Analysis of Methods for Monitoring the Condition of Building Facades Based on Visual Data
DOI:
https://doi.org/10.18372/1990-5548.86.20557Keywords:
facade monitoring, unmanned aerial vehicles, computer vision, artificial intelligence, neural networks, Gaussian filter, crack segmentationAbstract
The article explores the use of information technology to monitor the condition of building facades based on visual data obtained from unmanned aerial vehicles. The study highlights the growing role of unmanned aerial vehicles in structural inspections, noting their key advantages, including increased safety, efficiency, and accuracy, compared to traditional methods. The study is structured into three main sections. The first section provides an overview of existing approaches to facade monitoring, comparing traditional inspection methods with UAV-based methods. The second section discusses the technological aspects of data collection, processing, and analysis, focusing on artificial intelligence, computer vision, and photogrammetry. The final section presents the practical application of these technologies, an overview of relevant software tools, examples, and economic benefits. The results show that unmanned aerial vehicles, combined with advanced image processing technologies, significantly increase the efficiency and reliability of building facade assessments.
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