The overall objective of this project is to advance the transition towards “intelligent” learning in order to optimize teaching, not only distance learning but also face-to-face and hybrid learning.

The project aims to identify the key factors influencing the perception of urban safety in selected neighborhoods of Alicante by analyzing elements such as lighting quality, graffiti, population density, and other relevant indicators. Through the use of artificial intelligence and video analysis tools, it seeks to create an objective, data-driven diagnostic that maps urban conditions affecting perceived safety.

The goal of this project is to develop an intelligent system for analyzing and managing recycled plastic samples in compliance with regulations. It involves creating an online data management platform to organize experiments and verify conformity, a computer vision system for automated quality classification using deep learning, and a quality evaluation framework based on machine learning and PCA methods.

This project covers several aspects of the process for verifying compliance with regulations based on samples of recycled plastic material — from analyzing the applicable standards to developing new methods of sample processing using artificial intelligence techniques.