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What is IoT Edge Gateway

Deep Neural Networks for Multimodal Imaging and Biomedical Applications
It can generate and exchange data within single framework. It offered Remote patient monitoring system which reduces the time duration.
Published in Chapter:
The Pivotal Role of Edge Computing With Machine Learning and Its Impact on Healthcare
Muthukumari S. M. (Bharathidasan University, India) and George Dharma Prakash E. Raj (Bharathidasan University, India)
DOI: 10.4018/978-1-7998-3591-2.ch014
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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