Creation of trainable knowledge models that benefit from a personalised and precise integration of air quality data acquisition with the real-time evolution of physiological parameters in the development of several breathing disorders
Effects of the daily exposition to some prevalent atmospheric pollutants on patients with COVID-19 and other high-risk respiratory diseases, such as COPD and asthma
Cutting-edge unobtrusive sensing technologies and advanced AI techniques to create a health monitoring system enabling early prediction of Diabetes Mellitus, Congestive Heart Failure and related diseases
Monitoring of Activities of Daily Living (ADL) of elders living alone at home, using gas sensors and applied AI to design identification algorithms through ML techniques
Use of graphene sensor networks in Ambient Assisted Livings environment to detect human activities, and integration into a monitoring system to feed AI and decision support algorithms