Smart navigation for firefighters in hazardous environments: A ban-based approach

Abstract

Recent advances in integrated electronic devices motivated the use of Body Area Networks in many applications including monitoring, localization, tracking and navigation. In this paper we introduce an indoor navigation approach based on Body Area Network to assist firefighters in finding their way to save human lives and to combat fires. For this we develop a technique based on a real-time graph called Temporal Weighted Graph that provides some special functions such as localization, navigation, communication, and hazard estimation. Then we implement a real time solution aiming to predict firefighters' isolation time in an indoor space by estimating the horizon of risk deterioration in the graph. And finally, we demonstrate the importance of the presented technique in assisting firefighters during the navigation process. A set of simulation scenarios are conducted to evaluate the performance of the solution. © 2013 Springer-Verlag.