Green AI power impact on development of smart cities

Abstract

Smart cities are increasingly integrating Internet of Things (IoT) and Artificial Intelligence (AI) technologies to collect real-time data and respond to citizens' needs. The objective of this study is to examine the impact of Green Artificial Intelligence (Green AI) on the sustainable development of smart cities, focusing on how energy-efficient algorithms and environmentally conscious machine learning systems can optimize urban operations. The research aims to demonstrate how Green AI supports the creation of climate-resilient, resource-efficient, and human-centered urban ecosystems. Building upon prior work in sustainable innovation and AI for environmental management, this study extends the discourse toward the intersection of Green AI and smart city transformation. Previous research in sustainable urban design and AI-enabled infrastructure has shown the potential of intelligent technologies to reduce emissions and improve resource utilization, yet few studies explicitly address the sustainability of the AI systems themselves. The present paper contributes to this emerging field by proposing an integrative conceptual framework grounded in theoretical review. The approach synthesizes existing literature and case evidence to analyze the role of Green AI in energy management, mobility optimization, and digital governance. The analysis suggests that Green AI has the potential to enhance predictive analytics for urban planning, support smart grid efficiency, enable adaptive traffic and waste management systems, and strengthen environmental monitoring through low-carbon computation. The implications of this study are significant for academics, policymakers, and urban developers, offering insights into how sustainable AI deployment can balance technological advancement with ecological preservation. The value of the paper lies in its holistic perspective on Green AI as both a catalyst and a constraint in smart city evolution, providing an original theoretical foundation for future empirical research and policy development in sustainable digital urbanization.