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Carnegie Mellon firefighting drones to hit the market in 2025

Carnegie Mellon firefighting drones to hit the market in 2025

Fighting deadly forest fires is proving to be quite a challenge for firefighters, even with the use of cutting-edge drone technology.

Carnegie Mellon University’s Robotics Institute is working to develop technology to do just that. The institute is working to build an autonomous drone that can fly low enough to provide real-time information about terrain and fires to minimize risk to firefighters, according to graduate student Andrew Jong, the lead researcher on the project.

“The team plans to use AI to automatically avoid power lines, thin branches, and other obstacles hidden in smoke,” Jong told Technical.ly. “This will allow firefighters to quickly gather important information up close in high-risk environments.”

According to the researchers, after years of development work, the basic version of the technology should be available by the end of 2024, with local testing starting in 2025.

Drones advise firefighters how to allocate limited resources

Since 2020, the Robotics Institute has been researching opportunities to improve situational awareness for firefighters as part of a low-flying drone project funded by the U.S. Department of Agriculture.

According to the department, the drones that will be used to extinguish the fires will also allow for a three-dimensional mapping of the area affected by the forest fires.

Timely information helps firefighters allocate resources effectively based on where lives and homes are at risk. In places where wildfires meet urban areas, it helps with vulnerability triage, according to the department. Drone technology is especially useful in situations where firefighters have limited resources, Jong said.

“For example, they trained models to detect fire assets, such as crews and trucks, using long-wave infrared cameras mounted on the drone,” Jong said. “Now they’re using AI to enable the drone to navigate quickly and safely through smoky and hazardous conditions, a task that would be extremely difficult to pilot manually alone.”

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