207 results about "Spatial maps" patented technology

The invention provides a three-dimensional space collision avoidance system based on multiple tower cranes, and relates to the technical field of port hoisting operation, a three-dimensional voxel grid VoxelGrid space map is constructed, and the three-dimensional space collision avoidance system comprises a first horizontal coverage map, a second descending coverage map, a third fan-shaped area occupation map, a fourth track occupation area map and a fifth interference area map; the system can identify the space overlapping area of the tower crane operation path at the voxel level, breaks through the limitation of the traditional path planning method on the dimension and precision of space modeling, and enhances the fine granularity and accuracy of collision detection. A dynamic acquisition module and a dynamic interference module are introduced, dynamic disturbance caused by factors such as stormy waves and tides on a ship in a port operation environment can be sensed in real time, the deviation trend of the tail end of the lifting appliance is predicted, target correction and track compensation are carried out before track execution, and the situation that the lifting appliance is accidentally touched or falls off due to track drifting is effectively promoted to be reduced.

The invention discloses a hybrid network method for hyperspectral image water quality inversion, and relates to the technical field of hyperspectral image analysis. The model comprises a spectral feature extraction module, an improved Transform encoder, an LSTM (Long Short Term Memory) module, a cross-time attention module and an adaptive feature fusion module. The model extracts spatial and spectral features through a deep convolutional network, enhances feature expression by using multi-scale embedding and an attention mechanism, and optimizes prediction precision in combination with a dynamic weight fusion strategy. Through end-to-end training of the model, water quality parameters (total nitrogen, dissolved oxygen and the like) in a hyperspectral image can be effectively estimated, and a spatial map of water quality distribution is generated. Compared with a traditional method (such as support vector regression, partial least square regression and the like), the hybrid network provided by the invention has the advantage that the accuracy and robustness of water quality parameter inversion are remarkably improved. Experimental results show that the method has excellent performance in a complex water body environment, and an efficient and reliable technical means is provided for accurately monitoring and evaluating water quality pollution.

The invention discloses a database-based space conflict treatment method and device and a medium, and relates to the technical field of electric digital data processing. The method comprises the steps of determining conflicting pattern spots with conflicts in space pattern spots through a preset space analysis function according to a geometrical relationship between the space pattern spots corresponding to a planning land in a space database; analyzing the spatial relationship and the ownership planning relationship corresponding to the conflict pattern spots to determine the conflict intensity corresponding to each conflict pattern spot; based on the spatial relationship network, determining a hotspot conflict area with spatial aggregation according to the conflict intensity; determining treatment priorities corresponding to the conflict pattern spots according to a descending order of the conflict intensity, and adjusting the treatment priorities of the conflict pattern spots according to conflict linkage paths among the conflict pattern spots in the hotspot conflict area; and generating a space governance path in the hotspot conflict area through the adjusted governance priority, so as to realize the space conflict governance of the planned land through the space governance path.

The invention discloses a three-area three-line database automatic quality inspection evaluation method based on deep learning. The method comprises the following steps of S1, obtaining three-area three-line database data and performing preprocessing; s2, checking a directory structure and a file name of the original data set; s3, extracting spatial layer data from the hierarchical data set; s4, performing segmentation and attribute information extraction on various pattern spots in the layer data after spatial verification; s5, inputting the pattern spot relation characteristic data into an artificial fish swarm algorithm; s6, automatically comparing the pattern spot area and distribution data with a quality inspection standard preset in a three-area three-line database; and S7, performing parallel processing on an automatic comparison result through a multi-thread thread pool. According to the method, an artificial fish swarm algorithm, a relational attention network and a task allocation and thread pool management technology are combined, and three-area three-line database automatic quality inspection evaluation based on deep learning is realized.

