A Review of AI-Driven Predictive Modeling for Urban Slum Regeneration and Sustainable Development

Urban slums represent a significant global challenge, characterized by poverty, inadequate infrastructure, and social inequality. Addressing these issues effectively requires innovative and scalable solutions. Artificial Intelligence (AI) has emerged as a transformative technology with the potential to revolutionize urban planning and management, offering capabilities in analyzing vast datasets, forecasting trends, and optimizing resource allocation. This report examines the potential of AI for predictive modeling and informed decision-making in urban slum regeneration and sustainable development projects within the last five years (۲۰۱۹-۲۰۲۴). The analysis highlights the effectiveness of AI techniques, particularly machine learning and deep learning, in areas such as slum mapping, growth prediction, and resource optimization. Several case studies demonstrate the practical application of AI in creating smarter and more resilient urban environments. However, the report also addresses the limitations and challenges associated with AI implementation, including data availability and quality, ethical considerations, and the need for transparency. Ultimately, the successful integration of AI in urban slum regeneration and sustainable development necessitates interdisciplinary collaboration and a commitment to addressing these challenges to build more equitable and sustainable urban futures.

کلیدواژه ها:

Artificial Intelligence ، Urban Development ، Machine Learning for Informal Settlements ، Predictive Modeling