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A spatiotemporal intelligent framework and experimental platform for urban digital twins

Virtual Reality & Intelligent Hardware 2023年第3期5卷 213-231页

作者： Jinxing HU Zhihan LV Diping YUAN Bing HE Wenjiang CHEN Xiongfei YE Donghao LI Ge YANG Shenzhen Institute of Advanced Technology Chinese Academy of SciencesShenzhen 518055China Department of Game Design Faculty of ArtsUppsala UniversityUppsala SE-75105Sweden Shenzhen Urban Public Safety and Technology Institute Co.Ltd Shenzhen 518172China

Backgrounds This work emphasizes the current research status of the urban Digital Twins to establish an intelligent spatiotemporal framework.A Geospatial Artificial Intelligent(GeoAI)system is developed based on the Geographic Information System and Artificial *** integrates multi-video technology and Virtual City in urban Digital *** Besides,an improved small object detection model is proposed:YOLOv5-Pyramid,and Siamese network video tracking models,namely MPSiam and FSSiamese,are ***,an experimental platform is built to verify the georeferencing correction scheme of video *** The MultiplyAccumulate value of MPSiam is 0.5B,and that of ResNet50-Siam is ***,the model is compressed by *** inference speed has increased by 3.3 times,reaching 83 Frames Per Second.3%of the Average Expectation Overlap is ***,the urban Digital Twins-oriented GeoAI framework established here has excellent performance for video georeferencing and target detection problems.

关键词： spatiotemporal intelligence Urban digital twins Geographic information system Artificial intelligence Small target detection

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Network SpaceTime AI:Concepts,Methods and Applications

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Journal of Geodesy and Geoinformation Science 2022年第3期5卷 78-92页

作者： Tao CHENG Yang ZHANG James HAWORTH SpaceTimeLab Department of CivilEnvironmental and Geomatic EngineeringUniversity College LondonLondon WC1E 6BTUK

SpacetimeAI and GeoAI are currently hot topics,applying the latest algorithms in computer science,such as deep learning,to spatiotemporal *** deep learning algorithms have been successfully applied to raster data due to their natural applicability to image processing,their applications in other spatial and space-time data types are still *** paper sets up the proposition of using a network(&graph)-based framework as a generic spatial structure to present space-time processes that are usually represented by the points,polylines,and *** illustrate network and graph-based SpaceTimeAI,from graph-based deep learning for prediction,to space-time clustering and *** applications demonstrate the advantages of network(graph)-based SpacetimeAI in the fields of transport&mobility,crime&policing,and public health.

关键词： spatiotemporal intelligence network graph deep learning spatiotemporal prediction spatiotemporal clustering spatiotemporal optimization

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