The main goal of this project is to explore the applications and limitations of artificial intelligence (AI) algorithms with accelerated processing hardware capabilities, as a unit of the IPSentinel for the digestion of large volumes of remotely sensed data, to produce level-3 products for land applications with the least amount of human intervention.

We propose exploring two artificial intelligence approaches, one applying active learning techniques, and another based on fuzzy logic.

1- Software Products:
- Scientific advances in the generation of land-cover land-use maps using active learning techniques in the context of Big Data for remote sensing
- Exploring the application of an intelligent data fusion algorithm for the classification of multispectral images

2- Hardware:
- Implementation on dedicated hardware (GPU and FPGA) for acceleration of the data processing.