Remote Sensing of Multimodal Transportation Assets Using Drones [Brief]

Details

• Creators:
  Bridgelall, Raj ; Tolliver, Denver ; Askarzadeh, Taraneh
• Corporate Creators:
  Mountain-Plains Consortium ; North Dakota State University
• Corporate Contributors:
  United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  Artificial Intelligence Asset Management Drones Remote Sensing
• Resource Type:
  Brief
• Geographical Coverage:
  United States
• Edition:
  Research Brief
• Corporate Publisher:
  Mountain-Plains Consortium
• Abstract:
  Drone technologies offer a paradigm shift in railroad inspection and monitoring, enhancing operational efficacy, reducing carbon footprint, and mitigating safety hazards. Similarly, drones, especially when integrated with real-time kinematic global positioning systems and artificial intelligence, offer a compelling solution for efficient roadway condition monitoring. Despite the burgeoning applications of drones in various infrastructure sectors, there remains a research gap in quantifying their specific utility and evaluating the cost-effectiveness of drone use for railroad inspection and monitoring. There is a critical need for objective performance metrics and cost-benefit analyses to guide future adoption and optimization
• Format:
  PDF
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:06ff773bbfd620db1c5ff74a6712504f803142f5ea11944b09c65f310aaf550a2718dc469fd4107b9478b193158072cfe81df327c8a27fb946b3faf3f31cc6ab
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/76989/dot_76989_DS1.pdf
• File Type:
  [PDF - 450.96 KB ]