Annotated Bridge Inspection Imagery and Videos From AI-Powered Defect Detection in Kansas Bridges [Dataset]

Details

• Alternative Title:
  SMART Counties in Kansas Dataset
• Creators:
  Cui, Qingbin
• Corporate Creators:
  North Central Regional Planning Commission
• Contributors:
  Zhang, Yunfeng
• Corporate Contributors:
  Strengthening Mobility and Revolutionizing Transportation (SMART) Program
• Subject/TRT Terms:
  • Datasets
  • Bridges
  • Structural health monitoring
  • Concrete
  • Drones
  • Unmanned aircraft systems
  • Artificial intelligence
• DOI:
  https://doi.org/10.5281/zenodo.17477702
• Resource Type:
  Dataset
• Right Statement:
  Open Access; https://creativecommons.org/licenses/by/4.0/
• Geographical Coverage:
  United States ; Kansas
• Corporate Publisher:
  North Central Regional Planning Commission
• Abstract:
  This dataset contains annotated images and videos generated from drone-collected bridge inspection imagery used in AI-based defect detection research across four Kansas counties. The files include visual outputs from YOLOv11 instance segmentation models trained to identify and outline eight types of concrete surface defects: Crack, ACrack, Efflorescence, WConccor, Spalling, Wetspot, Rust, and ExposedRebars. Each annotated image shows detection polygons with defect labels and per-image class counts. Supplementary TXT files summarize per-image defect counts. ; These data were collected as part of research on AI-powered bridge condition assessment conducted at the University of Maryland in collaboration with Kansas counties. The dataset supports reproducibility, benchmarking, and further research on automated infrastructure inspection. ; The total size of the ZIP file is 25.4 GB.
• Content Notes:
  This item is made available under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) license https://creativecommons.org/licenses/by/4.0/. Use the following citation: Tsegaye, N. T. (2025). Annotated bridge inspection imagery and videos from AI-powered defect detection in Kansas bridges (v1.0) Data set. Zenodo. https://doi.org/10.5281/zenodo.17477702; Training Code: https://doi.org/10.5281/zenodo.17488232; Deployment Code: https://doi.org/10.5281/zenodo.17488363
• Format:
  ZIP
• Funding:
  69A3552341015 SMARTFY22N1P1G24
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/88076/dot_88076_DS1.json
• File Type:
  [JSON - 15.54 KB]
• Collection(s):
  Artificial Intelligence Deployment Center of Excellence (AI COE) ; SMART Program
• Main Document Checksum:
  urn:sha-512:feb5d67f80139b6ee53c40b5aebb39544a45babb5aaae884ab63f094c4b9a37393338aa50d1262bc557d65afe07d40a65fbf65ac3223d7f22c86e56b1fe288c7