Computer Vision Applications (Phase 2)

This research project, led by the Salesian Polytechnic University (UPS), focuses on applying computer vision techniques to address critical challenges in the city of Quito. The multidisciplinary team uses advanced algorithms for two main subprojects: environmental management through the analysis of aerial images captured by drones to monitor solid waste and pollution, and the analysis of facial patterns to identify the ethnic composition of the Ecuadorian population, potentially facilitating the early detection of genetic diseases. The methodological approach is based on the scientific method, using quantitative experimentation to validate prototypes developed with free software. By avoiding costly methods like DNA testing and providing environmental monitoring tools, the project seeks to improve informed decision-making and promote urban sustainability. Expected results include functional prototypes, open-access datasets, and indexed scientific articles. This work not only strengthens the state of the art in artificial intelligence but also fosters engagement with society by raising awareness about waste management and offering accessible technological alternatives for medical diagnosis and scientific research.<br/><br/><b>Goal</b>: <br/>Develop computer vision applications to solve everyday problems in the environmental and medical fields, contributing to quality of life and sustainable development. The project aims to implement functional prototypes for urban waste analysis and the identification of ethnic-facial patterns.<br/><br/><b>Research lines</b>: <br/>Artificial intelligence and data mining