Artificial Intelligence for Condition Assessment of Critical Infrastructure

Unexpected deterioration and failure of concrete infrastructure causes major disruptions and in the most severe
cases, results in lives lost. According to the 2019 Canadian Infrastructure Report Card, Canadian public
infrastructure is at risk therefore, detecting and addressing deterioration in such structures is crucial. The Damage
Rating Index (DRI), a reliable novel quantitative microscopic procedure, is currently used to assess deterioration
in concrete. Yet, its use is limited since it is time-consuming besides requiring experienced operators. Automating
the DRI using artificial intelligence (AI), reducing human error and increasing its accessibility leading towards more
complete diagnosis, has the potential to revolutionize the monitoring and management of critical concrete
infrastructure, enabling early detection, preventing minor disruptions and catastrophic failures and helping in the
selection of rehabilitation strategies to extend the lifespan of aging/deteriorating structures. Combined with the
collaboration of Englobe and their expertise in concrete materials, this project will achieve fruitful results.

Faculty Supervisor:

Leandro Sanchez

Student:

Partner:

Englobe

Discipline:

Engineering

Sector:

Construction; Artificial Intelligence

University:

University of Ottawa

Program: