This application provides a method and
system for campus security situation assessment and early warning based on multi-
source data fusion, relating to the field of campus
security management technology. First, it collects multi-
source data streams from campus video surveillance, IoT sensors,
information system logs, and
access control systems,
parsing out security-related event fragments. Then, it matches and associates these security-related event fragments with a pre-built campus event
knowledge base to construct a campus event network diagram. Based on this campus event network diagram, it drives
simulation and constraint-based
inference models to perform
event propagation inferences. The fusion results generate a set of snapshots of
inference scenarios. The snapshots are processed to generate representative future security scenarios and trace key event fragment sequences. Based on these, a set of campus security early warning and response instructions is generated. This invention can comprehensively and accurately assess the campus security situation and provide timely early warnings.