The invention relates to a few-sample image classification method based on hyperbolic space image-text local feature alignment, and belongs to the technical field of image recognition and artificial intelligence, and the method comprises the steps: generating word-level attribute description for a support set image through employing a multi-mode large language model; encoding the image and the text by adopting a vision-language model; constructing a hyperbolic local feature alignment module in a hyperbolic space, screening most relevant image local features for text local features by calculating hyperbolic cosine similarity, and fusing by using hyperbolic weighted average; designing a hyperbolic cross attention module, and aggregating key information from the multi-modal local features of the support set to construct a category prototype by taking query image aggregation features as guidance; and finally performing classification based on the hyperbolic geodesic distance. According to the method, the hierarchical modeling capability of the hyperbolic space and the semantic priori knowledge of the large language model are fully utilized, fine-grained multi-modal feature alignment is realized, and the small sample image classification performance is improved.

The invention discloses an intelligent flight route planning method and system for a low-altitude logistics aircraft, and the method comprises the steps: obtaining the three-dimensional space map data of the current position of the aircraft, including the coordinate information of a building and a telegraph pole, and the boundary range of a no-fly zone; acquiring wind speed, wind direction and rainfall data of the current area from a meteorological data source, and calculating meteorological impact factors by combining aircraft performance parameters; dynamically adjusting the candidate flight routes according to the maneuvering characteristic parameters of the aircraft, and calculating the flight time, the energy consumption cost and the safety risk score of each route; meteorological changes in the flight process are monitored in real time, and if the meteorological conditions exceed a preset threshold value, the meteorological data are obtained again, and the meteorological influence factors are updated; and carrying out local optimization adjustment on the current flight route according to the updated meteorological influence factor, generating a new flight route segment and replacing the original segment.

According to one embodiment, a method, computer system, and computer program product for dynamic image reconstruction is provided. The present invention may include training a physics-informed neural network (PINN) using received training data; receiving wind field velocity measurements in a geographical domain from one or more weather information sources and air pollutant concentration measurements of one or more air pollutants from the geographical domain using a sparse sensor network to produce a plurality of input data; processing the plurality of input data through multiple physics-informed masked convolutional layers in the trained PINN to perform a three-dimensional partial convolution process; and performing the dynamic image reconstruction on the processed plurality of input data using the trained PINN to generate a reconstructed continuous spatial map of the geographical domain.

The invention discloses a mangrove forest distribution information extraction method based on deep learning and remote sensing images, and the method comprises the steps: firstly, constructing a spatial diagram fusing ecological priori knowledge such as hydrological connectivity, and extracting high-dimensional features containing a complex space-time dependence relation from an irregular satellite image time sequence through employing a PG-STGT network; a physical information guided antagonism decoupling mechanism is subsequently adopted to explicitly decompose the high-dimensional feature into three subspaces. And finally, according to the method, a high-robustness distribution diagram is generated by applying the decoupled identity feature vectors, and a multi-dimensional mangrove forest health index is generated by using residual error abnormal features. According to the method, the physical mechanism and deep learning are deeply fused, the time consistency of the classification result is improved, and the ability of diagnosing the health condition of the ecological system is provided.

The invention discloses a spatio-temporal feature fusion modeling method for multi-source sensing data, and relates to the technical field of data processing, and the method comprises the steps: obtaining multi-source original spatio-temporal data of a sensor, including densely distributed data and sparse dotted data; for the dense distribution data, extracting statistical distribution characteristics of the process state data, calculating an operation entropy and an operation temperature, and generating regional dynamic characteristic data; for sparse point data, extracting space and time sequence statistical characteristics of environment parameters, calculating environment difference degree and environment stability, and generating regional environment characteristic data; generating target spatio-temporal feature data based on unified spatio-temporal granularity alignment, asynchronous missing detection and dynamic interpolation; modeling is carried out through a time sequence branch, a space map branch and a cross-source fusion branch, and a prediction result is output; the sensing accuracy and the prediction reliability of the industrial operation environment coupling system are improved by introducing the dynamic characteristics and the environment characteristics.

