A SURVEY ON INTELLIGENT AND SECURE ARCHITECTURES FOR HEALTHCARE IOT SYSTEMS

Abstract

The integration of Internet of Things (IoT) devices into healthcare has accelerated the transition toward Healthcare 4.0, enabling real-time monitoring, predictive analytics, and personalized care delivery. Despite significant advances in cloud-centric, edge/fog, blockchain, and AI-enabled systems, challenges such as latency, interoperability, security, and energy efficiency continue to limit large-scale adoption. Existing reviews have largely examined these architectures in isolation, providing limited insights into their combined impact. To address this gap, this survey systematically reviews 120+ peer-reviewed studies published between 2020 and 2025 sourced from IEEE, ACM, Springer, Elsevier, and Scopus-indexed journals. The articles were identified using keywords including Healthcare IoT, Edge AI, Blockchain in IoMT, Secure Architectures, and Healthcare 4.0. This survey makes three key contributions. First, it proposes a taxonomy of intelligent and secure IoT healthcare architectures, classifying solutions into cloud-based, edge/fog-assisted, blockchain/privacy-preserving, and AI-driven frameworks. Second, it provides a comparative performance analysis of representative studies, highlighting trade-offs in scalability, latency, energy consumption, and data security. Third, it synthesizes open challenges and emerging trends such as digital twins, federated learning, 6G-enabled IoT, and energy-harvesting wearables, offering a roadmap for future research. Findings reveal that while AI-driven and edge/fog-based systems dominate recent work, practical deployment still suffers from poor interoperability, limited trust models, and regulatory constraints. A hybrid architecture that integrates cloud scalability, edge responsiveness, blockchain security, and AI-driven intelligence emerges as the most promising direction for resilient Healthcare 4.0 systems. By consolidating current progress and exposing unresolved gaps, this survey provides actionable insights for researchers, system designers, and policymakers aiming to build trustworthy, scalable, and patient-centric IoT healthcare infrastructures.