This project aims the development of an environment for analysis, cleaning and visualization of large amounts of spatio-temporal urban data. We also consider the definition of algorithms to detect possible unexpected events from the analysis of different datasets. This project is a collaboration with Behrooz Omidvar-Tehrani from The Ohio State University (United States). We will start analysing heterogeneous urban datasets (in CSV, XML and JSON formats) and design a JavaScript-based tool which imports these files and visualize the data on a geographical map. A JavaScript-based tool benefits from being portable, light, efficient and minimally dependent to the system configuration. We also consider defining a generic model for spatio-temporal data and propose recommendation and prediction algorithms. The results of this project will be a web-based framework that shall be developed to validate the models and algorithms in this research work.
Projeto importado do Suap em 13/08/2026 às 03:11 (há 3 horas, 13 minutos)