Use of Internet of Things With Data Prediction on Healthcare Environments: A Survey

Use of Internet of Things With Data Prediction on Healthcare Environments: A Survey

Gabriel Souto Fischer, Rodrigo da Rosa Righi, Vinicius Facco Rodrigues, Cristiano André da Costa
ISBN13: 9781668471326|ISBN10: 1668471329|EISBN13: 9781668471333
DOI: 10.4018/978-1-6684-7132-6.ch043
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MLA

Fischer, Gabriel Souto, et al. "Use of Internet of Things With Data Prediction on Healthcare Environments: A Survey." Research Anthology on Convergence of Blockchain, Internet of Things, and Security, edited by Information Resources Management Association, IGI Global, 2023, pp. 778-798. https://doi.org/10.4018/978-1-6684-7132-6.ch043

APA

Fischer, G. S., Righi, R. D., Rodrigues, V. F., & André da Costa, C. (2023). Use of Internet of Things With Data Prediction on Healthcare Environments: A Survey. In I. Management Association (Ed.), Research Anthology on Convergence of Blockchain, Internet of Things, and Security (pp. 778-798). IGI Global. https://doi.org/10.4018/978-1-6684-7132-6.ch043

Chicago

Fischer, Gabriel Souto, et al. "Use of Internet of Things With Data Prediction on Healthcare Environments: A Survey." In Research Anthology on Convergence of Blockchain, Internet of Things, and Security, edited by Information Resources Management Association, 778-798. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/978-1-6684-7132-6.ch043

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Abstract

Internet of Things (IoT) is a constantly growing paradigm that promises to revolutionize healthcare applications and could be associated with several other techniques. Data prediction is another widely used paradigm, where data captured over time is analyzed in order to identify and predict problematic situations that may happen in the future. After research, no surveys that address IoT combined with data prediction in healthcare area exist in the literature. In this context, this work presents a systematic literature review on Internet of Things applied to healthcare area with a focus on data prediction, presenting twenty-three papers about this theme as results, as well as a comparative analysis between them. The main contribution for literature is a taxonomy for IoT systems with data prediction applied to healthcare. Finally, this article presents the possibilities and challenges of exploration in the study area, showing the existing gaps for future approaches.