An Iot-Based Framework For Infant Vital Signs Monitoring With Aws Serverless

The continuous monitoring of vital signs such as respiratory rate, blood pressure, and heart rate in infants presents significant challenges. Currently, nurses and other healthcare professionals rely on manual methods to track these vital signs periodically, a process that necessitates constant patient observation and is susceptible to human error, potentially increasing infant mortality rates. This research proposes an innovative IoT-based framework for monitoring vital signs in infant incubators, utilizing serverless computing on the AWS platform to enhance efficiency and reduce costs. By employing AWS Kinesis streams for the analysis of large volumes of vital signs data and AWS Lambda for cost reduction, the framework aims to offer healthcare professionals access to real-time data on infants’ health status. This approach, combining AWS cloud services with deep learning techniques, promises to significantly improve data processing and analysis, enabling quicker and more accurate responses to any changes in an infant’s vital signs. Furthermore, the model introduces a serverless emergency alert system designed to optimize the efficiency of monitoring systems in neonatal intensive care units (NICU). The automation of alarm generation for nurses is poised to transform infant care by ensuring continuous safety and comfort for infants, thereby enhancing their overall well-being and the performance of healthcare providers.