DIGITAL NEIGHBORHOODS AND INTELLIGENT SYSTEMS IN SMART URBAN DEVELOPMENT

Digital neighborhoods and intelligent systems have facilitated the development of various smart urbanframeworks, offering signifcant economic, environmental, and social benefts. Advancements in intelligent infrastructureare reshaping traditional notions of urban governance and spatial planning, creating opportunities to enhance theefciency of smart urban development. However, limited research exists on where digital transformation is acceleratingoutside metropolitan hubs and developed economies. This study aims to map the dimensions of urban innovation wheredigital transformation is gaining traction.Using data from regression models and Analytical Hierarchy Process (AHP) evaluations across selected urban areas, weidentify a long tail of emerging digital ecosystems and adaptive urban solutions. A total of N unique intelligent system modelsoperate across key domains, including energy optimization, real-time trafc management, and predictive urban analytics.Our fndings demonstrate a strong positive correlation between technological integration and urban sustainability metrics.However, urban stakeholders do not passively comply with these changes; instead, their decision-making dynamics andbehavioral patterns are embedded within the framework of data-driven urbanization.The study concludes by outlining policy implications, assessing the application of AHP-driven decision support models insmart urban planning, and offering recommendations for future governance models. These empirical insights contribute toa deeper understanding of intelligent urban systems and their role in digital transformation and socio-technical adaptation.