application range of the computable road network is expanded. The computable road network constructed by the method is high in operation efficiency and suitable for different production environments.

The invention discloses a question answering system and a construction method for a motor vehicle driving teaching knowledge graph, and aims to overcome the defects of knowledge coverage integrity, scene adaptability, reasoning depth and interaction naturalness in the prior art. A traffic regulation document, coach voice and short videos and vehicle-mounted real-time data are integrated through a data acquisition module to cover rules and experience knowledge, a knowledge construction module constructs a space-time dynamic knowledge graph containing static and dynamic nodes based on Dgraph, space-time association is achieved by means of GeoHash coding, real-time updating is completed through an MQTT protocol, and the time-space dynamic knowledge graph is stored through a storage module. The intelligent reasoning module calls a DoWhy model to construct an'operation, principle and result 'causal chain in combination with a physical formula so as to output deep interpretation, and the interaction module achieves multi-mode immersion teaching through speech synthesis, gesture recognition and 3D animation, dynamically optimizes knowledge pushing according to student operation data, and achieves multi-mode teaching. The comprehensiveness, the real-time performance, the scientificity and the interaction naturalness of driving teaching are improved, and the method is suitable for intelligent driving teaching scenes.

The invention discloses an industrial smart energy multi-energy evaluation visualization system and method, and relates to the technical field of energy big data visualization crossover, and the method comprises the steps: collecting and preprocessing multi-source heterogeneous data, and generating space-time aligned high-dimensional energy data through a space-time hash coding method; based on the three-dimensional manifold coordinate model, converting equipment energy efficiency parameters into an equivalent energy mass field, and through an energy field reconstruction and geometric optimization method, generating a curved manifold space and identifying an optimal transmission path and a distortion strength cloud picture; and based on the distortion strength cloud picture, generating a thermodynamic color gradation through a thermodynamic color gradation mapping algorithm, rendering three-dimensional gradient field distribution of the equivalent energy mass field by adopting a ray tracing method, and generating a visual energy evaluation interface. According to the method, space and time hash codes are generated through a space-time hash coding method, the equipment-grid mapping relation is established in combination with GeoHash coding, and accurate space-time alignment of multi-source heterogeneous data is achieved.

The invention relates to a territorial space purpose control data processing method based on a space-time knowledge graph. The method comprises the steps that map entities and semantic relations between the map entities are configured in a mode layer, and the categories of the map entities comprise space-time entities used for representing space-time slice states and event entities used for representing human activities generating actual or potential influences on land states; establishing a grid system comprising a plurality of grids based on Geohash coding, associating administrative division and multi-source heterogeneous data with the grid system respectively, and constructing a grid layer; extracting territorial space purpose control data, carrying out entity and entity relationship initialization according to the mode layer and the grid layer, and constructing a graph layer; and establishing an application layer based on the map layer and the grid layer. Compared with the prior art, the method can support reasoning and prediction of geographic phenomena, introduces multi-dimensional information features, and effectively supports business application.

The disclosure is generally directed to a method and system for charge station management including collecting data related to a plurality of charge stations, the data identifying location data, an operator, and a data provider for each of the plurality of charge stations, collating the data to match the location data with the operators of each of the plurality of charge stations, and merging the location data based on a set of criteria including the data from each of the data providers within an identified geohash location. Merging includes setting a geohash about a data provider, and merging location data within the predetermined perimeter to remove redundant locations based on a set of criteria, including criteria identifying a same operator within the geohash.

The invention discloses an intelligent park risk identification method based on position information, and relates to the technical field of park safety management. According to the method, personnel and vehicle positioning data, fixed risk source coordinates, equipment states, environment parameters and video stream data are collected in real time; a Geohash algorithm is adopted to carry out grid division on the park, and multi-source data space-time alignment is realized by sliding a time window; the YOLOv8 model is improved and trained, and a real-time park abnormal behavior detection result is output; quantifying a moving target behavior risk based on an entropy weight method, and superposing an equipment environment standard exceeding risk to generate a grid-level superposition risk value; combining the real-time park abnormal behavior detection result with the superposed risk value to obtain a final risk result; the method breaks through the data island limitation of a traditional monitoring system, improves the risk recognition rate early warning response speed, reduces the risk false detection rate, and achieves the conversion from passive response to active prevention and control.

