International Journal of Science and Technology (IJST)

AI-Based Real-Time Monitoring Systems in Healthcare: Challenges and Opportunities

The integration of Artificial Intelligence (AI) into real-time monitoring systems marks a significant advancement in healthcare, enabling continuous patient surveillance, early detection of critical events, and enhanced clinical decision-making. AI-powered monitoring systems analyze streams of physiological, biochemical, and behavioral data to identify anomalies and predict adverse outcomes, improving patient safety and care quality. This paper provides a comprehensive review of current AI-based real-time monitoring technologies deployed across various healthcare settings, including intensive care units, remote patient monitoring, and chronic disease management. It discusses the algorithms and sensor technologies underpinning these systems, their clinical applications, and the measurable benefits realized. The paper also critically examines the challenges hindering widespread adoption, such as data privacy concerns, algorithmic biases, integration complexities, and regulatory hurdles. Finally, it explores future opportunities including the use of multimodal data, advances in wearable sensors, edge computing, and personalized monitoring frameworks, emphasizing the potential of AI to revolutionize healthcare delivery and patient outcomes through proactive and continuous monitoring.