Internet of Self-Powered Sensors: Towards a Scalable Long-Term Condition-based Monitoring & Maintenance of Civil Infrastructure

This is a collaborative research project between Washington University in St. Louis, Michigan State University and University of Nevada Reno and is investigating a cyber-physical framework for scalable, long-term monitoring and condition-based maintenance of civil infrastructures. Civil infrastructure constitutes a network of interdependent systems and utilities (e.g., highways, bridges, rail systems, buildings) that are necessary for supporting social and economic activities. 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 and due to unforeseen disasters. This research project is making significant pro-gress 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 intellectual merits of this research addresses different elements of the proposed i-IoT framework by bringing together expertise from three universities (Washington Univ. in St. Louis, Michigan State University and University of Nevada, Reno) in the area of self-powered sensors, energy scavenging processors, structural health monitoring and earthquake engineering. At the fundamental level, the project is investigating novel variants of our previously reported self-powered piezo-floating-gate sensors that will require zero-maintenance and can continuously operate over the useful life-span 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 investigating techniques that will 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 being 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 algo-rithmic level the project is exploring 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 natural crisis (for example an earth-quake). To date we have designed and prototype variants of wireless PFG sensors that can be embedded inside concrete structures. Here is an example of an H-gauge prototype that we are currently evaluating for smart highways. We have designed and prototyped the first version of a variance-based logic processor that combines energy scavenging, computation and communication at the logic level. The collaborative and interdisciplinary nature of this research is providing opportunities for unique outreach programs involving undergraduate and graduate students in areas of sensors, IoTs and structural health monitoring. To date the project is supporting the research of 5 Ph.D. students across three institutions. The project is also providing 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. We are verifying the functionality of the baseline self-powered sensor prototypes at the Mackinac bridge in Michigan, the Bio-pave project in France and NREL at Denver, Colorado. Also, we are conducing controlled test and verification of the sensor prototypes at the Earthquake Engineering Laboratory at the University of Nevada in Reno.