ABSTRACT

Among the variety of efforts required to restore the functionality of civil infrastructure components (CICs) after natural disasters, rapid damage assessment is a critical task that helps residents, business owners, and emergency management authorities evaluate the extent of loss, and subsequently, secure the resources necessary for recovery at the earliest possible time. In reality, however, immediate access to enough professional crews trained for the inspection and condition assessment of CICs is not always possible, especially after a natural disaster that impacts a large geographic region. Consequently, the post-disaster safety and condition assessment of a vast number of buildings and other critical facilities can take several weeks to months, not only delaying the restoration of the community, but also incurring significant indirect losses due to disruptions in everyday activities. To address this critical issue, the proposed research plans to introduce a data-informed platform to systematically utilize the hidden capacity of the general public for the rapid damage assessment of CICs.

The overarching goal of the proposed research activities is to engage those who have traditionally had no direct contribution to the safety and condition assessment of damaged CICs. For this purpose, the requirements necessary to establish a rigorous computational platform to evaluate human performance in the context of CIC damage assessment will be studied. Building on the capabilities of such a platform, investigations will also be performed to understand the technical and societal aspects of experiential learning methodologies appropriate for training the general public to perform rapid damage assessment activities. To ensure that a high-fidelity platform is delivered, the outcome of the individual tasks, as well as the entire platform, will be systematically verified and validated. Specifically, an array of community-of-practice activities have been planned to scale up the investigations and engage a diverse group of non-expert citizens. By creating a unique multidisciplinary opportunity to test the related hypotheses from both technical and social science perspectives, the outcome is expected to greatly facilitate mitigating the consequences of natural disasters, especially in vulnerable communities.

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.

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