The Boston Fire Department started to use emerging technology to fight fires in the last couple of years. In collaboration with Karen Panetta, an IEEE fellow and dean of Graduate Education at Tufts University's School of Engineering, the department is using AI for object recognition. The goal is to be able to use a drone or robot that can locate objects in a burning building. Panetta worked with the department to develop prototype technology that leverages IoT sensors and AI in tandem with robotics to help first responders "see" through blazes to detect and locate objects – and people. The AI technology she developed analyzes data coming from sensors that firefighters wear, and it recognizes objects that can be navigated in a fire.

As 12,000 lightning strikes pummeled the Bay Area this month, igniting hundreds of fires, fire spotters sprang into action. Their arsenal of tools includes thermal imagery collected by space satellites; real-time feeds from hundreds of mountaintop cameras; a far-flung array of weather stations monitoring temperature, humidity and winds; and artificial intelligence to munch and crunch the vast data troves to pinpoint hot spots. For decades, wildfires in remote regions were spotted by people in lookout towers who scanned the horizon with binoculars for smoke -- a tough and tedious job. They reported potential danger by telephone, carrier pigeon or Morse code signals with a mirror. Now, fire spotting has gone high tech.

A satellite image of Alaska captured in August 2005 shows the extent of smoke coverage from wildfires in the state's boreal forests. The blazes are likely to become large in exceptionally hot and dry conditions and when there's a high percentage of black spruce trees in the affected areas – key factors in a new predictive model developed by UCI scientists. An interdisciplinary team of scientists at the University of California, Irvine has developed a new technique for predicting the final size of a wildfire from the moment of ignition. Built around a machine learning algorithm, the model can help in forecasting whether a blaze is going to be small, medium or large by the time it has run its course – knowledge useful to those in charge of allocating scarce firefighting resources. The researchers' work is highlighted in a study published today in the International Journal of Wildland Fire.

The state firefighting service of California collaborated with a unit of California Air National Guard and deployed military wartime drones in order to receive real time photos and videos of the massive wildfire which spread across the area. According to a report by USA Today, this is only the third time such collaboration had taken place. The Reaper MQ-9, operated by the 163d Attack Wing at March Air Reserve Base in the Riverside County, will fly five miles above and transmit relevant information to commanders on the ground. This also includes information about spot-fire detection. Scott McLean, Deputy Chief of California Department of Forestry and Fire Protection, said, "It's out of the way."