Firefighting Technology for Safer Communities

Autonomous Data Collection and Machine Learning for Improved Response

ABOUT THE PROJECT

Engineered fire drone and rover sit on top of a metal lab table.

Sponsor:

THRC's Community Health and Economic Resilience Research (CHERR) Center of Excellence

PI:

Dr. Damian Valles

Research Pillar(s):

An icon of a road with a leaf cluster as the middle pavement marking.
A briefcase icon with a Red Cross symbol, meant to represent the STEM and Healthcare Workforce priority.
A head icon with a heart in place of a brain, meant to represent the Personal Health and Wellbeing pillar.
An icon of an medical monitor showing heart beat activity, meant to represent the Digital Healthcare Transformation pillar.
An ambulance moving at high speed with the siren on, meant to represent the Emergency Preparedness pillar.

This project involves the design and development of an advanced AI system of autonomous units, including rovers and drones, to assist first responders in navigating fires in buildings by detecting heat signatures, human screams, and toxic gases. 

By leveraging the power of machine learning and AI, this research aims to increase rescue efficiency, ensure firefighter safety, and support better decision-making during emergency responses. The project contributes to the health+resilience of first responders and the public, because healthy first responders are critical to maintaining healthy communities.

Researchers & Collaborators

Headshot of Dr. Damian Valles.

Dr. Damian Valles

Faculty Fellow, THRC

Assistant Professor, Ingram School of Engineering