The invention discloses a GIS (Geographic Information System) big data processing storage and real-time rendering method based on HBase, which belongs to the technical field of general geographic information systems, and comprises the following steps: S1, accessing original geographic space data, partitioning the original geographic space data based on GeoHash, and carrying out vectorization loading to obtain service vector data; s2, carrying out hierarchical splitting on the service vector data by utilizing a pyramid model, and carrying out attribute or space aggregation on the split vector data; s3, storing the aggregated vector data into an HBase (Hadoop Base); and S4, according to an input loading range, obtaining the aggregated vector data from the HBase, and performing real-time rendering. Vector data in geographic data are loaded to the HBase, retrieval testing is carried out, and the retrieval response time can reach the millisecond level.

The present invention discloses a method for intelligently identifying park risks based on location information, which relates to the technical field of park safety management. The method collects personnel and vehicle positioning data, fixed risk source coordinates, equipment status, environmental parameters and video stream data in real time; adopts the Geohash algorithm to divide the park into grids, and realizes spatiotemporal alignment of multi-source data through a sliding time window; improves and trains the YOLOv8 model to output real-time park abnormal behavior detection results; quantifies the behavior risks of mobile targets based on the entropy weight method, and superimposes the risks of equipment and environmental exceeding the standard to generate grid-level superimposed risk values; combines the real-time park abnormal behavior detection results with the superimposed risk values ​​to obtain the final risk results. The present invention breaks through the data island limitations of traditional monitoring systems, improves the risk identification rate and early warning response speed, reduces the risk false detection rate, and realizes the transformation from passive response to active prevention and control.

The invention discloses a space query optimization method based on a Salted Key. The method comprises the following steps: step 1, data cleaning and format conversion; step 2, converting geographic coordinates of the converted data obtained in the step 1 into Geohash codes; 3, completing data storage by adopting multiple dimensions of time and space; and 4, querying the data stored in the distributed database HBase, and obtaining a query result through two query modes. The invention belongs to the technical field of geographic information systems and data storage, solves the problems of low geographic data storage efficiency and poor query performance of large-scale geographic information in the prior art, is particularly suitable for large-scale geographic data storage and real-time query, can process a large amount of data without sacrificing performance, and is high in practicability. And application requirements of traffic flow, weather forecast and the like which need to consider space and time factors at the same time can be met.

The application discloses a GeoHash determination method, device, equipment and medium. In the embodiment of the application, the target GeoHash length of each GeoHash block is determined in advance according to the target area of a target geofence, and for each target GeoHash block contained in the target geofence, the target GeoHash encoding with the length of the target GeoHash length of the target GeoHash block is determined and saved. The length of the GeoHash encoding suitable in length can be selected according to the area of the constructed target geofence, so that the number of corresponding GeoHash encodings in the target geofence is appropriate, the saved target GeoHash encodings are prevented from being too many, and the accuracy of the range represented by the GeoHash encoding is ensured.

The application discloses a kind of fusion and compression method of multi-source trajectory information, it is related to data processing field.The application uses the thought of smoothing analysis, by adaptive calculation angle, speed error threshold, each positioning terminal trajectory is denoised in real time;Real-time calculation window time each trajectory data quality;According to the weight of each trajectory of trajectory data quality adaptive calculation, improved exponential weighted average algorithm is proposed, the weighted average value of longitude and latitude of multi-source trajectory point is calculated as the fused trajectory coordinates;The roughness of fused trajectory in sliding time window is calculated, and the sub-block size of GeoHash algorithm is dynamically adjusted by integrating trajectory roughness, to realize efficient real-time compression under the premise of maintaining high compression accuracy.The application can realize adaptive fusion and compression of multi-source trajectory by comprehensive data quality, with the advantages of reasonable fusion weight and high real-time compression efficiency.

A data processing service executes a new forward and reverse geohashing process that is correct up to a threshold geohash precision. The forward and reverse geohashing processes described are correct for precisions up to 18, where a precision corresponds to 5 geohash bits. The forward geohashing process gives correct results for precisions up to 19, and the reverse geohashing process gives correct results for precisions up to 20. The geohashing methods described herein is configured to perform a relatively small number of floating point and integer operations to avoid the iterative nature of existing geohashing processes. Moreover, the transformations are completed in an accurate way while saving more computational power compared to existing geohash algorithms.

The invention discloses an embedded star catalogue data storage and query method oriented to a bare computer environment, relates to the technical field of embedded data query processing, solves the problem of mismatch between a DSP system structure and a star map query task in the prior art, and comprises the steps of star block storage, star block query, primary selection of star blocks in star block query and determination of navigation stars. In the star block storage, the GeoHash coding technology is adopted to take the star block as a primary key value, and a B + tree is adopted to store the star block in an easy-to-search form; a star map shot by an astronomical camera is preliminarily decomposed into primarily-selected star blocks in a partition mode, then corresponding storage star blocks in a bare computer environment are inquired respectively, and high flexibility and adaptability are achieved. The method is compatible with the GeoHash coding technology, parallel computing of a multi-core bare computer is facilitated, and the query speed can be doubled.

