Akter, Nipa and Mohammed, Awais and Almunshi, Muhammad Yousuf (2023) Artificial Intelligence Allowed Structural Health Monitoring for Resilient Infrastructure Systems. American Journal of Engineering , Mechanics and Architecture (2993-2637), 1 (7). ISSN 2993-2637

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Abstract

Background: The development of Artificial Intelligence (AI)-based Structural Health Monitoring (SHM) systems brings a new advanced system which protects infrastructure sustainability and safety through established performance standards. Methods: Implemented a quantitative cross-sectional survey study through Google Forms, they used to distribute their online questionnaire. The study gathered 175 complete answers from people at worked in engineering and AI and infrastructure-related fields. Descriptive statistical methods which combined frequency distribution with percentage analysis to study people understood things and how they perceived things and their readiness to adopt and their major obstacles. Results: AI-based SHM systems well because damage detection systems received the highest recognition at 76.8%. The survey results demonstrated a strong positive perception because 82.1% of respondents agreed that AI technology boosts structural safety and 79.6% of participants reported better monitoring performance. The survey results showed that 78.9% of participants supported AI technology for smart infrastructure development. The survey showed that 68.6% of participants wanted to use AI-powered SHM systems but 19.4% of them stayed uncertain about their choice. Conclusion: AI-powered SHM systems as effective tools which improve both structural security and operational efficiency and environmental sustainability. The moderate adoption rate exists because financial obstacles combine with technological barriers and infrastructure problems. The worldwide adoption of AI-based resilient infrastructure systems needs barrier elimination because this process enables faster implementation and full system potential achievement.

Item Type:	Article
Uncontrolled Keywords:	Artificial Intelligence, Structural Health Monitoring, Smart Infrastructure, Predictive Maintenance, Infrastructure Resilience
Subjects:	H Social Sciences
Depositing User:	admin eprints
Date Deposited:	02 Jul 2026 04:13
Last Modified:	02 Jul 2026 04:13
URI:	http://eprints.umsida.ac.id/id/eprint/16749

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