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“I think it is a game changer … It has enhanced our abilities to validate situational awareness and then respond in a quick fashion,” Phillip SeLegue, Cal Fire’s staff chief for fire intelligence, told 【 - Free Access to Community 】.

Deep in the California wilderness of the Cleveland National Forest in San Diego County, a fire started in the middle of a July night. No fire officials were in the area, but AI was watching and alerted the authorities.

“The dispatch center there was not aware of the fire,” said Scott Slumpff, battalion chief of the intel program at Cal Fire, who was testing the new technology at the time and received the initial alert.

Cal Fire, in partnership with the University of California at San Diego’s Alert California program and its network of more than 1,000 cameras across the state, is using the technology to spot fires early.

“The camera had done its 360 [degree turn], identified an anomaly, stopped and was zoomed in,” Slumpff explained. He then confirmed it was a fire and immediately dispatched resources. “They were able to hold it to a 10 by 10 [foot] spot out in the middle of the forest.”

“The next morning, that fire would have been a fire of significance” without the AI detection, SeLegue said.

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“Once the camera system detects an anomaly, which is a different version of the last image, it red flags it,” said Dean Veik, a fire department liaison for Alert California and a former firefighter. “It’s predominantly looking for smoke.”

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“Our goal as an agency is to keep 95% of our fires at 10 acres or less, so this tool increases our ability to ensure that we’re keeping those fires small in the incipient phase,” said SeLegue, adding the cameras can see about 70 miles out during the day and approximately 110 miles out at night. “We have multiple successes of fires at night that had gone undetected that we were able to suppress before a 911 call had even come into the command centers.”

Cal Fire says 40% of fires since July 10 have been detected by AI before a 911 call was received – and the technology is continuing to learn and improve.

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“The learning part of it comes in with the human intervention to say ‘that looked like smoke, but that wasn’t smoke; it was dust,’” Norton told 【 - Free Access to Community 】. “Then the next time the camera picks something up, it’s less likely to say that that is smoke.”

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“Nothing can take the place of the boots on the ground,” said Slumpff. “We absolutely are able to, in my opinion, save lives and property.”

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