Data driven risk management for fire services

This project aims to develop a flexible hierarchical statistical framework for the analysis and prediction of various types of fires. It will deliver a model for spatio-temporal inference (including monitoring, filtering and prediction) that is able to recognize patterns in historic data and convert these to a prediction. This is realized by applying Bayesian techniques to carry out simultaneous state and parameter estimation. The research will be carried out in close cooperation with the Twente Fire Brigade (TFB) that have been collecting data on every reported fire since 2004. It builds upon the knowledge gathered from successful collaborations that have been carried out in the recent past. The Dutch fire services can use the results of this study for both repression and prevention. Repression involves improved vehicle and personnel planning in the fire stations. Prevention involves informing the right people at the right time and evaluation of effectivity of public awareness campaigns.

  • Projectnummer / Project number: 18004
  • Gebruikers / Users: 6 instellingen / 6 institutions
  • Projectleider / Project leader: Prof. dr. M.N.M. van Lieshout, Universiteit Twente
  • Type project / Type project: Lopend
  • Startdatum / Start date: 1-1-2020
  • Einddatum / End date: 1-1-2024
  • Programma / Programme: Open Technologieprogramma
  • Vakgebied / Discipline: Wiskunde / Mathematics


Drs. Paul Blank (Programmamedewerker) Drs. Paul Blank (Programmamedewerker) +31 (0)30 6001347