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News Every Day |

How AI can help spot wildfires

This article is from The Spark, MIT Technology Review’s weekly climate newsletter. To receive it in your inbox every Wednesday, sign up here.

In February 2024, a broken utility pole brought down power lines near the small town of Stinnett, Texas. In the following weeks, the fire reportedly sparked by that equipment grew to burn over 1 million acres, the biggest wildfire in the state’s history.

Anything from stray fireworks to lightning strikes can start a wildfire. While it’s natural for many ecosystems to see some level of fire activity, the hotter, drier conditions brought on by climate change are fueling longer fire seasons with larger fires that burn more land.

This means that the need to spot wildfires earlier is becoming ever more crucial, and some groups are turning to technology to help. My colleague James Temple just wrote about a new effort from Google to fund an AI-powered wildfire-spotting satellite constellation. Read his full story for the details, and in the meantime, let’s dig into how this project fits into the world of fire-detection tech and some of the challenges that lie ahead.

The earliest moments in the progression of a fire can be crucial. Today, many fires are reported to authorities by bystanders who happen to spot them and call emergency services. Technologies could help officials by detecting fires earlier, well before they grow into monster blazes.

One such effort is called FireSat. It’s a project from the Earth Fire Alliance, a collaboration between Google’s nonprofit and research arms, the Environmental Defense Fund, Muon Space (a satellite company), and others. This planned system of 52 satellites should be able to spot fires as small as five by five meters (about 16 feet by 16 feet), and images will refresh every 20 minutes.

These wouldn’t be the first satellites to help with wildfire detection, but many existing efforts can either deliver high-resolution images or refresh often—not both, as the new project is aiming to do.

A startup based in Germany, called OroraTech, is also working to launch new satellites that specialize in wildfire detection. The small satellites (around the size of a shoebox) will orbit close to Earth and use sensors that detect heat. The company’s long-term goal is to launch 100 of the satellites into space and deliver images every 30 minutes.

Other companies are staying on Earth, deploying camera stations that can help officials identify, confirm, and monitor fires. Pano AI is using high-tech camera stations to try to spot fires earlier. The company mounts cameras on high vantage points, like the tops of mountains, and spins them around to get a full 360-degree view of the surrounding area. It says the tech can spot wildfire activity within a 15-mile radius. The cameras pair up with algorithms to automatically send an alert to human analysts when a potential fire is detected.

Having more tools to help detect wildfires is great. But whenever I hear about such efforts, I’m struck by a couple of major challenges for this field. 

First, prevention of any sort can often be undervalued, since a problem that never happens feels much less urgent than one that needs to be solved.

Pano AI, which has a few camera stations deployed, points to examples in which its technology detected fires earlier than bystander reports. In one case in Oregon, the company’s system issued a warning 14 minutes before the first emergency call came in, according to a report given to TechCrunch.

Intuitively, it makes sense that catching a blaze early is a good thing. And modeling can show what might have happened if a fire hadn’t been caught early. But it’s really difficult to determine the impact of something that didn’t happen. These systems will need to be deployed for a long time, and researchers will need to undertake large-scale, systematic studies, before we’ll be able to say for sure how effective they are at preventing damaging fires. 

The prospect of cost is also a tricky piece of this for me to wrap my head around. It’s in the public interest to prevent wildfires that will end up producing greenhouse-gas emissions, not to mention endangering human lives. But who’s going to pay for that?

Each of PanoAI’s stations costs something like $50,000 per year. The company’s customers include utilities, which have a vested interest in making sure their equipment doesn’t start fires and watching out for blazes that could damage its infrastructure.

The electric utility Xcel, whose equipment allegedly sparked that fire in Texas earlier this year, is facing lawsuits over its role. And utilities can face huge costs after fires. Last year’s deadly blazes in Hawaii caused billions of dollars in damages, and Hawaiian Electric recently agreed to pay roughly $2 billion for its role in those fires. 

The proposed satellite system from the Earth Fire Alliance will cost more than $400 million all told. The group has secured about two-thirds of what it needs for the first phase of the program, which includes the first four launches, but it’ll need to raise a lot more money to make its AI-powered wildfire-detecting satellite constellation a reality.


Now read the rest of The Spark

Related reading

Read more about how an AI-powered satellite constellation can help spot wildfires faster here

Other companies are aiming to use balloons that will surf on wind currents to track fires. Urban Sky is deploying balloons in Colorado this year

Satellite images can also be used to tally up the damage and emissions caused by fires. Earlier this year I wrote about last year’s Canadian wildfires, which produced more emissions than the fossil fuels in most countries in 2023. 

Another thing

We’re just two weeks away from EmTech MIT, our signature event on emerging technologies. I’ll be on stage speaking with tech leaders on topics like net-zero buildings and emissions from Big Tech. We’ll also be revealing our 2024 list of Climate Tech Companies to Watch. 

For a preview of the event, check out this conversation I had with MIT Technology Review executive editor Amy Nordrum and editor in chief Mat Honan. You can register to join us on September 30 and October 1 at the MIT campus or online—hope to see you there!

Keeping up with climate  

The US Postal Service is finally getting its long-awaited electric vehicles. They’re funny-looking, and the drivers seem to love them already. (Associated Press)

→ Check out this timeline I made in December 2022 of the multi-year saga it took for the agency to go all in on EVs. (MIT Technology Review)

Microsoft is billing itself as a leader in AI for climate innovation. At the same time, the tech giant is selling its technology to oil and gas companies. Check out this fascinating investigation from my former colleague Karen Hao. (The Atlantic)

Imagine solar panels that aren’t affected by a cloudy day … because they’re in space. Space-based solar power sounds like a dream, but advances in solar tech and falling launch costs have proponents arguing that it’s a dream closer than ever to becoming reality. Many are still skeptical. (Cipher)

Norway is the first country with more EVs on the road than gas-powered cars. Diesel vehicles are still the most common, though. (Washington Post

The emissions cost of delivering Amazon packages keeps ticking up. A new report from Stand.earth estimates that delivery emissions have increased by 75% since just 2019. (Wired)

BYD has been dominant in China’s EV market. The company is working to expand, but to compete in the UK and Europe, it will need to win over wary drivers. (Bloomberg)

Some companies want to make air-conditioning systems in big buildings smarter to help cut emissions. Grid-interactive efficient buildings can cut energy costs and demand at peak hours. (Canary Media)

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