Detection and Quantification of Methane Leaks
Engineering students
(Left to Right):
Abdulkarem Sennain (MSEE)
Oscar Salcido (CS)
Jared Rosario (CS)
Francisco Arellano (ME)
Antony Okeani (MSME)
PI: Emma E. Regentova, Professor Electrical and Computer Engineering, UNLV
co-PI: Alexander Barzilov, Professor of Mechanical Engineering, UNLV
Team meetings
A kick-off meeting : February 28th, 10:30 am – noon AEB251. Goals and objectives, team introduction, tema member tasks.
March 20th, 10:30 – 11:30 am: Progress update and tasks; study plan for students.
March 22: Weather station exploration.
March 25: Study meeting (Image Processing on NVIDIA Jetson Nano)
April 10: Project update, Activity report.
The Project "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 concerned with development of airborne, autonomous (but human pilot monitored), real-time leak detection technology that applies machine learning to passive optical sensor data with the goal of mitigating methane leak emissions through early detection.
Students are exploring NVIDIA Jetson Nano board for embedded data processing
Students are installing the weather station.
