Edge Computing For Smart Health: Context-aware Approaches, Opportunities, and Challenges

• URL: http://arxiv.org/abs/2004.07311v1
• Date: Wed, 15 Apr 2020 19:50:24 GMT
• Title: Edge Computing For Smart Health: Context-aware Approaches, Opportunities, and Challenges
• Authors: Alaa Awad Abdellatif, Amr Mohamed, Carla Fabiana Chiasserini, Mounira Tlili, Aiman Erbad
• Abstract summary: Among the most promising approaches for enabling smart healthcare (s-health) are edge-computing capabilities and next-generation wireless networking technologies. We envision a MEC-based architecture and discuss the benefits that it can bring to realize in-network and context-aware processing. We present two main functionalities that can be implemented leveraging such an architecture to provide efficient data delivery.
• Score: 13.506100532943162
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Improving efficiency of healthcare systems is a top national interest worldwide. However, the need of delivering scalable healthcare services to the 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 paper, we present our vision of exploiting multi-access edge computing (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.

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