In order to support the governance of digital business environment in free trade ports, this paper proposes a dynamic monitoring and collaborative governance framework that integrates multi-source data access, time series status recognition, cross-departmental relationship modeling, risk diagnosis and strategy generation. The system processes 1.28 million records in data streams such as administrative approval, customs declaration, tax service, enterprise feedback, logistics circulation, and public complaints, and encodes 36 indicators into a unified time series representation. The timing identification module characterizes fluctuations in market access, service efficiency, contract enforcement, and regulatory response, and a graph-based collaboration mechanism captures inter- departmental dependencies and triggers linkage disposals. Experimental results show that the model achieves 93.4% state recognition accuracy, 0.917 Macro-F1, 91.8% trend consistency rate and 90.6% governance matching degree. The linkage completion rate reaches 90.9%, and the average response time is compressed to 4.2 hours. This framework provides a more effective and computable path for the monitoring and collaborative governance of the business environment of free trade ports under dynamic conditions.
