AI-Driven Patient Monitoring in Smart Hospitals: A Survey on Edge Computing Integration and Applications
Ranjani R, Ramu Naresh · 2025
The integration of artificial intelligence (AI) and edge computing in healthcare is transforming patient monitoring systems, particularly within smart hospitals. These technologies enable real-time data processing, enhanced decision-making, and improved patient outcomes by shifting computational tasks closer to data sources, reducing latency, and alleviating the burden on centralized cloud infrastructures. This survey paper provides a comprehensive review of the current state of AI-driven patient monitoring systems in smart hospitals, focusing on the role of edge computing. It explores key applications, such as vital sign monitoring, early disease detection, and predictive analytics, while highlighting the benefits of edge computing, including real-time analytics, enhanced data privacy, and resource efficiency. Furthermore, the paper examines challenges in the deployment of AI and edge computing in clinical settings, such as data security, interoperability, scalability, and the need for robust AI algorithms tailored to healthcare environments. The survey concludes with a discussion of future research directions and potential advancements to further enhance AI-driven patient monitoring systems in smart hospitals. This review serves as a valuable resource for researchers and healthcare professionals aiming to understand the intersection of AI and edge computing in modern healthcare infrastructures.