Application of Artificial Intelligence in Smart Cities: A Systematic Review using the Methodi Ordinatio
Artificial intelligence offers highly suitable solutions for numerous challenges in urban transformation and development, such as ensuring an adequate water supply, energy management, waste management, and reducing traffic congestion, noise, and pollution. Given the social and technical nature of smart cities and the applications of artificial intelligence in this field, university research has seen a significant increase in recent years. Furthermore, an analysis of the popularity of keywords "smart city" and "artificial intelligence" on Google Trends indicates that these key terms have been increasingly popular from 2014 to the present. Therefore, this article systematically examines the current status and future directions of research on the application of artificial intelligence in smart cities through a sequential review method. To this end, the databases "Scopus" and "Google Scholar" were searched, identifying a total of 3384 articles. Following a systematic review and final screening process, 61 articles were selected for analysis. The findings show an increasing trend in research publications in this area from 2018 onwards. Additionally, an examination of the thematic scope of selected research indicates that the application of artificial intelligence in smart cities is predominantly focused on urban management and sustainable development (30%), smart living and intelligent infrastructures (28%), and intelligent environment (21%). The results also reveal that 64% of studies have employed qualitative methods, 21% quantitative methods, and 15% a combination of methods. As the application of artificial intelligence in smart cities is still in the conceptualization stage, the noticeable preference for qualitative methods among researchers in this field is evident. However, the advancement and expansion of artificial intelligence applications in smart cities have led to an increased use of experimental approaches and quantitative methods in the years 2023 and 2024. Furthermore, the analyses show that these selected studies are concentrated in three paradigmatic levels, namely specific theory with 46%, analytical methods with 29%, and empirical observations with 25% focus.
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