Integrating Building Information Modeling and Digital Twins to Enhance Sustainable Construction Project Efficiency

Abstract

This study explores the synergistic integration of Building Information Modeling (BIM) and Digital Twins (DT) as a transformative paradigm to enhance project efficiency throughout the lifecycle of sustainable construction projects. Employing a qualitative research design rooted in a systematic literature review and library research, this paper critically examines recent scholarly contributions, technical frameworks, and industry reports across primary academic databases. The findings demonstrate that while static BIM serves as a robust digital repository for design and structural data, dynamic Digital Twins extend these capabilities by integrating real-time IoT sensor data, enabling predictive maintenance, continuous performance monitoring, and adaptive energy management. The integration bridges critical information gaps between pre-construction planning and post-occupancy facility management, thereby significantly reducing resource waste, carbon footprint, and life-cycle operational costs. Furthermore, this research identifies key technological, organizational, and interoperability challenges hindering widespread implementation and proposes an integrative strategic framework to mitigate these barriers. Ultimately, this paper underscores that combining static structural modeling with dynamic cyber-physical data streams is essential for achieving truly sustainable, smart, and resilient built environments, offering actionable insights for AEC practitioners and policymakers aiming to advance sustainable digital transformation.