ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE SMART CITIES: MACHINE LEARNING APPLICATIONS IN INTELLIGENT URBAN GOVERNANCE AND INFRASTRUCTURE

Abstract

The rapid expansion of urban populations and increasing sustainability challenges created a growing demand for intelligent technologies capable of improving governance effectiveness and infrastructure performance. This study examined the role of artificial intelligence and machine learning applications in advancing sustainable smart cities through intelligent urban governance and infrastructure management. A quantitative research design was employed to investigate the perceptions of professionals involved in smart city initiatives. Data were collected from a sample of 350 respondents, including urban planners, municipal administrators, infrastructure managers, policymakers, and technology specialists. The study utilized descriptive statistics, reliability analysis, and one-sample t-test analysis to evaluate the research objectives. The findings revealed strong support for the adoption of intelligent technologies in urban environments. Artificial Intelligence Adoption recorded a mean score of 4.19 with a standard deviation of 0.61, while Machine Learning Applications achieved a mean score of 4.24 with a standard deviation of 0.58. Intelligent Urban Governance reported a mean value of 4.15 and Sustainable Smart City Development achieved the highest mean value of 4.28. Reliability analysis indicated strong internal consistency, with Cronbach’s Alpha coefficients ranging from 0.835 to 0.879, while the overall reliability coefficient reached 0.856. Furthermore, one-sample t-test results demonstrated statistically significant support for all study variables at p = 0.000. The study concluded that artificial intelligence and machine learning technologies enhanced governance responsiveness, improved infrastructure efficiency, strengthened resource management practices, and supported sustainable urban development. The findings provided valuable insights for policymakers, urban planners, and technology developers seeking to create resilient, efficient, and environmentally sustainable smart cities.