Integration of cyber-physical systems and IoT in cloud-based health care solutions: a systematic review
TL;DR
The findings show that CPS-IoT-cloud systems support improved patient monitoring, enhanced data analytics, real-time decision support, remote healthcare delivery, personalized care, and operational efficiency, but a gap between technical feasibility and deployment readiness is revealed.
Abstract
The convergence of cyber-physical systems (CPS), the Internet of Things (IoT), and cloud-based technologies is reshaping healthcare delivery through real-time monitoring, remote diagnostics, personalized service, and data-driven decision-making. However, evidence on their combined integration remains fragmented, particularly regarding implementation barriers, security, interoperability, and deployment readiness. This systematic literature review synthesizes recent research on CPS-IoT-cloud computing integration in healthcare following Kitchenham’s review guidelines and the PRISMA protocol. Following the PRISMA protocol, searches of Scopus, ScienceDirect, and IEEE Xplore identified 76 records, of which 11 peer-reviewed studies published between 2020 and 2025 met the inclusion and quality criteria. The findings show that CPS-IoT-cloud systems support improved patient monitoring, enhanced data analytics, real-time decision support, remote healthcare delivery, personalized care, and operational efficiency. However, data security vulnerabilities were the most recurrent challenge, identified in 8 studies, followed by privacy concerns and regulatory compliance in 7 and 6 studies, respectively. Interoperability, scalability, computational overhead, IoT-device security, user trust, and governance also remained significant barriers. The review further reveals a gap between technical feasibility and deployment readiness, as many solutions were validated through simulations, controlled experiments, or limited testbeds rather than real clinical environments. Future research should prioritize standards-based interoperability, adaptive edge-fog-cloud architectures, lightweight security, privacy-preserving AI, real-world clinical validation, and lifecycle sustainability. Overall, successful adoption depends on translating technological advances into secure, scalable, interoperable, clinically reliable, and governance-ready healthcare systems.