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

本研究调查了一个网络物理框架，用于民用基础设施的可扩展，长期监测和维护。随着世界经济及其人口的增长，对更大和更复杂的民用基础设施网络的依赖性不断增加，如联邦、州和地方政府花费数十亿美元来升级或修理运输系统或公用设施所证明的。尽管有这些巨大的支出，该国继续遭受基础设施老化的惊人后果。因此，未来智慧城市的概念最重要的是智能民用基础设施的概念，它可以自我监控，预测任何即将发生的故障，并在极端事件（如地震）的情况下确定需要立即修复的部分，并优先考虑紧急响应的区域。该研究项目的一个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涉及技术领域的本科生和研究生的独特外展计划提供机会，例如，传感器、物联网和结构健康监测。该项目还将提供渠道，向州政府的利益攸关方传播这项研究的结果，并将研究结果转化为可实地部署的原型。 这项研究通过汇集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。在基础层面上，该项目涉及研究自供电传感器，这些传感器无需维护，并且可以在结构的使用寿命内连续运行，而不会出现任何停机时间。在这方面的挑战是，传感器需要占据足够小的体积，使得这些设备的阵列可以容易地嵌入，并且可以在结构成像中提供准确的空间分辨率。本研究还调查技术，使真实的时间无线收集数据从一个阵列的自供电传感器嵌入在一个结构，而不采取的结构停止服务。要探索的方法包括结合能量收集，转换，整流和逻辑计算的物理，以提高系统的能量效率和减少系统延迟。在算法层面，该项目基于从嵌入在不同空间位置的自供电传感器收集的历史数据，探索新的结构失效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）后快速识别结构的最脆弱部分。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.