Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Fire Fighting Technology Group

The Fire Fighting Technology Group (FFTG) enables advances in fire fighter safety, fire ground operations, and effectiveness of the fire service; develops and applies technology, measurements and standards, and improves the understanding of the behavior, prevention and control of fires to enhance fire fighting operations and equipment, fire suppression, fire investigations, and disaster response.

News and Updates

Projects and Programs

High Temperature Performance of Fire Fighter Equipment

Ongoing
OBJECTIVE: To improve the safety and effectiveness of fire fighters by developing science-based standard test methods that characterize the performance of fire fighting equipment and gear under fire environment conditions. TECHNICAL IDEA: This project aims to improve the performance of fire fighter

Per- and Polyfluoroalkyl Substances (PFAS)

Ongoing
Perfluorinated and polyfluorinated alkyl substances (PFAS) constitute a family of compounds that are distinguished by partial or complete fluorination of alkyl hydrocarbons. Dubbed “forever chemicals”, the unique chemistry of PFAS imparts a high level of stability, making the compounds resistant to

Smart Fire Fighting

Ongoing
Objective: Develop the measurement science that enables fusion of cyber-physical systems from buildings, apparatus, personal protective equipment, and robotics that enhances situation awareness, operational effectiveness, and fire fighter safety. What is the new technical idea? The new technical

Publications

Detecting Firefighter's Tenability Utilizing Machine Learning

Author(s)
Qi Tong, Hongqiang FANG, Eugene Yujun Fu, Wai Cheong Tam, Thomas Gernay
The proposed research aims to leverage machine learning to detect thermal operating classes and improve the tenability of firefighters in a commercial building

Awards