The NSF S&CC program, started in 2016, supports foundational research to solve complex challenges faced by communities in the 21st century. It focuses on fostering deep collaborations between researchers, local governments, industry, and community organizations. The program harnesses interdisciplinary research across various fields — including AI, ML, IoT, social sciences, and beyond — to improve the quality of life for all. Learn more about the S&CC program at:

Abigail Horn and her USC Viterbi team developed MINT, an AI-based model analyzing menus from 600,000 U.S. restaurants to predict nutritional quality. MINT highlights disparities in food access, showing less healthy options in low-income and predominantly Black neighborhoods. It also aids policymakers in identifying healthier dining spots for programs like CalFresh. Horn aims to refine MINT to include ingredient use and processing. This tool aligns with USC’s Frontiers of Computing initiative for ethical advancements in AI.

Fort Hays State University received a $74,446 NSF Civic Innovation Planning Grant to enhance health equity for gender-based violence survivors in rural western Kansas. The project focuses on bridging systemic gaps in services like transportation and housing while fostering trauma-informed community support. Collaborating with local organizations, the team aims to create sustainable, survivor-centered advocacy and prepare for a larger implementation grant.

Read more here.

Researchers at the University of Michigan’s Taubman College, led by Sharon Haar, have secured a $75,000 NSF grant for the “Rehab for America” project, aimed at helping Detroit residents rehabilitate vacant homes. The initiative addresses the housing affordability crisis by creating resources and improving efficiencies for restoring abandoned properties, benefiting community and city development. This research collaboration could influence other post-industrial U.S. cities facing similar challenges.

Villanova researchers have been awarded a $750,000 NSF grant, part of a $2 million project, to address the impact of urban flooding on transportation for underserved communities. Led by Dr. Chenfeng Xiong and colleagues, the study focuses on Philadelphia’s flood-prone areas, evaluating flood risks and developing strategies to maintain access to public transit during severe weather events. This project aims to reduce vulnerability by ensuring mobility resilience in high-risk areas.

The University of Memphis, led by Dr. Sabya Mishra, has received a $75,000 National Science Foundation grant to study transit options for Ford’s Blue Oval City workforce in rural Tennessee. The project will assess fixed-line buses and on-demand micro-transit services, focusing on timely, efficient transit solutions for industrial-area workers. Supported by Congressman Steve Cohen, this research aims to improve transportation for the region’s growing workforce.

The National Science Foundation's Smart and Connected Communities (S&CC) program held a visioning workshop in February 2024 alongside its annual PI meeting. This workshop brought together researchers and practitioners to identify priorities for advancing smart community research, encouraging high-risk, high-reward projects, and supporting community-driven challenges. The report outlines key focus areas, including methods to foster innovative research and recommendations for budget and funding adjustments to enhance the transition to practice.

Purdue University’s Center on AI for Digital, Autonomous and Augmented Aviation (AIDA3) recently celebrated the opening of its Smart Operations Center (SOC) at Purdue Airport. As the hub of the new Smart Crossways air corridor—a 200-mile pathway for autonomous aerial vehicles (AAVs)—the SOC aims to support safe, AI-powered UAV flights for diverse applications, from cargo transport to medical deliveries.

Researchers at NYU Tandon, in collaboration with May Mobility, have released the MARS (MultiAgent, multitraveRSal, and multimodal) dataset, a groundbreaking collection of real-world driving data aimed at advancing autonomous vehicle (AV) technology. 

Lead Principal Investigator, Chen Feng, is an NYU Tandon assistant professor working on computer vision for autonomous vehicles and mobile robots, whose NSF CAREER award funded this project.