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Traditional methods for assessing infrastructure are costly, challenging and at times infrequent due to inaccessibility. To overcome these challenges, the U.S. Army Engineer Research and Development Center (ERDC) is leveraging imagery collected by inexpensive digital cameras along with computer vision and machine learning algorithms to monitor and evaluate structural health of critical infrastructure. The techniques, referred to as “vision-based monitoring,” allow for the measurement of large areas of a structure while only needing a clear line-of-sight. By eliminating the need to physically access infrastructure, vision-based monitoring provides a cost-effective method to complement traditional manual inspections and contact-based structural health monitoring. When coupled with state-of-the-art techniques, these vision-based approaches enable diagnostic and prognostic analysis of structural performance, inform metrics on structural condition and provide decision support information for prioritizing often-limited maintenance funding for critical infrastructure. Key applications include monitoring the state of stress in structural components; automated identification of common damage types on structures, such as cracking and corrosion; and monitoring structural performance metrics from imagery acquired during normal operations. US Army US Army Corps of Engineers #infrastructure #data #dataanalytics #imaging #algorithms #machinelearning #engineer #engineers #engineering #information #mainteance #preventativemaintenance #science #innovation #technology #research #researchanddevelopment #PowerofERDC