Motorists were inconvenienced for months last year, when a section of Route 30 near East Pittsburgh was closed due to a landslide.
LISTEN to the story:
Last year was an active and brutal year for landslides in western Pennsylvania, which is already prone to this type of natural disaster. Land movements caused millions of dollars in property damage, and evicted dozens of people from their homes.
Landslides are difficult to predict, but a Carnegie Mellon University robotics researcher is working to create an early-warning system using “deep learning.” This type of artificial intelligence programs computers to recognize patterns and then make predictions based on existing data.
CMU’s Christoph Mertz uses photographs of hillsides around Pittsburgh, which computer algorithms analyze to identify and calculate where a landslide is more likely to occur.
“You detect those things and then you can do statistics on them,” said Mertz. “Like you know, if you see that there is more dirt than there used to be. Or that the crack has become more larger, or more frequent, or has changed very recently.”
Mertz predicts this project could be completed in about five years, when it may be even more crucial than it is today.
The land movements that occurred last year were due largely to a wetter than usual winter, that was likely related to climate change. Experts say western Pennsylvania can anticipate more landslides in its future.
WESA receives funding from Carnegie Mellon University.
This story is produced in partnership with StateImpact Pennsylvania, a collaboration among The Allegheny Front, WPSU, WITF and WHYY to cover the commonwealth's energy economy.
