Computer Vision based inspection on post-earthquake with UAV synthetic dataset

The area affected by the earthquake is vast and often difficult to entirely cover, and the earthquake itself is a sudden event that causes multiple defects simultaneously, that cannot be effectively traced using traditional, manual methods. This article presents an innovative approach to the problem of detecting damage after sudden events by using an interconnected set of deep machine learning models organized in a single pipeline and allowing for easy modification and swapping models seamlessly. Models in the pipeline were trained with a synthetic dataset and were adapted to be further evaluated and used with unmanned aerial vehicles (UAVs) in real-world conditions. Thanks to the methods presented in the article, it is possible to obtain high accuracy in detecting buildings defects, segmenting constructions into their components and estimating their technical condition based on a single drone flight.Comment: 15 pages, 8 figures, published version, software available from https://github.com/MatZar01/IC_SHM_P

UAV Assisted Bridge Defect Inspection System

Part 7: Fault DiagnosisInternational audienceTraditional bridge inspection methods require lane closures, inspection equipment, and most importantly the experiences and knowledge of the inspectors. This increases not only the inspection cost and time, but also the risk to the travelling public. Due to the lengthy and costly traditional bridge inspection methods, there has been an increasing backlog of inspection activities. In this research, we design an unmanned aerial vehicle (UAV) assisted bridge defect inspection system, in which a UAV can capture the image and transmit the information to the ground station for further analysis. The system can be divided into 2 subsystems: electromechanics & communication system, and image processing system. The electromechanics & communication systems ensure the self-locating, flight control, image transmission, and human intervention functions. The image processing system performs the image preprocessing, defect extraction, and provides the inspection report. This system, if put into practice, can save the cost up to 70%. We believe that the UAV assisted bridge inspection can be popular in the future