ASU team uses artificial intelligence to detect wildfires before they become catastrophic

In 2017, nearly 72,000 wildfires burned more than 10 million acres nationwide, according to the National Interagency Fire Center.

It cost $2.4 billion to fight them.

In Arizona last year, more than 2,300 wildfires scorched nearly 430,000 acres, and the prediction for fires this season is above average, the agency reported.

An Arizona State University team has come up with a way to use artificial intelligence to detect wildfires before they grow to catastrophic intensity, and the project has a shot at winning a $100,000 prize from Microsoft next month.

The project, called Prometheus, which came in fourth place in the national Microsoft Imagination Cup competition in May, was created by three students: Murong He and Facundo Santiago, who both received master’s degrees in business analytics from the W. P. Carey School of Business last month, and David Azcona, a PhD student at Dublin City University who spent the last year at ASU on a Fulbright fellowship.

The three students invented a software program that analyzes data from a surveillance drone. The drone flies about 100 meters high, taking images of the ground and scrutinizing them to accurately pinpoint whether there’s an early-stage wildfire. If there is, the software sends the coordinates to a fast-response fire-fighting group.

“It’s very difficult to teach the computer to detect fire,” Santiago said. “Instead of writing an algorithm, we are submitting a lot of images — ‘This is a fire, this is a fire, this is not a fire.’ We’re pointing out, ‘The fire is here, so please learn it and come up with the rules to classify it correctly.’