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.

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.

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.

An intelligent traffic management system that uses artificial intelligence and computer vision to monitor road conditions and control traffic signals dynamically. It analyzes real-time traffic data from cameras and sensors to reduce congestion, optimize signal timing, and improve road safety.

Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials. Smart Traffic Control using AI leverages artificial intelligence to analyze traffic patterns and dynamically control signals, reducing congestion and improving urban transportation efficiency.