چکیده مقاله
Urban infrastructure governance is increasingly shaped by complex interactions between technical performance, institutional decision making, and public accountability While structural health monitoring and digital twin technologies have enhanced data availability and analytical capability, their influence on actual governance and decision processes remains limited In many cases, advanced analytics operate in parallel with traditional decision structures rather than informing them directly This study proposes an AI enabled decision support framework that integrates structural health monitoring, digital twins, and governance oriented decision logic to support urban infrastructure management The framework focuses on translating technical evidence into actionable insights aligned with institutional roles, accountability structures, and policy constraints Rather than automating decisions, the approach emphasizes decision augmentation, preserving human judgment while improving transparency, consistency, and defensibility The framework is demonstrated through a case study of urban infrastructure governance in Tehran Results show that AI enabled digital twins can improve prioritization of interventions, enhance coordination across departments, and reduce ambiguity in responsibility by making decision logic governance practice, supporting more resilient, accountable, and adaptive urban infrastructure explicit The study highlights how decision support systems can bridge the gap between technical analysis and management
کلیدواژهها
نویسندگان
Maryam Rahimi
۱ PhD Student, Public Administration Organizational Behavior , Firuzkuh Islamic Azad University, Iran
شیوه ارجاع
Rahimi, Maryam,1404,AI-Enabled Decision Support for Urban Infrastructure Governance Using Digital Twins: A Case Study of Tehran,29th National Conference on Civil Engineering, Architecture and Urban Planning,Shirvan
ارائهشده در
مجموعه مقالات بیست و نهمین کنفرانس ملی مهندسی عمران، معماری و شهرسازی28 بهمن 1404 · شیروان