According to WHO Report, 1 in 10 babies are born preterm. Approximately 1 million children die each year due to complications of preterm birth. India shares the highest Preterm birth burden in the World, accounting to 23% of preterm babies born globally. These babies are extremely vulnerable and usually die due to several birth complications, acquired infections and damage to their brain, lungs or eyes.


The global burden of preterm births and neonatal mortality is immense. Treatment of the premature infants involves hospitalization in which progress reports are maintained manually by nurses and doctors.
Even the calculations of drug dosage and nutrition as per the changing weight of the baby are done manually and the real-time data such as heart rate coming from devices connected to the baby is noted manually (on hourly basis by considering only the maximum/average values). These manual entries and calculations have potential to result in high error rate.
In addition, the data produced every second by devices is stored for a maximum of 72 hours and significant quantity of this crucial physiological data may remain unexplored.


iNICU automatizes the workflow of NICU starting from the day of admission/birth till the discharge of the baby, thus reducing the responsibilities of users (nurses, doctors and administrators).
The system comes with screens that are the exact replica of the NICU workflow like admission form, assessments and nursing charts. In addition, the system captures real-time clinical parameters of every neonate coming from multiple devices (which can be viewed on a single interface) and stores variations of the same forever on the cloud, so it can be accessed by the doctor at any point of time. In order to reduce human errors, the system has automatic calculators for ordering / prescribing /monitoring feeds and medication statuses.
It also provides the doctors with a solution to all the problems related to manual paperwork (such as duplication of records while preparing progress notes and discharge summary) by automatically generating progress notes of hospital stay as well as discharge summary.


iNICU leverages Beaglebone and Intel Edison based IoT integration with biomedical devices in NICU to capture real time vital parameters. These parameters captured by iNICU amount to millions of data points per day per child. Stream of data is sent to Apache Kafka layer which stores the same in Apache Cassandra NoSQL.
The data of feed intake, urine output, and daily assessment of child are captured in PostgreSQL database. INICU thus performs the role of the first Big Data hub (of both structured and unstructured data) of neonates across India offering temporal (longitudinal) data of their stay in NICU.
This not only allows clinicians to evaluate the efficacy of their interventions, but also provides avenues for translational research. To augment the research purposes, iNICU leverages drools based clinical rule based engine and deep learning based big data analytical model coded in R and PMML.