A machine learning model developed by University of Alberta scientists is improving efficiency and accuracy for one wide-area monitoring company that uses data to predict natural and man-made disasters around the world.
The computing science team, led by Irene Cheng, adjunct professor in the Department of Computing Science, is working in collaboration with 3vGeomatics (3vG) to clean data and automate quality assessment. 3vG, a Vancouver-based company, uses satellite images to study Earth’s surface and detect any changes that could indicate the onset of natural or man-made disasters, like landslides and earthquakes. Many activities, like oil exploration and extraction and mining, can affect the ground surface.
“The need for this data is growing, and the data is becoming more robust,” explained Cheng, director of the multimedia masters program.
“3vG saw the need to optimize their systems by minimizing the need for human intervention and increasing the speed for data processing. This means creating software that can automatically tell the quality of images, without human intervention, with the goal of speeding up the process.”