Ultimately the project aims to enhance the accuracy of glucose prediction, particularly with the aims of predicting hypoglycaemic and hyperglycaemic conditions. It is our highest priority to provide a solution that can predict the onset of hypo- and hyperglycaemia at least 30 min in advance, so that the patient can take actions and prevent the onset of the condition. We aim to provide a solution based on powerful artificial intelligence approaches that most effectively exploit the minimum amount of information and minimum amount of sensing devices in order to provide patients with technologies and algorithms in the form of an easily accessible application that is able to meet their expectations for glucose control.University of Bern is a recipient of JDRF's research grant — Identification of Areas of Artificial Pancreas Algorithm Enhancements Through Big-Data Analysis — supported by Tidepool Big Data Donation Project.