In this paper, we address the growing importance of Artificial Intelligence of Things (AIoT) in transforming healthcare systems, particularly in resource-constrained environments. We explore the transition from simple connectivity to intelligent decision-making, highlighting applications such as remote monitoring, predictive analytics, smart wearables, and automated hospital systems. At the same time, we examine the main challenges associated with the adoption of this technology, including data protection, infrastructure gaps, energy constraints, and algorithmic transparency. To support equitable integration, five enablers critical for AIoT adoption in African healthcare are identified: reliable digital infrastructure, local capacity building, contextualized solutions, financial and policy support, and ethical governance. Together, these elements form the foundation of a sustainable ecosystem for deployment in low-income settings, where resource limitations and cultural diversity demand tailored approaches. Building on these insights, the paper proposes a flexible four-layer architecture specifically designed for healthcare systems in low-income countries. By synthesizing current advancements and outlining a scalable model, this study presents a roadmap for making healthcare more intelligent, inclusive, and resilient.
Kasereka et al. (Thu,) studied this question.