This invention discloses a route trajectory query method and terminal. The method obtains the binary encoding value corresponding to a latitude and longitude map and constructs a tree-like index structure based on the binary encoding value. It receives second route trajectory data, performs binary encoding on the second route trajectory data to obtain a third binary encoding value corresponding to the second route trajectory data, and searches for target route trajectory data corresponding to the second route trajectory data from the tree-like index structure based on the third binary encoding value. Unlike existing technologies that rely on GeoHash value comparison for querying, this method searches for matching route trajectories by retrieving the tree-like index structure, enabling rapid retrieval of relevant route trajectories, reducing computation time, and thus improving the efficiency of route trajectory querying.

The application discloses a kind of wisdom energy multi-energy evaluation visualization system and method for industry, it is related to energy big data visualization cross technical field, including, acquisition multi-source heterogeneous data and pre-processing, by space-time hash coding method, generate high-dimensional energy data of space-time alignment;Based on three-dimensional manifold coordinate model, the equipment energy efficiency parameter is converted into equivalent energy quality field, by energy field reconstruction and geometric optimization method, generate curved manifold space and identify optimal transmission path and distortion intensity cloud chart;Based on distortion intensity cloud chart, generate thermal color scale by thermal color scale mapping algorithm, and the three-dimensional gradient field distribution of equivalent energy quality field is rendered using ray tracing method, generate visual energy evaluation interface.The application generates space and time hash code by space-time hash coding method, establishes equipment-grid mapping relationship in combination with GeoHash coding, realizes the accurate space-time alignment of multi-source heterogeneous data.

The invention provides a port function area mining method and system based on geographical hash coding. The method comprises the following steps: determining a ship berthing function area; performing berthing identification and classification on track points; different Geohash hierarchies are selected for the in-port area and the out-port area, and a clustering method based on connectivity is adopted to segment the parking area into a plurality of sub-areas; an outlier grid and an abnormal value are removed, and a functional area with actual operation significance is formed; determining a ship entry and exit main channel; identifying an area with significantly unbalanced entry and exit point distribution; extracting a track section of the ship from the port entry point to the first mooring point, and displaying the track section in a thermodynamic diagram form; and segmenting the region into a plurality of sub-regions by adopting a connectivity-based clustering method, removing an outlier grid, and finally dividing a main channel. The method has the advantages that accurate recognition and dynamic segmentation of multiple types of functional areas in a complex port environment are achieved, and the spatial index efficiency and the expandability of practical application are remarkably improved.

The invention provides a block chain network data transmission method and system, and the method comprises the steps: enabling each node to construct a five-layer binary tree based on the recursion of each character of Geohash coding, finally forming n binary trees, and enabling each tree to represent a geographic division of a different level; during first-round broadcasting, data information is diffused from an initiating node to a representative node in an area corresponding to a first leaf child node corresponding to a first character of a current node through a first binary tree; then, during step-by-step diffusion based on the propagation trees, the representative nodes receiving the data in each region can be propagated step by step along the second tree, the third tree, the fourth tree,..., and the nth tree based on the own propagation trees, and the representative nodes in the leaf region of each tree are responsible for propagating the data to the representative nodes in the next leaf sub-region; and the data finally arrives at the node with the minimum XOR distance in the k buckets. According to the invention, the data information can be efficiently diffused to the whole network in a shorter hop count, so that the data confirmation time is reduced.

The application relates to the technical field of games, in particular to a one-dimensional mapping positioning method for games, which comprises the following steps: collecting spatial coordinate data of game objects, constructing a regular gridded game map, and establishing a unified coordinate system; converting two-dimensional coordinates of the map into binary cross combination and decimal conversion to generate GeoHash codes suitable for the regular gridded game map; constructing a quadtree storage system, aggregating and storing the game objects in corresponding nodes according to the coding prefix association relationship, and dividing hot storage areas and cold storage areas in the nodes according to the position update frequency of the game objects; receiving a search request containing a center coordinate and a search radius, converting the center coordinate into a GeoHash code and intercepting a target prefix, optimizing the search precision by dynamically adjusting the coding prefix length, and accurately positioning the spatial position of the target game object within the search radius through multidimensional filtering and screening. The scheme can accurately position the spatial position of the game object through multidimensional screening.

