A Hybrid Model for an IoT-Enabled Healthcare System Using Machine Learning Algorithms

Author(s)	Dr. Rajshree
Country	India
Abstract	The growing demand for efficient and continuous patient monitoring has led to the integration of Internet of Things (IoT) technologies with machine learning (ML) algorithms in healthcare. This paper proposes a hybrid IoT-enabled health-care system that leverages wearable sensors for real-time data acquisition and applies ML models for disease prediction, anomaly detection, and personalized healthcare recommendations. The system architecture integrates data collection, preprocessing, cloud storage, and ML-based analysis to provide timely alerts and support clinical decision-making. Experimental evaluation demonstrates that the proposed hybrid approach improves prediction accuracy and response time, enabling proactive health management and remote patient monitoring. Experimental results show that the proposed system achieves an accuracy of 94.8%, demonstrating its effectiveness for real-time healthcare monitoring.
Keywords	IoT, health-care system, machine learning, wearable sensors, predictive analytics, remote monitoring.
Field	Computer
Published In	Volume 6, Issue 3, May-June 2025
Published On	2025-06-07

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