An Integrated AI Framework: A Smart Urban Model for Kish Island

The rapid advancement of artificial intelligence (AI) offers transformative opportunities for urban transportation, enabling predictive mobility management, automated service coordination, and data-driven decision-making. Despite global progress, most smart city applications remain fragmented, focusing on isolated services rather than integrated systems. This study introduces the Integrated AI Urban Transformation Framework (IAI-UTF), a four-layer architecture governed by a central “Urban AI Brain” that unifies sensing, processing, and service delivery across multiple subsystems. Kish Island, a major tourism hub and free economic zone in southern Iran, was selected as a pilot site due to its bounded geography and concentrated transport flows. The framework links airport flight schedules with predictive shuttle dispatch, integrates taxis and rideshares with demand forecasts, and balances visitor distribution across restaurants, attractions, and public spaces using occupancy data and dynamic billboards. A pilot corridor connecting Kish International Airport, hotel districts, and the beach promenade was evaluated using April ۲۰۲۴ flight data. Results demonstrated reductions in waiting times and overcrowding, improved fleet utilization, and enhanced tourist distribution. Comparative benchmarking against Singapore, Dubai, and Barcelona confirmed the framework's superior multi-domain efficiency. The IAI-UTF provides a replicable model for mid-sized cities in emerging economies, advancing sustainable, data-driven, and ethically governed urban mobility.

Keywords:

Artificial Intelligence(AI) , Urban Transportation , Kish Island , Congestion management , Predictive routing