Special Issue on Internet-of-Things and Big Data for Smarter Healthcare: From Device to Architecture, Applications and Analytics

March 11, 2016

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CALL FOR PAPERS
The Elsevier Journal of Future Generation Computer Systems (Impact Factor: 2.8)
Special Issue on

Internet-of-Things and Big Data for Smarter Healthcare: From Device to Architecture, Applications and Analytics

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The interaction between technology and healthcare has a long history. However, the rapid growth of Internet of Things (IoT) and Big Data, as well as the public embracement of miniature wearable biosensors have generated new opportunities for personalized eHealth and mHealth services. The advantages of these services include the availability and accessibility, ability to personalize and tailor content, and cost-effective delivery. Still, many challenges need to be addressed in order to develop consistent, suitable, safe, flexible and power-efficient systems fit for medical needs. To enable this transformation, it requires a large number of significant technological advancements in the hardware and software communities to come together. This special issue addresses all important aspects of novel IoT technologies for smart healthcare-wearable sensors, body area sensors, advanced pervasive healthcare systems, and Big Data analytics that are aimed at providing tele-health interventions to individuals for healthier lifestyles. Authors are invited to submit high quality papers containing original work from either academia or industry reporting novel advances in (but not limited to) the following topics:

TOPICS (non-exclusive)
* Internet of things for medical and healthcare applications
* Novel devices and circuits, and architectural support for healthcare-aware IoT
* Nano-CMOS and Post-CMOS based sensors, circuits, and controller
* Wearable and implantable computing and biosensors
* Cloud-enabled body sensor networks
* Secure middleware for eHealth and IoT
* Energy-efficient PHY/MAC and networking protocols for eHealth applications
* Reprogrammable and reconfigurable embedded systems for eHealth
* eHealth traffic characterization
* eHealth oriented software architectures (Agent, SOA, Middleware, etc.)
* Big-data analytics, machine learning algorithms and scalable/parallel/distributed algorithms
* Theory and practice of engineering semantic e-health systems, especially methods, means and best cases
* Fog computing/Edge clouds for health care cloud resource allocation and monitoring
* Privacy preserving and Security approaches for large scale analytics
* Fault tolerance, reliability and scalability
* Case studies of smart eHealth architectures (telemedicine applications, health management applications, etc.)
* Autonomic analysis, monitoring and situation alertness

Guest Editors:
* Farshad Firouzi, imec & KU Leuven, Belgium/Netherlands (farshad.firouzi@imec.be)
* Philip Wong, Stanford University, USA (hspwong@stanford.edu)
* Amir M. Rahmani, University of Turku, Finland (amirah@utu.fi)
* Kunal Mankodiya, University of Rhode Island, USA (kunalm@uri.edu)
* Geoff V. Merrett, University of Southampton, UK (gvm@ecs.soton.ac.uk)
* Bahar Farahani, Pirouzan Group, Iran (bahar.farahani@ut.ac.ir)
* Mustafa Badaroglu, Qualcomm, USA (mustafab@qti.qualcomm.com)

Important Dates:
Manuscript due: June 1st, 2016
Acceptance/rejection notification: September 15th, 2016
2nd round check: November 15th, 2016
Final manuscript due: December 15th, 2016

Submissions:
Submitted manuscripts will be reviewed according to the peer review policy of FGCS as available on-line at http://www.journals.elsevier.com/future-generation-computer-systems. Previously published conference papers should be clearly stated by the authors and an explanation should be provided how such papers have been extended to be considered for this special issue. Manuscripts should be formatted and be submitted online according to the instructions for FGCS at  https://www.elsevier.com/journals/future-generation-computer-systems/0167-739X/guide-for-authors. As papers are uploaded, authors should make sure to select the correct special issue (select “SI: IoT for eHealth” when reaching the Article Type step).

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