Wildfires in Southern California are growing more intense and unpredictable, pushing firefighters to embrace cutting-edge technology to stay ahead.
The growing unpredictability of wildfires was demonstrated on Tuesday when a windstorm ignited several fires throughout the Los Angeles area, including the foothills of Pacific Palisades and the Eaton Canyon area near Altadena, CA, north of Pasadena.
Over 25,000 acres are burning in California with zero containment, according to the California Department of Forestry and Fire Protection.
Artificial intelligence is becoming a critical tool, helping to detect fires sooner, improving firefighting strategies, and reshaping how wildfires are managed and fought. It's also becoming increasingly important in weather forecasting and natural disaster recovery.
One of the projects being utilized for wildfire detection is the ALERT California system developed by researchers at the University of California San Diego which manages thousands of cameras positioned throughout California.
On Friday, the Orange County Fire Authority shared a video of a vegetation fire in Irvine, CA, that was detected by AI using the Alert California system.
“What's unique about our particular story is that it's the first time in Orange County where we received notification from the camera system and artificial intelligence, without any humans calling 911,” Orange County Fire Authority Public Information Officer Captain Thanh Nguyen told Decrypt.
Nguyen noted the fire was spotted by cameras positioned in what the agency called remote “high-risk areas.”
The Alert California system consists of a network of 1,000 cameras that use machine learning to determine if there is indeed a fire and can relay this information to operators and emergency responders.
“Unless you happen to be looking at the camera view at that moment, you may miss it, and that's where the AI came in,” Nguyen said. “It detected there was something off about this video, and then it notified the people at ALERT California.”
The Alert California network is monitored by at least two people who occupy shifts around the clock, Nguyen explained. The team evaluates videos once they're notified and then determines whether it's something that needs to be flagged to a local fire department.
“Delays allow fires to grow uncontrollably, increasing the risk to communities and the environment,” Arvind Satyam, co-founder of Pano AI, told Decrypt. “Additionally, the vast and often remote landscapes susceptible to wildfires make comprehensive monitoring challenging.”
Launched in 2019, San Francisco-based Pano AI develops AI-powered wildfire and brushfire detection technology.
There’s a “need for faster scaling and more actionable insights,” Satyam said. “Meeting this demand requires increased support and funding at state and federal levels.”
The co-founder further explained natural disasters, such as wildfires, are a “societal ‘we’ problem” requiring investment prevention technologies that “must become a public/private partnership to make this a priority.”
As the latest California wildfires spread, cameras are capturing the devastation caused by the Palisades and Eaton Canyon fires.
“We knew Monday that Palisades was a really high danger area,” CEO of Ember Flash Aerospace Joseph Norris told Decrypt. “So that's a good opportunity for people to go and check and make sure that their sensors are out and they're working and collecting the data that we need.”
Launched in 2021 and based in San Francisco, Ember Flash Aerospace develops wildfire detection devices and applications, though detecting wildfires takes more than just spotting smoke.
“It's particle detection as well as an optical sensor,” Norris said. “We don't take video, but we use machine learning and AI to identify small patterns indicating smoke. A network of sensors allows us to triangulate using multiple sensors in the field.”
As Norris explains, speed is the key element that makes using AI ideal for wildfire detection and mitigation.
“It's almost 100% speed because we can aggregate data from many sources,” he said. “It allows our company to share data with others, aggregate it, and make faster decisions. In real-time, things can change, and AI makes that more possible than ever before.
Even with widespread camera deployment, Norris emphasized the need for even greater fire detection speed and efficiency.
“The biggest challenge is simply awareness,” he said. “It's awareness and adoption. The cameras are expensive, and mounting them adds to the cost, limiting deployment and leaving blind spots,” he said.
Norris is optimistic that more inexpensive options will be brought to bear against wildfires as costs go down.
“I know this will improve,” he said.
Edited by Sebastian Sinclair
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