The invention relates to a geographic interest point retrieval method based on tree sampling and a large language model. The method is suitable for location-based service scenes such as map navigation and online travel. The core process of the method comprises the following steps of: mapping a POI geographic coordinate into a character string through Geohash coding, and constructing a prefix tree index; sampling positive and negative samples on the basis of a spatial proximity strategy of a prefix tree, and training a representation model with spatial semantic expression ability in combination with unsupervised spatial contrast loss; and recalling a candidate POI set through a vector database, constructing a Prompt template by the candidate POI set and user query, inputting a large language model after LoRA fine tuning, and completing semantic rearrangement in combination with a retrieval enhancement generation (RAG) mechanism. According to the scheme, unified modeling of geographic space and text semantics is achieved, the comprehensive matching precision of retrieval results is effectively improved, dynamic changes such as POI addition and position change can be rapidly adapted, the cross-region and cross-domain generalization ability is achieved, and a more accurate and efficient retrieval solution is provided for various position-based service systems.

The invention provides a mobile terminal security protection design method based on edge intelligence, which comprises the following steps: firstly, performing security threat assessment on a mobile intelligent terminal based on a graph and a topological potential function, and determining the importance degree of each node in a threat graph by calculating the entropy value of each node in the threat graph, thereby achieving the purpose of performing security assessment on the mobile intelligent terminal; secondly, based on the GeoHash technology of the geographic position, the mobile intelligent terminals and the Mobile nodes in the same range are organized into a group, a mobile intelligent terminal with high computing power is arranged in the group to serve as an edge server, the defect of resource information of a single edge server node is overcome by utilizing the convenience of P2P network information sharing, and the service life of the edge server node is prolonged. And sharing and distributed storage of DoS attack information are realized. And finally, the edge server counts idle resources of the standby edge server in the group in real time, when the edge server is subjected to DoS attack, attack traffic is forwarded to nodes of the standby edge server in the group, and the DoS attack is relieved through traffic load balancing, so that the safety protection capability of the edge server is improved.

The application belongs to the technical field of charging facilities, and discloses a charging station site selection and capacity configuration optimization method based on multi-source space-time data, which collects six-dimensional full multi-source space-time data of vehicles, power grids and the like, divides basic and vehicle-end characteristic data categories, performs full-process standardized processing, completes exception correction, missing completion and unification of CGCS2000 space coordinate system and dynamic time granularity, also realizes vehicle-network space-time calibration and builds an integrated index database of GeoHash coding; improves planning basic data precision, eliminates space-time matching deviation of different data sources, realizes rapid retrieval and linkage query of vehicle-network charging data; through construction of a three-level space-time constraint system, high feasibility alternative stations are screened, multi-dimensional decision variables are determined and a site selection-capacity-vehicle-end adaptation collaborative correlation matrix is built, five core multi-objective optimization directions are established, and an improved NSGA-III algorithm is used for solving and sorted by an entropy weight-TOPSIS method.

The application discloses a nearest neighbor query optimization algorithm of GeoHash, and based on inherent geometric characteristics of GeoHash, by mining the inherent correlation between the geometric characteristics of the GeoHash grid and the spherical constraint, a judgment tool optimized specially for the grid level comparison is constructed, and unified processing from the grid to the point level judgment is realized; in view of the difficulty of the nearest neighbor query, a multi-level progressive pruning architecture is innovatively proposed based on the spatial distribution physical characteristics, the accurate calculation complexity is reduced to the minimum through a distance factor pre-computation model, and a complete optimization solution is provided for large-scale spatial data retrieval.

The invention discloses a range query method for multi-layer data with spatial attributes of a smart city, which comprises the following steps: an index construction stage: creating a spatial index table with a uniform structure for a plurality of Geohash precision levels in advance, and inserting the spatial attributes of all data layers into one or more covered Geohash cell partitions according to geometrical shapes of the spatial attributes, and meanwhile, the non-spatial attributes are independently stored. In the query execution stage, after a query request is received, an optimal Geohash precision level is dynamically selected according to a query radius, intersected Geohash cells are calculated, a candidate object set is quickly retrieved from a corresponding index table, a final result is screened out through precise geometric filtering, and finally complete attribute information is assembled. The problem that an existing NoSQL database is low in supporting efficiency for complex space query, especially cross-multi-layer joint query is solved, and high-performance and high-concurrency-range query for mass urban space data is achieved.

