Firefighter prediction

Recent increase in wild fires in France, and around the world, are an unfortunate example of the current challenges firefighters face nowadays. Data science can provide a solution for such challenges. Through various visualizations, we can empower our public services to react faster and more efficiently to extreme situations. The firefighter project aims to empower fire departments and provide them with the tools necessary for data based decision-making. 

The project focuses on the data from the firefighter department in the French Alps. It consists in three distinct challenges. First, the amount of fire stations present in French Alps make data aggregation difficult and complicates the applications of decisions taken at a departmental level. Various visualizations or dashboard can be a powerful tool for management to take appropriate decisions. Second, the amount of intervention has been increasing over the last years. Predictive models enable us to have a clearer picture of what needs a fire department may have in the future. Third, firefighter is a stressful and arduous profession. Data science can help us make sure that firefighters are not overworked, and that each station has enough staff in case of emergencies. In such a case, a combination of visualizations and scenario-based prediction can insure the functioning of each individual fire station in a department.  

Dr. Mathis Mourey
Researcher
I am a Lecturer in Finance/Statistics at THUAS and hold a PhD in Finance from the University Grenoble Alpes (UGA). My research mainly focuses on Systemic Risk measurement. I also have research interests in Data Science and Cryptocurrencies.