The invention relates to the technical field of image recognition, in particular to a method and system for early warning below a portal crane, and the method comprises the steps: obtaining site environment sensing data, constructing a space map, and recognizing the position and motion state of equipment in real time; predicting an equipment motion track and a load swing range, and generating a predicted dangerous area; image acquisition devices are installed at a plurality of fixed positions, field images are acquired, an image recognition model is used for detecting a target, and the spatial position and the posture state of the target are obtained; tracking a target trajectory based on a motion estimation model and predicting a future position of the target trajectory; dynamically switching the image acquisition devices according to the motion state of the equipment; and comparing the future position of the target with the predicted dangerous area in real time, when the future position and the predicted dangerous area coincide, carrying out potential interference prediction, calculating predicted interference time, and carrying out grading processing in combination with the attitude state of the target. According to the invention, equipment dynamic perception and personnel behavior prediction are realized, and the intelligent protection capability of the operation area is improved.

According to the OPC result correction method and the result verification device thereof provided by the invention, the NILS value is introduced as an index for measuring correction quality on the basis of the existing OPC correction method, so that the absolute value of the EPE value of the target graph after OPC correction is ensured to meet the requirement of the preset EPE standard value, and the NILS value of the target graph can be improved; according to the method, the target graph after OPC correction has better spatial graph contrast, and better imaging quality is obtained in the actual exposure process, so that the problem of disconnection or bridging caused by size deviation of the target graph is effectively avoided, and further, the image quality is improved. The better spatial pattern contrast can bring better photoresist morphology and a larger photoetching process window, so that the generation of pattern defects is reduced, and the improvement of the yield of products is more facilitated.

The invention relates to the technical field of AGV intelligent control, and discloses an AGV intelligent control method and system based on end-cloud collaboration, and the method comprises the steps: obtaining the position, obstacle and environment data of an AGV in real time, constructing a dynamic space map, carrying out the grid processing, and when the channel width is detected to be not enough for safe passing, carrying out the grid processing of the dynamic space map; the method comprises the following steps: firstly, adopting an A * algorithm to quickly generate an alternative path, then carrying out multi-AGV cooperative conflict detection through path overlapping comparison, carrying out global optimization on a scheduling sequence and a passing priority of multiple AGVs by applying a genetic algorithm, and finally generating a conflict-free efficient scheduling instruction. According to the method, through multi-algorithm fusion and a real-time decision-making mechanism, the passing efficiency and the space resource utilization rate of multiple AGVs in a dynamic environment are improved.

The invention relates to the technical field of water quality monitoring, and discloses a sewage quality on-line monitoring method and system.The sewage quality on-line monitoring method comprises the steps that time alignment processing and data quality evaluation are conducted on original water quality sequences collected at all monitoring point positions, and aligned data and data quality weights are obtained; constructing a time delay space diagram; performing joint estimation on the global water quality state to obtain global state estimation and uncertainty; performing anomaly detection and identifying an abnormal propagation path and a suspected source to obtain an anomaly score and a source confidence sorting list; formulating a self-adaptive sampling strategy, and determining the sampling frequency of each monitoring point position; on the basis of the time-delay observation equation and weighted optimization, online joint estimation of the global water quality hidden state is achieved, reverse traceability is carried out by combining the residual standardization anomaly score and the time-delay space diagram, the anomaly can be found, the possible source and propagation direction of the anomaly can be located, and the pertinence and interpretability of disposal are improved.

The invention relates to a bridge crane operation attitude control method and a control system, which are used for accurately hoisting a heavy object in a narrow space, and the method comprises the following steps: obtaining operation area space constraint information to generate a space map, and determining a hoisting path and a path width; planning a driving track of the driving mechanism along the central line of the path, marking direction switching nodes, and calculating the walking distance of each straight line segment; determining an allowable maximum swing range according to the width of the lower-section path; a speed control scheme is formulated according to the walking distance and the swing space, and it is ensured that weight swing does not exceed the limit during direction switching. By actively planning the swing space and intelligently adjusting the motion parameters, the hoisting efficiency is remarkably improved while the safety is guaranteed.

