ERN: Emergence Rescue Navigation with Wireless Sensor Networks

Abstract

Navigation with wireless sensor networks (WSNs) can help people escape safely from an emergency. Previous navigation algorithms attempt to find safe and efficient escape paths for individuals under various environmental dynamics but ignore possible congestion caused by the individuals rushing for the exits. Moreover, all the previous works have overlooked the fact that the emergency rescue force can take actions strategically in order to save people out of danger. We propose ERN, Emergence Rescue Navigation algorithm by treating WSNs as navigation infrastructure. ERN takes both pedestrian congestion and rescue force flexibility into account. A directed graph is used to model the emergency regions. Human’s movements are regarded as network flows on the graph. By calculating the maximum flow and minimum cut on the graph, the system can provide firemen rescue commands to eliminate key dangerous areas, which may significantly reduce congestion and save trapped people. We have performed extensive simulations under dynamic environments to evaluate the effectiveness and response time of ERN. Simulation results show that with ERN people in emergency are evacuated much faster and less congestion is observed