• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar
  • Home
  • News
  • Research
  • People
  • Publications
  • Gallery
  • Facilities

American Bureau of Shipping (ABS) - Laboratory for Ocean Innovation (LOI)

Laboratory for Ocean Innovation

Texas A&M University College of Engineering

Automated Inventory Management

Artificial Intelligence – Rapid Component Identification Using AI-trained Algorithms to Rapidly Build Virtual Vessel Component List

The ability to efficiently and accurately survey and inventory offshore facilities is critical for owners and operators. Proper accounting of assets and equipment can be accomplished by analyzing images and videos. A project involving Texas A&M and ABS seeks to use AI for rapid component detection and labeling.

Experimental data sets are being analyzed by Dr. Paul Koola and his team at Texas A&M, Harsh Mattoo, and Madhulika Dey. They are working with ABS’ Subrat Nanda on case development and refinement. Computational process development is being worked on along with testing and quantification of the accuracy and level of detail. The work is being conducted under a Texas A&M-ABS research agreement covering the Laboratory for Ocean Innovation

© 2016–2025 American Bureau of Shipping (ABS) - Laboratory for Ocean Innovation (LOI) Log in

Texas A&M Engineering Experiment Station Logo
  • Home
  • News
  • Research
  • People
  • Publications
  • Gallery
  • Facilities
  • State of Texas
  • Open Records
  • Risk, Fraud & Misconduct Hotline
  • Statewide Search
  • Site Links & Policies
  • Accommodations
  • Environmental Health, Safety & Security
  • Employment