Computational Intelligence for Sustainable Urban Planning and Smart Cities

Urbanization is increasing at an accelerated rate, specifically in developing countries such as Pakistan, which leads to urban planning and sustainability challenges. Conventional urban planning approaches have the inadequacy of flexibility, potential for growth, and sophistication to handle the dynamic urban needs, resulting in issues like wastage of energy usage, contamination, traffic congestion, and inferior infrastructure governance. Computational intelligence (CI), incorporating approaches such as machine learning, artificial intelligence, and fuzzy logic, provides innovative solutions to improve urban systems and strengthen sustainability. This study utilizes a quantitative statistical approach based on primary original data obtained from the urban planning professionals in Pakistan to analyze the impact of CI on sustainable urban development. 180 inputs were received from respondents, and used the Partial Least Squares Structural Equation Modeling (PLS-SEM). This study explores the influence of CI tools on the different sustainability indicators. The results support that the adoption of CI significantly promotes the environmental, social, and economic sustainability. The outcomes not only fill the gap of the methodology in the prior literature but also offer actionable suggestions for policymakers and urban planners in terms of Pakistan. This study highlights the transformative potential of CI in enhancing smart urban cities and supports the climate efforts.