Abstract

The integration of Internet of Things (IoT) technologies into healthcare systems has transformed traditional care models by enabling real-time, continuous, and remote patient monitoring. This chapter presents an in-depth exploration of IoT-based Remote Patient Monitoring (RPM) and telemedicine solutions, emphasizing their role in enhancing healthcare accessibility, affordability, and quality. The fusion of wearable sensors, edge computing, cloud platforms, and intelligent analytics allows for proactive management of chronic diseases, early detection of clinical deterioration, and reduction in unnecessary hospitalizations. The chapter outlines the core components of RPM systems, including sensor technologies, communication infrastructure, and data lifecycle management, while examining the functional role of healthcare providers in interpreting data and ensuring responsive care delivery. Special attention is given to behavioral health and sleep monitoring use cases, showcasing the adaptability of RPM across diverse clinical scenarios. Challenges such as data privacy, system interoperability, and patient engagement are critically evaluated, alongside future research directions focusing on AI-driven personalization, federated learning, and inclusive design. By addressing both the technological and systemic aspects of IoT-enabled healthcare, this chapter offers a comprehensive roadmap for leveraging RPM in scalable and sustainable telehealth solutions.

Introduction

The growing burden on global healthcare systems, driven by aging populations, chronic disease prevalence, and infrastructure limitations, has intensified the need for alternative models of care that are accessible, efficient, and scalable [1]. Traditional in-hospital or clinic-based healthcare often struggles to meet the demands of patients requiring continuous or long-term monitoring [2]. In this context, the adoption of Internet of Things (IoT)-enabled Remote Patient Monitoring (RPM) and telemedicine solutions presents a transformative approach [3]. By harnessing connected sensors, mobile technologies, and data analytics, RPM enables the real-time collection, transmission, and interpretation of physiological and behavioral health data [4]. These capabilities support a shift from reactive, episodic care to proactive and preventive health management, improving patient outcomes and optimizing resource utilization across diverse care settings [5]. RPM systems capitalize on the synergy between wearable technologies, cloud computing, edge analytics, and secure communication networks [6]. Devices worn or embedded in patients' environments collect continuous streams of health metrics such as heart rate, glucose levels, blood pressure, sleep patterns, and activity levels [7]. Data is then transmitted through secure channels to healthcare providers, where it can be analyzed for trends, anomalies, and clinical relevance. This digital infrastructure ensures seamless communication between patients and providers, enabling timely interventions and reducing the need for frequent in-person consultations [8]. The ability to detect deterioration in health status early allows for rapid medical response, minimizing complications and reducing hospital readmissions [9]. These systems also support long-term disease management by providing healthcare teams with comprehensive and continuous health records, replacing fragmented or incomplete episodic health data [10].