Internet-of-Things and big data for smarter healthcare: from device to architecture, applications and analytics
Internet-of-Things and big data for smarter healthcare: from device to architecture, applications and analytics
The technology and healthcare industries have been deeply intertwined for quite some time. New opportunities, however, are now arising as a result of fast-paced expansion in the areas of the Internet of Things (IoT) and Big Data. In addition, as people across the globe have begun to adopt wearable biosensors, new applications for individualized eHealth and mHealth technologies have emerged. The upsides of these technologies are clear: they are highly available, easily accessible, and simple to personalize; additionally they make it easy for providers to deliver individualized content cost-effectively, at scale. At the same time, a number of hurdles currently stand in the way of truly reliable, adaptive, safe and efficient personal healthcare devices. Major technological milestones will need to be reached in order to address and overcome those hurdles; and that will require closer collaboration between hardware and software developers and medical personnel such as physicians, nurses, and healthcare workers. The purpose of this special issue is to analyze the top concerns in IoT technologies that pertain to smart sensors for health care applications; particularly applications targeted at individualized tele-health interventions with the goal of enabling healthier ways of life. These applications include wearable and body sensors, advanced pervasive healthcare systems, and the Big Data analytics required to inform these devices.
583-586
Firouzi, Farshad
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Rahmani, Amir
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Mankodiya, K.
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Badaroglu, M.
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Merrett, G.
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Wong, P.
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Farahani, B.
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January 2018
Firouzi, Farshad
20d74cfe-26e3-49d5-81a7-be1b57e7f522
Rahmani, Amir
29d4af1a-c798-46c9-8c72-27db9a53920e
Mankodiya, K.
5f034db4-903d-42fb-9b7b-ac5081f51692
Badaroglu, M.
760c4d3c-d829-436d-b656-5b55c94ed499
Merrett, G.
89b3a696-41de-44c3-89aa-b0aa29f54020
Wong, P.
1a5cc602-ada1-4fae-8c8d-e94de331a5c5
Farahani, B.
72b47b81-3fa1-4c7a-bea6-f009844168c4
Firouzi, Farshad, Rahmani, Amir, Mankodiya, K., Badaroglu, M., Merrett, G., Wong, P. and Farahani, B.
(2018)
Internet-of-Things and big data for smarter healthcare: from device to architecture, applications and analytics.
Future Generation Computer Systems, 78 (Part 2), .
(doi:10.1016/j.future.2017.09.016).
Abstract
The technology and healthcare industries have been deeply intertwined for quite some time. New opportunities, however, are now arising as a result of fast-paced expansion in the areas of the Internet of Things (IoT) and Big Data. In addition, as people across the globe have begun to adopt wearable biosensors, new applications for individualized eHealth and mHealth technologies have emerged. The upsides of these technologies are clear: they are highly available, easily accessible, and simple to personalize; additionally they make it easy for providers to deliver individualized content cost-effectively, at scale. At the same time, a number of hurdles currently stand in the way of truly reliable, adaptive, safe and efficient personal healthcare devices. Major technological milestones will need to be reached in order to address and overcome those hurdles; and that will require closer collaboration between hardware and software developers and medical personnel such as physicians, nurses, and healthcare workers. The purpose of this special issue is to analyze the top concerns in IoT technologies that pertain to smart sensors for health care applications; particularly applications targeted at individualized tele-health interventions with the goal of enabling healthier ways of life. These applications include wearable and body sensors, advanced pervasive healthcare systems, and the Big Data analytics required to inform these devices.
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Editorial Paper
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Submitted date: 5 September 2017
Accepted/In Press date: 22 September 2017
e-pub ahead of print date: 23 September 2017
Published date: January 2018
Identifiers
Local EPrints ID: 414127
URI: http://eprints.soton.ac.uk/id/eprint/414127
ISSN: 0167-739X
PURE UUID: 4c634e18-3405-4118-a30c-34c605cdc77a
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Date deposited: 15 Sep 2017 16:30
Last modified: 16 Mar 2024 05:44
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Contributors
Author:
Farshad Firouzi
Author:
Amir Rahmani
Author:
K. Mankodiya
Author:
M. Badaroglu
Author:
G. Merrett
Author:
P. Wong
Author:
B. Farahani
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