ABSTRACT
Intelligent disaster mitigation is one of the most important parts of intelligent construction, which is of great significance to maintaining the safety and stability of buildings. To evaluate a building's performance under disasters, it is necessary to obtain its structural dynamic characteristic degeneration through structural dynamic response analyses, which can then be used to assess the degeneration of structural stiffness, and ultimately evaluate the damage degree of the structure. Among them, the degeneration of structural dynamic characteristics and the detection of structural damage can be realized through system identification and local damage detection, respectively. With the development of computer vision and deep learning, many state-of-the-art techniques such as convolutional neural networks are used to automatically detect a building's dynamic characteristics and local damage. Besides, the unmanned aerial vehicle (UAV) has good maneuverability and wide detection range, so deploying algorithms on UAVs can achieve more efficient intelligent detection of buildings. This chapter mainly introduces the research progress of intelligent disaster mitigation based on computer vision from two aspects of system identification and local damage detection.
