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Title Review Of Fog And Edge Computing–Based Smart Health Care System Using Deep Learning Approaches
ID_Doc 46447
Authors Rath M.; Tripathy S.S.; Tripathy N.; Panigrahi C.R.; Pati B.
Year 2023
Published Deep Learning in Personalized Healthcare and Decision Support
DOI http://dx.doi.org/10.1016/B978-0-443-19413-9.00012-6
Abstract Fog/edge computing enables Internet of things (IoT) applications by employing computational node resources to evaluate the gathered data, meet latency requirements, and boost the scalability and energy efficiency of IoT systems. But there are a few challenging problems that need to be resolved before fog/edge computing for IoT can be fully utilized. Fog/edge computing, for instance, has a tendency to be unstable because the bulk of its compute nodes run on batteries. Further research is required on how to effectively provide computing resources to latency-sensitive IoT operations (like amplified actuality and essential realism, haptic technology, intelligent manufacturing, connected autonomous driving, and others), as well as how to seamlessly integrate fog/edge computing with cloud computing to deliver scalable services. The current research piece gives a thorough analysis of the device knowledge and subterranean erudition techniques utilized to address various tribulations in submissions connected to fog and edge computing. © 2023 Elsevier Inc. All rights reserved.
Author Keywords Edge computing; Fog computing; IoT; Smart city; Smart health care


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