EHSIO: Energy-Harvesting Stream-Enabled Intelligent Healthcare Optimization Framework for Sustainable Medical IoT Systems

This paper presents EHSIO, an innovative framework integrating energy harvesting technologies with stream processing for sustainable healthcare IoT systems. The framework addresses critical challenges in powering wearable and implantable medical devices through a novel combination of THz-based communication and adaptive energy optimization. Our approach implements a sparse-aware stream processing algorithm that enhances energy efficiency while maintaining highthroughput data processing capabilities. Experimental results across 14 international healthcare facilities demonstrate that EHSIO achieves 43% improved energy efficiency, 39% reduced data latency, and 45% enhanced processing throughput compared to existing methods. The framework provides a sustainable solution for next-generation medical IoT systems requiring continuous operation and real-time data processing.

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Publication Details

Published
2024-12-17
DOI
https://doi.org/10.1109/icicnis64247.2024.10823387
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
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article

EHSIO: Energy-Harvesting Stream-Enabled Intelligent Healthcare Optimization Framework for Sustainable Medical IoT Systems

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IoT and Edge/Fog Computing
article

EHSIO: Energy-Harvesting Stream-Enabled Intelligent Healthcare Optimization Framework for Sustainable Medical IoT Systems

R. C. Karpagalakshmi, Rajesh Sharma R, Sheila Mahapatra, Akey Sungheetha, G S Pradeep Ghantasala, A. Ezil Sam Leni
article en

Abstract

This paper presents EHSIO, an innovative framework integrating energy harvesting technologies with stream processing for sustainable healthcare IoT systems. The framework addresses critical challenges in powering wearable and implantable medical devices through a novel combination of THz-based communication and adaptive energy optimization. Our approach implements a sparse-aware stream processing algorithm that enhances energy efficiency while maintaining highthroughput data processing capabilities. Experimental results across 14 international healthcare facilities demonstrate that EHSIO achieves 43% improved energy efficiency, 39% reduced data latency, and 45% enhanced processing throughput compared to existing methods. The framework provides a sustainable solution for next-generation medical IoT systems requiring continuous operation and real-time data processing.

Alliance University (IN)
Openalex Percentile: Top 71%
IoT and Edge/Fog Computing
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