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  1. Science and Technology Directorate
  2. News Room
  3. News Release: S&T Successfully Evaluates Wildfire Sensors

News Release: DHS S&T Successfully Evaluates Wildfire Sensors with California Emergency Responders

Release Date: June 10, 2021

FOR IMMEDIATE RELEASE
S&T Public Affairs, 202-254-2385

RED BLUFF, CALIFORNIA – The Department of Homeland Security (DHS) Science and Technology Directorate (S&T) successfully tested four prototype technologies for early detection of wildfires in California this week. The evaluation was conducted during a controlled, prescribed burn at the Dye Creek Preserve near Red Bluff, California, in partnership with the California Department of Forestry and Fire Protection (CAL FIRE) and The Nature Conservancy. Additional observers included partners from the California Governor’s Office of Emergency Services and the U.S. Fire Administration (USFA).

The test was the second phase of S&T’s Wildland Urban Interface (WUI) wildfire sensor technology program, part of the Smart Cities Internet of Things Innovation (SCITI) Labs initiative, which brings together government and private sector partners to identify technologies that meet first responders’ operational needs and ensure the nation’s critical infrastructure remains secure and resilient.

In recent months, S&T worked with four industry partners—Ai4 Technologies, Inc., of San Francisco, California; Breeze Technologies UG of Hamburg, Germany; N5 Sensors, Inc., of Rockville, Maryland; and Valor Fire Safety of Londonderry, New Hampshire—to refine and enhance their unique wildfire sensors technologies and platforms. S&T connected the companies with the ultimate end-users, including the Federal Emergency Management Agency (FEMA), and state and local fire services, to gain valuable feedback as the products are readied for the commercial marketplace.

During this week’s prescribed burn, the prototype sensors were deployed at various distances from the ignition point and were monitored to establish time and distance for alert generation. The demonstration provided further evidence that the sensor technologies can provide a valuable resource for first responders and the public at large. 

“Through a combination of particulate, air quality, optical sensing, thermal imagery and photoelectric sampling, as well as the development of detection algorithms, this sensor technology will assist with early warning for wildfires, especially those near communities that have been devastated by these events in the past,” said S&T Program Manager Jeff Booth.

Field testing follows months of computer modeling and laboratory testing

Prior to this week’s field tests, the SCITI Labs program validated the sensors in laboratory settings. S&T worked with Blue Sky Modeling on extensive computer modeling to predict the dispersion of smoke and air pollution associated with the initial stage of a wildfire using corresponding historical meteorological data from previous wildfires. This modeling was used to inform and design laboratory and real-world test scenarios.

S&T also partnered with the engineering and consulting services firm Jensen Hughes to design a test plan and in-lab apparatus to control and replicate the level of smoke concentrations found at varied distances from the early stages of a wildfire. The tests simulated 13 different real-world scenarios by burning native vegetation with various levels of heat, wind, and air flow rates. These tests successfully indicated the ability of the sensor technologies to detect the smoke from a wildfire at very low levels of concentration.

“Working with our partners from FEMA, USFA, CAL FIRE and The Nature Conservancy has enabled research progress, even with the constraints of COVID-19,” said Booth. “These partners have been instrumental in the success of the program, and we will continue to support them in their emergency response mission through these SCITI Labs research initiatives.”

For more information about SCITI Labs, please visit https://www.dhs.gov/science-and-technology/st-smart-city-internet-things-innovation-sciti-labs.

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Last Updated: 10/18/2023
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