A robotic device scans at least a portion of an environment. The robotic device includes one or more LiDAR sensors to scan the environment. A management system receives sensor data generated by the one or more LiDAR sensors to determine a three dimensional (3D) point cloud representing at least the portion of the environment. A layout of the environment is determined, where the layout represents a location of objects within the environment. At least one discrepancy between the 3D spatial map and the layout is determined. Based at least in part on at least one discrepancy, a map of the environment is generated.

In various examples, embodiments are directed to identifying map data (e.g., relevant to a route) using a quad-tree spatial index. In this regard, spatial map data that indicates various map features is represented in a quad-tree spatial index for use in identifying map data. To identify map data, bounding shapes may be generated in association with various segments of a route. An indication of an object-oriented bounding shape may be used to query the quad-tree spatial index to identify map data related to the object-oriented bounding shape. In embodiments, an object-oriented spatial index may be generated that indexes the object-oriented bounding shapes associated with the route. The object-oriented spatial index may be used to query the quad-tree spatial index to identify map data related to the corresponding object-oriented bounding shapes. Alternatively, the quad-tree spatial index may be used to query the object-oriented spatial index to identify map data.

The invention provides a large-space real-time positioning method and system based on SLAM and visual graphics, and relates to the technical field of space positioning and intelligent navigation, and the method comprises the steps: obtaining a space scene image and an environment point cloud, and carrying out the preprocessing; detecting the scene image based on a deep learning target detection model, and identifying a dynamic target and a corresponding category and a bounding box; static space feature points of the environment point cloud are reserved, and an initial space point cloud map is constructed; oRB feature extraction is carried out on the static spatial feature points to obtain feature descriptors, and a spatial visual feature map is constructed; performing joint optimization on the initial spatial point cloud map and the spatial visual feature map to generate a multi-modal global spatial map; the dynamic target is subjected to pose estimation in combination with space inertial measurement information to obtain an initial pose, and the initial pose is optimized to obtain a final pose, so that the positioning precision and robustness in a large-space dynamic environment can be improved, the consistency of a multi-modal map can be optimized, and the positioning stability in the dynamic environment can be enhanced.

The invention relates to the technical field of intelligent transportation, and particularly discloses a site selection optimization method and system for a temporarily-built plant station of a highland mountainous area expressway. The method comprises the following steps: acquiring functions of a concrete mixing station, a precast beam field and a temporarily-built plant station of a steel bar processing plant to obtain a BIM risk simulation program; acquiring a plateau mountainous area live-action three-dimensional model, and fusing the plateau mountainous area live-action three-dimensional model with a BIM risk Acquiring geological and climate data, converting the geological and climate data into a GIS space map layer, and associating the GIS space map layer with a BIM risk simulation program; a built-in geological taboo rule is set, rasterizing scanning is automatically carried out on the whole domain, and a high-risk area is eliminated; dangerous source identification is carried out on terrain risks, climate risks and construction interaction risks; according to the identification risk type and grade, recommending a protection structure and generating a BIM component; and automatically generating a plurality of site selection coordinates and a plant station layout optimization scheme. According to the method, the period of traditional site selection and protection design is shortened, and meanwhile the scientificity and economical efficiency of the scheme are guaranteed.

The invention relates to the field of map data processing, and particularly provides a railway space data processing and integrating method based on a GIS (geographic information system) map, which comprises the following steps: constructing a geographic information system by adopting a distributed resource management technology; a containerization and micro-service architecture is adopted, businesses of the geographic information system are split into independent service units, and the independent service units run in a Docker container; integrating the basic base map data, constructing a basic spatial data resource pool, establishing railway thematic data, loading map data, performing data analysis and processing, and constructing a railway spatial map; dynamic updating and interaction effects of the railway space map are realized by processing user input events; railway facility information is superposed on a railway space map in a layer form by adopting a layer superposition technology, so that visual display of railway space information is realized. Based on a GIS one-map service mode, integration and sharing exchange of spatial information resources are achieved, and all-weather reliable support is provided for railway space application.

