AI-driven Tools for Implementation of Smart Cities in Nigeria: An Agile Perspective

Автор: Ikenna Caesar Nwandu, Francisca O. Nwokoma, Azubuike I. Erike

Журнал: International Journal of Education and Management Engineering @ijeme

Статья в выпуске: 1 vol.16, 2026 года.

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This study investigates the incorporation of artificial intelligence (AI)-driven technologies, in facilitating automation, intelligent decision-making, predictive analytics, and responsive urban management, as essentials to the change inherent in developing smart cities. This need for efficiency, sustainability, and improved quality of life has led to a radical change in contemporary urban planning as urban areas are gradually developing into smart cities. Through networked systems and real-time data analysis, smart cities use cutting-edge technologies to optimize governance, infrastructure, and services. Smart energy grids, waste optimization, adaptive traffic control, and customized citizen services are all made possible by these technologies. However, an agile and iterative approach to technology implementation is necessary due to the dynamic and complex nature of urban systems. This study examines Agile methodology as a strategic framework for the creation and application of AI-driven tools in smart city settings. Agile's fundamental principles, namely collaborative development, incremental delivery, and responsiveness to change, align well with the demands of adjusting to changing user needs, technological advancements, and sociopolitical factors. This study examines how Agile practices support stakeholder coordination, iterative prototyping, and quick adaptation in AI-based urban solutions through a mixed-methods research design that includes case studies from a few chosen smart city initiatives. The results show that the proposed Nigeria Agile Integration for Smart City Transformation (NAI-SMART) framework showed that Abuja, Enugu, and Ibadan are more technology-compliant at the time of this study than a few other cities used in this research. NAI-SMART was able to achieve this via AI-based technologies namely GRU time series model, Reinforcement learning, XGBoost, and Scikit-learn that were employed during NAI-SMART Urban Intelligence Engine (NAI-SMART UIE) model creation. This research therefore, contributes to both theory and practice by proposing a step-by-step framework for AI-powered smart city development using Agile principles. Ultimately, the study underscores the synergistic potential of AI and Agile in actualizing the vision of inclusive, data-driven, and adaptive smart cities in Nigeria.

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Smart Cities, AI-Driven Tools, NAI-SMART, NAI-SMART UIE, Urban Digitization, Agile

Короткий адрес: https://sciup.org/15020226

IDR: 15020226   |   DOI: 10.5815/ijeme.2026.01.05