Real-time assistance of endangered people in forest fires
Problem Statement:
In recent years several human and natural disasters have caused a significant number of fatalities, mainly due to the lack of preparation of populations. In recent years, Europe has experienced several natural disasters. In particular, large forest fires have been reported in several countries mainly due to climate change (drought and extreme high temperatures), combined with a poor spatial planning: Portugal, Spain, Greece, Norway. Nevertheless, the evacuation plans on the affected communities have not been completely implemented related to forest fires and other disasters. Therefore, these communities continue to be vulnerable to future forest fires. It is also expected that countries which never had serious risks of fire disasters (e.g. Scandinavian countries, Netherlands) start to become at risk due to the summer prolonged heat waves and high temperatures. In a previous semester, we have developed “Escape Wildfires”, a system and mobile app which can be used by citizens in order to safely evacuate wildfires occurring nearby them:
https://superworld.cyens.org.cy/project11.html
https://github.com/rise-centre/Escape-Wildfires
https://superworld.cyens.org.cy/papers/kamilaris_PerAwareCity_6pages.pdf
Task:
This project will address the problem of providing real-time support to people in danger in case of forest fires happening in the surrounding area. A mobile application needs to be extended and enhanced with new features, which will better guide the user, based on his/her current location and the information received from a central server on which way to take in order to escape safely the fire. The application needs to consider whether users have access to car, bike, if people have mobility problems etc. If the life of the user is in danger, then the application needs to inform automatically/immediately rescue services. The most important part of the project would be to improve the mobile app’s evacuation algorithm, by considering the case study of a recent massive wildfire in Troodos, Cyprus, testing the app and the algorithm in different evacuation scenarios: https://newseu.cgtn.com/news/2021-07-05/Massive-fatal-Cyprus-wildfire-under-full-control--11EpuKaIPwQ/index.html
Work:
10% Theory, 10% Simulations, 30% Modelling and Algorithms, 30% Programming, 20% Writing
Contact:
Andreas Kamilaris (a.kamilaris@utwente.nl)