Towards an IoT and Big Data Analytics Platform for the Definition of Diabetes Telecare Services

Abstract

Diabetes is considered as one of chronic disease that requires patient self-monitoring processes and constant care. Patients need to perform frequently a control of glucose level in the blood in order to prevent hypoglycemia episodes. However, efficient detection of hypoglycemia could be done by checking other vital signs. The gaps in the manual monitoring and heavy control process prevent some patients to daily control and follow the progress of their disease; therefore, several metabolic problems could be noticed and need to be taken seriously into consideration. Therefore, tools for efficient disease control are required to allow self-monitoring of blood glucose and other vitals and measures (e.g., activities, dietary). This will allow filling the gap between patients and carers with the main objective to enhance comfort of patients and reduce the treatment costs. The work presented in this paper aims to develop a platform that combines IoT and complex event processing techniques for hypoglycemia detection. A prototype is introduced together with preliminary results to show its effectiveness for the definition of diabetes telecare services, mainly for hypoglycemia detection.