Abstract :

The Rapid Advancement Of Wearable Technologies, The Internet Of Medical Things (IoMT), And Electronic Health Records Has Led To The Generation Of Massive Volumes Of Continuous Healthcare Data, Necessitating Efficient Real-time Monitoring And Predictive Analytics Frameworks. This Paper Proposes An Intelligent And Scalable Architecture Based On Data Streaming Technologies To Enable Continuous Patient Monitoring And Proactive Clinical Decision-making. The Proposed Framework Integrates High-throughput Streaming Platforms With Machine Learning And Deep Learning Models To Analyse Heterogeneous Data Streams, Including Physiological Signals, Medical History, And Environmental Parameters In Real Time. A Hybrid Edge–cloud Computing Paradigm Is Adopted To Ensure Low-latency Processing And Optimal Resource Utilization. At The Edge Layer, Lightweight Models Perform Initial Filtering And Anomaly Detection, Reducing Transmission Overhead And Enabling Immediate Alerts For Critical Conditions. The Cloud Layer Supports Advanced Predictive Analytics Using Adaptive Models Capable Of Learning Over Time And Detecting Early Signs Of Health Deterioration. To Enhance System Reliability And Scalability, The Architecture Incorporates Fault-tolerant Streaming Pipelines And Dynamic Model Updating Mechanisms Capable Of Handling High-velocity And High-volume Data Streams. Furthermore, The Framework Emphasizes Data Security And Privacy Through Encryption Techniques And Federated Learning, Allowing Decentralized Model Training Without Compromising Sensitive Medical Data. Experimental Results Demonstrate Significant Improvements In Prediction Accuracy, Response Time, And Scalability Compared To Traditional Batch-processing Healthcare Systems. The Proposed System Effectively Identifies Early Warning Signs Of Chronic Diseases And Acute Events, Enabling Timely Interventions And Reducing Hospitalization Rates. Overall, The Study Highlights The Transformative Potential Of Integrating Real-time Data Streaming With Predictive Analytics In Modern Healthcare Systems, Paving The Way For Intelligent, Autonomous, And Data-driven Medical Services.

Published:

07-5-2026

Issue:

Vol. 26 No. 5 (2026)

Page Nos:

317-331

Section:

Articles

License:

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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