NSF Abstract

Many low-income households in the United States face high energy bills, with some spending up to 13% of their income on energy, compared to the national average of 2.9%. This disparity is often due to inefficient windows and poor insulation, especially in older homes built before the 1960s. These homes suffer from air leaks, drafts, and inconsistent indoor temperatures, leading to increased energy consumption and higher bills. Additionally, the residents' health is adversely affected during extreme weather conditions such as heatwaves and wildfires. Traditional methods to measure window air leakage, like the blower-door test, are expensive and disruptive, making them impractical for many low-income communities. Without documented leakage data, these communities miss out on retrofit grants meant to improve energy efficiency and climate resilience. This project aims to fill this gap by developing a cost-effective, community-driven method to accurately measure window air infiltration and leakage using drone-mounted infrared/thermal imaging combined with artificial intelligence (AI).

The project will co-develop an innovative approach for rapid data collection and analysis by focusing on overburdened communities. The objectives are to conduct stakeholder focus groups, coordinate future window replacements, and perform in-lab and field experiments to calibrate thermal imaging for air leakage detection. The project aims to empower these areas to access retrofit grants, enhance climate resilience, improve energy efficiency, and ultimately reduce energy costs and improve residents' health and safety. This initiative also addresses environmental injustice, ensuring that affordable and sustainable housing is accessible to those who need it most.

This project is in response to the Civic Innovation Challenge program?s Track B. Bridging the gap between essential resources and services & community needs and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Award Abstract #2431169