Machine Learning Times
Machine Learning Times
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2 years ago
AI Could Spot Wildfires Faster Than Humans

Originally published in Scientific American, June 17, 2021.

A prediction system undergoes testing as the U.S. West braces for another potentially devastating wildfire season.

During his eight years as community alert and warning manager in Sonoma County, California, Sam Wallis has repeatedly watched wildfires roar through the cities and small towns he protects. Often with little warning, fires have razed homes and charred the area’s picturesque hillsides, valleys and vineyards just north of San Francisco. Wallis had to evacuate his own home last year. And in 2017 his property was strewn with wind-blown debris from the deadly, 37,000-acre Tubbs Fire, one of the most destructive in California’s history. “The Tubbs Fire was the seminal event, an absolutely massive and fast-moving fire that we had no way of tracking,” Wallis says.

Once that blaze was squelched, several local agencies began installing a system of tower-mounted cameras, called ALERTWildfire, to look for smoke and flames so that fires could be attacked before raging out of control. Sonoma County’s 21 high-powered devices scan and photograph fire-prone areas. Every 10 seconds they send images that help confirm—and sometimes discover—flare-ups. Dispatchers in the county’s fire emergency center try to keep tabs on these incoming images, displayed on a wall of video monitors, and alert emergency crews if they see any suspicious smoke. They also take 911 calls from citizens.

It is a lot for any human to do, particularly when the stakes are so high, Wallis says. “You can’t really have somebody staring at that wall all day and all night, waiting for fire to happen.”

Today he has a powerful—and indefatigable—new partner: Since May 1, artificial intelligence software linked to the cameras has been sifting through all the images, comparing them with historical photographs of the same spots at a rate impossible for human eyes. If anything looks out of place, the system alerts the dispatch center. The goal is to investigate potential fire starts earlier and get firefighters to them more quickly, says Graham Kent, who developed the ALERTWildfire system and directs the Nevada Seismological Laboratory at the University of Nevada, Reno.

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