How AI Wildfire Detection Helps First Responders Find Fires Faster

There have been tremendous advances in wildfire detection recently, thanks to the use of remote cameras, sensors, and other information-gathering devices to alert first responders as soon as flames break out.

But all this information comes with a downside. There is so much of it to process that the sheer task of doing so can overwhelm the human mind. This is why artificial intelligence (AI) has been tasked with making sense of all these inputs. AI’s ability to analyze and sort information based on predetermined priorities allows these systems to provide first responders with the most relevant and actionable information possible.

How AI Is Changing Wildfire Detection

Adding AI to detection can reduce response times, allowing agencies to deploy resources when a fire is still manageable. This is because AI constantly analyzes real-time video and sensor data to detect the earliest stages of an ignition.

How AI Identifies Smoke and Fire Activity

Modern wildfire detection systems rely on AI “machine learning models” to process live video feeds and sensor data. Sean Landavazo, a CAL FIRE Intel Battalion Chief, explained the immense scale of this process in a video featured on the CAL FIRE TV YouTube channel. “There’s a little over a thousand cameras throughout California,” he said. “To be able to look at these cameras every second of the day—this is what AI does for us.”

Landavazo noted that CAL FIRE’s AI has successfully spotted ignitions at 2:00 a.m. in desolate areas. Without AI, these fires would have likely gone undetected until a massive smoke column was spotted by humans. By rapidly identifying heat signatures and early smoke, these AI systems are supporting CAL FIRE’s goal of keeping 95% of all fires within its jurisdiction to 10 acres or less.

Reducing False Alarms With Automated Analysis

One historical challenge associated with using automated wildfire sensors was their high rate of false positives. Today’s AI systems are reducing these false alarms by checking camera feeds to tell the difference between actual smoke and look-alikes such as fog or dust clouds. The system can assign a confidence score before alerting human operators, helping analysts focus on the events most likely to be real fires.

Dr. Neal Driscoll, the driving force behind the ALERTCalifornia wildfire camera system, emphasized on the PSBTA’s Catching Wildfire podcast that AI is being used to augment human analysts, not replace them. “We will always have a subject matter expert, a firefighter in the pipeline from AI detect to verification to alert,” he said. “We will never remove that human component because we need to keep noise down and false positives down.”

AI, Cameras, and Wildfire Detection Systems

Together, AI, cameras, and wildfire detection networks are helping agencies find fires earlier.

How AI Supports Wildfire Camera Networks

Across the western United States, sprawling networks of high-definition pan-tilt-zoom (PTZ) cameras serve as digital watchers looking out for trouble. When integrated with AI, these camera networks become proactive, 24/7 sentinels.

ALERTCalifornia is a prime example of this. Based at UC San Diego, the program manages a network of over 1,200 monitoring cameras, each one performing 360-degree sweeps of fire-vulnerable areas approximately every two minutes.

The results speak for themselves. In 2023, CAL FIRE, ALERTCalifornia, and industry partner DigitalPath rolled out an AI-enabled detection system across all 21 CAL FIRE Dispatch Centers. In its first season, the AI system detected over 1,200 fires across the state, beating humans making 911 calls to report the fires more than 30% of the time.

“We define the success of this program as the fires you’ve never heard about,” Dr. Driscoll said on the Catching Wildfire podcast. “They’ve been suppressed early in their history in the incipient phase, so that we have a fighting chance.”

To further enhance its detection capabilities, ALERTCalifornia is deploying next-generation infrared and hyperspectral cameras that can see through poor atmospheric conditions and dense orange smoke. This will allow the AI detection system to function effectively even during massive fire events.

Using Satellite and Airborne Sensors to Detect Wildfires

While wildfire cameras are watching specific parts of fire-prone areas, satellites and airborne sensors are watching large regions from above. Once again, AI is being used to process and analyze their transmissions to alert humans to wildfires as soon as they’re detected.

