A Study on the Architecture Design of Intelligent Public Health Prevention and Control Platforms

With the increasing complexity of infectious disease prevention and control and critical care emergency work, the traditional manual monitoring and early warning system has been difficult to meet the needs of modern public health management and regional medical coordination. To cope with this challenge, this paper constructs a whole-process medical intelligence optimization platform, based on cutting-edge technologies such as Internet of Things (IoT), 5G communication, artificial intelligence (AI) and blockchain, to realize the full-cycle medical management of pre-hospital emergency care, in-hospital treatment and post-hospital rehabilitation. The platform adopts a five-layer architecture of data collection, transmission, analysis, decision support and user interaction, and integrates edge computing, federated learning and deep learning algorithms to ensure safe data sharing and real-time processing. This paper elaborates the system architecture and key technologies of the platform, and discusses its application value in public health emergency response and personalized rehabilitation management, which provides a feasible path for the construction of a smart healthcare ecosystem.