Vol. 3 No. 2 (2023): Journal of Deep Learning in Genomic Data Analysis
Articles

Innovative IoT Solutions for Monitoring and Managing Neonatal Intensive Care Units: Designs IoT-based monitoring systems tailored for neonatal intensive care units to enhance patient monitoring and care delivery for premature infants

Dr. Maria Garcia
Associate Professor of Public Health Informatics, Universidad Nacional Autónoma de Honduras
Cover

Published 22-12-2023

Keywords

  • Neonatal Intensive Care Units,
  • Premature Infants,
  • Real-time,
  • Machine Learning

How to Cite

[1]
Dr. Maria Garcia, “Innovative IoT Solutions for Monitoring and Managing Neonatal Intensive Care Units: Designs IoT-based monitoring systems tailored for neonatal intensive care units to enhance patient monitoring and care delivery for premature infants”, Journal of Deep Learning in Genomic Data Analysis, vol. 3, no. 2, pp. 35–46, Dec. 2023, Accessed: Nov. 14, 2024. [Online]. Available: https://thelifescience.org/index.php/jdlgda/article/view/48

Abstract

Neonatal Intensive Care Units (NICUs) play a crucial role in providing specialized care for premature infants. However, traditional monitoring systems in NICUs often lack the ability to provide real-time, comprehensive data on vital signs and patient status. This paper presents the design and implementation of IoT-enabled Smart Monitoring Systems for NICUs, aimed at improving patient outcomes by enhancing monitoring capabilities and care delivery. The proposed system integrates various IoT devices and sensors to collect data such as heart rate, respiratory rate, oxygen saturation, and temperature, providing a holistic view of the infant's health status. This data is then analyzed using machine learning algorithms to detect abnormalities and trends, enabling early intervention by healthcare providers. The system also includes a user-friendly interface for caregivers to monitor infants remotely and receive alerts in case of emergencies. Overall, the IoT-enabled Smart Monitoring Systems have the potential to revolutionize NICU care by providing real-time, personalized monitoring and improving clinical decision-making.

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