Research on multimodal railway spatio-temporal data architecture and fusion processing technology

With the multimodality of railroad spatio-temporal data and the surge of data volume, as well as the recent vigorous promotion of the transformation of Xinchuang Adaptation, resulting in a large number of different types of data have not been realized based on the domestic data software organization architecture. At the same time, large-scale data require a large amount of storage space and computing resources for processing and analysis, and a substantial data storage and processing infrastructure needs to be established to ensure data security and high efficiency. To solve the above problems, it is imperative to build a standardized spatio-temporal data architecture as well as an efficient fusion processing flow. This paper proposes a benchmark architecture of railroad high-precision spatio-temporal data based on the linear coordinate system and researches the lightweight processing technology of large-volume multi-scale 3D model data, standardized fusion processing technology of railroad high-precision spatio-temporal data, and on-demand high-efficiency accessing technology of railroad linear spatio-temporal sequence data based on the domestic GIS engine. The result surfaces: constructing multimodal railroad spatio-temporal data architecture can bring more efficient, safer and smarter railroad operation and management effects, and lays the foundation for the development of railroad digital twin systems.