Systems and methods for generating high-resolution spatial maps of microbiome and physicochemical indices for an agriculture site are provided. The spatial maps are generated from a limited / reduced number of physical samples acquired using a smart sampling tool provided by the systems and methods described. Insights for the agriculture site can be used to guide selection and application of interventions, according to various intervention archetypes, based upon the customized needs of the agriculture site. Performance of the agriculture site can thus be enhanced in an unprecedented, accessible, and sustainable manner.

The invention discloses a sparse space map and dynamic path fused indoor AR navigation system and method, and relates to the technical field of augmented reality navigation, and the system comprises a sparse map construction module, a man-machine interaction adaptation module, a landmark mark management module, a dynamic path fusion module and an AR navigation execution module. The sparse map construction module is used for realizing three-dimensional reconstruction and persistent storage of an indoor scene, the man-machine interaction adaptation module is used for resolving ground height parameters in real time and dynamically correcting a space coordinate system, and the landmark marking management module is used for generating an editable marking object containing space coordinates and attribute data. The dynamic path fusion module is used for carrying out topological association on a user-defined path and an algorithm planning path, the AR navigation execution module is used for realizing path visualization and path dynamic optimization through a path matching algorithm and realizing AR navigation, and the defects that an existing indoor navigation technology is low in positioning precision, high in mapping cost and poor in dynamic adaptability can be overcome.

The invention discloses a crowdsourcing digital information trace leaving system and method for an augmented reality environment, and relates to the technical field of augmented reality, the system comprises a client device and a cloud server, and data interaction is carried out between the client device and the cloud server; wherein the client equipment comprises an environment sensing module, a positioning module and a digital nick processing module; the cloud server comprises a map index module, a digital nicking module, a management module and an operation calculation module; the environment sensing module senses the environment and its own position based on a sensor. Professional team acquisition is replaced by a crowdsourcing mode, construction and dynamic extension of a global high-precision AR space map are realized at extremely low cost, and the core pain point of industry high-cost mapping is solved; the four interaction media cover discrete information marking-spatio-temporal backtracking-3D creation-2D anchoring of a whole scene, deep binding of digital information and a physical space is achieved, unprecedented AR social immersion is provided, and a sustainable profit mode is provided for a platform.

The invention provides a building information model and city information model cross-scale consistency three-dimensional modeling method based on space intelligence. The method comprises the following steps: extracting a three-dimensional geometric patch set from an original building information model, constructing an initial modeling object and a component space diagram, and calculating a transformation operator through footprint matching to realize automatic alignment; the user-defined family attributes are analyzed to execute cross-scale semantic mapping, semantic classification information is generated, and a building shell model is generated through geometric generalization processing; opening features are extracted and mapped to the shell model, three-dimensional topology reconstruction is executed in combination with the component space diagram, and city information model target components with topology closing performance are generated. And finally, performing incremental updating based on the alignment deviation. According to the method, the problems of inaccurate geographic alignment, geometric degradation and semantic loss in cross-scale model fusion are solved, and the logic leakproofness and data maintenance efficiency of urban digital twin base modeling are effectively improved.

In one aspect, a device management platform is provided. The device management platform includes environmental sensors and a host system. The environmental sensors are deployed at different locations within a gaming venue, each including at least one sensor configured to capture environmental data at one of the different locations. The host system is configured to receive, from the environmental sensors, the environmental data, identify spatial data that defines a floor layout of the gaming venue and the different locations of the environmental sensors, correlate the spatial data with the environmental data to generate a spatial map of the environmental data within the gaming venue, and identify a subscriber for the spatial map. The host system is further configured to determine, based on the subscriber, access rules for the spatial map, and provide, based on the access rules, at least a portion of the spatial map to the subscriber.

