Dynamic Emergency Navigation Based on Prediction via Wireless Sensor Networks

Abstract

Wireless sensor networks (WSNs) are distributed networking systems consisting of many self-organized sensor nodes deployed in monitoring areas of interest. Emergency navigation is an emerging application of WSNs, which aims to solve the problem that users choose the optimal path and reach the designated target safely based on the sensed information in dangerous environments. However, traditional distributed emergency navigation algorithm has relatively low dynamic adaptability and navigation efficiency. In this paper, a dynamic emergency navigation algorithm based on prediction via WSNs is proposed. First, we introduce a prediction model based on time series to predict the dynamic changes of the environment sensed by WSNs. Then, for each user requesting the navigation path, the potential field of each node is established by comprehensively considering its distance to the target and corresponding predictive danger value. Based on the dynamically updated potential field, the users exploit the gradient descent method to efficiently approach the target areas node by node. The simulation results demonstrate the superiority of the proposed algorithm in terms of the navigation efficiency and safety in dynamic environments.