Using AI to Map Environmental Risks

New York City’s buildings are responsible for nearly 80 percent of its greenhouse gas emissions. Coupled with the ongoing effects of climate change and natural disasters such as 2023’s Tropical Storm Ophelia, the consequences of a lack of eco-friendly practices are growing. Ophelia flooded 45 subway stations, requiring 11 rescue operations and contributing to nationwide damages of more than $450 million.

Now a team of faculty and student researchers in the College of Engineering and Computing Sciences has published new findings that demonstrate how artificial intelligence (AI) can be used to improve sustainability efforts in New York City and beyond.

As seen in IEEE Xplore in June, researchers in the college’s Network and Innovation Lab have identified methods to improve flood preparedness and urban resilience and sustainability in New York City’s five boroughs.

“The growing impacts of climate change, including increased flooding, pose urgent challenges for urban communities,” says principal investigator Ziqian (Cecilia) Dong, Ph.D., professor of electrical and computer engineering. “Our goal is to help cities become more adaptive, sustainable, and equitable in the face of climate risks.”

Supported by Dong’s National Science Foundation funding—including an award for her ongoing City-as-Lab research coordination effort and RAPID flooding analysis project—the studies leverage AI-based machine learning models and web-based tools to map and visualize datasets on flash flooding, building energy efficiency, and fallen trees. The research team, which included a Ph.D. student and several graduate and undergraduate students, successfully demonstrated that the technology could allow city officials to make data-informed decisions and better prepare against urban environmental issues, including neighborhood-level energy efficiency; heat stress; and localized concerns, like downed trees, pests, and power outages.