| KEYWORD |
DAUIN - GR-06 - ELECTRONIC DESIGN AUTOMATION - EDA
Air Quality and pollutants estimation
Thesis in external company
keywords DEEP LEARNING, MACHINE LEARNING, ARTIFICIAL NEURAL NETWORKS
Reference persons ALESSANDRO ALIBERTI, EDOARDO PATTI
Research Groups DAUIN - GR-06 - ELECTRONIC DESIGN AUTOMATION - EDA, ICT4SS - ICT FOR SMART SOCIETIES
Thesis type DATA ANALYSIS
Description Air pollution stands as one of the foremost health concerns worldwide. Specifically, the Pianura Padana ranks among the most polluted regions globally. To assess air quality in such regions, data on pollutants such as PM2.5, PM10, NO2, and O3 levels are commonly utilized. These parameters provide critical insights into the composition of the atmosphere, enabling us to gauge the severity of air pollution and its potential impacts on human health and the environment.
In the context of a business research project, the student will investigate the state-of-the-art forecasting and classification techniques for air quality and pollutant estimation to develop new methodologies by leveraging the latest Machine Learning techniques.
Required skills Programming skills in languages like Python, Java, or similar.
Proficiency in working with ML / AI / DL techniques.
Deadline 02/05/2025
PROPONI LA TUA CANDIDATURA