FW-HTF-P: Distributed Intelligent Assistant to Infrastructure Inspection Workers

Case Western Reserve University, Cleveland OH

Investigators

Abstract

Sustainable, safe infrastructure carries the prosperity of our society. The Nation faces a grave infrastructure challenges in maintaining and upgrading its infrastructure to deliver an adequate standard of service compatible to the expectations of its citizens. Besides, the prosperity of our communities requires to embrace and erect emerging types of service infrastructure (i.e., autonomous vehicles, connected vehicles, Internet of Things, etc.) to meet modern-day expectations of digital and connected world. Infrastructure inspection provides important data to support decisions on its management, rehabilitation, and reconstruction plan, which cost billions of dollars each year. Various infrastructure service sectors conduct routine inspections of their infrastructure conditions (such as road, bridges, culvert, transmission lines, etc.). The infrastructure inspection industry employs tens of thousands workers in the private sector. The public sectors also maintains in-house workforce to inspect public infrastructure such as interstate highway, bridges, levees, etc. While there are significant advancement in robotics and information technologies, there are major technical barriers to make them fully integrated to augment human inspection and judgment. Consequently, human inspection remains as the mainstream for information collection across a variety of infrastructure sectors. This planning grant aims to define the road map towards how robotics and AI-driven techniques can be seamlessly integrated with human inspectors to improve their efficiency, reliability, and safety. The hypothesis is that the nexus of inspection workers and technology will support sound data-driven infrastructure decisions, and therefore help improve the level of service of the existing infrastructure system as well as better target high payoff futuristic infrastructure investments. It therefore will explore the frontier of human-technology nexus in domain with high impacts on the welfare of the infrastructure inspection workers as well as on the general public. The planning activities by this project will implement a number of strategies to build a roadmap for human-robotics integration center upon infrastructure inspection workers. The integrated research theme is defined in the areas of Inspection efficiency and reliability, Inspector safety and cybersecurity, Decision machine in support of inspection decisions, Open framework for public engagement in infrastructure inspection. A number of planning activities will be implemented including the planning workshops, an interdisciplinary lecture series, regular teleconference meetings, and thrust leaders’ convocations. Stakeholders of infrastructure owners, inspection service providers, community colleges will be involved to provide inputs to refine the roadmap to advance convergence research agenda. Concerted efforts will be targeting at fostering workforce training and innovation culture. Besides providing extensive opportunities for dynamic interactions and transdisciplinary engagement, the planning activities will also provide participants with training of essential team science skills. The effectiveness of the planning activities will be measured by timely collecting feedbacks, which will be incorporated to further improve the planning activities for the best outcomes. This project will catalyze the integration of robotics and AI-driven techniques to help efficiency and safety of workers during infrastructure inspection, crucial to the sustainability and resilience of our infrastructure system. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.