基于WSN的灾难现场最优逃生路径规划

针对当前建筑灾难救援中存在的诸多亟需解决的问题，利用布设在建筑物内的无线传感器网络获取实时信息，根据灾难现场的全局环境信息及其变化趋势，建立灾难威胁模型.利用改进的蚁群算法DACA(Dijkstra antcolonyalgorithm)实现逃生路径规划:一方面有效利用Dijkstra算法的优点改进蚁群算法，另一方面通过改进信息素浓度更新机制来改进蚁群算法的性能.在动态的灾难环境中，该方法能够在建筑物处于紧急状态时给出优化的人员疏散策略，有效实现被困人员逃生和消防员营救的路径导航，减少人员伤亡，提高救援效率.

WSN-based Optimal Path Planning for Escaping from Disaster Scene

For many problems to be solved in the building disaster relief currently, a new approach was proposed to plan the escaping paths for people trapped in the building. In this method, a model of disaster threat was developed using the real-time information from the wireless sensor network laid in the building, including the global environmental information of disaster scenes and its changes. The conventional ant colony (AC) algorithm was improved by using the Dijkstra algorithm and the pheromone updating mechanism, thus optimal escaping paths were obtained using the improved AC algorithm. In the dynamic disaster environment, the proposed method can provide an optimal strategy for person evacuation, guiding the trapped people and firefighters, which can effectively reduce casualties and increase rescue efficiency.