An Intelligent System For Infant Incubator Using The IoMT

Main Article Content

Eniyaa PP
Jeya Pragathi RS
Kalki V
Monica ST
Mrs. Nithya C

Abstract

Giving birth to a child is one of the most precious moments of life, a moment that brings immense joy and a profound sense of responsibility. The birth of a baby is a wondrous yet intricate process. Both mother and infant undergo a multitude of physical and emotional changes. Every second, a new life enters the world, but not all babies are fortunate enough to be born healthy. Newborns requiring special medical attention are typically admitted to the Neonatal Intensive Care Unit (NICU). Most of the infants in the NICU are premature. The neonatal period is a critical phase in an infant's life, particularly for premature babies or those born with health complications. Providing optimal care during this period is paramount to their well-being and long-term development. A neonatal incubator is a specialized enclosure where a premature infant will be kept in a clean and controlled environment for observation and care. The biological parameters are monitored to ensure the safety of the babies and reduce mortality rates. Traditional baby incubators have played a fundamental role in neonatal care by providing a controlled environment that supports the growth and stability of infants. Advancements in technology, however, present an opportunity to enhance the capabilities of these incubators, transforming them into smart systems capable of intelligent monitoring and intervention. The development of a smart baby incubator utilizes small sensors inside the incubator to keep track of important things like temperature, humidity, and oxygen levels, as well as sound sensors using IoMT. These sensors will send this information to a Microcontroller using the internet. Once the data arrives at the central computer, Python programs will analyse it. These programs will employ algorithms to analyze the data and determine if the baby's environment is within normal parameters. The results will be shown to doctors and nurses on their computers or phones through easy-to-understand charts and graphs. By using Python and IoMT, we're making it easier for healthcare providers to keep a close eye on babies in incubators, ensuring they stay safe and healthy during this critical period of their early lives.

Article Details

How to Cite
Eniyaa PP, Jeya Pragathi RS, Kalki V, Monica ST, & Mrs. Nithya C. (2023). An Intelligent System For Infant Incubator Using The IoMT. Journal for ReAttach Therapy and Developmental Diversities, 6(10s), 2129–2135. https://doi.org/10.53555/jrtdd.v6i10s.2830
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Articles
Author Biographies

Eniyaa PP

Biomedical Engineering V.S.B Engineering College (Autonomous) Karur-India.                            

Jeya Pragathi RS

Biomedical Engineering V.S.B Engineering College (Autonomous) Karur-India. 

Kalki V

Biomedical Engineering V.S.B Engineering College (Autonomous) Karur-India.

Monica ST

Biomedical Engineering V.S.B Engineering College (Autonomous) Karur-India. 

Mrs. Nithya C

Assistant professor in Biomedical Engineering V.S.B Engineering College (Autonomous) Karur-India.                                             

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