1. EscapeWildFire: Assisting People to Escape Wildfires in Real-Time
- Author
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Kamilaris, Andreas, Filippi, Jean-Baptiste, Padubidri, Chirag, Provoost, Jesper, Karatsiolis, Savvas, Cole, Ian, Couwenbergh, Wouter, and Demetriou, Evi
- Subjects
Computer Science - Computers and Society ,Computer Science - Computer Vision and Pattern Recognition - 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., Comment: 6th IEEE International Workshop on Pervasive Context-Aware Smart Cities and Intelligent Transport System (PerAwareCity), Proc. of PerCom 2021, Kassel, Germany, March, 2021
- Published
- 2021