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The Pivotal Role of Edge Computing With Machine Learning and Its Impact on Healthcare
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Author(s): Muthukumari S. M. (Bharathidasan University, India)and George Dharma Prakash E. Raj (Bharathidasan University, India)
Copyright: 2020
Pages: 18
Source title:
Deep Neural Networks for Multimodal Imaging and Biomedical Applications
Source Author(s)/Editor(s): Annamalai Suresh (Department of Computer Science and Engineering, Nehru Institute of Engineering and Technology, Coimbatore, India), R. Udendhran (Department of Computer Science and Engineering, Bharathidasan University, India)and S. Vimal (Department of Information Technology, National Engineering College (Autonomous), Kovilpatti, India)
DOI: 10.4018/978-1-7998-3591-2.ch014
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Abstract
The global market for IoT medical devices is expected to hit a peak of 500 billion by the year 2025, which could signal a significant paradigm shift in healthcare technology. This is possible due to the on-premises data centers or the cloud. Cloud computing and the internet of things (IoT) are the two technologies that have an explicit impact on our day-to-day living. These two technologies combined together are referred to as CloudIoT, which deals with several sectors including healthcare, agriculture, surveillance systems, etc. Therefore, the emergence of edge computing was required, which could reduce the network latency by pushing the computation to the “edge of the network.” Several concerns such as power consumption, real-time responses, and bandwidth consumption cost could also be addressed by edge computing. In the present situation, patient health data could be regularly monitored by certain wearable devices known as the smart telehealth systems that send an enormous amount of data through the wireless sensor network (WSN).
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