MPC Research Enhances Use of UAVs for Bridge Inspections
Posted: Feb 11, 2022
Recent advancements in commercial unmanned aerial vehicles (UAVs) have made them ideal for collecting images during bridge inspections. However, measuring the extent of a defect, its growth, and its exact location using those images can be cumbersome. Researchers at Colorado State University developed new computation and machine learning algorithms that can quantify, track, and identify the location of bridge damage using inspection photos from UAVs. These data analytics tools will allow more quantitative condition assessment, which is superior to the existing practice. The tools are expected to help the inspection industry and state DOTs reduce the cost of bridge inspections while increasing the frequency and usefulness of inspections for efficiently maintaining bridges.
Recent advancements in commercial unmanned aerial vehicles (UAVs) have made them ideal for collecting images during bridge inspections. However, measuring the extent of a defect, its growth, and its exact location using those images can be cumbersome. Researchers at Colorado State University developed new computation and machine learning algorithms that can quantify, track, and identify the location of bridge damage using inspection photos from UAVs. These data analytics tools will allow more quantitative condition assessment, which is superior to the existing practice. The tools are expected to help the inspection industry and state DOTs reduce the cost of bridge inspections while increasing the frequency and usefulness of inspections for efficiently maintaining bridges.