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Title: A systematic literature review of data forecast and internet of things on the e-health landscape

Authors: Gabriel Souto Fischer; Rodrigo Da Rosa Righi; Vinicius Facco Rodrigues; Cristiano André Da Costa

Addresses: Academic Research and Graduate Unit, Applied Computing Graduate Program, Universidade do Vale do Rio dos Sinos, São Leopoldo, Brazil ' Academic Research and Graduate Unit, Applied Computing Graduate Program, Universidade do Vale do Rio dos Sinos, São Leopoldo, Brazil ' Academic Research and Graduate Unit, Applied Computing Graduate Program, Universidade do Vale do Rio dos Sinos, São Leopoldo, Brazil ' Academic Research and Graduate Unit, Applied Computing Graduate Program, Universidade do Vale do Rio dos Sinos, São Leopoldo, Brazil

Abstract: Internet of things (IoT) is a constantly expanding paradigm that promises to revolutionise healthcare applications and could be associated with several other techniques. Data forecast is another paradigm widely used, where data captured over time are analysed in order to identify and predict problematic situations that may happen in the future. After research, we did not find surveys that address IoT combined with data prediction in healthcare area in literature. In this context, this work presents a systematic literature review on internet of things applied to e-health landscape with a focus on data forecast, presenting as results 14 papers about this theme, and a comparative analysis between them. Our main contribution for literature is a taxonomy for IoT systems with data forecast applied to healthcare. Finally, this paper presents some possibilities and challenges of exploration in the study field, showing existing gaps for future approaches.

Keywords: internet of things; IoT; health; data forecast; sensors; distributed systems; taxonomy; healthcare environments; survey.

DOI: 10.1504/IJCMH.2019.104359

International Journal of Computational Medicine and Healthcare, 2019 Vol.1 No.1, pp.34 - 58

Received: 28 Apr 2018
Accepted: 27 Mar 2019

Published online: 06 Jan 2020 *

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