Diabetes Risk Monitoring Tool

Cyber Wearable

the Cloud

big Data analyticS

This project involved the design, construction and testing of a prototype genomic lab on chip (LOC), able to identify specific genetic and epigenetic variants associated with the risk of diabetes and variability in response to nutritional interventions and/or exercise. In addition to the use of physical wearable systems, such as the LOC device, IDF Sharid envisages the use of other IOT devices and the implementation of a big data analytics cloud platform with an innovative interface that is capable of interpreting the data collected by the LOC and providing a molecular diagnosis.

Machine Learning, Big Data Analytics

With the hope of obtaining significant benefits in terms of usable information, SCAI Lab decided to process vast quantities of information and data using innovative machine learning, big data analytics solutions, and cognitive-oriented prediction systems.

The project is part of the following call for tenders: 2014-2020 Research and Innovation Operational Programme – call for the submission of industrial research and experimental development projects in the 12 Areas of Specialisation identified by the 2015-2020 NRP, Specialisation Area: Health.