SMART FACE-MASK FOR MONITORING HEALT-RELATED PARAMETERS IN THE BREATHING ZONE
Componente | Categoria |
---|---|
Nicola Lovecchio | Componenti strutturati del gruppo di ricerca / Structured participants in the research project |
Augusto Nascetti | Componenti strutturati del gruppo di ricerca / Structured participants in the research project |
Vincenzo Ferrara | Componenti strutturati del gruppo di ricerca / Structured participants in the research project |
Giampiero De Cesare | Componenti strutturati del gruppo di ricerca / Structured participants in the research project |
Mauro Olivieri | Componenti strutturati del gruppo di ricerca / Structured participants in the research project |
The SARS-CoV 2 pandemic has forced the use of surgical or FFP2 face masks for a considerable number of hours during the day. The chemical-physical characterization of the air between the face and the mask (breathing zone) is useful both for identifying air quality and for any monitoring of the person's vital parameters.
To this aim, this research project proposes to develop an intelligent mask containing sensors capable of monitoring both the quality of the breathing zone (temperature, humidity and concentration of carbon dioxide) and some parameters of the breath (volatile organic compounds whose presence could indicate possible diseases). The sensors will be interfaced with electronic circuits able to transmit the acquired data via WiFi to a local network (for example a mobile phone) which in turn sends them to a database that can be accessed through a website. The website will present the data to registered users with different levels of access depending on whether the users themselves are researchers, doctors or hospitals.
The results achieved with this project are really versatile because the same electronic circuits and the same IT structure (website with databases at different access levels) can also be used in different applications, such as in telemedicine, sustainable agriculture or environmental monitoring. For example, air quality monitoring could be achieved using the same electronic circuits (but different sensors) and collecting the data taking advantage of a bicycle or and electric scooter that goes around the city.