CPS:TTP Option: Synergy:Collaborative Research:Internet of Self-powered Sensors - Towards a Scalable Long-term Condition-based Monitoring and Maintenance of Civil Infrastructure

这项研究调查了用于可扩展、长期监控和维护民用基础设施的网络物理框架。随着世界经济和人口的增长，人们对更大、更复杂的民用基础设施网络的依赖日益增加，联邦、州和地方政府花费数十亿美元升级或修复交通系统或公用事业就证明了这一点。尽管支出巨大，但该国仍继续遭受基础设施衰退带来的惊人后果。因此，未来智慧城市概念中最重要的是智能民用基础设施的概念，它可以自我监控以预测任何即将发生的故障，并在极端事件（例如地震）的情况下识别需要立即修复的部分，并优先考虑紧急响应区域。该研究项目的目标是通过研究使用自供电嵌入式健康监测传感器网络的基础设施物联网 (i-IoT) 框架，在实现这一宏伟愿景方面取得重大进展。这项研究的协作和跨学科性质将为传感器、物联网和结构健康监测等技术领域的本科生和研究生参与的独特外展项目提供机会。该项目还将提供向州政府利益相关者传播研究结果以及将研究结果转化为可现场部署原型的途径。 这项研究汇集了三所大学在自供电传感器、能量收集处理器、结构健康监测和地震工程领域的专业知识，解决了拟议的 i-IoT 框架的不同要素。从根本上讲，该项目涉及研究自供电传感器，这些传感器需要零维护，并且可以在结构的使用寿命内持续运行，而无需经历任何停机。这方面的挑战是传感器需要占据足够小的体积，以便可以轻松嵌入这些设备的阵列，并可以在结构成像中提供准确的空间分辨率。这项研究还研究了能够从嵌入结构内的自供电传感器阵列实时无线收集数据的技术，而无需使结构停止服务。所探索的方法包括将能量收集、转换、整流和逻辑计算等物理原理结合起来，以提高系统的能效并减少系统延迟。在算法层面，该项目基于从嵌入不同空间位置的自供电传感器收集的历史数据，探索新颖的结构故障预测和结构取证算法。这包括内核算法，可以利用数据在人为或自然危机（例如地震）后快速识别结构中最脆弱的部分。最后，本研究的技术转化计划是在实际部署中验证所提出的 i-IoT 框架，其中包括建筑物、多跨桥梁和高速公路。

This research investigates a cyber-physical framework for scalable, long-term monitoring and maintenance of civil infrastructures. With growth of the world economy and its population, there has been an ever increasing dependency on larger and more complex networks of civil infrastructure as evident in the billions of dollars spent by the federal, state and local governments to either upgrade or repair transportation systems or utilities. Despite these large expenditures, the nation continues to suffer staggering consequences from infrastructural decay. Therefore, paramount to the concept of a smart city of the future is the concept of smart civil infrastructure that can self-monitor itself to predict any impending failures and in the cases of extreme events (e.g. earthquakes) identify portions that would require immediate repair, and prioritize areas for emergency response. A goal of this research project is to make significant progress towards this grand vision by investigating a framework of infrastructural Internet-of-Things (i-IoT) using a network of self-powered, embedded health monitoring sensors. The collaborative and interdisciplinary nature of this research would provide opportunities for unique outreach programs involving undergraduate and graduate students in technical areas, e.g., sensors, IoTs and structural health monitoring. The project would also provide avenues for disseminating the results of this research to stakeholders in the state governments and for translating the results of the research into field deployable prototypes. This research addresses different elements of the proposed i-IoT framework by bringing together expertise from three universities in the area of self-powered sensors, energy scavenging processors, structural health monitoring and earthquake engineering. At the fundamental level, the project involves investigating self-powered sensors that will require zero maintenance and can continuously operate over the useful lifespan of the structure without experiencing any downtime. The challenge in this regard is that sensors need to occupy a small enough volume such that an array of these devices could be easily embedded and can provide accurate spatial resolution in structural imaging. This research is also investigates techniques that would enable real time wireless collection of data from an array of self-powered sensors embedded inside a structure, without taking the structure out-of-service. The methods to be explored involve combining the physics of energy scavenging, transduction, rectification and logic computation to improve the system's energy-efficiency and reduce the system latency. At the algorithmic level the project explores novel structural failure prediction and structural forensic algorithms based on historical data collected from self-powered sensors embedded at different spatial locations. This includes kernel algorithms that can exploit the data to quickly identify the most vulnerable part of a structure after a man-made or a natural crisis (for example an earthquake). Finally, the technology translation plan for this research is to validate the proposed i-IoT framework in real-world deployment, which includes buildings, multi-span bridges and highways.