Edge Computing for Smart Health: Context-Aware Approaches, Opportunities, and Challenges | IEEE Journals & Magazine | IEEE Xplore
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Edge Computing for Smart Health: Context-Aware Approaches, Opportunities, and Challenges


Abstract:

Improving the efficiency of healthcare systems is a top national interest worldwide. However, the need to deliver scalable healthcare services to patients while reducing ...Show More

Abstract:

Improving the efficiency of healthcare systems is a top national interest worldwide. However, the need to deliver scalable healthcare services to patients while reducing costs is a challenging issue. Among the most promising approaches for enabling smart healthcare (s-health) are edge-computing capabilities and next-generation wireless networking technologies that can provide real-time and cost-effective patient remote monitoring. In this article, we present our vision of exploiting MEC for s-health applications. We envision a MEC-based architecture and discuss the benefits that it can bring to realize in-network and context-aware processing so that the s-health requirements are met. We then present two main functionalities that can be implemented leveraging such an architecture to provide efficient data delivery, namely, multimodal data compression and edge-based feature extraction for event detection. The former allows efficient and low distortion compression, while the latter ensures high-reliability and fast response in case of emergency applications. Finally, we discuss the main challenges and opportunities that edge computing could provide and possible directions for future research.
Published in: IEEE Network ( Volume: 33, Issue: 3, May/June 2019)
Page(s): 196 - 203
Date of Publication: 26 March 2019

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