Tackling Geotechnical Risks in Tailings Dams Using High-Resolution UAV Imaging and Advanced Image Processing

Details

• Personal Author:
  Ghahramanieisalou M ; Gomez Llerena JA ; Sattarvand J
• Description:
  Recent technological developments in remote sensing and image analysis and their introduction into the mining industry have opened the door for updating risk analysis techniques. The R&D team of the Mining Automation Lab of the University of Nevada-Reno develops UAV-based photogrammetry and image analysis technologies to address the geotechnical risks of the tailings dam. All procedures are based on high-resolution imaging by a special UAV control software for terrain-following and photogrammetry for 3D modeling. The system can efficiently cover large areas and capture high-resolution images as input for novel image analysis methods. This approach's biggest challenge is acquiring enough annotated samples to train a model that produces high-accuracy results in various rock types and environmental conditions. The results can be used for localized risk analysis of rockfall using available empirical models. Our team at UNR is working on including multispectral imaging and unifying all the data formats and analysis techniques under a digital twin framework. Description provided by NIOSH
• Subjects:
  • Automation
  • Occupational Health
  • Safety
• Keywords:
  • Geotechnical engineering
  • Automation
  • Remote control
  • Imaging techniques
  • Emerging technology
  • Mining engineering
• ISBN:
  9780784484975
• ISSN:
  0895-0563
• Document Type:
  Text
• Funding:
  Contract
• Editor:
  Ching J; Najjar S; Wang L
• Genre:
  Proceedings
• Place as Subject:
  Nevada ; OSHA Region 9
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  220-228
• NIOSHTIC Number:
  nn:20069249
• Citation:
  Geo-Risk Conference 2023: Innovation in Data and Analysis Methods: selected papers from sessions of Geo-Risk 2023, July 23-26, 2023, Arlington, Virginia. Ching J, Najjar S, Wang L, eds. Reston, VA: American Society of Civil Engineers (ASCE), 2023 Jul; GSP 345:220-228
• Contact Point Address:
  Jose A. Gomez Llerena, Graduate Research Assistant, Dept. of Mining and Metallurgical Engineering, Univ. of Nevada, Reno, NV
• Email:
  jgomezllerena@unr.edu
• Editor(s):
  Ching J; Najjar S; Wang L
• Federal Fiscal Year:
  2023
• Performing Organization:
  University of Nevada, Reno
• Peer Reviewed:
  True
• Start Date:
  20190901
• Source Full Name:
  Geo-Risk Conference 2023: Innovation in Data and Analysis Methods: selected papers from sessions of Geo-Risk 2023, July 23-26, 2023, Arlington, Virginia
• Download URL:
  https://stacks.cdc.gov/view/cdc/207758/cdc_207758_DS1.pdf
• File Type:
  [PDF - 1.15 MB]
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:00a288996e742740bee79c0f08af6efe404d28f18cff740307f73d3f6aaf0ae5473dd4885caed2b29261e68d497a65f6dccc01fde44abb324fdcd3ac3baec5f2