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We report the design and implementation of an affordable bedside device, Neo is capable of acquiring vital data in real time by integrating with diverse devices connected to newborns in neonatal intensive care units (NICUs). NICUs are equipped with multiple vital sign monitoring devices that are connected to the premature newborn and acquire a few gigabytes of data every day. The continuous vital data from these devices are manually documented every hour. This introduces errors and loses a large amount of high-resolution data. The intermittent documentation of physiological data also makes it difficult for clinicians to visualize and detect the trends of diagnostic utility. Neo is built on an affordable Internet of Things platform that aggregates and sends the real-time data to a cloud-based big data platform called integrated NICU. Apart from minimizing documentation errors, the device enables data acquisition at sufficiently real-time rates as to indicate the current status of all the patients at the NICU. Neo automates immediate vital sign status and past trends as graphs or charts that the doctor and nurses can view from anywhere through the Internet. Physiological signal and clinical parameters from Neo is used to score different diseases like sepsis, respiratory distress syndrome, necrotizing enterocolitis, and retinopathy of prematurity. This score predicts the physiological health of the newborn and aid clinicians in decision-making ensuring timely intervention. INDEX TERMS Big data, cloud-based, device aggregator, early warning scores, IoT, neonatal intensive care units.

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