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Article type: Research Article
Authors: Deepa, S.a; * | Sridhar, K.P.b | Baskar, S.b | Mythili, K.B.c | Reethika, A.d | Hariharan, P.R.e
Affiliations: [a] Department of Electronics and Communication Engineering, Karpagam College of Engineering, Coimbatore | [b] Department of Electronics and Communication Engineering, Karpagam Academy of Higher Education, Coimbatore, India | [c] Environmental Engineer, Karupa Foundation, Coimbatore, India | [d] Department of Electronics and Communication Engineering, KPR Institute of Engineering and Technology, Coimbatore | [e] Department of Scientific and Industrial Research, New Delhi, India
Correspondence: [*] Corresponding author. S. Deepa, Assistant Professor, Department of Electronics and Communication Engineering, Karpagam College of Engineering, Coimbatore. E-mail: [email protected].
Abstract: A smart healthcare network can use sensors and the Internet of Things (IoT) to enhance patient care while decreasing healthcare expenditures. It has become more difficult for healthcare providers to keep track and analyze the massive amounts of data it generates. Health care data created by IoT devices and e-health systems must be handled more efficiently. A wide range of healthcare industries can benefit from machine learning (ML) algorithms in the digital world. However, each of these algorithms has to be taught to anticipate or solve a certain problem. IoT-enabled healthcare data and health monitoring-based machine learning algorithms (IoT-HDHM-MLA) have been proposed to solve the difficulties faced by healthcare providers. Sensors and IoT devices are vital for monitoring an individual’s health. The proposed IoT-HDHM-MLA aims to deliver healthcare services via remote monitoring with experts and machine learning algorithms. In this system, patients are monitored in real-time for various key characteristics using a collection of small wireless wearable nodes. The health care business benefits from systematic data collection and efficient data mining. Thus, the experimental findings demonstrate that IoT-HDHM-MLA enhances efficiency in patient health surveillance.
Keywords: Health monitoring, machine learning algorithms, IoT, smart healthcare
DOI: 10.3233/JIFS-221274
Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 2, pp. 2927-2941, 2023
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