Detection and Quantification of Methane Leaks
funded by DOE EM (Battelle Savannah River Alliance, LLC)
funded by DOE EM (Battelle Savannah River Alliance, LLC)
University of Nevada, Las Vegas
PI: Emma E. Regentova, Professor, Electrical and Computer Engineering
Co-PI: Alexander Barzilov, Professor, Mechanical Engineering
Engineering Students
Abdulkarem Sennain (MSEE)
Oscar Salcido (CS)
Jared Rosario (CS)
Antony Okeani (MSNE)
Dennis Weirich II (ME)
Jerome Ariola (ME)
Aurelia X6 MAX with Teledyne FLIR G300a camera and NVIDIA Jetson Nano
Presentation at UNLV's Undergraduate Research Forum
Oscar Rosario (left) and Jared Salcido (right) present a poster
"ADVANCED ML-BASED ANALYSIS OF OPTICAL SENSOR DATA ON THE DRONE PLATFORM FOR ROBUST DETECTION OF METHANE LEAKS" is funded by Battelle Savannah River Alliance, LLC
The project is focused on the development of airborne, autonomous (but human pilot monitored), real-time methane leak detection technology that applies machine learning to passive optical sensor data with the goal of mitigating methane leak emissions through early detection.
Experiments with methane detection