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2026 Vol.63, Issue 3 Preview Page

Research Paper

30 June 2026. pp. 303-316
Abstract
References
1

An, J., Dong, S., Wang, X., Li, C., and Zhao, W., 2025. Research on UAV aerial imagery detection algorithm for mining-induced surface cracks based on improved YOLOv10, Scientific Reports, 15, 30101.

10.1038/s41598-025-14880-640820225PMC12358575
2

de Melo, R.R.S., Costa, D.B., Álvares, J.S., and Irizarry, J., 2017. Applicability of unmanned aerial system (UAS) for safety inspection on construction sites, Safety Science, 98, p.174-185.

10.1016/j.ssci.2017.06.008
3

Jiao, X., Wu, N., Zhang, X., Fan, J., Cai, Z., Wang, Y., and Zhou, Z., 2024. Enhancing tower crane safety: A UAV-based intelligent inspection approach, Buildings, 14(5), 1420.

10.3390/buildings14051420
4

Kerle, N., Nex, F., Gerke, M., Duarte, D., and Vetrivel, A., 2019. UAV-Based Structural Damage Mapping: A Review, ISPRS International Journal of Geo-Information, 9(1), 14.

10.3390/ijgi9010014
5

Khanam, R. and Hussain, M., 2024. YOLOv11: An Overview of the Key Architectural Enhancements, arXiv preprint arXiv:2410.17725.

10.48550/arXiv.2410.17725
6

Kim, E.S. and Choi, S.K., 2013. Failure analysis of connecting bolts in collapsed tower crane, Fatigue & Fracture of Engineering Materials & Structures, 36(3), p.228-241.

10.1111/j.1460-2695.2012.01716.x
7

Lyu, C., Lin, S., Lynch, A., Zou, Y., and Liarokapis, M., 2025. UAV-based deep learning applications for automated inspection of civil infrastructure, Automation in Construction, 177, 106285.

10.1016/j.autcon.2025.106285
8

Maboudi, M., Alamouri, A., De Arriba López, V., Bajauri, M.S., Berger, C., and Gerke, M., 2021. Drone-based container crane inspection: Concept, challenges and preliminary results, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-1-2021, p.121-128.

10.5194/isprs-annals-V-1-2021-121-2021
9

Morgenthal, G. and Hallermann, N., 2014. Quality assessment of unmanned aerial vehicle (UAV) based visual inspection of structures, Advances in Structural Engineering, 17(3), p.289-302.

10.1260/1369-4332.17.3.289
10

Occupational Safety and Health Administration, 2026.05.06., https://www.osha.gov/laws-regs/regulations/standardnumber/1926/1926.1401

11

Panigati, T., Zini, M., Striccoli, D., Giordano, P.F., Tonelli, D., Limongelli, M.P., and Zonta, D., 2025. Drone-based bridge inspections: Current practices and future directions, Automation in Construction, 173, 106101.

10.1016/j.autcon.2025.106101
12

Sadeghi, H. and Zhang, X., 2024. Towards safer tower crane operations: An innovative knowledge-based decision support system for automated safety risk assessment, Journal of Safety Research, 90, p.272-294.

10.1016/j.jsr.2024.05.011
13

Shin, I.J., 2015. Factors that affect safety of tower crane installation/dismantling in construction industry, Safety Science, 72, p.379-390.

10.1016/j.ssci.2014.10.010
14

Ultralytics YOLO Docs, 2025.10.14, https://docs.ultralytics.com

15

Wang, C., Chen, G., Huang, M., and Lin, J., 2020. Rust defect detection and segmentation method for tower crane, Proceedings of the 2020 Cross Strait Radio Science & Wireless Technology Conference (CSRSWTC), IEEE, Fuzhou, China, p.1-3.

10.1109/CSRSWTC50769.2020.9372457
16

Winkelmaier, G., Battulwar, R., Khoshdeli, M., Valencia, J., Sattarvand, J., and Parvin, B., 2021. Topographically guided UAV for identifying tension cracks using image-based analytics in open-pit mines, IEEE Transactions on Industrial Electronics, 68(6), p.5415-5424.

10.1109/TIE.2020.2992011
17

Yang, H., Kim, S., and Choi, Y., 2025a. Development of drone and AI based framework for exterior inspection and damage classification of tower cranes, Tunnel and Underground Space, 35(6), p.741-759.

18

Yang, H., Kim, S., and Choi, Y., 2025b. Review of UAV–AI-Based automated visual inspection technologies and their applicability to high-risk construction machinery, Journal of the Korean Society of Mineral and Energy Resources Engineers, 62(5), p.567-583.

10.32390/ksmer.2025.62.5.567
19

Zhou, Q., Ding, S., Qing, G., and Hu, J., 2022. UAV vision detection method for crane surface cracks based on Faster R-CNN and image segmentation, Journal of Civil Structural Health Monitoring, 12(4), p.845-855.

10.1007/s13349-022-00577-1
Information
  • Publisher :The Korean Society of Mineral and Energy Resources Engineers
  • Publisher(Ko) :한국자원공학회
  • Journal Title :Journal of the Korean Society of Mineral and Energy Resources Engineers
  • Journal Title(Ko) :한국자원공학회지
  • Volume : 63
  • No :3
  • Pages :303-316
  • Received Date : 2026-05-21
  • Revised Date : 2026-06-16
  • Accepted Date : 2026-06-16