Infrastructure assessment post-disaster: Remotely sensing bridge structural damage by unmanned aerial vehicle in low-light conditions.

The initial experiment explores the viability of using a low-cost unmanned aerial vehicle equipped with thermal imaging and lowlight camera to assess structural damage to steel girders. Damage assessments following natural disasters are daunting and arduous tasks that are resources intensive and dangerous. Unmanned aerial vehicles with remote sensing (UAV-RS) technology have been used in recent largescale disaster events such as Hurricanes Katerina, Harvey, Irma, and Maria as well as others. Current assessment methods of structures include inspectors physically conducting detailed and rapid surveys of damage with or without the assistance of special equipment, use of helicopters, satellite imagery, and new innovative methods using UAV-RS technology. The initial experiment utilized the Steel Bridge Research, Inspection, Training, and Engineering and Training Center (S-BRITE) facility at Purdue University and a small building in Lafayette, Indiana. Two steel girders located at S-BRITE were used in the experiment with damages that render them structurally deficient. The small building was used for semiautonomous inspection during hours of darkness. Most scientific studies have focused on using UAV-RS during hours of daylight. In this article, the authors explore the use of UAV-RS during low-light conditions (ie, early evening nautical twilight and night) for detecting global damage to steel girders. The authors' goal is to present evidence for further study in the use of UAV-RS during low-light conditions for inspecting structures to include primary load bearing members. The authors conclude that while the UAV-RS can detect global damage in low visibility conditions, further experiments in varying low-light conditions including 3D imaging and semiautonomous inspection are necessary for structural damage assessments.