EscapeWildFire: Assisting People to Escape Wildfires in Real-Time
This addresses the urgent need for pervasive systems to guide citizens to safety during wildfires, potentially aiding fire authorities globally.
The paper tackles the problem of assisting people to escape wildfires by presenting EscapeWildFire, a mobile app with a backend system that models and predicts wildfire progression in real-time, with a small pilot indicating correctness.
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.