The integration of the Internet of Things (IoT) into healthcare is enabling more connected, personalized, and data-driven medical services. This narrative review provides a comprehensive overview of healthcare IoT architectures, focusing on core components, including wearable and implantable sensors, communication protocols, and computing paradigms such as cloud, edge, and fog computing. Interconnected technologies support remote patient monitoring, adaptive treatment planning, and data-informed hospital management, influencing clinical decision-making and patient care. However, adoption remains constrained by challenges, including device heterogeneity, fragmented interoperability standards, cybersecurity and data privacy concerns, ethical considerations such as patient consent and algorithmic bias, and technological limitations such as network latency, limited battery life, and uneven infrastructure across regions. Recognizing the limitations of narrative synthesis, this review discusses heterogeneity in reported findings and highlights that the transformative potential of IoT depends on context-specific implementation. Emerging approaches, including AI-enabled IoT (AI-IoT), digital twins for personalized simulation, and ultra-low-latency 6G networks, offer opportunities to address current barriers. Finally, the review provides recommendations for researchers, policymakers, and healthcare providers to guide the development of safe, interoperable, and ethically responsible digital health systems.
Ogenyi et al. (2026) studied this question.
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