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Internet of Things (IoT) and Data Analytics for Realizing Remote Patient Monitoring

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IoT Based Control Networks and Intelligent Systems (ICICNIS 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 789))

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Abstract

In the wake of recent advancements in technologies such as 5G, the Internet of Things (IoT), and Artificial Intelligence (AI), unprecedented smart solutions are made possible. Plenty of IoT use cases that have not been practical so far. IoT is being used to realize eHealth and mHealth applications to enable Ambient Assisted Living (AAL) in the healthcare domain. The health of human beings has been given the highest importance and there are many practical issues in the existing healthcare domain. The problems include delays in healthcare service and high costs involved in the procedures. Many prominent personalities died of heart attacks due to delays in medical intervention. Therefore, the need of the hour is to have real-time patient monitoring and treatment without causing delay. IoT has brought its grace to realize applications like remote patient monitoring (RPM). Wearable devices (biosensors) with IoT integration transmit the vital signs from patients to doctors in real time, enable to initiate treatment immediately. The phenomenon RPM has the potential to save time, healthcare costs, and improve the quality of life of patients and the quality of healthcare services as well. This paper throws light on the present state of the art on RPM using IoT and paves the way for identifying potential research gaps for leveraging RPM systems. The proposed IoT-integrated RPM for patient health monitoring employs an algorithm called data analytics for remote patient monitoring and presented experimental results that lead the system to analyze patient health details.

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Correspondence to A. Bharath .

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Bharath, A., Merlin Sheeba, G. (2024). Internet of Things (IoT) and Data Analytics for Realizing Remote Patient Monitoring. In: Joby, P.P., Alencar, M.S., Falkowski-Gilski, P. (eds) IoT Based Control Networks and Intelligent Systems. ICICNIS 2023. Lecture Notes in Networks and Systems, vol 789. Springer, Singapore. https://doi.org/10.1007/978-981-99-6586-1_29

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  • DOI: https://doi.org/10.1007/978-981-99-6586-1_29

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  • Print ISBN: 978-981-99-6585-4

  • Online ISBN: 978-981-99-6586-1

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