AIR Institute applies Deep Learning and Big Data to improve atmospheric forecasting

One of today’s greatest challenges is to boost the use of clean, renewable energy, and technology is playing a key role in achieving this. Projects such as AQUILON, an initiative developed by AIR Institute together with SOLUTE, are a clear example. This platform provides a new source of weather forecasts by harnessing massive open data, BOLD sources, and AI models.

Throughout the project, researchers have worked on the development of a platform based on Cloud Computing and Big Data technologies for data fusion, alongside Deep Learning techniques to improve both data quality and the accuracy of atmospheric predictions.

All collected information and forecasts are made available to interested entities, enabling them to obtain more precise data and accurately anticipate weather events. The platform also supports the development of a greener electricity system and a more efficient agricultural sector, all powered by artificial intelligence.

At AIR Institute, we remain committed to the efficient and sustainable use of our natural resources, as well as to researching and developing technological solutions that promote sustainability while enhancing quality of life.

The AQUILON project is funded by the Spanish Ministry of Science and Innovation (CPP2021-008737) and the European Union through NextGenerationEU/PRTR.