JOURNAL ARTICLE

Edge intelligence for empowering IoT-based healthcare systems

Year: 2021 Journal:   Digital Collections portal (Koç University)   Publisher: Koç University

Abstract

The demand for real-time, affordable, and efficient smart healthcare services is increasing exponentially due to the technological revolution and burst of population. To meet the increasing demands on this critical infrastructure, there is a need for intelligent methods to cope with the existing related challenges. In this regard, edge computing technology can reduce latency and energy consumption by moving processes closer to the data sources in comparison to the traditional centralized cloud and IoT-based healthcare systems. In addition, by bringing automated insights into the smart healthcare systems, artificial intelligence (AI) provides the possibility of detecting and predicting high-risk diseases in advance, decreasing medical costs for patients, and offering efficient treatments. The objective of this article is to highlight the benefits of the adoption of the edge intelligent technology, along with the use of AI in smart healthcare systems. Moreover, a novel smart healthcare model is proposed to boost the utilization of AI and edge technology in smart healthcare systems. Additionally, we discuss potential challenges and future research directions arising when integrating these different technologies.

Keywords:
Computer science Edge computing Cloud computing Health care Enhanced Data Rates for GSM Evolution Healthcare system Internet of Things Population Data science Computer security Risk analysis (engineering) Artificial intelligence Business Medicine

Metrics

88
Cited By
9.77
FWCI (Field Weighted Citation Impact)
15
Refs
0.98
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

IoT and Edge/Fog Computing
Physical Sciences →  Computer Science →  Computer Networks and Communications
Context-Aware Activity Recognition Systems
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
EEG and Brain-Computer Interfaces
Life Sciences →  Neuroscience →  Cognitive Neuroscience
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