Deputy Fire Chief Zachary Wells and UC San Diego professor Neal Driscoll explain how ALERTCalifornia uses cameras, cloud computing, and AI to detect wildfires early and help firefighters respond faster.
Wildfires devastate communities, ecosystems, and lives, and they are becoming harder to stop. But what if firefighters could spot a blaze in its earliest moments, before anyone even calls 911?
In this episode of Tools and Weapons, Brad Smith travels to California to meet Deputy Fire Chief Zachary Wells and Dr. Neal Driscoll, a professor at the University of California, San Diego and one of the leaders behind ALERTCalifornia, an ambitious early warning and situational awareness system designed to detect wildfires as quickly as possible.
Brad speaks with Wells and Driscoll about how their partnership, along with contributions from Microsoft’s AI for Good Lab and other collaborators, has helped build a system that improves situational awareness for emergency responders and expands access to life saving information for the public.
They also discuss the future of wildfire technology, from predicting how fires might spread to making advanced tools more affordable and accessible to communities around the world.
Neal Driscoll: These fires just devastate people, devastate communities. If we can prevent this anxiety amd fear and deep-rooted just concern from people that have gone through this, that's a success.
Zachary Wells: First priority is life. And the more that I can do to engage in technology that helps protect my communities and protects my firefighters, that those are no-brainers.
Brad Smith (VO): That’s Deputy Fire Chief Zachary Wells and Dr. Neal Driscoll, a professor at the University of California, San Diego. Together, they are two of the bright minds behind ALERTCalifornia—one of the most ambitious early-warning systems for wildfires anywhere in the world. The Microsoft AI for Good team has worked with Zach and Neal to use AI and cloud computing to detect fires earlier, share intelligence faster, and give firefighters the real-time data they need when every minute counts.
Zachary Wells: ALERTCalifornia is an enhanced situational awareness platform. We have cameras strategically placed on mountaintops to allow us to visually identify and confirm fire in its incipient phase.
Brad Smith (VO): We talk about how this technology is already starting to change the way firefighters protect lives and communities, and what it will take to scale its life-saving potential around the world. Up next on Tools & Weapons.
Brad Smith: Now when did the two of you meet?
Zachary Wells: 2017. A Ventura County firefighter said, “You have to hear about what they're doing at UC San Diego, and meet this guy named Neal.” And we've hit it off. We've learned how to work with each other from the fire side, the university side, and develop tools that can be turned over to firefighters for them to use at no cost to them.
Brad Smith: And Neal, what was the inspiration for you that got you going down this path in the first place?
Neal Driscoll: 2003.
Brad Smith: What happened in 2003?
Neal Driscoll: Impacted a lot of people. Was the largest fire at the time in California. Yeah. Skirted up my neighborhood.
Brad Smith: Oh really?
Neal Driscoll: There was like 23, 24 people lost their lives. We didn't know where to go. So, we called 9 1 1 and said, “I can't see.” The whole sky was orange. Where do I go? They couldn't tell me. And this fire jumped all the lanes at Miramar. My kids were so frustrated and, and scared. They kept saying, “Are we gonna be safe?”I'm still scarred by fire.
Brad Smith: Sure.
Neal Driscoll: I had to take a pause there.
Brad Smith: Yeah.
Neal Driscoll: And I didn't lose my house. I didn't lose a loved one. If we can prevent this anxiety and this fear and deep rooted just concern from people that have gone through this, that's a success. These fires just devastate people, devastate communities, compromised bio habitats changing the vegetation. We need to use every bit of technology to try to hold them in check. And I have been building this network. I build instruments to bring signals from out in the wilderness back to laboratories. We decided to put a couple of cameras and actually use the infrastructure to bring in information from remote areas.
I can have a firefighter from Oregon run my system if I need to import. They don't have to know anything about the mountain ranges, the camera names, the AI says, “Look at these cameras. Something has changed since I've rotated or I've taken the 60 degree image.” So, the AI is just saying, “Go look at the change. Tell me if it's a fire.” Right. Or it's, it's the marine layer. It's fog, it's a dust devil. So, all of a sudden we have a change detector that allows watch-stander fatigue to be removed. It reduces the noise. If fire or an incident comes up, it just hits that screen and you can see it. There's nothing else there but that fire or that event. And then you can interrogate it and figure out what it is.
Brad Smith: Can you say a little bit about how much territory you cover and then compare the size of that territory with the number of fire engines or pieces of equipment and, and people that you have to cover that territory?
Zachary Wells: Yeah. So, in Kern County, we cover 8,141 square miles. It's the rough size of the three smallest states in the continental US. And I protect that area with 47 fire stations. So, each station has a fire engine with three firefighters. About 170 firefighters in our department is on every single day.
Brad Smith: Okay.
Zachary Wells: But 170 spread throughout 8,000 square miles is, uh, is a big area to cover.
Brad Smith:We live in a time when I think most of us are used to having a smoke detector our homes.
And the obvious principle is, if you detect the fire early, that's how you best put it out. This is
like an effective, an AI driven smoke detector for this entire region. What is the impact of early detection
for somebody like you and your team as you're responsible for putting out these kinds of fires?
