Monitoring System for Operating Variables in Incubators in the Neonatology Service of a Highly Complex Hospital through the Internet of Things (IoT)

Abstract

Background: Around 15 million premature babies are born annually, requiring specialized care. Incubators are vital for maintaining their body temperature, which is crucial for their well-being. Ensuring optimal conditions in incubators, including constant temperature, oxygen control, and comfort, is essential for improving the care and survival rates of these infants. Methods: To address this, an IoT-based monitoring system was developed in a hospital setting. The system comprised hardware components such as sensors and a microcontroller, along with software components including a database and a web application. The microcontroller collected data from the sensors, which was then transmitted to a broker via WiFi using the MQTT protocol. The broker validated and stored the data in the database, while the web application provided real-time access, alerts, and event recording. Results: Two certified devices were created, employing high quality components. The system was successfully implemented and tested in both the biomedical engineering laboratory and the neonatology service of the hospital. The results of the pilot test supported the concept of IoT-based technology, demonstrating satisfactory responses in temperature, humidity, and sound variables within the incubators. Conclusions: The monitoring system facilitated efficient record traceability, allowing access to data over various timeframes. It also captured event records (alerts) related to variable problems, providing information on duration, date, hour, and minutes. Overall, the system offered valuable insights and enhanced monitoring capabilities for neonatal care.

Developing a smart system for infant incubators using the internet of things and artificial intelligence

“…Subsequent research regarding developing an incubator system to monitor temperature and humidity through a web application. The system uses a Wi-Fi network and MQTT protocol to send data to the broker service at node-RED Parra et al [15]. Then, research on developing a system to monitor the respiratory rate and detect the incidence of apnea in premature babies with the internet of things concept.…”

IoT-enhanced infant incubator monitoring system with 1D-CNN temperature prediction model

“…2, May 2024: 900-912 902 developing a system for monitoring and controlling temperature and humidity in an incubator using a hybrid fuzzy-PID method. Aya-Parra et al [8] investigated a baby incubator monitoring system using IoT. The sensors used included temperature, humidity, and sound.…”

“…However, some studies only concentrated on monitoring temperature and humidity without any systematic control. In the monitoring process, the use of an IoT broker from Node-RED platform, a third-party provider, may imply potential insecurity of patient data or limitations in using its features [8], [9]. Based on the conducted research, we have developed a predictive system for future temperature conditions in an incubator by integrating IoT and artificial intelligence.…”

Enhancing Neonatal Incubator Energy Management and Monitoring through IoT-Enabled CNN-LSTM Combination Predictive Model

“…Furthermore, previous research has employed a hybrid fuzzy and PID approach in incubator control systems. Researchers have also researched incubator monitoring and apnea detection systems for premature babies using IoT and wearable devices [6][7][8][9]. However, no research has effectively combined artificial intelligence (AI) with IoT within the context of baby incubators.…”

“…In the context of the incubator, numerous studies have been conducted previously, but most of them utilized control methods such as PID and Fuzzy [6][7][8][9], as shown in Table 1. Our research aims to extend the development of the incubator with artificial intelligence to monitor energy usage based on temperature conditions inside the incubator.…”