SCC-CIVIC-PG Track A: Full Building Scans for Targeted Micro-retrofits using Drones, Radars, and Deep Learning

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Poor air and moisture sealing in building envelopes contribute to worse buildings emissions and occupant health outcomes. Finding moisture using thermal scans can be a laborious and environmentally constrained process. Our contribution in ground penetrating radar involves using machine learning to find anomalous areas of interest in radar scans. We will be able to find trapped and hidden moisture that is not detectable with current non destructive testing techniques. By partnering with the City of New York and NGOs like District 2030, this project will (a) research the applicability of radar scans on different types of building facades, (b) create real, actionable outcomes that will improve the quality of life for residents of disadvantaged communities in NYC by creating better buildings through improving building envelopes with targeted micro-retrofits, (c) create a product that is beneficial to the new construction, the existing construction, the building insurance, the property management, and the building engineering industries. This project will enhance US competitiveness, produce new products, bolster economic growth, and benefit society at large. The findings from this project have the potential to scale and produce similar positive outcomes across the nation.Poorly maintained building envelopes exacerbate building greenhouse gas emissions and cause quality of life problems. We propose a non-invasive integrated solution to locate and document moisture intrusion, thermal bridges, and air leaks to diagnose building envelope issues. The system identifies and quantifies common envelope defects and applies long-wave radar and deep learning to detect hidden deep moisture penetration and other major envelope defects. This project aims to perform inspections on public and private buildings in New York City, specifically in low-income communities. We will work with community organizations and local government departments already carrying out this work and enhance their efforts through AI and robotics technologies being actively developed in the PI/Co-PI’s labs. This project will improve the quality of life for residents in low-income communities by creating more comfortable and usable buildings. With this system, it is possible to perform low-cost, targeted micro-retrofits to address envelope issues. We will either address building envelope issues directly through low-cost targeted micro-retrofits or we will propose a list of retrofits to our partners when that is not possible. This project is in response to the Civic Innovation Challenge program—Track A. Living in a changing climate: pre-disaster action around adaptation, resilience, and mitigation—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.