This project focuses on predicting NYC taxi trip durations 🚖🗽 using machine learning techniques. By analyzing factors such as pickup and drop-off locations, timestamps, and traffic conditions, it aims to provide accurate duration estimates to enhance rider and driver experiences in New York City.

This repository contains the analysis of urban accidents for the municipality of Coimbra. Specifically, for the period 2019–2024, the critical points of the city network and the accident accumulation areas were analyzed, year by year.

MOBIbike Dresden: Code Scripts (in .R) and Project Report (.pdf)

An SPA aimed at optimizing urban parking in Ghent, utilizing open data and APIs to simplify the search for parking spaces. It's the first step towards improving mobility and integrating the city's art and technology.