A Comprehensive Literature Review of IoT-Based Smart Healthcare Monitoring Systems

Abstract

The Internet of Things (IoT) has become an essential driver of modern medicine, facilitating automated patient tracking, remote clinical assessment, and instant diagnostic support. Innovations across wearable biosensors, wireless networking, edge-cloud architectures, and artificial intelligence have significantly propelled the evolution of intelligent health monitoring platforms. 
This study offers a Systematic Literature Review (SLR) examining smart healthcare monitoring systems powered by the IoT from 2015 through 2025. Following the PRISMA 2020 guidelines, 300 records were initially identified through a systematic search. After applying the predefined inclusion and exclusion criteria, 50 studies were selected for detailed analysis. Throughout the review, attention is given to structural IoT frameworks, sensor modalities, networking protocols, medical uses, AI methodologies, and upcoming technological shifts. 
This survey highlights the dominant technological solutions, outlines their practical clinical uses, and critically evaluates core obstacles such as cybersecurity, data privacy, cross-system interoperability, system scalability, power consumption, and operational reliability. Furthermore, it underscores high-potential research frontiers, encompassing localized edge intelligence, decentralized federated learning, blockchain protocols, digital twin representations, and explainable AI. 
Ultimately, the synthesized insights present a holistic snapshot of today’s IoT healthcare landscape while delivering actionable guidelines for building more effective, safe, and smart medical technologies.