8 results about "Spatiotemporal database" patented technology

This invention discloses a deep learning method and system for generating trajectory data that supports heterogeneous data fusion, belonging to the fields of smart cities and smart transportation. The invention first acquires multi-source heterogeneous data such as GPS and traffic monitoring video, and performs a preprocessing process. Then, using a divide-and-conquer strategy, an attention-based RNN model predicts pedestrian trajectories, and a fusion model combining macroscopic traffic flow and GNN predicts vehicle trajectories, introducing multimodal features to generate a high-precision set of predicted trajectories. A spatiotemporal database is constructed to create a composite index for each trajectory. Finally, a digital twin system integrating these prediction results is built to achieve dynamic rendering and evolution. This invention effectively solves the problem of multi-source heterogeneous data fusion and significantly improves trajectory prediction accuracy.

The application discloses a kind of based on machine learning's main girder erects elevation adjustment method, belong to elevation adjustment technical field, this method constructs space-time database by gathering the data of no cable section construction period;Adopt the mixed model of LSTM-Transformer to process time series data, extract long-period characteristic, output initial predicted value of elevation;Nonlinear variable such as the change rate of cable force, sunshine gradient and material age is analyzed using XG-Boost algorithm, and compensation factor is output;Fusion and generate joint predicted value;Construct reinforcement learning intelligent agent, with construction stage as state space, elevation adjustment quantity as action space, the deviation of predicted value and measured value and construction stability are minimized as reward function, and output adjustment instruction;According to driving hydraulic system, adjust erecting elevation, and real-time update database.The application improves the precision and stability of elevation adjustment by multi-dimensional data fusion and intelligent optimization.

This invention belongs to the field of stellar positioning and navigation technology, and particularly relates to an auxiliary altimetry method for stellar positioning. The method includes constructing a three-dimensional spatiotemporal coordinate system, collecting raw altimetry data, constructing a three-dimensional spatiotemporal database, analyzing the spatial and temporal correlations of measurement points, calculating the spatial and temporal correlations between different measurement point areas and surrounding measurement point areas in the latitudinal and meridional directions, identifying correlated data based on the correlation of the altimetry data, eliminating other invalid samples without correlation, and performing spatiotemporal weighted fusion based on the spatial correlation of adjacent measurement points and the temporal correlation at different times to obtain fused altimetry data. This application integrates the spatial correlation of measurement points during the altimetry data acquisition process, as well as the temporal correlation attributes of the same measurement point at different times, into the verification statistics of the altimetry data results, providing a data foundation for subsequent output verification of altimetry data and correction of erroneous data.

This invention discloses a method and system for designing a spatiotemporal database of land value, applied in the fields of spatial geographic information data processing and image correction technology. The method involves acquiring spectral remote sensing image data; performing geographic coordinate matching on the spectral remote sensing image data to generate coordinate spectral remote sensing image data; digitally rasterizing the spectral remote sensing image data using a digital elevation model to generate point cloud data; performing 3D reconstruction based on the point cloud data to obtain a 3D terrain model; performing boundary region reconstruction processing on the 3D terrain model to obtain a reconstructed model; extracting ground features from the reconstructed model to obtain ground feature data; and constructing a spatiotemporal database by spatiotemporally indexing the ground feature data. This method can correct the brightness of edge defects of interval-type and linear ground features based on predicted brightness changes, significantly reducing grayscale distortion in 3D images and eliminating blurring caused by interference.

The present application relates to the field of traffic infrastructure digital twinning, and aims to provide a large traffic infrastructure full life cycle immersive traceability system and interaction method based on spatial imaging, so as to realize the fusion management, efficient traceability and collaborative decision of the full life cycle data of large traffic infrastructure. The technical scheme of the present application comprises: a multi-source data access and fusion engine for accessing and processing multi-source heterogeneous data from different sources; a three-dimensional space-time database for storing and associating multi-source heterogeneous data to form space-time objects; a progressive immersive interaction and rendering engine for reading data of the three-dimensional space-time database and rendering a three-dimensional scene in a spatial imaging environment and a collaborative interaction terminal; a spatial imaging environment and a collaborative interaction terminal for presenting the three-dimensional scene rendering through projection mode to realize the visual display of the infrastructure; and a server for running the multi-source data access and fusion engine, the three-dimensional space-time database and the progressive immersive interaction and rendering engine.

The application provides a data intelligent analysis method and system applied to carbon emission monitoring, and comprises the following method: a dynamic non-negative row vector is obtained by executing an NMF load decoupling algorithm, the dynamic non-negative row vector comprises a resident coefficient and an industrial coefficient, carbon emission intensities of residents and industries corresponding to a current period are calculated according to the non-negative row vector and a space-time database, and are updated to the space-time database; future carbon emission prediction values corresponding to future different periods are calculated and generated according to the space-time database; and abnormality detection calculation is performed according to the carbon emission intensity and the future carbon emission prediction values corresponding to the current period. By using the above method, the carbon emission intensity situation of the whole region can be indirectly reflected intuitively, in real time and in a non-falsifiable manner.

This invention discloses a method and system for dynamic obstacle avoidance path planning for robots. The method includes: collecting data such as images and UWB tag coordinates from multiple mobile robots via an edge computing terminal, and using this data to construct a dynamic environment spatiotemporal database; preprocessing the collected images; identifying and classifying static and dynamic obstacles; outputting their feature information and motion vectors; obtaining the reliable weights of each robot; predicting the future position and trajectory of dynamic obstacles; forming predicted risk areas; using static landmarks to correct positioning errors; dynamically adjusting obstacle avoidance strategies and path planning; generating collaborative scheduling instructions to guide local obstacle avoidance or global task reallocation; and recording detailed execution logs. By implementing the method of this invention, robot swarms can achieve high-precision, low-latency, continuous, and safe autonomous obstacle avoidance and path planning in complex dynamic environments.

This invention discloses an intelligent decision-making method and system for assessing the suitability of urban industrial layout, relating to the field of urban planning and regional development. The method includes: collecting multi-source heterogeneous data of the target urban area to establish a standardized spatiotemporal database; constructing an initial assessment factor system based on the standardized spatiotemporal database; loading the standardized spatiotemporal database into three-dimensional geographic information units to construct an urban multi-agent simulation environment; using a causal inference engine, calculating the causal net effect of candidate industrial layout schemes on preset urban indicators based on historical data in the standardized spatiotemporal database, and generating a causal net effect assessment report; and fusing the real-time data of the initial assessment factor system, the current state of the urban multi-agent simulation environment, and the causal net effect assessment report to generate a dynamic decision state vector. This achieves a leap from static location assessment to dynamic path planning, improving the foresight of industrial layout decisions.