节能型无线传感器网络在森林环境监测中的应用

发布时间：2018-06-18 08:29

本文选题：无线传感器网络 + 森林环境监测　；参考：《南京林业大学学报(自然科学版)》2014年04期

【摘要】：根据森林环境监测数据变化率相对较慢、数据冗余度较高,监测期间突发事件(如降雨、火灾)又有快速突变等特点,结合无线传感器网络在森林环境监测中的试验,从系统架设、传感器采样周期、基于系统休眠的自适应网络路由算法等方面分析了长期有效采集环境数据的系统结构,实时捕捉环境因子变化的方法;研究了网络节能、延长系统生命周期的方法;提出了采用变周期自适应采样法解决长期休眠丢失有效信息的方法,设计出一种结合系统休眠和分簇算法的自适应动态路由(SDRP)。系统实测结果表明,与常规森林资源与环境监测技术相比,节能型无线传感器网络不仅在时间和空间上提高了环境数据采集深度,同时提升了系统对环境因子变化的响应速度。此外,采用结合系统休眠的变周期采样技术以及针对系统节能的自适应动态路由都可有效降低系统能耗,维持系统工作的稳定性与数据的可靠性,适合森林环境监测。
[Abstract]:According to the characteristics of relatively slow change rate of forest environment monitoring data, high data redundancy, and rapid abrupt changes of sudden events (such as rainfall and fire) during monitoring, the experiment of wireless sensor network in forest environment monitoring is carried out. From the aspects of system erection, sensor sampling period, adaptive network routing algorithm based on system dormancy, this paper analyzes the system structure of collecting environmental data effectively for a long time, and studies the method of capturing the change of environmental factors in real time. In this paper, the method of prolonging the system life cycle is presented, and the method of adaptive sampling with variable period is proposed to solve the loss of effective information in long-term dormancy, and an adaptive dynamic routing scheme based on system sleep and clustering algorithm is designed. The measured results show that compared with the conventional forest resource and environment monitoring technology, the energy-saving wireless sensor network not only improves the depth of environmental data acquisition in time and space, but also improves the response speed of the system to the change of environmental factors. In addition, the variable period sampling technique combined with system dormancy and adaptive dynamic routing for energy saving can effectively reduce the energy consumption of the system, maintain the stability of the system and the reliability of the data, and are suitable for forest environment monitoring.
【作者单位】：南京林业大学信息科学技术学院;
【基金】：南京林业大学科技创新基金项目国家重点基础研究发展计划(2012CB416904)
【分类号】：TP212.9;TN929.5

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