This project leverages YOLO (You Only Look Once) to detect various traffic violations in real-time, aimed at improving road safety and compliance.

This project basically aims to speed up the ticketing process for Traffic Sergeants by using their mobile phones and issue tickets by taking a couple of photos and uses Computer Vision APIs to process information from those photos.

Web (Django) application and Python appplication to keep track of traffic violations through RFID System in Raspberry Pi 3B.

A platform, 'Traffic-Violation-Report-System', enabling users in Taiwan to upload and share responses from law enforcement to traffic violations. This system aims for greater transparency in traffic law enforcement. It utilises Django for backend and Flutter for a separated frontend web development.

The aim of the project is to apply different global, local and performance interpretability methods as well as model fairness evaluations to a dataset with protected attributes. The dataset regards traffic violations in Montgomery, Maryland, USA. This is a fork of a group project of my Data Science for Business Master's Degree at HEC Paris.

This project is to determine the safest and the most dangerous neighborhoods in Chicago and provide suggestions for how to avoid many violations in certain areas.