Abstract: The core objective of this research is to address the fundamental challenges in traditional construction management-namely, delayed information transmission, prominent safety risks, and significant schedule deviations—while simultaneously filling the practical gap in applying smart construction site technologies to the "end-to-end management of industrial transformation projects." Guided by the principle of "enhancing construction management quality and efficiency through technological empowerment," this research integrates advanced technologies including AI-enabled smart safety helmets for mobile inspections, AI facial recognition attendance systems, BIM full-process modeling, and IoT-based real-time environmental monitoring. It establishes an integrated smart construction site management system encompassing precise personnel management, dynamic safety monitoring, real-time environmental tracking, closed-loop progress control, and full-chain quality traceability. Practical validation demonstrates remarkable outcomes: personnel attendance accuracy rose from 85% to 98%, with peak-hour attendance processing reduced to under 30 minutes; safety incident rates dropped from 2.5‰ to 0.5‰, with unsafe behavior identification reaching 95%; construction schedule deviation was controlled within 5%, while quality traceability enabled full lifecycle visualization of raw materials. The project achieved Guangzhou's Two-Star Smart Construction Site Process Certification in June 2025. The established smart construction system not only enhances digital and refined management levels but also enables synergistic collaboration with the denim industry cluster. This dual achievement of "smart construction and industrial synergy" provides a replicable and scalable practical solution for intelligent construction projects within the context of traditional industry transformation.