Integrated sensing and RFID solutions in challenging environments

今天，我们有能力集成两个尖端的无线系统：即射频识别(RFID)和无线传感器网络(WSNs)。RFID能够大规模识别物体，而无线传感器网络则提供有关物体及其附近环境的信息池。它们与RFID传感器网络(RSN)的集成将实现重要的住宅、商业和公共部门应用。 在具有挑战性的环境中的采用受到三个因素的阻碍：i)无线通信在工业环境中本质上是困难的；ii)在RSN中集成不同的组件使通信协议进一步复杂化；以及iii)针对尺寸、能源效率和部署方案的限制，对准确性、健壮性和系统响应性的要求提出了重大挑战。 在我们以前在RSN和具有挑战性的环境中所做工作的基础上，我们提出了一个集成的RSN架构，它将通过优化RSN的本地化、监控、转发和报告来克服这些障碍。我们的目标包括设计和开发能够承受石油开采操作环境的RSN节点原型。我们的样机将部署在辛克鲁德的麦克默里堡油田，以监控挖掘部件的健康状况，并促进任何损坏部件的有效回收。 我们的架构将通过在油砂开采中引入一种新的传感和识别范例，为加拿大提供技术和经济优势。因此，我们的研究对于在任何具有挑战性的环境中进行有效的工业监控将是重要的。 四名研究生(两名博士和两名硕士)和一名研究工程师将通过这个项目接受实用的、最先进的RSN设计方面的培训。

Today we have the technical capacity to integrate two cutting-edge wireless systems: namely radio-frequency identification (RFID) and wireless sensor networks (WSNs). RFIDs enable large scale identification of objects while WSNs provide a pool of information about the objects and environment in its vicinity. Their integration into RFID sensor networks (RSNs) will enable significant residential, commercial and public sector applications. Adoption in challenging environments has been hindered by a three factors: i) wireless communication is intrinsically difficult in industrial environments; ii) integrating heterogeneous components in RSNs further complicates communication protocols; and iii) the requirements for accuracy, robustness and system responsiveness present major challenges against the constraints of size, energy efficiency and deployment schemes. Building upon our prior work in RSNs and in challenging environments, we propose an integrated RSN architecture that will overcome these obstacles by optimizing RSN localization, monitoring, relaying and reporting. Our objectives include the design and development RSN node prototypes that are capable of withstanding the oil extraction operating environment. Our prototypes will be deployed in Syncrude's Fort McMurray field to monitor the health of digging components and to facilitate the efficient retrieval of any damaged components. Our architecture will provide both a technical and economical advantage for Canada by introducing a novel paradigm of sensing and identification in oil sand mining. As a result, our research will be important for effective industrial monitoring in any challenging environment. Four graduate students (two PhD and two MSc) and an research engineer will be trained in practical, state-of-the art RSN design through this project.