The invention relates to the technical field of urban thermal environment assessment and ecological space optimization, and discloses an earth surface heat island intensity assessment method, system and device and a storage medium, and the method comprises the steps: obtaining blue-green landscape fragmentation results under different window scales; determining an optimal threshold window for blue-green landscape fragmentation measurement; calculating the foreground area density of the blue-green landscape in the research area under the optimal threshold window; based on the foreground area density, carrying out fragmentation type division on the blue-green landscape to generate a blue-green landscape fragmentation type spatial distribution diagram; acquiring ground surface heat island intensity data of the research area in different time periods, and performing spatial matching with the blue-green landscape fragmentation type spatial distribution diagram; and constructing a comprehensive evaluation model. According to the method, the defects that a traditional landscape index result is abstract and is greatly influenced by unit division, and functional forms cannot be distinguished are overcome, and an intuitive and operable space map basis is provided for thermal environment regulation and control.

The invention discloses a transformer substation multi-source heterogeneous data processing method and system based on space layer superposition, and relates to the technical field of electric power data processing, and the method comprises the steps: classifying the multi-source heterogeneous data of a transformer substation based on a data structure type, and obtaining a plurality of category data sets; pre-processing the plurality of category data sets to obtain a plurality of pre-processed category data sets, and storing the pre-processed category data sets in different domains; establishing a unified model based on equipment common attributes of the transformer substation, and embedding the plurality of preprocessed category data sets into a bottom geographic distribution map based on the unified model; the bottom geographic distribution map comprises a plurality of space map layers, and each space map layer corresponds to one data type; and performing dynamic coupling on the plurality of space layers, and constructing a three-dimensional fusion model with a space-time correlation characteristic. According to the method, the technical problems of long time consumption and weak spatial dimension analysis capability of spatial correlation analysis of multi-source heterogeneous data in the prior art are solved.

This invention discloses an artificial intelligence-based method and system for visualizing urban planning, belonging to the field of data processing technology. The method includes: acquiring multi-source heterogeneous urban basic data and planning schemes to be evaluated; constructing a heterogeneous attribute spatial map through temporal denoising and feature matching; using the planning scheme as a priori excitation condition, inputting it along with the map into a multi-layer spatiotemporal perception graph neural network model with topology preservation loss, and outputting a spatiotemporal evolution prediction matrix tensor; constructing an adaptive weighted grid evaluation model based on multi-dimensional constraints such as perspective, predicted polarization gradient, and hardware load, and combining it with PID closed-loop monitoring of dynamic threshold, to reconstruct a high-efficiency urban visualization 3D chassis model with weighted allocation in real time. This invention effectively solves the problems of false connectivity distortion in traditional topology prediction and computational power collapse caused by rigid LOD distance pruning, achieving deep collaboration between highly realistic situational evolution and adaptive computational power.

A scanner includes a camera, a light source for generating a probe light incorporating a spatial pattern, an optical system for transmitting the probe light towards the object and for transmitting at least a part of the light returned from the object to the camera, a focus element within the optical system for varying a position of a focus plane of the spatial pattern on the object, unit for obtaining at least one image from said array of sensor elements, unit for evaluating a correlation measure at each focus plane position between at least one image pixel and a weight function, a processor for determining the in-focus position(s) of each of a plurality of image pixels for a range of focus plane positions, or each of a plurality of groups of image pixels for a range of focus plane positions, and transforming in-focus data into 3D real world coordinates.

This invention discloses an AI-interactive AR (Augmented Reality) cultural wall system for cultural tourism, belonging to the field of AR system technology. The surface of the cultural wall is equipped with a pre-embedded feature set, including visual markers, differentiated texture features, 3D depth variation areas, and specifically designed interactive hotspots. These features provide the system with stable visual benchmarks, semantic distinction criteria, depth cues, and precise positioning anchors. The system includes: a feature point acquisition module, used to collect the feature set on the cultural wall through a multimodal feature extraction algorithm to construct a 3D spatial map with semantic annotations; a user positioning and pose estimation module; an AI content generation engine; and a spatial adaptation and rendering module. Through the cultural wall feature set and the multi-module collaborative system, precise spatial integration of virtual content and the physical wall surface is achieved, along with intelligent dynamic content generation based on user behavior, effectively enhancing the immersion, interactivity, and personalization of the AR cultural experience.