Internet of Things-Based Smart Infant-Incubators Using Machine Learning Analysis

Many international manufacturers of infant incubators use IoT technology, presenting tough competition for local manufacturers. This research examines methods to fulfill parents’ need to monitor their babies directly when they are lying inside an incubator. This bridges the gap present in neonatal care units. As such, this study proposes a prototype for an incubator that employs IoT along with different sensors to monitor babies occupying these incubators in real time and send the data to a remote server. With the different technologies used in this monitoring system, parents have the ability to listen to their babies remotely through a mobile application. A convolutional neural network (CNN) algorithm is used to take neonatal care a step further. It then goes beyond monitoring by interpreting the nature of a baby’s cries inside the specified incubator. The proposed prototype represents a step forward in the applications of Industry 4.0 in healthcare, especially those related to infant care and, more specifically, incubators for babies. This research is part of advancements in the use of IoT and handheld applications for the future development of baby incubators, fulfilling the needs of parents to constantly monitor their infants and neonatal care, specifically within modern healthcare.