This application relates to Geographic Information System (GIS) technology and discloses a method for converting geofences into geohash blocks. By dynamically adjusting the bit depth of the geohash algorithm based on the approximate extent of the geofence, the accuracy of the subsequently generated geohash blocks is adapted to the specific geofence. Furthermore, by sequentially filtering geohash blocks associated with the smallest bounding rectangle of the geofence, a ray casting method is used to detect whether the filtered geohash blocks are simultaneously associated with the geofence. The geohash blocks associated with the geofence are recorded as the output, thus accurately converting the geofence into the corresponding geohash block. This application also discloses an apparatus, electronic device, and computer-readable storage medium for converting geofences into geohash blocks. The purpose of this application is to achieve accurate conversion of geofences into corresponding geohash blocks.

A data processing service executes a new forward and reverse geohashing process that is correct up to a threshold geohash precision. The forward and reverse geohashing processes described are correct for precisions up to 18, where a precision corresponds to 5 geohash bits. The forward geohashing process gives correct results for precisions up to 19, and the reverse geohashing process gives correct results for precisions up to 20. The geohashing methods described herein is configured to perform a relatively small number of floating point and integer operations to avoid the iterative nature of existing geohashing processes. Moreover, the transformations are completed in an accurate way while saving more computational power compared to existing geohash algorithms.

This invention provides a method, apparatus, electronic device, and storage medium for determining GeoHash codes. First, the minimum bounding rectangle of the region to be identified is determined. Next, the GeoHash codes corresponding to the vertex grids containing any three vertices of the minimum bounding rectangle are determined. Then, based on the GeoHash codes of the three vertex grids, a preset character table is looked up multiple times to determine the GeoHash codes of all grids within the minimum bounding rectangle. Finally, from the GeoHash codes of all grids, the GeoHash codes of each target grid that overlaps with the region to be identified are selected. In this invention, the preset character table includes 32 characters from a Base32 encoding table, and the positions of these 32 characters in the preset character table are determined based on the encoding principle of GeoHash codes. Therefore, the GeoHash codes of all grids within the minimum bounding rectangle can be determined by looking up the table. Compared to the multiple encoding conversions in existing technologies, this invention uses a table lookup method, reducing the computational load and improving the computational speed.

The present invention proposes a spatio-temporal semantic query optimization method that integrates an attribute graph database and a relational database. It belongs to database querying, and uses a hybrid storage method of GDBMS and RDBMS to manage spatio-temporal data, and optimizes the indexing of spatio-temporal entities through specific indexing strategies. In the time dimension, MTT indexing and time table partitioning are used; in the space dimension, Geohash encoding is adopted for partitioning. A spatio-temporal entity semantic link between databases is established through an entity association mechanism based on object mapping. The hybrid query is converted into executable sub-queries for GDBMS and RDBMS, and data synchronization is performed between the two databases. The method of the present invention can bridge the attribute graph and the spatial engine to achieve efficient spatio-temporal semantic querying. The cross-database spatio-temporal encoding index accelerates graph traversal and pattern matching. It supports customizable geo-spatio-temporal analysis and enhances semantic representation capabilities. The lightweight and low-code architecture is conducive to integration with existing GIS platforms.

The invention discloses a block chain-based big data information security management method, which comprises the following steps of: constructing a hierarchical block chain architecture which comprises a core chain and a plurality of sub-chains, and recording chain head hash values, data storage positions and access permissions of the sub-chains by the core chain; collecting features of to-be-stored data, and generating a feature data set in combination with Geohash coding; constructing a priority division model based on a linear weighting algorithm and a TOPSIS algorithm, and performing priority division on the data features in the feature data set to generate priority scores; dynamically distributing the to-be-stored data to a high-security-level sub-chain or a low-security-level sub-chain through a cold and hot separation storage strategy; recording a data storage index and an access permission to the core chain; analyzing a query request of a user by using the core chain, distributing the query request to the corresponding sub-chain, and returning a query result to the core chain after the sub-chain processes the query request in parallel; and verifying the access authority of the user through the core chain, and reading the data stored in the corresponding sub-chain according to the query result after the verification is passed.

The invention discloses a WAN (wide area network) RTK (real-time kinematic) enhanced service resolving and broadcasting method based on GeoHash, which comprises the following steps of: coding positions of virtual reference stations in a service area to obtain a virtual reference station set; matching a nearest neighbor base station for each virtual reference station in the virtual reference station set, and carrying out base station networking; when detecting that the data of the reference station is abnormal or the newly added reference station is accessed, triggering a reference station dynamic recombination network based on GeoHash coding; and receiving a request of a moving station, and performing virtual observation data broadcasting based on GeoHash coding. According to the method, the computational efficiency challenge confronted when a large-scale base station generates high-precision differential data in real time in a wide area range is overcome, and the performance bottleneck problem of quick matching of virtual grid points and real-time broadcasting of the differential data under the scene of concurrent requests of massive users is solved.