Design of smart baby incubator for low-birth-weight newborns - Pradana, Dio Alif; Mukhammad, Yanuar; Suharto, Idola Perdana Sulistyoning; Setiawan, Fachruddin Ari (Journal of Soft Computing Exploration, 2024)
The newborns mortality rate in Indonesia is still quite high, indicated by the neonatal mortality rate (AKN) of 15 per 1000 Live Births, where the target is only below 10 per 1000 Live Births. This mortality rate can be caused by Low-Birth-Weight (BBLR) cases that leads to death. One form of handling for these cases is using a Baby Incubator for intensive cares, which requires monitoring manually and requires the presence of a nurse around the baby incubator so that the condition of the baby incubator room remains stable. Several studies have been conducted and produced a smart incubator system to address these shortcomings. However, most of the smart incubators only focused on monitoring the condition of the incubator room without observing the condition of the baby inside. Based on this, a study was conducted that focused to producing a smart baby incubator that is capable of real-time monitoring of of room conditions (temperature, humidity, and oxygen levels) and baby conditions (temperature, heart rate, oxygen saturation, baby crying, and baby visuals) by applying the Internet of Things (IoT). The results of this study have the largest number of parameters monitored compared to previous studies.