|APPLICATION OF SMALL SENSOR SYSTEM (S3) IN THE AGRI-FOOD FIELD
The main goal of my PhD is the application of a Small Sensor System (S3) based on innovative nanowires chemical sensors in the agri-food field. In this field, S3 is manly used to evaluate the food quality and identity and it can also be integrated in household appliances in the Internet of Things perspective. There are two main lines of research that I deal with: the assessment of quality of Parmigiano Reggiano in order to avoid different types of fraud and the study of how sensors work in domestic ovens. My work is mainly based on data analysis of sensors signals, from univariate and multivariate statistical analysis to pattern recognition. With particular attention, I design and train artificial neural networks in order to resolve regression and classification problems.
I’m a Biomedical Engineer and during my master’s degree I specialized in data analysis. My knowledge in this field goes from univariate and multivariate statistical analysis to pattern recognition with the use of different classifiers. With particular attention, I design and train artificial neural networks in order to resolve regression and classification problems. The main application of my research is the data analysis of sensors signals, especially chemical sensors organized in arrays (electronic noses). In my work, e-noses are mainly used in the agri-food field, both in the evaluation of food quality and in the integration of the instrument in household appliances in the Internet of Things’ perspective.
Curriculum: Physical Sciences for Engineering
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