使用无人机无线传感器网络进行环境监测

B. Potter, Gina Valentino, Laura Yates, T. Benzing, A. Salman
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引用次数: 13

摘要

嵌入式电子设备和传感器在弥合物理世界和虚拟世界之间的鸿沟方面发挥着重要作用。智能手机、智能手表、可穿戴设备、医疗植入物和无线传感器节点等数十亿设备被认为是实现物联网的基石。此类设备通常携带敏感或专有数据,并用于关键应用,例如使用无线传感器节点远程捕获大气温室气体排放数据。此外,一些用于收集数据的设备被部署在偏远地区,这些地区不容易访问,并且由于缺乏网络连接,无法传输用于处理的数据。此外,无线传感器节点的使用已被证明可以使数据收集更快,劳动强度更低,更具成本效益。在本文中,我们提出了一种从无线传感器节点中的三个传感器远程采集数据的有效方法。该项目的预期目的是远程监测谢南多厄河南叉的一条支流。该系统利用无人驾驶飞行器从远程流站点收集数据。我们详细介绍了一种定制的无人机在无线传感器节点的连接范围内飞行的方法,建立一个通信通道来上传和存储待处理分析的数据。通过环境案例研究展示了所使用的方法,该方法说明了实现无线传感器节点的优势,包括访问远程位置,连续数据收集,以及减少与现场数据收集方法相关的劳动力和成本。我们展示了我们的节点在功率和能耗方面是高效的。
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Environmental Monitoring Using a Drone-Enabled Wireless Sensor Network
Embedded electronic devices and sensors are playing a major role in bridging the gap between the physical world and the virtual world. Billions of devices such as smartphones, smart watches, wearables, medical implants, and wireless sensor nodes are considered building blocks in making the Internet of Things a reality. Such devices often carry sensitive or proprietary data and are used in critical applications, such as the use of wireless sensor nodes to remotely capture atmospheric greenhouse gas emissions data. Additionally, some of the devices used to collect data are being deployed in remote areas where accessibility is not easy and transmission of data for processing is not available due to the lack of network connectivity. Additionally, the use of wireless sensor nodes has been proven to making data collection faster, less labor intensive, and more cost effective. In this paper, we present an efficient method to remotely collect data from three sensors in a wireless sensor node. The intended purpose of this project is to remotely monitor a tributary to the South Fork of the Shenandoah River. The system makes use of an unmanned aerial vehicle to collect data from a remote stream site. We detail the methodology in which a customized unmanned aerial vehicle flies within range of connectivity of a wireless sensor node, establishing a communication channel to upload and store the data for pending analysis. The methodology utilized is shown through an environmental case study which illustrates the advantages of implementing a wireless sensor node which includes accessing a remote location, continuous data collection, and reduction of labor and costs associated with field data collection methodologies. We show that our node is efficient in terms on its power and energy consumption.
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