| KEYWORD |
Area Engineering
Exploration of machine learning algorithm for smart agriculture application
keywords MACHINE LEARNING, SMART AGRICULTURE
Reference persons DANILO DEMARCHI, UMBERTO GARLANDO, MAURIZIO MARTINA
Research Groups MiNES (Micro&Nano Electronic Systems)
Thesis type EXPERIMENTAL
Description The candidate will deal with the exploration of machine learning models applied to precision agriculture. In particular, impedance and environmental data will be used to create predictive models to discriminate a plant's health status. In the first part of the work, reordering and manipulation of acquired data are requested to ease the subsequent implementation of predictive algorithms. Then, an analysis of machine learning models is requested to evaluate their effectiveness in discriminating the health status of a plant. In the end, integration of the analyzed models is requested inside an existing framework implemented in Python
Required skills Python programming, Git versioning software (appreciated)
Deadline 21/11/2023
PROPONI LA TUA CANDIDATURA