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FlashNet Can Save Lives of Firefighters Predicting Danger

Key Highlights

  • More difficulty is involved in spotting the warning signs of flashovers during firefighting.
  • As per the research published, currently, AI can detect dangers or flashovers and can save the lives of firefighters.

Flashover is one of the major reasons for the deaths of many firefighters. These types of dangers occur when a combustible material starts igniting all of a sudden. In the last ten years, nearly 800 firefighters died, and over 3.2 lakh got injured in the United States while on duty. Nearly 13 percent of the deaths are due to flashovers.

For the last two decades, various scientists have been developing methods to predict flashovers in real-time. Finally, a new AI has been created recently. AI can currently detect flashovers and can save firefighters’ lives. As per the research, it is known that artificial intelligence can warn the responders when a flashover is predicted.

Details on FlashNet

So far, firefighters could not detect the location of the fire, floorplan, and other details during deadly events. Flashovers may suddenly flare to nearly 600 degrees Celsius, and the temperatures may increase. Though some tools relied on temperature data, it was hard to detect the issue and rescue people.

A new flashover prediction neural network has been developed by researchers at the National Institute of Standards and Technology (NIST), Hong Kong Polytechnic University, and other institutions. This network is also known as FlashNet.

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Accuracy Percentage

The team that developed FlashNet has simulated various data types, such as building layouts, fire and temperature conditions, surface materials, smoke detectors, etc. Nearly 25,000 fire cases were utilized iData Analyticsn the training process, and 16,000 were used to test and finetune it.

Compared to any other forecasting tools that were developed earlier, FlashNet can be able to predict flashovers second before occurrence. As per the study, it was shown that FlashNet had an accuracy of nearly 92.1 percent.

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