AI-Driven Housing Evaluation for Rural Community Development

The absence of a comprehensive assessment of housing quality in rural areas of Iowa hinders resource allocation and negatively impacts residents' well-being and economic growth. Evaluating existing housing conditions is subjective and lacks thorough investigations due to limited resources. To address these challenges, an AI-driven approach was proposed. By utilizing web scraping and AI models, housing features could be categorized as good or poor quality, enabling targeted investment strategies, and directing financial resources where they are most needed. This project aimed to eliminate biases, streamline housing evaluations, and inform decision-making for rural housing investment and development initiatives.