SCC-DG: Leveraging Data and Community-Driven Freight Systems to Support Urban Agriculture Models for Enhancing Food Access

This Smart and Connected Communities (S&CC) development project supports research that aims to enhance access to fresh, nutritious food in urban areas by designing integrated supply-side, community-driven freight systems and urban agriculture models that scale into economically viable urban food logistics networks. This initiative aims to establish urban agriculture as a vital component of infrastructure, enhancing the availability of food for everyone. Despite the availability of food outlets in cities across the U.S., many neighborhoods still lack reliable access to healthy food due to persistent logistical, infrastructure, and economic barriers. Previous efforts have focused on consumer behavior and demand-side systems, while supply-side logistic systems—particularly those leveraging existing community assets—have remained underexplored. This research seeks to enable the U.S. to improve national health outcomes and urban economic vitality by supporting neighborhood-based food production and delivery, developing new planning tools for cities, and expanding opportunities for students and residents to actively participate in designing food distribution systems. The research project's vision is to establish a data collection system that will eventually enable the development of an Artificial Intelligence-Enabled Decision-Support System (AIEDSS), which models food distribution through the combined perspectives of infrastructure, logistics, and social networks. This project seeks to pioneer a new class of hybrid systems models that capture the interdependencies between spatial infrastructure, logistical performance, and social dynamics in urban food systems. The proposed AIEDSS looks to combine artificial intelligence, optimization, geospatial modeling, and social network theory to support context-aware, supply-focused, community-informed logistics planning and community-based logistics. The project also looks to integrate the Asset-Based Community Development (ABCD) framework into engineering and computational modeling, advancing the design of freight systems that reflect community-identified priorities, institutional relationships, and local food networks. The primary outcome of this effort is anticipated to be the definition of structured input-output relationships and validation-ready data templates that will directly inform system development during the next research phase. The datasets, analytical findings, and validation logic generated in this phase look to be immediately applicable to prototype development and calibration. These contributions seek to represent a conceptual shift in AI-enabled infrastructure planning from purely performance-driven models to adaptive, participatory systems grounded in local knowledge and social embeddedness. 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.