Zach: So, I've experienced already the ability to detect fire and confirm it in the incipient phase, respond an effective firefighting force, a first alarm of engines and chiefs, and all the crews that we need and extinguish that fire without ever receiving a 911 call. Going back to the protecting life, property, and the environment, first priority is life. And the, the more that I can do to engage in technology that helps protect my communities and protects my firefighters, that those are no-brainers,
Running a fire department, we don't have an R&D budget, we don't have time other than our priority is responding to emergencies. We're not gonna stop every single fire. You know, it's, there's, um, over 10,000 wildfires that happen in California every year. So seeing a, a program like Alert California in figuring out that we can invest our people and our effort opening up our radio towers to add a camera on a tower that exists, for our daily use, we feel that we can make a dent in the universe and make an impact.We already have a, am action plan in a system that works really well, but we wanna make it better. We want to be able to engage those that are the boots on the ground that are doing the hard work.
Brad Smith: And obviously a big part of your success is sending the right people and the right equipment to the right place at the right time.
Zachary Wells: It's hard to predict where an incident is gonna occur, but using AI, using these cameras that are always looking and finding and, and observing, and then getting that signal through all the noise to the right people, the dispatchers, the firefighters, so that they can make those decisions, that's where we've found success. That's where we'll continue to find success as technology, technology drives this, uh, to more advanced levels.
Brad Smith: One of the things I find fascinating about the progress the two of you are making together is that you are making the technology better and cheaper.
Neal Driscoll: Yes.
Brad Smith: At the same time. Which is of course the story of computing.
Neal Driscoll: We also, with the technology we're developing, we share that with other people, and so they cost them nothing. So here we share that R&D, which is huge. Look at this, look at this area. Look at how much area is covered by this one camera. Okay. And, and you get up every day, I look at all cameras, and then I look at cameras that have been recently moved, active cameras. Because that tells me somebody that's been trained by us-
Brad Smith: Right.
Neal Driscoll: -onboarded, deliberately moved a camera. So there had to be some reason. And so you look there first and you go, “Oh, that doesn't look good. Interesting.” And then they, you see 'em triangulate. And so here the public can see that you can go on and say, click the button that says “active cameras” and see where, where firefighters are looking. That's such a benefit. And we have layers with maps from ESRI that all the street maps are in there. So you can look at where your house is. You wanna know where your house is, and then you can see the perimeter of the fire. And you can say, “You know, I don't need a firefighter or a sheriff to knock on my door. I'm right in front of that fire that's coming at me, and it's moving north. And I live right here.”
Brad Smith: Wow.
Zachary Wells: It's the benefit of having an open system and having the imagery available to the public. And we connect with other technology providers that provide information, including CAL FIRE that posts the imagery through our system on their site when they're posting official information. When you're dealing with emergencies to this magnitude, you don't have the time to dust off username and passcodes. You just need to be able to see it, to make decisions very quickly that for your department, for your community, for yourself. And that's where being an open system has greatly benefited us.
Neal Driscoll: You have to use it because in an event when fire's at your back door, trust me, it, it's a, it's a – you’re so anxious and you're not making good decisions.
Brad Smith: When you think about the decade over which this work has been going forward, I mean, a lot has changed, cameras have gotten sharper, connectivity has gotten faster, batteries have gotten smaller, computers have improved. What has been the impact in the last year or two of AI?
Neal Driscoll: I look at the metric that the AI is providing, uh, reducing noise. It allows the dispatcher to have situational awareness and, and, and observe how things are changing. And it's telling me where I have change And now I want to have it telling me where I have changed faster, with better clarity. Andwhat Zach has taught me, he says, “Neal, when I can look at a fire in almost real time, like video, I gain so much knowledge in that first four to five minutes. It's critical. I can tell so much from that little time slice, especially if I get frame rates higher.” We're never gonna take the subject matter expert out of the loop. So, when people ask me, well, is this gonna take jobs? No. It's gonna create hybrid jobs.
Zachary Wells: AI is not meant to replace firefighters. It's meant to enhance firefighters to allow them to do their job. But through AI, being able to see the signal of an incipient fire and be able to respond, that's something that I can do something about. We can contain and confine those fires when we know about them. What AI does is reduces the potential for large complex fires and allows us to mitigate them at the smallest level, which means my firefighters get to return home to the areas that they respond to medical aids and traffic accidents and structure fires. And those resources are then prepared for the next fire. AI has a way to help keep us safer and notify us so that we can do our job.
Brad Smith: And Juan, as the person who's brought the AI technology to all of this, it's sort of a story of the firefighter, the professor, and the data scientist from the data science side. What's the key to working effectively in this kind of team?
Juan Lavista Ferres: For us, what is critical is the fact that we need the, get very good quality data. So these cameras not only provide an amazing data, butyou have great people understand what is a fire, what is not a fire to label the data and indicate to the AI models. That's, that's the key for our success. Firefighters labeling data, that's critical for us. Uh, so the, the, the next part is the fact that you have these, these models to have the ability to control the cameras and actually zoom in. Necause that will provide much better, like much better quality data. That's another thing that is key for us.
