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A Synergetic Framework for Efficient and Sustainable Internet of Medical Things

  • Amrita Vishwa Vidyapeetham

Research output: Contribution to journalArticlepeer-review

Abstract

Reliable operation of the Internet of Medical Things (IoMT) is critical for patient safety and operational efficiency of healthcare systems. The objectives of resource management of battery-operated devices in IoMT are to extend device longevity and minimize environmental impact. Current IoMT frameworks often treat resource efficiency and carbon sustainability as independent objectives, without a mechanism to resolve conflicts that arise when energy conservation and emission reduction goals compete simultaneously during clinical emergencies. Most of these frameworks employ strategies that compromise the precision of drug delivery or environmental responsibility during emergencies. This study introduces synergy, an on-device unified IoMT framework that integrates a Resource Efficiency Agent and a Sustainability Agent under a Centralized Decision Policy (CDP) engine, which arbitrates inter-agent conflicts by prioritizing safety, clinical precision, energy conservation, and carbon sustainability in sequence. It incorporates techniques such as adaptive sampling, hierarchical caching, Markov Decision Process (MDP) policy-driven resource allocation, and real-time carbon emission tracking. Synergy was validated across 157 infusion cycles using a clinical-grade micro-infusion pump as a representative single-device laboratory evaluation. The results demonstrated net energy savings of 28.3%, a 15 to 20% reduction in carbon footprint, and a 26% increase in the operational lifespan of the device, while maintaining drug delivery accuracy within 1% of the clinical safety threshold. The results indicate that the framework can improve healthcare efficiency and simultaneously meet environmental sustainability goals.

Original languageEnglish
Pages (from-to)51830-51845
Number of pages16
JournalIEEE Access
Volume14
DOIs
StatePublished - 2026

Keywords

  • Adaptive sensing
  • Internet of Medical Things (IoMT)
  • battery life
  • carbon-aware resource management
  • energy optimization
  • environmental impact
  • modular framework
  • resource efficiency
  • sustainability

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