SmartRescue: Architecture for Fire Crisis Assessment and Prediction

Mehdi Ben Lazreg, Jaziar Radianti, Ole-Christoffer Granmo

ABSTRACT

In case of indoor fire hazards, firefighters face difficulties at assessing the fire situation and evacuating trapped victim inside the building,  especially when the fire is big, and the building is unknown to them. On the other hand, modern sensor technologies in smartphone are becoming more advanced, widespread, and can be exploited for helping the firefighting operation. This paper proposes using smartphones as a distributed sensing and computing platform, for supporting firefighters to conduct their mission. The developed solution is based on collecting sensor data from smartphones. A Bayesian network then uses this data to generate a picture of the fire and predict its development. The additional indoor positioning feature make this proposed solution a promising tool to make the firefighter intervention more efficient and fast in order to save more lives.

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