Integrating Artificial Intelligence for Sustainable Structural Health Monitoring and Wastewater Treatment in Civil and Environmental Engineering

Abstract

This research assesses the adoption of AI by civil and environmental engineering, including its contributions to better SHM and sewage treatment in Pakistan. A total of 120 engineers took part in a self-administered survey, giving quantitative evidence on how critical infrastructure sectors use and benefit from AI technology. From using regression, multiple regression and correlation analyses, we saw that AI integration enhances the accuracy and dependability of SHM systems, helping detect vulnerabilities early and cutting maintenance expenses. It was also found that applying AI to wastewater treatment makes the process more effective, easier to oversee and better able to eliminate contaminants. The analysis revealed that using AI led to improved sustainability indicators such as a lower impact on nature, reduced resource use and longer lifespans for key infrastructures, broadly supporting AI’s contribution to sustainable engineering. The results of our research correspond to those of prior literature, emphasizing that AI plays a key role in making infrastructure solutions better for the environment. The research shared several reasons that prevent AI from becoming more broadly used such as poor data quality, the lack of needed experts and concerns about the morality of using AI in public infrastructure systems. Solving these problems calls for industry experts from different fields to join forces, strengthen their capabilities and design suitable support from policymakers for proper and timely use of AI in engineering. All in all, this research gives useful ideas to engineers, policymakers and researchers aiming to use AI to develop stronger and more sustainable infrastructure in Pakistan and similar emerging nations.