CareEdge: A Lightweight Edge Intelligence Framework for ECG-Based Heartbeat Detection

The large-scale application of the Internet of Things technology has made the edge of net more attention. The large amount of data generated at the edge requires AI processing, which creates the field of Edge Intelligence (EI). The research on EI, whether in academia or industry, is still in its infancy. We proposed a novel fast and lightweight application framework for EI, named CareEdge. The framework can promote IoT-Edge-Cloud integration and provide a good interface for IoT smart applications. It can build IoT edge applications for developers and provide data analysis programs for multiple users. In the deployment phase, it can be configured according to the needs of the IoT scenario to effectively utilize related resources. We demonstrate the effectiveness of CareEdge by building an ECG-based heartbeat detection system as a case study. We also evaluated the characteristics of CareEdge. The experimental result shows that CareEdge has lower latency than similar frameworks. (C) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the International Conference on Identification, Information and Knowledge in the internet of Things, 2020.

Automated summary

The large-scale application of Internet of Things technology has brought more attention to the edge of the network, where a large amount of data generated requires AI processing, leading to the development of Edge Intelligence. The novel and lightweight CareEdge framework promotes IoT-Edge-Cloud integration, provides a good interface for IoT smart applications, and effectively utilizes related resources by offering data analysis programs for multiple users. CareEdge has demonstrated lower latency than similar frameworks in the experiment, showcasing its effectiveness.