5G, Edge Computing, and AI for Secure and Scalable Cyber-Healthcare Interoperability

Abstract

The integration of 5G, Edge Computing, and Artificial Intelligence (AI) in cyber-healthcare interoperability aims at making healthcare data exchange more efficient, secure, and scalable. This paper suggests a new paradigm using ultra-low latency of 5G for real-time data transmission, edge computing for local data processing, and AI-driven models for intelligent decision-making. The integration of these technologies optimizes the dependency of healthcare on services by allowing reduced latency with decreased bandwidth, ensuring secure and safe data access. Mathematical modeling for network latency, edge efficiency, and the AI-driven predictive decision-making analysis is discussed below to evaluate this proposed approach with respect to all performance metrics such as data communication speed, and edge efficiency at reduced latency times. A comparative analysis with existing methods will show the proposed approach's better performance, and it will prove to be a promising solution for next-generation healthcare systems.