Project for Visual Analytics course (2022/23) at Sapienza University of Rome.
Road accidents are a significant contributor to global mortality and injuries. In a bustling metropolis like Rome, an average of 79 accidents occur daily, resulting in 0.3 fatalities and 100 injuries.
The study and analysis of traffic accidents can provide valuable insights into the underlying causes, consequences, and risk factors associated with these incidents, ultimately aiding the development of effective road safety strategies.
Discover the live version of our project:
- running the server file
/app.py - reaching the
http://localhost:63342/visual-analytics/index.htmlthrough your browser.
A direct window will be provided to explore functionalities and features.
A PowerPoint presentation and a detailed scientific paper have been realized to provide a complete project documentation:
- PowerPoint Presentation 🔗, to describe project goals, the data structure, and the chosen visualizations.
- Scientific Paper🔗, to describe the whole design process, rationale and prototype.
- d3.js
a javascript library for producing dynamic, interactive data visualizations in web browsers. - scikit-learn a python library used for dimensionality reduction.
- pandas a python library used for analyzing, cleaning, exploring, and manipulating data.
- geopandas a python library used for handling and analyzing geospatial data.
The team is composed of two students currently enrolled at Engineering in Computer Science:
Mario Cosimo Angelini [2029254]
angelini.2029254@studenti.uniroma1.it
Daniela Rieti [1762973]
rieti.1762973@studenti.uniroma1.it