Fog Computing in Healthcare: Systematic Review

Abstract

Healthcare has seen many advances in sensor technology, but with recent improvements in networks and the addition of the Internet of Things, it is even more promising. Current solutions to managing healthcare data with cloud computing may be unreliable at the most critical moments. High response latency, large volumes of data, and security are the main issues of this approach. The promising solution is fog computing, which offers an immediate response resistant to disconnections and ways to process big data using real-time analytics and artificial intelligence (AI). However, fog computing has not yet matured and there are still many challenges. This article presents for a computer scientist a systematic review of the literature on fog computing in healthcare. Articles published in six years are analysed from the service, software, hardware, information technologies and mobility with autonomy perspectives. The contribution of this study includes an analysis of recent trends, focus areas and benefits of the use of AI techniques in fog computing e-health applications.

Review and Computational Study on Practicality of Derivative-Free DIRECT-Type Methods

“…We conducted this review systematically examining the literature while adhering to a well-defined methodology to ensure a comprehensive and unbiased analysis (Moher et al, 2009). This methodology, with slight modifications, is widely utilized in various research endeavours (see, for example, Navakauskas and Kazlauskas, 2023;Torkayesh et al, 2023).…”