📆 Project Period | March - June, 2024 |
👤 CIN Visiting Researcher |
Project Description
- Handling and processing in situ data acquired from ESA IoT air quality devices (so called Air Quality Platform - AQP) and official ARPA stations
- Time/space co-locating with EO satellite data (Sentinel-5p) to assess their correlation.
- Machine learning techniques will be investigated to propose joint IoT/EO fusion products
Tools
- Electronic Laboratory
- Catboost library
- ML Python libraries
Development outputs obtained during the project
- Correlation between Satellite data (Sentinel-5p), in-situ Data (ARPA Lazio) and IoT data (AQP system)
- Presentation at phi-lab
- Thesis degree: Evaluation of environmental parameters with Copernicus Sentinel-5P data, ARPA, AQP in situ data and Deep Learning techniques