iNICU automates 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.