Artificial Intelligence (AI)

Lead: Ciro Farinelli ([email protected])


Artificial Intelligence (AI) is a powerful tool used to process high quantities of data. Within the scope of STEA, the data to be analyzed are mainly gathered from Earth Observation (EO) programs. STEA has a strong internal expertise, composed of data scientists, mathematicians and developers. Some of the technologies we are experienced with are: deep learning, evolutionary computation, probabilistic models, and neural networks.
The applications of these technologies have direct impacts on the SDGs n. 4, 11 and 17.

Key Application Areas

Disaster Management

By using machine learning and deep learning techniques, we can process data from Earth Observation (EO) missions and produce models which can be used to define human behavior in several types of situations, such as environmental disasters (e.g. hurricanes, earthquakes), or social changes (e.g. wars, Ebola disease spread behavior). These analyses can be coupled with on-site data provided by local or international partners. AI techniques are able to have direct impacts on the SDGs n. 1, 2, 6, 9, 11, 13, 15, but also indirect impacts on all the remaining SDGs.

Earth’s Water

Climate change effects modeling using neural networks and reinforcement learning technologies will be able to create models based on Space data (e.g. from the Sentinels – part of the EU’s Copernicus program), which will be partially drained on earth-based data. The aim is to create models which can show the effects of climate change and potentially show how much currently adopted solutions are actually beneficial. This will have a direct impact on the SDG n. 13, and indirect impacts on the SDGs n. 7, 11 and 14. An example of a potential project is a study of the climate change impacts on the rise of the level of the water in Venice.