TinyML pipeline for efficient crack classification in UAV-based structural health inspections

Abstract Structural health monitoring (SHM) of civil, aerospace, and energy infrastructure increasingly relies on UAVs with vision sensors for efficient inspections. Crack classification is a central task, yet cloud-based inference introduces bandwidth, power, connectivity, and privacy challenges th...

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主要な著者:	Yuxuan Zhang, Arne Nürnberg, Luciano Sebastian Martinez Rau, Quynh Nguyen Phuong Vu, Yuchen Lu, Bengt Oelmann, Sebastian Bader
フォーマット:	Artigo
言語:	Inglês
出版事項:	Nature Portfolio 2026-03-01
シリーズ:	Scientific Reports
主題:	TinyML Convolutional neural networks Structure health monitoring Crack classification Embedded systems Model compression
オンライン･アクセス:	https://doi.org/10.1038/s41598-026-43534-4
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