EscapeWildFire: Assisting People to Escape Wildfires in Real-Time
Andreas Kamilaris, Jean-Baptiste Filippi, Chirag Padubidri, Jesper, Provoost, Savvas Karatsiolis, Ian Cole, Wouter Couwenbergh, Evi Demetriou

TL;DR
EscapeWildFire is a real-time mobile system that models wildfire progression to help people escape safely, aiming to reduce wildfire casualties through an open-source tool.
Contribution
The paper introduces a novel mobile application with backend wildfire prediction modeling to assist in real-time evacuation during wildfires.
Findings
System correctness demonstrated in a pilot study
Open-source code available for adoption
Potential to improve wildfire safety and evacuation efficiency
Abstract
Over the past couple of decades, the number of wildfires and area of land burned around the world has been steadily increasing, partly due to climatic changes and global warming. Therefore, there is a high probability that more people will be exposed to and endangered by forest fires. Hence there is an urgent need to design pervasive systems that effectively assist people and guide them to safety during wildfires. This paper presents EscapeWildFire, a mobile application connected to a backend system which models and predicts wildfire geographical progression, assisting citizens to escape wildfires in real-time. A small pilot indicates the correctness of the system. The code is open-source; fire authorities around the world are encouraged to adopt this approach.
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