Artificial Intelligence-Powered Smart City Transformation: A Framework and Comparative Case Study Analysis

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Abstract
Rapid urbanisation necessitates reconsidering conventional urban management strategies and embracing creative alternatives for sustainable development due to rapid urbanisation and growing environmental challenges, including climate change, air pollution, and resource scarcity, which are mounting environmental concerns. In this regard, the idea of "smart cities" has surfaced as a strategic framework for enhancing urban efficiency via data-driven governance, digital technology, and intelligent infrastructure systems. This study looks at how digital infrastructure, artificial intelligence, and governance frameworks can be integrated into existing cities to create smart and sustainable urban systems. A comparative case study analysis of Barcelona, Singapore, Dubai, and Baghdad is used in conjunction with a conceptual integration technique. Infrastructure, data systems, artificial intelligence, and governance are the four interconnected layers that make up the study's Smart City Transformation Framework. The results emphasise how crucial data-driven decision-making, adaptive governance, and legacy infrastructure integration are to attaining sustainable urban change. The report also highlights important issues, such as data ethics, energy demands, and sociopolitical limitations. By presenting a multi-layered, context-sensitive model for changing existing cities, the suggested framework advances urban theory.

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