Sensors show up in some far-reaching applications, even for predicting wildfires and volcanos.
Sensors are being developed for early detection of wildfire ignitions to reduce the time it takes to respond. Four prototypes for early detection were successfully tested in June during a field event in California.
“We are hopeful that wildland fire sensors can play a contributing role in the early detection of ignitions,” said Jeff Booth, director of the Science and Technology Directorate in the Department of Homeland Security.
“If we can reduce the time it takes from ignition to detection to response, then we may be able to prevent a small smoldering fire from becoming a catastrophic fire disaster.”
The field event featured eight sensors from four companies with analysis of sensor performance on smoke threshold levels, time and distance for alert generation from the point of ignition and other data on cost performance.
Two companies were picked in August based on the test for showing potential for operational deployment and dual-purpose wildfire detection and air quality monitoring: Breeze Technologies UG of Hamburg, Germany, and N5 Sensors of Rockville, Maryland.
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Sensors are also being used to predict volcanic eruptions.
The former Deep Carbon Observatory began placing gas sensors on active volcanoes more than five years ago to measure the rise of magma. Researchers placed boxes containing the sensors in the volcano to measure carbon dioxide, sulfur dioxide and water vapor, then to transmit the data via antennae on the surface. The ratio of the gases indicated when a buildup of pressure inside a volcano occurs. Smithsonian Magazine first wrote about their work in 2016. Deep Carbon Observatory completed its work in 2020 and contributed its discoveries to scientific groups. Earlier work by Newcastle University began all the way back in 2010.
In a related effort, Jet Propulsion Laboratory collects thermal radiation from NASA satellites that had flown over recently erupted volcanoes. Their data showed increasing temperatures over a multi-year span prior to each eruption. It is data that could be harnessed for early predictions in the future.