This post is also available in: heעברית (Hebrew)

Unmanned drones are gradually expanding their fields of application. One of these is the use of UAV technology in the management of natural disasters, such as wildfires.
A Georgia State researcher and collaborators have been awarded a $1.2 million federal grant to develop the use of drones in wildfire management, providing more timely data that could allow authorities to give residents in affected areas more time to evacuate, as well as helping firefighters working on the ground.
“This technology has the potential to save lives,” said Xiaolin Hu, associate professor of computer science and principal investigator of the grant. “It will help contain wildfires. It will support fire-spread prediction and inform the decision-making of fire managers as they work to contain wildfires.”, according to news.gsu.edu.
According to the National Interagency Fire Center, there were nearly 56,000 wildfires in the United States last year, with about 8.6 million acres burned. Last summer, California suffered its most deadly wildfire on record. The so-called Camp fire killed 86 people and burned more than 153,000 acres, destroying nearly 14,000 homes and more than 4,800 other buildings across Butte County, according to the San Francisco Chronicle.
Hu said that the technology his team is developing can help with these disaster situations in the future. Drones, also known as unmanned aircraft systems (UAS), will collect real-time data on live wildfires and will monitor the safety of firefighters and other people in deadly wildfire areas, he said.
“One important aspect of this project is to develop human-UAS collaboration where fire managers and firefighters work together with drones in collaborative tasks,” he said. “By pairing this technology with drones, we are expanding on our previous research and opening up new possibilities that we can only imagine.”
In a previous study, sponsored by the National Science Foundation, Hu and fellow researchers developed computer models to simulate and predict wildfire patterns.