Paul Brackman loads 3D-printed metal samples into a tower for examination using an X-ray CT scan in DOE’s Manufacturing Demonstration Facility at ORNL. Credit: Brittany Cramer/ORNL, U.S. Dept. of Energy
Deep learning makes X-ray CT inspection of 3D-printed parts faster, more accurate
A preliminary study by ORNL and GRIDSMART shows promise of a new system to keep trucks moving through intersections and reduce fuel consumption. Credit: Thomas Karnowski/Oak Ridge National Laboratory, U.S. Dept. of Energy
Vehicles – Fuel savings green light
Examples from the ORNL Overhead Vehicle Dataset, generated with images captured by GRIDSMART cameras. Image: Thomas Karnowski/ORNL
ORNL Project Demonstrates Viability of ‘Smart’ Traffic Cameras to Save Fuel

Multimodal Sensor Analytics

Multimodal Sensor Analytics

Conducts advanced research, design and development of algorithms and systems employing computational sensing approaches with Images and signals.

Contact

Philip Bingham
Philip R Bingham
Section Head - Energy Sensing, Analytics, and Communications
binghampr@ornl.gov