Cross-scale time series data fusion method and system for Internet of Things

The invention provides a cross-scale time series data fusion method and system oriented to the Internet of Things. The method comprises the following steps: acquiring cross-scale time sequence data from various subsystems and various types of sensors; carrying out time window sliding processing on the cross-scale time series data, wherein a processed result comprises two types of data of an equally-spaced multivariable time series and a multivariate association relationship; modeling feature fusion is carried out on two types of data of the equal-interval multivariate time sequence and the multivariate incidence relation, and synchronously, parameters are dynamically loaded and run along with a transaction processing cycle to obtain fused implicit feature data; and processing the fused implicit feature data according to specific steps, and applying the processed implicit feature data to safety monitoring, system situation assessment and inter-subsystem linkage operation decision. The system can effectively so