为了降低应用于突发事件监测的无线传感器网络的能量消耗,设计实现了一种基于事件驱动的动态分簇路由算法。在人体神经系统工作机制和传感器网络分簇路由协议的基础上,建立了基于人体神经系统的传感器节点模型,提出簇的生存时间和覆盖范围依据事件情况而动态调整,以有效提高数据融合性能,避免冗余分簇。仿真实验结果表明,该算法与TEEN相比消耗的能量更少,可以有效延长网络的生存时间。 In order to reduce the energy consumption of wireless sensor networks used in emergency monitoring, an event-driven dynamic clustering routing algorithm is designed and implemented. Based on human nervous system working mechanism and sensor network clustering routing protocol, a sensor node model based on human nervous system is established, and the survival time and coverage of the cluster are dynamically adjusted according to the events so as to effectively improve data fusion performance, Avoid redundant clustering. The simulation results show that the proposed algorithm consumes less energy than TEEN and can effectively prolong the lifetime of the network.