Neal Driscoll: So I've had one dream fulfilled with this project.
Brad Smith: What's that dream?
Neal Driscoll: That dream is that I wanted to have, I could drop a pin on the map and I could see every camera that could see that pin illuminated and I can go look at it. That's what I wanted. That was the dream. So I can know what cameras have unobstructed view of a fire. Okay. And that was hard to do. Okay. But now with the data quality and, and what Juan's talking about is how do we take these data and get them, so they go into the model? All of a sudden we're reaching what we believe is a better, uh, targeting, on the fire than we had before. And I think that we're in a total agreement that we have to have awesome data, and we have to have enough of it that we can have, you know, populate the model. This is very promising.
Juan Lavista Ferres: The next step is if we, in places where we have multiple cameras, is that the model will detect the camera. You have two, as long as you have two cameras that can look at the same fire, you actually know the location of the fire. Yeah. Because the, then the model will basically indicate the location of the fire. That's critical for you.
Brad Smith: Well, think about the decade that you all have been on this journey. You started ten years ago, think about it, eight years, how far you've come. Think about 2035. What would you hope would be the state of the art in 2035? Not just in terms of what technology can do, but what technology actually is doing. Not just here in California, but everywhere where these wildfires are such a hazard.
Neal Driscoll: My dream is that the camera, after it sees what's a potential fire, it moves all the cameras around it automatically points it at it, and they zoom in automatically. So, I don't have to do all that, all that work is done because that's kind of tedious. It takes time. And then the, the firefighter just can look and say, “Yes, that this is an issue. Is it a small issue? Is it a big issue? Is it a controlled burn? Do I have to address this?” All these things are running through the dispatcher's mind. And if, if we can give them high-quality data and enhanced, you know, situational awareness, the dispatcher's going to be able to make a data-driven decision that is more complete. Every fire is different and every fire has the chance to get out of the box. And, and that's what we're trying to solve, is let's not let the fire out of the box.
Juan Lavista Ferres: And the good thing here is also because you have so many cameras and you have, unfortunately, given the amount of fires that you have every year, you have every fire you can learn from the fire.
Neal Driscoll: Yep.
Juan Lavista Ferres: Right now the focus has been on detection. The next, I think the next also phase is prediction is what's gonna happen with that fire, correct? And that's something like, yes, every fire is different, but as long as if you have enough of these fires, you can train models to see what's going to happen in the next hour, in the next thirty minutes.
Neal Driscoll: So, we give our data to people that model fires and fire behavior. And they ha use MesoWest, the wind data, the weather data. So, they can say that we start, we see a fire, we confirm it by firefighters saying, “Yes, that's a fire.” The dispatcher then dispatches according to that, while that's all happening, we're having a model, Technosylva and WIFIRE, they're taking the pin, which we gave them. They've got the weather conditions, they've got the topography, they've got the fuel loads, they've got the fuel health, and they make models. Where's the fire going to be in five hours? Ten hours? And then we can see if that's correct and we can iterate on that. And so we're learning about how topography controls where fires go.
Brad Smith: Yeah. Wow. And what would you say, Zach? Ten years from now, what would you hope would be the state of the art?
Zachary Wells: in the fire service we have a saying, “Everybody goes home, you know, and I talked to you guys about the priority of life safety. So, in 2035, I'd love to see that this system is driving down the loss of life and driving down the injuries to firefighter. I would love to see the technology generated here expand the other areas so that other people can benefit. Because we have areas that don't have the economic means to, you know, develop the technology, but through a sharing model and training them, to do what we've done in partnership with Microsoft, we see the ability to expand this. That only drives the economy of scale up, which drives the cost of operation down, which makes it easier for my firefighters in California to use. We can do this anywhere.
Brad Smith: That is what is amazing to me, because you all have perfected the technology, brought down the cost and made it something that is affordable to scale.
Neal Driscoll: Right. Right.
Brad Smith: And so, now you go to like the, and the Greek government, the Italian government, the Canadian government, the US government, I mean, the, the level of investment compared to the costs that are being incurred.
Neal: It’s huge.
Brad Smith: Well, it's an inspiration. I mean, it's first of all extraordinary to see the inspiration that you had that led to this work and this partnership between the two of you, to see the impact it's having and to see the future.
Zachary Wells: Speaking freely, working with people like Juan and AI for Good Lab has been huge. we couldn't be happier with the partnership and, you know, partnerships need to be win-win and so that we can work together to accomplish something bigger than us individually.
Brad Smith: Well, thank you for the privilege. Because there really has been a privilege that you've given to us at Microsoft and you know, to Sai and Juan. And on behalf of others I know who are part of this team at Microsoft, it's easy to see why everybody is so enthusiastic about just the opportunity to work with two of you. So, thank you.
Neal Driscoll: The honor is ours. Yeah.
Brad Smith: Thanks.
Neal Driscoll: I'm gonna get misty