Towards Next-Generation Healthcare: Architectural Insights into an AI-Driven, Smartwatch-Compatible mHealth Application

Abstract

With the rise of telemedicine and wearable technology, mHealth (mobile health) applications are becoming increasingly important in providing real-time, personalized healthcare solutions. However, integrating these technologies effectively to deliver high-quality care is a significant challenge. This paper proposes a novel system architecture for an AIassisted mHealth application that seamlessly integrates video conferencing platforms, smartwatch APIs, and AI algorithms. Our proposed architecture facilitates real-time health monitoring during video consultations by allowing healthcare providers to access patients' health data gathered from their wearable smartwatches. Furthermore, integrating AI algorithms provides personalized health recommendations based on patterns identified from the collected data. Additionally, this research delves deep into the implementation considerations and cloud architectural paradigms, underscoring the challenges and discrepancies between proposed designs and real-world application feasibility. The proposed architecture addresses the needs of modern healthcare services and offers the potential for further enhancements in the realm of AI-assisted telemedicine.