Theoretical Model and Application of BIM-AI-IoT Integrated Construction Progress Management for Smart Residential Buildings

Abstract

Construction schedule management is fundamental to the success of residential building projects, yet traditional approaches frequently suffer from information lag, fragmented data, poor multi-party coordination, and insufficient proactive risk prediction. To address these limitations, this paper proposes an intelligent construction progress management model integrating Building Information Modeling (BIM), Artificial Intelligence (AI), and Internet of Things (IoT) technologies. The model adopts a four-layer architecture comprising a perception layer, data layer, intelligence layer, and application layer, governed by a core mechanism of "data-driven, intelligent decision-making, and closed-loop optimization." IoT devices enable real-time collection of multi-source site data; BIM serves as the unified platform for engineering information integration and visualization; AI algorithms perform progress deviation identification, duration prediction, and resource allocation optimization. The three technologies form a mutually supportive, closed-loop collaborative system. Simulation experiments on a typical high-rise residential complex demonstrate that the model significantly reduces data collection cycles, improves early warning accuracy, and enhances multi-party collaborative decision-making. Compared with traditional management methods, the proposed model shows clear advantages in real-time perception, proactive risk control, and overall schedule performance, providing a practical solution for intelligent progress management in residential construction projects.