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Incorporating AI into Housing and Community Development

Recorded October 17, 2024 This 2-part presentation explores the use of AI in two North Central Region Extension projects. Part 1: AI-Driven Detection and Mapping of Manufactured Housing Communities Manufactured housing communities (MHCs) are residential neighborhoods consisting mainly of factory-built homes, providing affordable housing for economically disadvantaged households in the United States. Presently, there are few, if any, systematically created datasets that accurately map and detail the physical characteristics of MHCs, e.g., individual structures and footprints. This presentation describes the methodology used based on high-resolution aerial imagery, computer vision techniques, and AI models to systematically detect and map MHCs. Applications of this dataset and methodology include urban planning, policy-making, disaster response, and research on housing and community development, providing insights beyond just mapping MHCs. Presenter: Armin Yeganeh, Ph.D., Assistant Professor, Construction Management Program, Michigan State University Part 2: Exploring the Potential Role of AI in Community Development Effectively addressing critical community issues in the world today requires relevant and reliable data resources, however, identifying, accessing, and understanding data is a challenge. This webinar will present the ongoing exploration of utilizing Artificial Intelligence (AI) into the complex work of community development, so decision makers have the data they need to create resilient communities. Presenters: Lisa Bates, Assistant Director of Community and Economic Development, Iowa State University Extension and Outreach Christopher J. Seeger, PLA, GISP, Morrill Professor and Extension Specialist, Landscape Architecture, Iowa State University Extension and Outreach Opinions or points of view expressed in this presentation represent the view of the presenter and does not necessarily represent the official position or policies of North Central Regional Center for Rural Development, USDA NIFA, or Purdue University.