For example, the Earth Fire Alliance’s FireSat program is building a satellite constellation designed specifically for wildfire detection, monitoring, and response. In July 2026, the organization announced that its first three operational FireSat satellites had reached orbit, marking a significant step toward faster space-based fire intelligence. Meanwhile, ALERTCalifornia is using LiDAR remote sensing and multispectral imaging from airplanes to conduct large-scale terrain mapping to assess forest health and vulnerabilities.

How AI Supports Wildfire Intelligence

AI is equally effective for wildfire prediction and wildfire modeling. By combining historical fire data, terrain maps, fuel conditions, and wind forecasts, AI-enabled platforms can help model how a wildfire may spread.

Dr. Driscoll detailed how the ALERTCalifornia platform jumps into action whenever a threat is identified: “I could drop a pin where someone has informed us that there’s a fire,” he said. “12 cameras light up. I can just look and verify, is there smoke?” This data can then be fed into modeling platforms—such as UC San Diego’s Wi-Fire—which can predict how the fire may spread in the next 10 to 30 minutes into the future.

Why Connectivity Is Essential for AI Wildfire Detection

Even with AI on board, the best fire detection platform is useless if it cannot communicate its findings. Connectivity is the lifeblood of effective AI wildfire detection. Without a reliable network, critical alerts and live video streams will never reach the people who need them.

This is where FirstNet comes into the picture. As the only wireless broadband network specifically built for first responders, FirstNet’s public safety priority service via Band 14 and its extensive coverage in the United States, ensure that fire detection platforms connect to those relying on their data as reliably and consistently as possible..

Moving Wildfire Intelligence to Incident Command

When an AI system detects a wildfire in a remote canyon, it must transmit heavy data payloads—including high-definition video and GPS coordinates—back to Dispatch fast. FirstNet helps move those alerts, video feeds, and coordinates more reliably during emergency operations.

During major wildfire incidents, commercial cellular networks frequently become overloaded. Thankfully, public safety agencies can bypass congestion by utilizing FirstNet deployables like Cell on Wheels (COWs) and Compact Rapid Deployables (CRDs).

Sharing Information Across Public Safety Agencies

Wildfire responses typically require multi-agency coordination to succeed. FirstNet’s national reach and capacity support the rapid sharing of actionable data across different agencies and jurisdictions.

This aligns perfectly with ALERTCalifornia’s open-source philosophy, which freely shares camera access with the University of Nevada, Reno, the University of Oregon, and U.S. Forest Service lookouts. The more people who can see the same data to fight the fires, the better.

How FirstNet Is Using AI in Wildfire Detection

FirstNet’s secure, resilient infrastructure makes advanced AI deployments possible at scale. Meanwhile, edge computing solutions like AT&T’s Video Intelligence for FirstNet allow surveillance cameras to securely stream video over the cellular network. This system processes video analytics directly at the edge, sending near real-time AI alerts to emergency operations centers without overwhelming bandwidth.

Put it all together, and the combination of FirstNet and AI-enabled wildfire detection is a potent pair. In an age where climate change and rising temperatures are making wildfires more common and deadly, this combination is the very tool that firefighters need to save lives and protect property.

FAQ

What is AI wildfire detection?

AI wildfire detection uses artificial intelligence to scan live video feeds and sensor data to spot the early signs of a fire. By identifying visual smoke anomalies and heat signatures quickly, it alerts first responders much faster than traditional 911 calls.

How do wildfire detection cameras work?

High-definition wildfire cameras perform continuous 360-degree sweeps, providing real-time visual feeds to emergency command centers. When integrated with AI software, these camera networks can autonomously detect potential fires and estimate the incident’s location, so that first responders can react fast.

How does FirstNet support wildfire technology?

FirstNet’s dedicated wireless broadband network ensures data-heavy transmissions and technologies, like AI camera feeds, remain connected during emergencies. By using specialized deployables, FirstNet extends coverage into remote wilderness areas where commercial cellular networks have poor coverage or do not exist.