DOI : https://doi.org/10.18517/ijaseit.7.6.4467

E-health-IoT Universe: A Review

Noemi Scarpato (1), Alessandra Pieroni (2), Luca Di Nunzio (3), Francesca Fallucchi (4)
(1) San Raffaele Roma Open University, Dept. of Human sciences and Promotion of the quality of life, Rome, Italy
(2) Guglielmo Marconi University, Dept. of Innovation and Information Engineering, Rome, Italy
(3) Department of Electronic Engineering, University of Rome Tor Vergata, Via Del Politecnico 1, Rome, 00133, Italy
(4) Guglielmo Marconi University, Dept. of Innovation and Information Engineering, Rome, Italy
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How to cite (IJASEIT) :
Scarpato, Noemi, et al. “E-Health-IoT Universe: A Review”. International Journal on Advanced Science, Engineering and Information Technology, vol. 7, no. 6, Dec. 2017, pp. 2328-36, doi:10.18517/ijaseit.7.6.4467.
Citation Format :
The Internet of Things (IoT) devices are able to collect and share data directly with other devices through the cloud environment, providing a huge amount of information to be gathered, stored and analyzed for data-analytics processes. The scenarios in which the IoT devices may be useful are amazing varying, from automotive, to industrial automation or remote monitoring of domestic environment. Furthermore, has been proved that healthcare applications represent an important field of interest for IoT devices, due to the capability of improving the access to care, reducing the cost of healthcare and most importantly increasing the quality of life of the patients. In this paper, we analyze the state-of-art of IoT in medical environment, illustrating an extended range of IoT-driven healthcare applications that, however, still need innovative and high technology-based solutions to be considered ready to market. In particular, problems regarding characteristics of response-time and precision will be examined.  Furthermore, wearable and energy saving properties will be investigated in this paper and also the IT architectures able to ensure security and privacy during the all data-transmission process. Finally, considerations about data mining applications, such as risks prediction, classification and clustering will be provided, that are considered fundamental issues to ensure the accuracy of the care processes.

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